Selfish operons: the evolutionary impact of gene clustering in prokaryotes and eukaryotes.

Science.gov (United States)

Lawrence, J

1999-12-01

The Selfish Operon Model postulates that the organization of bacterial genes into operons is beneficial to the constituent genes in that proximity allows horizontal cotransfer of all genes required for a selectable phenotype; eukaryotic operons formed for very different reasons. Horizontal transfer of selfish operons most probably promotes bacterial diversification.

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

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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

Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus

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Monier, Adam; Pagarete, António; de Vargas, Colomban; Allen, Michael J.; Read, Betsy; Claverie, Jean-Michel; Ogata, Hiroyuki

2009-01-01

Interactions between viruses and phytoplankton, the main primary producers in the oceans, affect global biogeochemical cycles and climate. Recent studies are increasingly revealing possible cases of gene transfers between cyanobacteria and phages, which might have played significant roles in the evolution of cyanobacteria/phage systems. However, little has been documented about the occurrence of horizontal gene transfer in eukaryotic phytoplankton/virus systems. Here we report phylogenetic evidence for the transfer of seven genes involved in the sphingolipid biosynthesis pathway between the cosmopolitan eukaryotic microalga Emiliania huxleyi and its large DNA virus EhV. PCR assays indicate that these genes are prevalent in E. huxleyi and EhV strains isolated from different geographic locations. Patterns of protein and gene sequence conservation support that these genes are functional in both E. huxleyi and EhV. This is the first clear case of horizontal gene transfer of multiple functionally linked enzymes in a eukaryotic phytoplankton–virus system. We examine arguments for the possible direction of the gene transfer. The virus-to-host direction suggests the existence of ancient viruses that controlled the complex metabolic pathway in order to infect primitive eukaryotic cells. In contrast, the host-to-virus direction suggests that the serial acquisition of genes involved in the same metabolic pathway might have been a strategy for the ancestor of EhVs to stay ahead of their closest relatives in the great evolutionary race for survival. PMID:19451591

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

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Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

A study of eukaryotic response mechanisms to atmospheric pressure cold plasma by using Saccharomyces cerevisiae single gene mutants

International Nuclear Information System (INIS)

Feng Hongqing; Wang Ruixue; Sun Peng; Wu Haiyan; Liu Qi; Li Fangting; Fang Jing; Zhang Jue; Zhu Weidong

2010-01-01

The mechanisms of eukaryotic cell response to cold plasma are studied. A series of single gene mutants of eukaryotic model organism Saccharomyces cerevisiae are used to compare their sensitivity to plasma treatment with the wild type. We examined 12 mutants in the oxidative stress pathway and the cell cycle pathway, in which 8 are found to be hypersensitive to plasma processing. The mutated genes' roles in the two pathways are analyzed to understand the biological response mechanisms of plasma treatment. The results demonstrate that genes from both pathways are needed for the eukaryotic cells to survive the complex plasma treatment.

Expression of the lysostaphin gene of Staphylococcus simulans in a eukaryotic system.

OpenAIRE

Williamson, C M; Bramley, A J; Lax, A J

1994-01-01

The lysostaphin gene of Staphylococcus simulans was cloned into Escherichia coli. The 5' end of the gene was modified to include a eukaryotic start codon, the Kozak expression start site consensus sequence, and an enzyme site to facilitate manipulation of the gene. Transcription of the modified gene in vitro yielded an RNA transcript which, when added to a rabbit reticulocyte cell-free translation system, directed the synthesis of several products. The largest product, migrating at approximat...

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.

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

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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.

Snapshot of the Eukaryotic Gene Expression in Muskoxen Rumen—A Metatranscriptomic Approach

Science.gov (United States)

O'Toole, Nicholas; Barboza, Perry S.; Ungerfeld, Emilio; Leigh, Mary Beth; Selinger, L. Brent; Butler, Greg; Tsang, Adrian; McAllister, Tim A.; Forster, Robert J.

2011-01-01

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. PMID:21655220

EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes.

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Clasen, Frederick Johannes; Pierneef, Rian Ewald; Slippers, Bernard; Reva, Oleg

2018-05-03

Genomic islands (GIs) are inserts of foreign DNA that have potentially arisen through horizontal gene transfer (HGT). There are evidences that GIs can contribute significantly to the evolution of prokaryotes. The acquisition of GIs through HGT in eukaryotes has, however, been largely unexplored. In this study, the previously developed GI prediction tool, SeqWord Gene Island Sniffer (SWGIS), is modified to predict GIs in eukaryotic chromosomes. Artificial simulations are used to estimate ratios of predicting false positive and false negative GIs by inserting GIs into different test chromosomes and performing the SWGIS v2.0 algorithm. Using SWGIS v2.0, GIs are then identified in 36 fungal, 22 protozoan and 8 invertebrate genomes. SWGIS v2.0 predicts GIs in large eukaryotic chromosomes based on the atypical nucleotide composition of these regions. Averages for predicting false negative and false positive GIs were 20.1% and 11.01% respectively. A total of 10,550 GIs were identified in 66 eukaryotic species with 5299 of these GIs coding for at least one functional protein. The EuGI web-resource, freely accessible at http://eugi.bi.up.ac.za , was developed that allows browsing the database created from identified GIs and genes within GIs through an interactive and visual interface. SWGIS v2.0 along with the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web-resource, provide the first comprehensive resource for studying HGT in eukaryotes.

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

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Margaret C W Ho

2009-11-01

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

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

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

2015-12-01

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

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

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

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Penny David

2007-10-01

Full Text Available Abstract Background Alternative splicing has been reported in various eukaryotic groups including plants, apicomplexans, diatoms, amoebae, animals and fungi. However, whether widespread alternative splicing has evolved independently in the different eukaryotic groups or was inherited from their last common ancestor, 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, we find several similarities in patterns of alternative splicing across these diverse eukaryotes. Conclusion Along with previous studies indicating intron-rich genes with weak intron boundary consensus and complex spliceosomes in ancestral organisms, our results suggest that at least a simple form of alternative splicing may already have been present in the unicellular ancestor of plants, fungi and animals. A role for alternative splicing in the evolution of multicellularity then would largely have arisen by co-opting the preexisting process.

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

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

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Francisco J. Romero-Campero

2013-08-01

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

Gene regulatory mechanisms in infected fish

DEFF Research Database (Denmark)

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

2011-01-01

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...... differentiation. Thus the expression of these miRNAs might be steered by different mechanisms in different cell types and have different roles in terms of the genes they target in different cell types. Thus gene regulation and function is better looked upon as a web of interactions. Data from zebrafish studies...

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

Science.gov (United States)

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

2012-07-01

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

topIb, a phylogenetic hallmark gene of Thaumarchaeota encodes a functional eukaryote-like topoisomerase IB.

Science.gov (United States)

Dahmane, Narimane; Gadelle, Danièle; Delmas, Stéphane; Criscuolo, Alexis; Eberhard, Stephan; Desnoues, Nicole; Collin, Sylvie; Zhang, Hongliang; Pommier, Yves; Forterre, Patrick; Sezonov, Guennadi

2016-04-07

Type IB DNA topoisomerases can eliminate torsional stresses produced during replication and transcription. These enzymes are found in all eukaryotes and a short version is present in some bacteria and viruses. Among prokaryotes, the long eukaryotic version is only observed in archaea of the phylum Thaumarchaeota. However, the activities and the roles of these topoisomerases have remained an open question. Here, we demonstrate that all available thaumarchaeal genomes contain a topoisomerase IB gene that defines a monophyletic group closely related to the eukaryotic enzymes. We show that the topIB gene is expressed in the model thaumarchaeon Nitrososphaera viennensis and we purified the recombinant enzyme from the uncultivated thaumarchaeon Candidatus Caldiarchaeum subterraneum. This enzyme is active in vitro at high temperature, making it the first thermophilic topoisomerase IB characterized so far. We have compared this archaeal type IB enzyme to its human mitochondrial and nuclear counterparts. The archaeal enzyme relaxes both negatively and positively supercoiled DNA like the eukaryotic enzymes. However, its pattern of DNA cleavage specificity is different and it is resistant to camptothecins (CPTs) and non-CPT Top1 inhibitors, LMP744 and lamellarin D. This newly described thermostable topoisomerases IB should be a promising new model for evolutionary, mechanistic and structural studies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Positive selection for unpreferred codon usage in eukaryotic genomes

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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

Convergent evolution of gene networks by single-gene duplications in higher eukaryotes

OpenAIRE

Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

2004-01-01

By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix–loop–helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks e...

Convergent evolution of gene networks by single-gene duplications in higher eukaryotes.

Science.gov (United States)

Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

2004-03-01

By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix-loop-helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks emerging through single-gene duplications, the dominant importance of molecular modularity in the bottom-up construction of complex biological entities, and the convergent evolution of networks.

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

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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.

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.

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

Science.gov (United States)

Guo, Liyuan; Wang, Jing

2018-01-04

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

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.

The COG database: an updated version includes eukaryotes

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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

Origins and evolution of viruses of eukaryotes: The ultimate modularity

International Nuclear Information System (INIS)

Koonin, Eugene V.; Dolja, Valerian V.; Krupovic, Mart

2015-01-01

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

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

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

Science.gov (United States)

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

2014-01-01

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

[Construction of the eukaryotic recombinant vector and expression of the outer membrane protein LipL32 gene from Leptospira serovar Lai].

Science.gov (United States)

Huang, Bi; Bao, Lang; Zhong, Qi; Shang, Zheng-ling; Zhang, Hui-dong; Zhang, Ying

2008-02-01

To construct the eukaryotic experssion vector of LipL32 gene from Leptospira serovar Lai and express the recombinant plasmid in COS-7 cell. The LipL32 gene was amplified from Leptospira strain 017 genomic DNA by PCR and cloned into pcDNA3.1, through restriction nuclease enzyme digestion. Then the recombinant plasmid was transformed into E.coli DH5alpha. After identified by nuclease digestion, PCR and sequencing analysis, the recombinant vector was transfected into COS-7 cell with lipsome. The expression of the target gene was detected by RT-PCR and Western blot. The eukaryotic experssion vector pcDNA3.1-LipL32 was successfully constructed and stably expressed in COS-7 cell. The eukaryotic recombinant vector of outer membrane protein LipL32 gene from Leptospira serovar Lai can be expressed in mammalian cell, which provides an experimental basis for the application of the Leptospira DNA vaccine.

Sequence-based model of gap gene regulatory network.

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

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

[Construction and functional identification of eukaryotic expression vector carrying Sprague-Dawley rat MSX-2 gene].

Science.gov (United States)

Yang, Xian-Xian; Zhang, Mei; Yan, Zhao-Wen; Zhang, Ru-Hong; Mu, Xiong-Zheng

2008-01-01

To construct a high effective eukaryotic expressing plasmid PcDNA 3.1-MSX-2 encoding Sprague-Dawley rat MSX-2 gene for the further study of MSX-2 gene function. The full length SD rat MSX-2 gene was amplified by PCR, and the full length DNA was inserted in the PMD1 8-T vector. It was isolated by restriction enzyme digest with BamHI and Xhol, then ligated into the cloning site of the PcDNA3.1 expression plasmid. The positive recombinant was identified by PCR analysis, restriction endonudease analysis and sequence analysis. Expression of RNA and protein was detected by RT-PCR and Western blot analysis in PcDNA3.1-MSX-2 transfected HEK293 cells. Sequence analysis and restriction endonudease analysis of PcDNA3.1-MSX-2 demonstrated that the position and size of MSX-2 cDNA insertion were consistent with the design. RT-PCR and Western blot analysis showed specific expression of mRNA and protein of MSX-2 in the transfected HEK293 cells. The high effective eukaryotic expression plasmid PcDNA3.1-MSX-2 encoding Sprague-Dawley Rat MSX-2 gene which is related to craniofacial development can be successfully reconstructed. It may serve as the basis for the further study of MSX-2 gene function.

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

Directory of Open Access Journals (Sweden)

Xiaosheng Wang

2010-03-01

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

Current approaches to gene regulatory network modelling

Directory of Open Access Journals (Sweden)

Brazma Alvis

2007-09-01

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

Microsatellites in the Eukaryotic DNA Mismatch Repair Genes as Modulators of Evolutionary Mutation Rate

Science.gov (United States)

Chang, Dong Kyung; Metzgar, David; Wills, Christopher; Boland, C. Richard

2003-01-01

All "minor" components of the human DNA mismatch repair (MMR) system-MSH3, MSH6, PMS2, and the recently discovered MLH3-contain mononucleotide microsatellites in their coding sequences. This intriguing finding contrasts with the situation found in the major components of the DNA MMR system-MSH2 and MLH1-and, in fact, most human genes. Although eukaryotic genomes are rich in microsatellites, non-triplet microsatellites are rare in coding regions. The recurring presence of exonal mononucleotide repeat sequences within a single family of human genes would therefore be considered exceptional.

Transcription factor trapping by RNA in gene regulatory elements.

Science.gov (United States)

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

2015-11-20

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

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

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

2016-01-01

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

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato

2016-08-25

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

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

Directory of Open Access Journals (Sweden)

Fei Xiao

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

Radiation and the regulatory landscape of neo2-Darwinism

International Nuclear Information System (INIS)

Rollo, C. David

2006-01-01

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 neo 2 -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

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.

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......, we find several similarities in patterns of alternative splicing across these diverse eukaryotes. CONCLUSION: Along with previous studies indicating intron-rich genes with weak intron boundary consensus and complex spliceosomes in ancestral organisms, our results suggest that at least a simple form...... of alternative splicing may already have been present in the unicellular ancestor of plants, fungi and animals. A role for alternative splicing in the evolution of multicellularity then would largely have arisen by co-opting the preexisting process....

Mutational robustness of gene regulatory networks.

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Aalt D J van Dijk

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

A Regulatory Network Analysis of Orphan Genes in Arabidopsis Thaliana

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.

Radiation and the regulatory landscape of neo{sup 2}-Darwinism

Energy Technology Data Exchange (ETDEWEB)

Rollo, C. David [Department of Biology, Life Sciences Building, 1280 Main St. West, Hamilton, Ont., Canada L8S 4K1 (Canada)]. E-mail: rollocd@mcmaster.ca

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 neo{sup 2}-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.

Learning gene regulatory networks from only positive and unlabeled data

Directory of Open Access Journals (Sweden)

Elkan Charles

2010-05-01

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

Sparsity in Model Gene Regulatory Networks

International Nuclear Information System (INIS)

Zagorski, M.

2011-01-01

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

Robustness and accuracy in sea urchin developmental gene regulatory networks

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Smadar eBen-Tabou De-Leon

2016-02-01

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

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

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.

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

DEFF Research Database (Denmark)

Palmgren, Michael; 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...

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

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

2014-01-01

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

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

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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.

Using hexamers to predict cis-regulatory motifs in Drosophila

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Kibler Dennis

2005-10-01

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

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

NARCIS (Netherlands)

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

2008-01-01

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

Deconstructing the pluripotency gene regulatory network

KAUST Repository

Li, Mo

2018-04-04

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

Deconstructing the pluripotency gene regulatory network

KAUST Repository

Li, Mo; Belmonte, Juan Carlos Izpisua

2018-01-01

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

Archaeal “Dark Matter” and the Origin of Eukaryotes

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Williams, Tom A.; Embley, T. Martin

2014-01-01

Current hypotheses about the history of cellular life are mainly based on analyses of cultivated organisms, but these represent only a small fraction of extant biodiversity. The sequencing of new environmental lineages therefore provides an opportunity to test, revise, or reject existing ideas about the tree of life and the origin of eukaryotes. According to the textbook three domains hypothesis, the eukaryotes emerge as the sister group to a monophyletic Archaea. However, recent analyses incorporating better phylogenetic models and an improved sampling of the archaeal domain have generally supported the competing eocyte hypothesis, in which core genes of eukaryotic cells originated from within the Archaea, with important implications for eukaryogenesis. Given this trend, it was surprising that a recent analysis incorporating new genomes from uncultivated Archaea recovered a strongly supported three domains tree. Here, we show that this result was due in part to the use of a poorly fitting phylogenetic model and also to the inclusion by an automated pipeline of genes of putative bacterial origin rather than nucleocytosolic versions for some of the eukaryotes analyzed. When these issues were resolved, analyses including the new archaeal lineages placed core eukaryotic genes within the Archaea. These results are consistent with a number of recent studies in which improved archaeal sampling and better phylogenetic models agree in supporting the eocyte tree over the three domains hypothesis. PMID:24532674

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

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David A Garfield

2013-10-01

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

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

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

2015-04-23

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

Evolutionary conservation of regulatory elements in vertebrate HOX gene clusters

Energy Technology Data Exchange (ETDEWEB)

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

2003-12-31

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

A dominant control region from the human β-globin locus conferring integration site-independent gene expression.

NARCIS (Netherlands)

D. Talbot; P. Collis; M. Antoniou (Michael); M. Vidal; F.G. Grosveld (Frank); D.R. Greaves (David)

1989-01-01

textabstractThe regulatory elements that determine the expression pattern of a number of eukaryotic genes expressed specifically in certain tissues have been defined and studied in detail. In general, however, the expression conferred by these elements on genes reintroduced into the genomes of cell

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.

Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae.

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Ido Yofe

2014-06-01

Full Text Available Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.

Dual Nature of Translational Control by Regulatory BC RNAs ▿

Science.gov (United States)

Eom, Taesun; Berardi, Valerio; Zhong, Jun; Risuleo, Gianfranco; Tiedge, Henri

2011-01-01

In higher eukaryotes, increasing evidence suggests, gene expression is to a large degree controlled by RNA. Regulatory RNAs have been implicated in the management of neuronal function and plasticity in mammalian brains. However, much of the molecular-mechanistic framework that enables neuronal regulatory RNAs to control gene expression remains poorly understood. Here, we establish molecular mechanisms that underlie the regulatory capacity of neuronal BC RNAs in the translational control of gene expression. We report that regulatory BC RNAs employ a two-pronged approach in translational control. One of two distinct repression mechanisms is mediated by C-loop motifs in BC RNA 3′ stem-loop domains. These C-loops bind to eIF4B and prevent the factor's interaction with 18S rRNA of the small ribosomal subunit. In the second mechanism, the central A-rich domains of BC RNAs target eIF4A, specifically inhibiting its RNA helicase activity. Thus, BC RNAs repress translation initiation in a bimodal mechanistic approach. As BC RNA functionality has evolved independently in rodent and primate lineages, our data suggest that BC RNA translational control was necessitated and implemented during mammalian phylogenetic development of complex neural systems. PMID:21930783

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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

2013-01-01

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

Morphological and ecological complexity in early eukaryotic ecosystems.

Science.gov (United States)

Javaux, E J; Knoll, A H; Walter, M R

2001-07-05

Molecular phylogeny and biogeochemistry indicate that eukaryotes differentiated early in Earth history. Sequence comparisons of small-subunit ribosomal RNA genes suggest a deep evolutionary divergence of Eukarya and Archaea; C27-C29 steranes (derived from sterols synthesized by eukaryotes) and strong depletion of 13C (a biogeochemical signature of methanogenic Archaea) in 2,700 Myr old kerogens independently place a minimum age on this split. Steranes, large spheroidal microfossils, and rare macrofossils of possible eukaryotic origin occur in Palaeoproterozoic rocks. Until now, however, evidence for morphological and taxonomic diversification within the domain has generally been restricted to very late Mesoproterozoic and Neoproterozoic successions. Here we show that the cytoskeletal and ecological prerequisites for eukaryotic diversification were already established in eukaryotic microorganisms fossilized nearly 1,500 Myr ago in shales of the early Mesoproterozoic Roper Group in northern Australia.

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

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Shuchi eSmita

2015-12-01

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

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

Science.gov (United States)

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

2012-01-01

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

Transfer of DNA from Bacteria to Eukaryotes

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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.

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

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

2014-12-10

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

[Construction of eukaryotic recombinant vector and expression in COS7 cell of LipL32-HlyX fusion gene from Leptospira serovar Lai].

Science.gov (United States)

Huang, Bi; Bao, Lang; Zhong, Qi; Zhang, Huidong; Zhang, Ying

2009-04-01

This study was conducted to construct eukaryotic recombinant vector of LipL32-HlyX fusion gene from Leptospira serovar Lai and express it in mammalian cell. Both of LipL32 gene and HlyX gene were amplified from Leptospira strain O17 genomic DNA by PCR. Then with the two genes as template, LipL32-HlyX fusion gene was obtained by SOE PCR (gene splicing by overlap extension PCR). The fusion gene was then cloned into pcDNA3.1 by restriction nuclease digestion. Having been transformed into E. coli DH5alpha, the recombiant plasmid was identified by restriction nuclease digestion, PCR analysis and sequencing. The recombinant plasmid was then transfected into COS7 cell whose expression was detected by RT-PCR and Western blotting analysis. RT-PCR amplified a fragment about 2000 bp and Western blotting analysis found a specific band about 75 KD which was consistent with the expected fusion protein size. In conclusion, the successful construction of eukaryotic recombinant vector containing LipL32-HlyX fusion gene and the effective expression in mammalian have laid a foundation for the application of Leptospira DNA vaccine.

Crystal structure of the regulatory subunit of archaeal initiation factor 2B (aIF2B) from hyperthermophilic archaeon Pyrococcus horikoshii OT3: a proposed structure of the regulatory subcomplex of eukaryotic IF2B

International Nuclear Information System (INIS)

Kakuta, Yoshimitsu; Tahara, Maino; Maetani, Shigehiro; Yao, Min; Tanaka, Isao; Kimura, Makoto

2004-01-01

Eukaryotic translation initiation factor 2B (eIF2B) is the guanine-nucleotide exchange factor for eukaryotic initiation factor 2 (eIF2). eIF2B is a heteropentameric protein composed of α-ε subunits. The α, β, and δ subunits form a regulatory subcomplex, while the γ and ε form a catalytic subcomplex. Archaea possess homologues of α, β, and δ subunits of eIF2B. Here, we report the three-dimensional structure of an archaeal regulatory subunit (aIF2Bα) from the hyperthermophilic archaeon Pyrococcus horikoshii OT3 determined by X-ray crystallography at 2.2 A resolution. aIF2Bα consists of two subdomains, an N-domain (residues 1-95) and a C-domain (residues 96-276), connected by a long α-helix (α5: 78-106). The N-domain contains a five helix bundle structure, while the C-domain folds into the α/β structure, thus showing similarity to D-ribose-5-phosphate isomerase structure. The presence of two molecules in the crystallographic asymmetric unit and the gel filtration analysis suggest a dimeric structure of aIF2Bα in solution, interacting with each other by C-domains. Furthermore, the crystallographic 3-fold symmetry generates a homohexameric structure of aIF2Bα; the interaction is primarily mediated by the long α-helix at the N-domains. This structure suggests an architecture of the three subunits, α, β, and δ, in the regulatory subcomplex within eIF2B

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

International Nuclear Information System (INIS)

Goodbourn, S.; Maniatis, T.

1988-01-01

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

Modeling stochasticity and robustness in gene regulatory networks.

Science.gov (United States)

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

2009-06-15

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

Seed storage protein gene promoters contain conserved DNA motifs in Brassicaceae, Fabaceae and Poaceae

Science.gov (United States)

Fauteux, François; Strömvik, Martina V

2009-01-01

Background Accurate computational identification of cis-regulatory motifs is difficult, particularly in eukaryotic promoters, which typically contain multiple short and degenerate DNA sequences bound by several interacting factors. Enrichment in combinations of rare motifs in the promoter sequence of functionally or evolutionarily related genes among several species is an indicator of conserved transcriptional regulatory mechanisms. This provides a basis for the computational identification of cis-regulatory motifs. Results We have used a discriminative seeding DNA motif discovery algorithm for an in-depth analysis of 54 seed storage protein (SSP) gene promoters from three plant families, namely Brassicaceae (mustards), Fabaceae (legumes) and Poaceae (grasses) using backgrounds based on complete sets of promoters from a representative species in each family, namely Arabidopsis (Arabidopsis thaliana (L.) Heynh.), soybean (Glycine max (L.) Merr.) and rice (Oryza sativa L.) respectively. We have identified three conserved motifs (two RY-like and one ACGT-like) in Brassicaceae and Fabaceae SSP gene promoters that are similar to experimentally characterized seed-specific cis-regulatory elements. Fabaceae SSP gene promoter sequences are also enriched in a novel, seed-specific E2Fb-like motif. Conserved motifs identified in Poaceae SSP gene promoters include a GCN4-like motif, two prolamin-box-like motifs and an Skn-1-like motif. Evidence of the presence of a variant of the TATA-box is found in the SSP gene promoters from the three plant families. Motifs discovered in SSP gene promoters were used to score whole-genome sets of promoters from Arabidopsis, soybean and rice. The highest-scoring promoters are associated with genes coding for different subunits or precursors of seed storage proteins. Conclusion Seed storage protein gene promoter motifs are conserved in diverse species, and different plant families are characterized by a distinct combination of conserved motifs

Seed storage protein gene promoters contain conserved DNA motifs in Brassicaceae, Fabaceae and Poaceae

Directory of Open Access Journals (Sweden)

Fauteux François

2009-10-01

Full Text Available Abstract Background Accurate computational identification of cis-regulatory motifs is difficult, particularly in eukaryotic promoters, which typically contain multiple short and degenerate DNA sequences bound by several interacting factors. Enrichment in combinations of rare motifs in the promoter sequence of functionally or evolutionarily related genes among several species is an indicator of conserved transcriptional regulatory mechanisms. This provides a basis for the computational identification of cis-regulatory motifs. Results We have used a discriminative seeding DNA motif discovery algorithm for an in-depth analysis of 54 seed storage protein (SSP gene promoters from three plant families, namely Brassicaceae (mustards, Fabaceae (legumes and Poaceae (grasses using backgrounds based on complete sets of promoters from a representative species in each family, namely Arabidopsis (Arabidopsis thaliana (L. Heynh., soybean (Glycine max (L. Merr. and rice (Oryza sativa L. respectively. We have identified three conserved motifs (two RY-like and one ACGT-like in Brassicaceae and Fabaceae SSP gene promoters that are similar to experimentally characterized seed-specific cis-regulatory elements. Fabaceae SSP gene promoter sequences are also enriched in a novel, seed-specific E2Fb-like motif. Conserved motifs identified in Poaceae SSP gene promoters include a GCN4-like motif, two prolamin-box-like motifs and an Skn-1-like motif. Evidence of the presence of a variant of the TATA-box is found in the SSP gene promoters from the three plant families. Motifs discovered in SSP gene promoters were used to score whole-genome sets of promoters from Arabidopsis, soybean and rice. The highest-scoring promoters are associated with genes coding for different subunits or precursors of seed storage proteins. Conclusion Seed storage protein gene promoter motifs are conserved in diverse species, and different plant families are characterized by a distinct combination

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

Science.gov (United States)

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

2013-09-22

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

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

Directory of Open Access Journals (Sweden)

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.

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

Indian Academy of Sciences (India)

2015-09-28

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

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

DEFF Research Database (Denmark)

Dahlgaard, Katja; Troelsen, Jesper

2018-01-01

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

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

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Flavia Vischi Winck

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

AUG is the only initiation codon in eukaryotes

Energy Technology Data Exchange (ETDEWEB)

Sherman, F; McKnight, G; Stewart, J W

1980-01-01

An analysis of mutants of the yeast Saccharomyces cerevisiae indicates that AUG is the sole codon capable of initiating translation of iso-1-cytochrome c. This result with yeast and the sequence results of numerous eukaryotic genes indicate that AUG is the only initiation codon in eukaryotes; in contrast, results with Escherichia colia and bacteriophages indicate that both AUG and GUG are initiation codons in prokaryotes. The difference can be explained by the lack of the t/sup 6/ A hypermodified nucleoside (N-(9-(..beta..-D-ribofuranosyl)purin-6-ylcarbamoyl)threonine) in prokaryotic initiator tRNA and its presence in eukaryotic initiator tRNA.

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

Science.gov (United States)

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

2017-06-12

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

Cloning and bioinformatic analysis of lovastatin biosynthesis regulatory gene lovE.

Science.gov (United States)

Huang, Xin; Li, Hao-ming

2009-08-05

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

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

Science.gov (United States)

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

2010-12-01

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

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

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Guo Zheng

2006-01-01

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

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

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

A metagenome for lacustrine Cladophora (Cladophorales) reveals remarkable diversity of eukaryotic epibionts and genes relevant to materials cycling.

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Graham, Linda E; Knack, Jennifer J; Graham, Melissa E; Graham, James M; Zulkifly, Shahrizim

2015-06-01

Periphyton dominated by the cellulose-rich filamentous green alga Cladophora forms conspicuous growths along rocky marine and freshwater shorelines worldwide, providing habitat for diverse epibionts. Bacterial epibionts have been inferred to display diverse functions of biogeochemical significance: N-fixation and other redox reactions, phosphorus accumulation, and organic degradation. Here, we report taxonomic diversity of eukaryotic and prokaryotic epibionts and diversity of genes associated with materials cycling in a Cladophora metagenome sampled from Lake Mendota, Dane Co., WI, USA, during the growing season of 2012. A total of 1,060 distinct 16S, 173 18S, and 351 28S rRNA operational taxonomic units, from which >220 genera or species of bacteria (~60), protists (~80), fungi (6), and microscopic metazoa (~80), were distinguished with the use of reference databases. We inferred the presence of several algal taxa generally associated with marine systems and detected Jaoa, a freshwater periphytic ulvophyte previously thought endemic to China. We identified six distinct nifH gene sequences marking nitrogen fixation, >25 bacterial and eukaryotic cellulases relevant to sedimentary C-cycling and technological applications, and genes encoding enzymes in aerobic and anaerobic pathways for vitamin B12 biosynthesis. These results emphasize the importance of Cladophora in providing habitat for microscopic metazoa, fungi, protists, and bacteria that are often inconspicuous, yet play important roles in ecosystem biogeochemistry. © 2015 Phycological Society of America.

Global Regulatory Differences for Gene- and Cell-Based Therapies

DEFF Research Database (Denmark)

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

2017-01-01

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

PhytoREF: a reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy.

Science.gov (United States)

Decelle, Johan; Romac, Sarah; Stern, Rowena F; Bendif, El Mahdi; Zingone, Adriana; Audic, Stéphane; Guiry, Michael D; Guillou, Laure; Tessier, Désiré; Le Gall, Florence; Gourvil, Priscillia; Dos Santos, Adriana L; Probert, Ian; Vaulot, Daniel; de Vargas, Colomban; Christen, Richard

2015-11-01

Photosynthetic eukaryotes have a critical role as the main producers in most ecosystems of the biosphere. The ongoing environmental metabarcoding revolution opens the perspective for holistic ecosystems biological studies of these organisms, in particular the unicellular microalgae that often lack distinctive morphological characters and have complex life cycles. To interpret environmental sequences, metabarcoding necessarily relies on taxonomically curated databases containing reference sequences of the targeted gene (or barcode) from identified organisms. To date, no such reference framework exists for photosynthetic eukaryotes. In this study, we built the PhytoREF database that contains 6490 plastidial 16S rDNA reference sequences that originate from a large diversity of eukaryotes representing all known major photosynthetic lineages. We compiled 3333 amplicon sequences available from public databases and 879 sequences extracted from plastidial genomes, and generated 411 novel sequences from cultured marine microalgal strains belonging to different eukaryotic lineages. A total of 1867 environmental Sanger 16S rDNA sequences were also included in the database. Stringent quality filtering and a phylogeny-based taxonomic classification were applied for each 16S rDNA sequence. The database mainly focuses on marine microalgae, but sequences from land plants (representing half of the PhytoREF sequences) and freshwater taxa were also included to broaden the applicability of PhytoREF to different aquatic and terrestrial habitats. PhytoREF, accessible via a web interface (http://phytoref.fr), is a new resource in molecular ecology to foster the discovery, assessment and monitoring of the diversity of photosynthetic eukaryotes using high-throughput sequencing. © 2015 John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2018-03-01

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

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.

Synchronous versus asynchronous modeling of gene regulatory networks.

Science.gov (United States)

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

2008-09-01

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

The Reconstruction and Analysis of Gene Regulatory Networks.

Science.gov (United States)

Zheng, Guangyong; Huang, Tao

2018-01-01

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

Nucleosome mediated crosstalk between transcription factors at eukaryotic enhancers

International Nuclear Information System (INIS)

Teif, Vladimir B; Rippe, Karsten

2011-01-01

A recent study of transcription regulation in Drosophila embryonic development revealed a complex non-monotonic dependence of gene expression on the distance between binding sites of repressor and activator proteins at the corresponding enhancer cis-regulatory modules (Fakhouri et al 2010 Mol. Syst. Biol. 6 341). The repressor efficiency was high at small separations, low around 30 bp, reached a maximum at 50–60 bp, and decreased at larger distances to the activator binding sites. Here, we propose a straightforward explanation for the distance dependence of repressor activity by considering the effect of the presence of a nucleosome. Using a method that considers partial unwrapping of nucleosomal DNA from the histone octamer core, we calculated the dependence of activator binding on the repressor–activator distance and found a quantitative agreement with the distance dependence reported for the Drosophila enhancer element. In addition, the proposed model offers explanations for other distance-dependent effects at eukaryotic enhancers. (communication)

A second pathway to degrade pyrimidine nucleic acid precursors in eukaryotes

DEFF Research Database (Denmark)

Andersen, Gorm; Bjornberg, Olof; Polakova, Silvia

2008-01-01

Pyrimidine bases are the central precursors for RNA and DNA, and their intracellular pools are determined by de novo, salvage and catabolic pathways. In eukaryotes, degradation of uracil has been believed to proceed only via the reduction to dihydrouracil. Using a yeast model, Saccharomyces kluyv...... of the eukaryotic or prokaryotic genes involved in pyrimidine degradation described to date.......Pyrimidine bases are the central precursors for RNA and DNA, and their intracellular pools are determined by de novo, salvage and catabolic pathways. In eukaryotes, degradation of uracil has been believed to proceed only via the reduction to dihydrouracil. Using a yeast model, Saccharomyces......, respectively. The gene products of URC1 and URC4 are highly conserved proteins with so far unknown functions and they are present in a variety of prokaryotes and fungi. In bacteria and in some fungi, URC1 and URC4 are linked on the genome together with the gene for uracil phosphoribosyltransferase (URC6). Urc1...

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

Science.gov (United States)

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

2018-02-16

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

The cauliflower Orange gene enhances petiole elongation by suppressing expression of eukaryotic release factor 1.

Science.gov (United States)

Zhou, Xiangjun; Sun, Tian-Hu; Wang, Ning; Ling, Hong-Qing; Lu, Shan; Li, Li

2011-04-01

The cauliflower (Brassica oleracea var. botrytis) Orange (Or) gene affects plant growth and development in addition to conferring β-carotene accumulation. This study was undertaken to investigate the molecular basis for the effects of the Or gene mutation in on plant growth. The OR protein was found to interact with cauliflower and Arabidopsis eukaryotic release factor 1-2 (eRF1-2), a member of the eRF1 family, by yeast two-hybrid analysis and by bimolecular fluorescence complementation (BiFC) assay. Concomitantly, the Or mutant showed reduced expression of the BoeRF1 family genes. Transgenic cauliflower plants with suppressed expression of BoeRF1-2 and BoeRF1-3 were generated by RNA interference. Like the Or mutant, the BoeRF1 RNAi lines showed increased elongation of the leaf petiole. This long-petiole phenotype was largely caused by enhanced cell elongation, which resulted from increased cell length and elevated expression of genes involved in cell-wall loosening. These findings demonstrate that the cauliflower Or gene controls petiole elongation by suppressing the expression of eRF1 genes, and provide new insights into the molecular mechanism of leaf petiole regulation. © 2010 The Authors. New Phytologist © 2010 New Phytologist Trust.

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

Science.gov (United States)

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

2015-01-01

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

A Common Ca2+-Driven Interdomain Module Governs Eukaryotic NCX Regulation

Science.gov (United States)

Giladi, Moshe; Sasson, Yehezkel; Fang, Xianyang; Hiller, Reuben; Buki, Tal; Wang, Yun-Xing; Hirsch, Joel A.; Khananshvili, Daniel

2012-01-01

Na+/Ca2+ exchanger (NCX) proteins mediate Ca2+-fluxes across the cell membrane to maintain Ca2+ homeostasis in many cell types. Eukaryotic NCX contains Ca2+-binding regulatory domains, CBD1 and CBD2. Ca2+ binding to a primary sensor (Ca3-Ca4 sites) on CBD1 activates mammalian NCXs, whereas CALX, a Drosophila NCX ortholog, displays an inhibitory response to regulatory Ca2+. To further elucidate the underlying regulatory mechanisms, we determined the 2.7 Å crystal structure of mammalian CBD12-E454K, a two-domain construct that retains wild-type properties. In conjunction with stopped-flow kinetics and SAXS (small-angle X-ray scattering) analyses of CBD12 mutants, we show that Ca2+ binding to Ca3-Ca4 sites tethers the domains via a network of interdomain salt-bridges. This Ca2+-driven interdomain switch controls slow dissociation of “occluded” Ca2+ from the primary sensor and thus dictates Ca2+ sensing dynamics. In the Ca2+-bound conformation, the interdomain angle of CBD12 is very similar in NCX and CALX, meaning that the interdomain distances cannot account for regulatory diversity in NCX and CALX. Since the two-domain interface is nearly identical among eukaryotic NCXs, including CALX, we suggest that the Ca2+-driven interdomain switch described here represents a general mechanism for initial conduction of regulatory signals in NCX variants. PMID:22768191

Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

Science.gov (United States)

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

2018-04-01

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

Selective constraints in experimentally defined primate regulatory regions.

Directory of Open Access Journals (Sweden)

Daniel J Gaffney

2008-08-01

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

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

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Grewal Savraj S

2010-01-01

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

An interspecific fungal hybrid reveals cross-kingdom rules for allopolyploid gene expression patterns.

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Murray P Cox

2014-03-01

Full Text Available Polyploidy, a state in which the chromosome complement has undergone an increase, is a major force in evolution. Understanding the consequences of polyploidy has received much attention, and allopolyploids, which result from the union of two different parental genomes, are of particular interest because they must overcome a suite of biological responses to this merger, known as "genome shock." A key question is what happens to gene expression of the two gene copies following allopolyploidization, but until recently the tools to answer this question on a genome-wide basis were lacking. Here we utilize high throughput transcriptome sequencing to produce the first genome-wide picture of gene expression response to allopolyploidy in fungi. A novel pipeline for assigning sequence reads to the gene copies was used to quantify their expression in a fungal allopolyploid. We find that the transcriptional response to allopolyploidy is predominantly conservative: both copies of most genes are retained; over half the genes inherit parental gene expression patterns; and parental differential expression is often lost in the allopolyploid. Strikingly, the patterns of gene expression change are highly concordant with the genome-wide expression results of a cotton allopolyploid. The very different nature of these two allopolyploids implies a conserved, eukaryote-wide transcriptional response to genome merger. We provide evidence that the transcriptional responses we observe are mostly driven by intrinsic differences between the regulatory systems in the parent species, and from this propose a mechanistic model in which the cross-kingdom conservation in transcriptional response reflects conservation of the mutational processes underlying eukaryotic gene regulatory evolution. This work provides a platform to develop a universal understanding of gene expression response to allopolyploidy and suggests that allopolyploids are an exceptional system to investigate gene

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

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Takeshi Hase

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

Establishing neural crest identity: a gene regulatory recipe

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Simões-Costa, Marcos; Bronner, Marianne E.

2015-01-01

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

In silico discovery of transcription regulatory elements in Plasmodium falciparum

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Le Roch Karine G

2008-02-01

Full Text Available Abstract Background With the sequence of the Plasmodium falciparum genome and several global mRNA and protein life cycle expression profiling projects now completed, elucidating the underlying networks of transcriptional control important for the progression of the parasite life cycle is highly pertinent to the development of new anti-malarials. To date, relatively little is known regarding the specific mechanisms the parasite employs to regulate gene expression at the mRNA level, with studies of the P. falciparum genome sequence having revealed few cis-regulatory elements and associated transcription factors. Although it is possible the parasite may evoke mechanisms of transcriptional control drastically different from those used by other eukaryotic organisms, the extreme AT-rich nature of P. falciparum intergenic regions (~90% AT presents significant challenges to in silico cis-regulatory element discovery. Results We have developed an algorithm called Gene Enrichment Motif Searching (GEMS that uses a hypergeometric-based scoring function and a position-weight matrix optimization routine to identify with high-confidence regulatory elements in the nucleotide-biased and repeat sequence-rich P. falciparum genome. When applied to promoter regions of genes contained within 21 co-expression gene clusters generated from P. falciparum life cycle microarray data using the semi-supervised clustering algorithm Ontology-based Pattern Identification, GEMS identified 34 putative cis-regulatory elements associated with a variety of parasite processes including sexual development, cell invasion, antigenic variation and protein biosynthesis. Among these candidates were novel motifs, as well as many of the elements for which biological experimental evidence already exists in the Plasmodium literature. To provide evidence for the biological relevance of a cell invasion-related element predicted by GEMS, reporter gene and electrophoretic mobility shift assays

Potential of industrial biotechnology with cyanobacteria and eukaryotic microalgae.

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Wijffels, René H; Kruse, Olaf; Hellingwerf, Klaas J

2013-06-01

Both cyanobacteria and eukaryotic microalgae are promising organisms for sustainable production of bulk products such as food, feed, materials, chemicals and fuels. In this review we will summarize the potential and current biotechnological developments. Cyanobacteria are promising host organisms for the production of small molecules that can be secreted such as ethanol, butanol, fatty acids and other organic acids. Eukaryotic microalgae are interesting for products for which cellular storage is important such as proteins, lipids, starch and alkanes. For the development of new and promising lines of production, strains of both cyanobacteria and eukaryotic microalgae have to be improved. Transformation systems have been much better developed in cyanobacteria. However, several products would be preferably produced with eukaryotic microalgae. In the case of cyanobacteria a synthetic-systems biology approach has a great potential to exploit cyanobacteria as cell factories. For eukaryotic microalgae transformation systems need to be further developed. A promising strategy is transformation of heterologous (prokaryotic and eukaryotic) genes in established eukaryotic hosts such as Chlamydomonas reinhardtii. Experimental outdoor pilots under containment for the production of genetically modified cyanobacteria and microalgae are in progress. For full scale production risks of release of genetically modified organisms need to be assessed. Copyright © 2013. Published by Elsevier Ltd.

Atypical mitochondrial inheritance patterns in eukaryotes.

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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.

Genomic analysis of the hierarchical structure of regulatory networks

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Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

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

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Wilczynski, Bartek; Furlong, Eileen E M

2010-04-15

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

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

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

2014-12-01

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

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

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Baumbach Jan

2007-11-01

Full Text Available Abstract Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user can be analyzed in the context of known

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.

Compositional patterns in the genomes of unicellular eukaryotes.

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Costantini, Maria; Alvarez-Valin, Fernando; Costantini, Susan; Cammarano, Rosalia; Bernardi, Giorgio

2013-11-05

The genomes of multicellular eukaryotes are compartmentalized in mosaics of isochores, large and fairly homogeneous stretches of DNA that belong to a small number of families characterized by different average GC levels, by different gene concentration (that increase with GC), different chromatin structures, different replication timing in the cell cycle, and other different properties. A question raised by these basic results concerns how far back in evolution the compartmentalized organization of the eukaryotic genomes arose. In the present work we approached this problem by studying the compositional organization of the genomes from the unicellular eukaryotes for which full sequences are available, the sample used being representative. The average GC levels of the genomes from unicellular eukaryotes cover an extremely wide range (19%-60% GC) and the compositional patterns of individual genomes are extremely different but all genomes tested show a compositional compartmentalization. The average GC range of the genomes of unicellular eukaryotes is very broad (as broad as that of prokaryotes) and individual compositional patterns cover a very broad range from very narrow to very complex. Both features are not surprising for organisms that are very far from each other both in terms of phylogenetic distances and of environmental life conditions. Most importantly, all genomes tested, a representative sample of all supergroups of unicellular eukaryotes, are compositionally compartmentalized, a major difference with prokaryotes.

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.

Evolution of DNA replication protein complexes in eukaryotes and Archaea.

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Nicholas Chia

Full Text Available BACKGROUND: The replication of DNA in Archaea and eukaryotes requires several ancillary complexes, including proliferating cell nuclear antigen (PCNA, replication factor C (RFC, and the minichromosome maintenance (MCM complex. Bacterial DNA replication utilizes comparable proteins, but these are distantly related phylogenetically to their archaeal and eukaryotic counterparts at best. METHODOLOGY/PRINCIPAL FINDINGS: While the structures of each of the complexes do not differ significantly between the archaeal and eukaryotic versions thereof, the evolutionary dynamic in the two cases does. The number of subunits in each complex is constant across all taxa. However, they vary subtly with regard to composition. In some taxa the subunits are all identical in sequence, while in others some are homologous rather than identical. In the case of eukaryotes, there is no phylogenetic variation in the makeup of each complex-all appear to derive from a common eukaryotic ancestor. This is not the case in Archaea, where the relationship between the subunits within each complex varies taxon-to-taxon. We have performed a detailed phylogenetic analysis of these relationships in order to better understand the gene duplications and divergences that gave rise to the homologous subunits in Archaea. CONCLUSION/SIGNIFICANCE: This domain level difference in evolution suggests that different forces have driven the evolution of DNA replication proteins in each of these two domains. In addition, the phylogenies of all three gene families support the distinctiveness of the proposed archaeal phylum Thaumarchaeota.

A deeper look into transcription regulatory code by preferred pair distance templates for transcription factor binding sites

KAUST Repository

Kulakovskiy, Ivan V.

2011-08-18

Motivation: Modern experimental methods provide substantial information on protein-DNA recognition. Studying arrangements of transcription factor binding sites (TFBSs) of interacting transcription factors (TFs) advances understanding of the transcription regulatory code. Results: We constructed binding motifs for TFs forming a complex with HIF-1α at the erythropoietin 3\\'-enhancer. Corresponding TFBSs were predicted in the segments around transcription start sites (TSSs) of all human genes. Using the genome-wide set of regulatory regions, we observed several strongly preferred distances between hypoxia-responsive element (HRE) and binding sites of a particular cofactor protein. The set of preferred distances was called as a preferred pair distance template (PPDT). PPDT dramatically depended on the TF and orientation of its binding sites relative to HRE. PPDT evaluated from the genome-wide set of regulatory sequences was used to detect significant PPDT-consistent binding site pairs in regulatory regions of hypoxia-responsive genes. We believe PPDT can help to reveal the layout of eukaryotic regulatory segments. © The Author 2011. Published by Oxford University Press. All rights reserved.

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

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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.

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

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

2009-01-01

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

Fused Regression for Multi-source Gene Regulatory Network Inference.

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Kari Y Lam

2016-12-01

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

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

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

2011-01-01

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

Distinct Trajectories of Massive Recent Gene Gains and Losses in Populations of a Microbial Eukaryotic Pathogen.

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Hartmann, Fanny E; Croll, Daniel

2017-11-01

Differences in gene content are a significant source of variability within species and have an impact on phenotypic traits. However, little is known about the mechanisms responsible for the most recent gene gains and losses. We screened the genomes of 123 worldwide isolates of the major pathogen of wheat Zymoseptoria tritici for robust evidence of gene copy number variation. Based on orthology relationships in three closely related fungi, we identified 599 gene gains and 1,024 gene losses that have not yet reached fixation within the focal species. Our analyses of gene gains and losses segregating in populations showed that gene copy number variation arose preferentially in subtelomeres and in proximity to transposable elements. Recently lost genes were enriched in virulence factors and secondary metabolite gene clusters. In contrast, recently gained genes encoded mostly secreted protein lacking a conserved domain. We analyzed the frequency spectrum at loci segregating a gene presence-absence polymorphism in four worldwide populations. Recent gene losses showed a significant excess in low-frequency variants compared with genome-wide single nucleotide polymorphism, which is indicative of strong negative selection against gene losses. Recent gene gains were either under weak negative selection or neutral. We found evidence for strong divergent selection among populations at individual loci segregating a gene presence-absence polymorphism. Hence, gene gains and losses likely contributed to local adaptation. Our study shows that microbial eukaryotes harbor extensive copy number variation within populations and that functional differences among recently gained and lost genes led to distinct evolutionary trajectories. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

International Nuclear Information System (INIS)

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

2005-01-01

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

Computational challenges in modeling gene regulatory events.

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Pataskar, Abhijeet; Tiwari, Vijay K

2016-10-19

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

DNA mismatch repair and its many roles in eukaryotic cells

DEFF Research Database (Denmark)

Liu, Dekang; Keijzers, Guido; Rasmussen, Lene Juel

2017-01-01

in the clinic, and as a biomarker of cancer susceptibility in animal model systems. Prokaryotic MMR is well-characterized at the molecular and mechanistic level; however, MMR is considerably more complex in eukaryotic cells than in prokaryotic cells, and in recent years, it has become evident that MMR plays...... novel roles in eukaryotic cells, several of which are not yet well-defined or understood. Many MMR-deficient human cancer cells lack mutations in known human MMR genes, which strongly suggests that essential eukaryotic MMR components/cofactors remain unidentified and uncharacterized. Furthermore......, the mechanism by which the eukaryotic MMR machinery discriminates between the parental (template) and the daughter (nascent) DNA strand is incompletely understood and how cells choose between the EXO1-dependent and the EXO1–independent subpathways of MMR is not known. This review summarizes recent literature...

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.

A dominant control region from the human β-globin locus conferring integration site-independent gene expression.

OpenAIRE

Talbot, D.; Collis, P.; Antoniou, Michael; Vidal, M.; Grosveld, Frank; Greaves, David

1989-01-01

textabstractThe regulatory elements that determine the expression pattern of a number of eukaryotic genes expressed specifically in certain tissues have been defined and studied in detail. In general, however, the expression conferred by these elements on genes reintroduced into the genomes of cell lines and transgenic animals has turned out to be at a low level relative to that of endogenous genes, and influenced by the chromosomal site of insertion of the exogenous construct. We have previo...

Portrait of Candida Species Biofilm Regulatory Network Genes.

Science.gov (United States)

Araújo, Daniela; Henriques, Mariana; Silva, Sónia

2017-01-01

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

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.

[Eukaryotic expression of Leptospira interrogans lipL32/1-ompL1/1 fusion gene encoding genus-specific protein antigens and the immunoreactivity of expression products].

Science.gov (United States)

Yan, Jie; Zhao, Shou-feng; Mao, Ya-fei; Ruan, Ping; Luo, Yi-hui; Li, Shu-ping; Li, Li-wei

2005-01-01

To construct the eukaryotic expression system of L.interrogans lipL32/1-ompL1/1 fusion gene and to identify the immunoreactivity of expression products. PCR with linking primer was used to construct the fusion gene lipL32/1-ompL1/1. The P.pastoris eukaryotic expression system of the fusion gene, pPIC9K-lipL32/1-ompL1/1-P. pastorisGS115, was constructed after the fusion gene was cloned and sequenced. Colony with phenotype His(+)Mut(+) was isolated by using MD and MM plates and His(+) Mut(+) transformant with high resistance to G418 was screened out by using YPD plate. Using lysate of His(+) Mut(+) colony with high copies of the target gene digested with yeast lyase as the template and 5'AOX1 and 3'AOX1 as the primers, the target fusion gene in chromosome DNA of the constructed P. pastoris engineering strain was detected by PCR. Methanol in BMMY medium was used to induce the target recombinant protein rLipL32/1-rOmpL1/1 expression. rLipL32/1-rOmpL1/1 in the medium supernatant was extracted by using ammonium sulfate precipitation and Ni-NTA affinity chromatography. Output and immunoreactivity of rLipL32/1-rOmpL1/1 were measured by SDS-PAGE and Western blot methods, respectively. Amplification fragments of the obtained fusion gene lipL32/1-ompL1/1 was 1794 bp in size. The homogeneity of nucleotide and putative amino acid sequences of the fusion gene were as high as 99.94 % and 100 %, respectively, compared with the sequences of original lipL32/1 and ompL1/1 genotypes. The constructed eukaryotic expression system was able to secrete rLipL32/1-rOmpL1/1 with an output of 10 % of the total proteins in the supernatant, which located the expected position after SDS-PAGE. The rabbit anti-rLipL32/1 and anti-rOmpL1/1 sera could combine the expressed rLipL32/1-rOmpL1/1. An eukaryotic expression system with high efficiency in P.pastoris of L.interrogans lipL32/1-ompL1/1 fusion gene was successfully constructed in this study. The expressed fusion protein shows specific

Visualizing Patterns of Marine Eukaryotic Diversity from Metabarcoding Data Using QIIME.

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Leray, Matthieu; Knowlton, Nancy

2016-01-01

PCR amplification followed by deep sequencing of homologous gene regions is increasingly used to characterize the diversity and taxonomic composition of marine eukaryotic communities. This approach may generate millions of sequences for hundreds of samples simultaneously. Therefore, tools that researchers can use to visualize complex patterns of diversity for these massive datasets are essential. Efforts by microbiologists to understand the Earth and human microbiomes using high-throughput sequencing of the 16S rRNA gene has led to the development of several user-friendly, open-source software packages that can be similarly used to analyze eukaryotic datasets. Quantitative Insights Into Microbial Ecology (QIIME) offers some of the most helpful data visualization tools. Here, we describe functionalities to import OTU tables generated with any molecular marker (e.g., 18S, COI, ITS) and associated metadata into QIIME. We then present a range of analytical tools implemented within QIIME that can be used to obtain insights about patterns of alpha and beta diversity for marine eukaryotes.

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

Directory of Open Access Journals (Sweden)

Zara Ghodsi

2017-03-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-01-05

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

Simple mathematical models of gene regulatory dynamics

CERN Document Server

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

2016-01-01

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

Fractal gene regulatory networks for robust locomotion control of modular robots

DEFF Research Database (Denmark)

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

2010-01-01

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

Characterization of prokaryotic and eukaryotic promoters usinghidden Markov models

DEFF Research Database (Denmark)

Pedersen, Anders Gorm; Baldi, Pierre; Brunak, Søren

1996-01-01

In this paper we utilize hidden Markov models (HMMs) and information theory to analyze prokaryotic and eukaryotic promoters. We perform this analysis with special emphasis on the fact that promoters are divided into a number of different classes, depending on which polymerase-associated factors...... that bind to them. We find that HMMs trained on such subclasses of Escherichia coli promoters (specifically, the so-called sigma-70 and sigma-54 classes) give an excellent classification of unknown promoters with respect to sigma-class. HMMs trained on eukaryotic sequences from human genes also model nicely...

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2011-01-01

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

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

KAUST Repository

Othoum, Ghofran K

2013-05-01

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

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

KAUST Repository

Othoum, Ghofran K

2013-01-01

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

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

Science.gov (United States)

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

2007-08-01

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

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

Science.gov (United States)

Jia, Bin; Wang, Xiaodong

2013-12-17

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

Comparison of evolutionary algorithms in gene regulatory network model inference.

LENUS (Irish Health Repository)

2010-01-01

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

Phylogenetic analysis of P5 P-type ATPases, a eukaryotic lineage of secretory pathway pumps

DEFF Research Database (Denmark)

Møller, Annette; Asp, Torben; Holm, Preben Bach

2008-01-01

prokaryotic genome. Based on a protein alignment we could group the P5 ATPases into two subfamilies, P5A and P5B that, based on the number of negative charges in conserved trans-membrane segment 4, are likely to have different ion specificities. P5A ATPases are present in all eukaryotic genomes sequenced so......Eukaryotes encompass a remarkable variety of organisms and unresolved lineages. Different phylogenetic analyses have lead to conflicting conclusions as to the origin and associations between lineages and species. In this work, we investigated evolutionary relationship of a family of cation pumps...... exclusive for the secretory pathway of eukaryotes by combining the identification of lineage-specific genes with phylogenetic evolution of common genes. Sequences of P5 ATPases, which are regarded to be cation pumps in the endoplasmic reticulum (ER), were identified in all eukaryotic lineages but not in any...

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.

The capacity for multistability in small gene regulatory networks

Directory of Open Access Journals (Sweden)

Grotewold Erich

2009-09-01

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

Mitochondrial uncoupling proteins in unicellular eukaryotes.

Science.gov (United States)

Jarmuszkiewicz, Wieslawa; Woyda-Ploszczyca, Andrzej; Antos-Krzeminska, Nina; Sluse, Francis E

2010-01-01

Uncoupling proteins (UCPs) are members of the mitochondrial anion carrier protein family that are present in the mitochondrial inner membrane and mediate free fatty acid (FFA)-activated, purine nucleotide (PN)-inhibited proton conductance. Since 1999, the presence of UCPs has been demonstrated in some non-photosynthesising unicellular eukaryotes, including amoeboid and parasite protists, as well as in non-fermentative yeast and filamentous fungi. In the mitochondria of these organisms, UCP activity is revealed upon FFA-induced, PN-inhibited stimulation of resting respiration and a decrease in membrane potential, which are accompanied by a decrease in membranous ubiquinone (Q) reduction level. UCPs in unicellular eukaryotes are able to divert energy from oxidative phosphorylation and thus compete for a proton electrochemical gradient with ATP synthase. Our recent work indicates that membranous Q is a metabolic sensor that might utilise its redox state to release the PN inhibition of UCP-mediated mitochondrial uncoupling under conditions of phosphorylation and resting respiration. The action of reduced Q (QH2) could allow higher or complete activation of UCP. As this regulatory feature was demonstrated for microorganism UCPs (A. castellanii UCP), plant and mammalian UCP1 analogues, and UCP1 in brown adipose tissue, the process could involve all UCPs. Here, we discuss the functional connection and physiological role of UCP and alternative oxidase, two main energy-dissipating systems in the plant-type mitochondrial respiratory chain of unicellular eukaryotes, including the control of cellular energy balance as well as preventive action against the production of reactive oxygen species. Copyright © 2009 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

Espinosa-Soto, Carlos

2018-05-01

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

Inorganic phosphate uptake in unicellular eukaryotes.

Science.gov (United States)

Dick, Claudia F; Dos-Santos, André L A; Meyer-Fernandes, José R

2014-07-01

Inorganic phosphate (Pi) is an essential nutrient for all organisms. The route of Pi utilization begins with Pi transport across the plasma membrane. Here, we analyzed the gene sequences and compared the biochemical profiles, including kinetic and modulator parameters, of Pi transporters in unicellular eukaryotes. The objective of this review is to evaluate the recent findings regarding Pi uptake mechanisms in microorganisms, such as the fungi Neurospora crassa and Saccharomyces cerevisiae and the parasite protozoans Trypanosoma cruzi, Trypanosoma rangeli, Leishmania infantum and Plasmodium falciparum. Pi uptake is the key step of Pi homeostasis and in the subsequent signaling event in eukaryotic microorganisms. Biochemical and structural studies are important for clarifying mechanisms of Pi homeostasis, as well as Pi sensor and downstream pathways, and raise possibilities for future studies in this field. Copyright © 2014 Elsevier B.V. All rights reserved.

AtTZF gene family localizes to cytoplasmic foci

OpenAIRE

Pomeranz, Marcelo; Lin, Pei-Chi; Finer, John; Jang, Jyan-Chyun

2010-01-01

In eukaryotes, mRNA turnover and translational repression represent important regulatory steps in gene expression. Curiously, when under cellular stresses, factors involved in these processes aggregate into cytoplasmic foci known as Processing bodies (P-bodies) and Stress Granules (SGs). In animals, CCCH Tandem Zinc Finger (TZF) proteins play important roles in mRNA decay within P-bodies. TTP, a P-body localized mammalian TZF, can bind to the 3'UTRs of mRNAs containing AU-rich elements (AREs)...

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.

How and why DNA barcodes underestimate the diversity of microbial eukaryotes.

Directory of Open Access Journals (Sweden)

Gwenael Piganeau

Full Text Available BACKGROUND: Because many picoplanktonic eukaryotic species cannot currently be maintained in culture, direct sequencing of PCR-amplified 18S ribosomal gene DNA fragments from filtered sea-water has been successfully used to investigate the astounding diversity of these organisms. The recognition of many novel planktonic organisms is thus based solely on their 18S rDNA sequence. However, a species delimited by its 18S rDNA sequence might contain many cryptic species, which are highly differentiated in their protein coding sequences. PRINCIPAL FINDINGS: Here, we investigate the issue of species identification from one gene to the whole genome sequence. Using 52 whole genome DNA sequences, we estimated the global genetic divergence in protein coding genes between organisms from different lineages and compared this to their ribosomal gene sequence divergences. We show that this relationship between proteome divergence and 18S divergence is lineage dependent. Unicellular lineages have especially low 18S divergences relative to their protein sequence divergences, suggesting that 18S ribosomal genes are too conservative to assess planktonic eukaryotic diversity. We provide an explanation for this lineage dependency, which suggests that most species with large effective population sizes will show far less divergence in 18S than protein coding sequences. CONCLUSIONS: There is therefore a trade-off between using genes that are easy to amplify in all species, but which by their nature are highly conserved and underestimate the true number of species, and using genes that give a better description of the number of species, but which are more difficult to amplify. We have shown that this trade-off differs between unicellular and multicellular organisms as a likely consequence of differences in effective population sizes. We anticipate that biodiversity of microbial eukaryotic species is underestimated and that numerous "cryptic species" will become

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

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Chemmangattuvalappil Nishanth

2012-09-01

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

Three distinct modes of intron dynamics in the evolution of eukaryotes.

Science.gov (United States)

Carmel, Liran; Wolf, Yuri I; Rogozin, Igor B; Koonin, Eugene V

2007-07-01

Several contrasting scenarios have been proposed for the origin and evolution of spliceosomal introns, a hallmark of eukaryotic genes. A comprehensive probabilistic model to obtain a definitive reconstruction of intron evolution was developed and applied to 391 sets of conserved genes from 19 eukaryotic species. It is inferred that a relatively high intron density was reached early, i.e., the last common ancestor of eukaryotes contained >2.15 introns/kilobase, and the last common ancestor of multicellular life forms harbored approximately 3.4 introns/kilobase, a greater intron density than in most of the extant fungi and in some animals. The rates of intron gain and intron loss appear to have been dropping during the last approximately 1.3 billion years, with the decline in the gain rate being much steeper. Eukaryotic lineages exhibit three distinct modes of evolution of the intron-exon structure. The primary, balanced mode, apparently, operates in all lineages. In this mode, intron gain and loss are strongly and positively correlated, in contrast to previous reports on inverse correlation between these processes. The second mode involves an elevated rate of intron loss and is prevalent in several lineages, such as fungi and insects. The third mode, characterized by elevated rate of intron gain, is seen only in deep branches of the tree, indicating that bursts of intron invasion occurred at key points in eukaryotic evolution, such as the origin of animals. Intron dynamics could depend on multiple mechanisms, and in the balanced mode, gain and loss of introns might share common mechanistic features.

Arginine deiminase pathway enzymes: evolutionary history in metamonads and other eukaryotes.

Science.gov (United States)

Novák, Lukáš; Zubáčová, Zuzana; Karnkowska, Anna; Kolisko, Martin; Hroudová, Miluše; Stairs, Courtney W; Simpson, Alastair G B; Keeling, Patrick J; Roger, Andrew J; Čepička, Ivan; Hampl, Vladimír

2016-10-06

Multiple prokaryotic lineages use the arginine deiminase (ADI) pathway for anaerobic energy production by arginine degradation. The distribution of this pathway among eukaryotes has been thought to be very limited, with only two specialized groups living in low oxygen environments (Parabasalia and Diplomonadida) known to possess the complete set of all three enzymes. We have performed an extensive survey of available sequence data in order to map the distribution of these enzymes among eukaryotes and to reconstruct their phylogenies. We have found genes for the complete pathway in almost all examined representatives of Metamonada, the anaerobic protist group that includes parabasalids and diplomonads. Phylogenetic analyses indicate the presence of the complete pathway in the last common ancestor of metamonads and heterologous transformation experiments suggest its cytosolic localization in the metamonad ancestor. Outside Metamonada, the complete pathway occurs rarely, nevertheless, it was found in representatives of most major eukaryotic clades. Phylogenetic relationships of complete pathways are consistent with the presence of the Archaea-derived ADI pathway in the last common ancestor of all eukaryotes, although other evolutionary scenarios remain possible. The presence of the incomplete set of enzymes is relatively common among eukaryotes and it may be related to the fact that these enzymes are involved in other cellular processes, such as the ornithine-urea cycle. Single protein phylogenies suggest that the evolutionary history of all three enzymes has been shaped by frequent gene losses and horizontal transfers, which may sometimes be connected with their diverse roles in cellular metabolism.

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

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Xiaobo Guo

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

RNase MRP and the RNA processing cascade in the eukaryotic ancestor.

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Woodhams, Michael D; Stadler, Peter F; Penny, David; Collins, Lesley J

2007-02-08

Within eukaryotes there is a complex cascade of RNA-based macromolecules that process other RNA molecules, especially mRNA, tRNA and rRNA. An example is RNase MRP processing ribosomal RNA (rRNA) in ribosome biogenesis. One hypothesis is that this complexity was present early in eukaryotic evolution; an alternative is that an initial simpler network later gained complexity by gene duplication in lineages that led to animals, fungi and plants. Recently there has been a rapid increase in support for the complexity-early theory because the vast majority of these RNA-processing reactions are found throughout eukaryotes, and thus were likely to be present in the last common ancestor of living eukaryotes, herein called the Eukaryotic Ancestor. We present an overview of the RNA processing cascade in the Eukaryotic Ancestor and investigate in particular, RNase MRP which was previously thought to have evolved later in eukaryotes due to its apparent limited distribution in fungi and animals and plants. Recent publications, as well as our own genomic searches, find previously unknown RNase MRP RNAs, indicating that RNase MRP has a wide distribution in eukaryotes. Combining secondary structure and promoter region analysis of RNAs for RNase MRP, along with analysis of the target substrate (rRNA), allows us to discuss this distribution in the light of eukaryotic evolution. We conclude that RNase MRP can now be placed in the RNA-processing cascade of the Eukaryotic Ancestor, highlighting the complexity of RNA-processing in early eukaryotes. Promoter analyses of MRP-RNA suggest that regulation of the critical processes of rRNA cleavage can vary, showing that even these key cellular processes (for which we expect high conservation) show some species-specific variability. We present our consensus MRP-RNA secondary structure as a useful model for further searches.

Deciphering Cis-Regulatory Element Mediated Combinatorial Regulation in Rice under Blast Infected Condition.

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Arindam Deb

Full Text Available Combinations of cis-regulatory elements (CREs present at the promoters facilitate the binding of several transcription factors (TFs, thereby altering the consequent gene expressions. Due to the eminent complexity of the regulatory mechanism, the combinatorics of CRE-mediated transcriptional regulation has been elusive. In this work, we have developed a new methodology that quantifies the co-occurrence tendencies of CREs present in a set of promoter sequences; these co-occurrence scores are filtered in three consecutive steps to test their statistical significance; and the significantly co-occurring CRE pairs are presented as networks. These networks of co-occurring CREs are further transformed to derive higher order of regulatory combinatorics. We have further applied this methodology on the differentially up-regulated gene-sets of rice tissues under fungal (Magnaporthe infected conditions to demonstrate how it helps to understand the CRE-mediated combinatorial gene regulation. Our analysis includes a wide spectrum of biologically important results. The CRE pairs having a strong tendency to co-occur often exhibit very similar joint distribution patterns at the promoters of rice. We couple the network approach with experimental results of plant gene regulation and defense mechanisms and find evidences of auto and cross regulation among TF families, cross-talk among multiple hormone signaling pathways, similarities and dissimilarities in regulatory combinatorics between different tissues, etc. Our analyses have pointed a highly distributed nature of the combinatorial gene regulation facilitating an efficient alteration in response to fungal attack. All together, our proposed methodology could be an important approach in understanding the combinatorial gene regulation. It can be further applied to unravel the tissue and/or condition specific combinatorial gene regulation in other eukaryotic systems with the availability of annotated genomic

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

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Frank Emmert-Streib

2013-02-01

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

A Versatile Method to Design Stem-Loop Primer-Based Quantitative PCR Assays for Detecting Small Regulatory RNA Molecules

OpenAIRE

Czimmerer, Zsolt; Hulvely, Julianna; Simandi, Zoltan; Varallyay, Eva; Havelda, Zoltan; Szabo, Erzsebet; Varga, Attila; Dezso, Balazs; Balogh, Maria; Horvath, Attila; Domokos, Balint; Torok, Zsolt; Nagy, Laszlo; Balint, Balint L.

2013-01-01

Short regulatory RNA-s have been identified as key regulators of gene expression in eukaryotes. They have been involved in the regulation of both physiological and pathological processes such as embryonal development, immunoregulation and cancer. One of their relevant characteristics is their high stability, which makes them excellent candidates for use as biomarkers. Their number is constantly increasing as next generation sequencing methods reveal more and more details of their synthesis. T...

Characterization of prokaryotic and eukaryotic promoters using hidden Markov models

DEFF Research Database (Denmark)

Pedersen, Anders Gorm; Baldi, P.; Chauvin, Y.

1996-01-01

In this paper we utilize hidden Markov models (HMMs) and information theory to analyze prokaryotic and eukaryotic promoters. We perform this analysis with special emphasis on the fact that promoters are divided into a number of different classes, depending on which polymerase-associated factors...... that bind to them. We find that HMMs trained on such subclasses of Escherichia coli promoters (specifically, the so-called sigma 70 and sigma 54 classes) give an excellent classification of unknown promoters with respect to sigma-class. HMMs trained on eukaryotic sequences from human genes also model nicely...

Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes

Energy Technology Data Exchange (ETDEWEB)

Kuo, Alan; Grigoriev, Igor

2009-04-17

Pyrosequencing technologies such as 454/Roche and Solexa/Illumina vastly lower the cost of nucleotide sequencing compared to the traditional Sanger method, and thus promise to greatly expand the number of sequenced eukaryotic genomes. However, the new technologies also bring new challenges such as shorter reads and new kinds and higher rates of sequencing errors, which complicate genome assembly and gene prediction. At JGI we are deploying 454 technology for the sequencing and assembly of ever-larger eukaryotic genomes. Here we describe our first whole-genome annotation of a purely 454-sequenced fungal genome that is larger than a yeast (>30 Mbp). The pezizomycotine (filamentous ascomycote) Aspergillus carbonarius belongs to the Aspergillus section Nigri species complex, members of which are significant as platforms for bioenergy and bioindustrial technology, as members of soil microbial communities and players in the global carbon cycle, and as agricultural toxigens. Application of a modified version of the standard JGI Annotation Pipeline has so far predicted ~;;10k genes. ~;;12percent of these preliminary annotations suffer a potential frameshift error, which is somewhat higher than the ~;;9percent rate in the Sanger-sequenced and conventionally assembled and annotated genome of fellow Aspergillus section Nigri member A. niger. Also,>90percent of A. niger genes have potential homologs in the A. carbonarius preliminary annotation. Weconclude, and with further annotation and comparative analysis expect to confirm, that 454 sequencing strategies provide a promising substrate for annotation of modestly sized eukaryotic genomes. We will also present results of annotation of a number of other pyrosequenced fungal genomes of bioenergy interest.

On the Archaeal Origins of Eukaryotes and the Challenges of Inferring Phenotype from Genotype.

Science.gov (United States)

Dey, Gautam; Thattai, Mukund; Baum, Buzz

2016-07-01

If eukaryotes arose through a merger between archaea and bacteria, what did the first true eukaryotic cell look like? A major step toward an answer came with the discovery of Lokiarchaeum, an archaeon whose genome encodes small GTPases related to those used by eukaryotes to regulate membrane traffic. Although 'Loki' cells have yet to be seen, their existence has prompted the suggestion that the archaeal ancestor of eukaryotes engulfed the future mitochondrion by phagocytosis. We propose instead that the archaeal ancestor was a relatively simple cell, and that eukaryotic cellular organization arose as the result of a gradual transfer of bacterial genes and membranes driven by an ever-closer symbiotic partnership between a bacterium and an archaeon. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

OpenAIRE

Kreiman, Gabriel

2004-01-01

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

Inferring the conservative causal core of gene regulatory networks

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Emmert-Streib Frank

2010-09-01

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

Inferring the conservative causal core of gene regulatory networks.

Science.gov (United States)

Altay, Gökmen; Emmert-Streib, Frank

2010-09-28

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

Guanine nucleotide binding to the Bateman domain mediates the allosteric inhibition of eukaryotic IMP dehydrogenases

Science.gov (United States)

Buey, Rubén M.; Ledesma-Amaro, Rodrigo; Velázquez-Campoy, Adrián; Balsera, Mónica; Chagoyen, Mónica; de Pereda, José M.; Revuelta, José L.

2015-11-01

Inosine-5'-monophosphate dehydrogenase (IMPDH) plays key roles in purine nucleotide metabolism and cell proliferation. Although IMPDH is a widely studied therapeutic target, there is limited information about its physiological regulation. Using Ashbya gossypii as a model, we describe the molecular mechanism and the structural basis for the allosteric regulation of IMPDH by guanine nucleotides. We report that GTP and GDP bind to the regulatory Bateman domain, inducing octamers with compromised catalytic activity. Our data suggest that eukaryotic and prokaryotic IMPDHs might have developed different regulatory mechanisms, with GTP/GDP inhibiting only eukaryotic IMPDHs. Interestingly, mutations associated with human retinopathies map into the guanine nucleotide-binding sites including a previously undescribed non-canonical site and disrupt allosteric inhibition. Together, our results shed light on the mechanisms of the allosteric regulation of enzymes mediated by Bateman domains and provide a molecular basis for certain retinopathies, opening the door to new therapeutic approaches.

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

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Allan Andrew C

2008-07-01

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

Symbiosis and the origin of eukaryotic motility

Science.gov (United States)

Margulis, L.; Hinkle, G.

1991-01-01

Ongoing work to test the hypothesis of the origin of eukaryotic cell organelles by microbial symbioses is discussed. Because of the widespread acceptance of the serial endosymbiotic theory (SET) of the origin of plastids and mitochondria, the idea of the symbiotic origin of the centrioles and axonemes for spirochete bacteria motility symbiosis was tested. Intracellular microtubular systems are purported to derive from symbiotic associations between ancestral eukaryotic cells and motile bacteria. Four lines of approach to this problem are being pursued: (1) cloning the gene of a tubulin-like protein discovered in Spirocheata bajacaliforniesis; (2) seeking axoneme proteins in spirochets by antibody cross-reaction; (3) attempting to cultivate larger, free-living spirochetes; and (4) studying in detail spirochetes (e.g., Cristispira) symbiotic with marine animals. Other aspects of the investigation are presented.

Dynamic SPR monitoring of yeast nuclear protein binding to a cis-regulatory element

International Nuclear Information System (INIS)

Mao, Grace; Brody, James P.

2007-01-01

Gene expression is controlled by protein complexes binding to short specific sequences of DNA, called cis-regulatory elements. Expression of most eukaryotic genes is controlled by dozens of these elements. Comprehensive identification and monitoring of these elements is a major goal of genomics. In pursuit of this goal, we are developing a surface plasmon resonance (SPR) based assay to identify and monitor cis-regulatory elements. To test whether we could reliably monitor protein binding to a regulatory element, we immobilized a 16 bp region of Saccharomyces cerevisiae chromosome 5 onto a gold surface. This 16 bp region of DNA is known to bind several proteins and thought to control expression of the gene RNR1, which varies through the cell cycle. We synchronized yeast cell cultures, and then sampled these cultures at a regular interval. These samples were processed to purify nuclear lysate, which was then exposed to the sensor. We found that nuclear protein binds this particular element of DNA at a significantly higher rate (as compared to unsynchronized cells) during G1 phase. Other time points show levels of DNA-nuclear protein binding similar to the unsynchronized control. We also measured the apparent association complex of the binding to be 0.014 s -1 . We conclude that (1) SPR-based assays can monitor DNA-nuclear protein binding and that (2) for this particular cis-regulatory element, maximum DNA-nuclear protein binding occurs during G1 phase

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

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Jennifer Ferguson

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

Small RNA-Controlled Gene Regulatory Networks in Pseudomonas putida

DEFF Research Database (Denmark)

Bojanovic, Klara

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

EUPAN enables pan-genome studies of a large number of eukaryotic genomes.

Science.gov (United States)

Hu, Zhiqiang; Sun, Chen; Lu, Kuang-Chen; Chu, Xixia; Zhao, Yue; Lu, Jinyuan; Shi, Jianxin; Wei, Chaochun

2017-08-01

Pan-genome analyses are routinely carried out for bacteria to interpret the within-species gene presence/absence variations (PAVs). However, pan-genome analyses are rare for eukaryotes due to the large sizes and higher complexities of their genomes. Here we proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing depth. In the previous studies, we demonstrated the effectiveness and high accuracy of EUPAN in the pan-genome analysis of 453 rice genomes, in which we also revealed widespread gene PAVs among individual rice genomes. Moreover, EUPAN can be directly applied to the current re-sequencing projects primarily focusing on single nucleotide polymorphisms. EUPAN is implemented in Perl, R and C ++. It is supported under Linux and preferred for a computer cluster with LSF and SLURM job scheduling system. EUPAN together with its standard operating procedure (SOP) is freely available for non-commercial use (CC BY-NC 4.0) at http://cgm.sjtu.edu.cn/eupan/index.html . ccwei@sjtu.edu.cn or jianxin.shi@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Introns Protect Eukaryotic Genomes from Transcription-Associated Genetic Instability.

Science.gov (United States)

Bonnet, Amandine; Grosso, Ana R; Elkaoutari, Abdessamad; Coleno, Emeline; Presle, Adrien; Sridhara, Sreerama C; Janbon, Guilhem; Géli, Vincent; de Almeida, Sérgio F; Palancade, Benoit

2017-08-17

Transcription is a source of genetic instability that can notably result from the formation of genotoxic DNA:RNA hybrids, or R-loops, between the nascent mRNA and its template. Here we report an unexpected function for introns in counteracting R-loop accumulation in eukaryotic genomes. Deletion of endogenous introns increases R-loop formation, while insertion of an intron into an intronless gene suppresses R-loop accumulation and its deleterious impact on transcription and recombination in yeast. Recruitment of the spliceosome onto the mRNA, but not splicing per se, is shown to be critical to attenuate R-loop formation and transcription-associated genetic instability. Genome-wide analyses in a number of distant species differing in their intron content, including human, further revealed that intron-containing genes and the intron-richest genomes are best protected against R-loop accumulation and subsequent genetic instability. Our results thereby provide a possible rationale for the conservation of introns throughout the eukaryotic lineage. Copyright © 2017 Elsevier Inc. All rights reserved.

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).

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

Regulation of endogenous human gene expression by ligand-inducible TALE transcription factors.

Science.gov (United States)

Mercer, Andrew C; Gaj, Thomas; Sirk, Shannon J; Lamb, Brian M; Barbas, Carlos F

2014-10-17

The construction of increasingly sophisticated synthetic biological circuits is dependent on the development of extensible tools capable of providing specific control of gene expression in eukaryotic cells. Here, we describe a new class of synthetic transcription factors that activate gene expression in response to extracellular chemical stimuli. These inducible activators consist of customizable transcription activator-like effector (TALE) proteins combined with steroid hormone receptor ligand-binding domains. We demonstrate that these ligand-responsive TALE transcription factors allow for tunable and conditional control of gene activation and can be used to regulate the expression of endogenous genes in human cells. Since TALEs can be designed to recognize any contiguous DNA sequence, the conditional gene regulatory system described herein will enable the design of advanced synthetic gene networks.

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

Science.gov (United States)

2014-01-01

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

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

Science.gov (United States)

Meier, Daniel; Schindler, Detlev

2011-01-01

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

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

Directory of Open Access Journals (Sweden)

Daniel Meier

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

Gene organization in rice revealed by full-length cDNA mapping and gene expression analysis through microarray.

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Kouji Satoh

Full Text Available Rice (Oryza sativa L. is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE genes, 33K annotated non-expressed (ANE genes, and 5.5K non-annotated expressed (NAE genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria.

GenColors-based comparative genome databases for small eukaryotic genomes.

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Felder, Marius; Romualdi, Alessandro; Petzold, Andreas; Platzer, Matthias; Sühnel, Jürgen; Glöckner, Gernot

2013-01-01

Many sequence data repositories can give a quick and easily accessible overview on genomes and their annotations. Less widespread is the possibility to compare related genomes with each other in a common database environment. We have previously described the GenColors database system (http://gencolors.fli-leibniz.de) and its applications to a number of bacterial genomes such as Borrelia, Legionella, Leptospira and Treponema. This system has an emphasis on genome comparison. It combines data from related genomes and provides the user with an extensive set of visualization and analysis tools. Eukaryote genomes are normally larger than prokaryote genomes and thus pose additional challenges for such a system. We have, therefore, adapted GenColors to also handle larger datasets of small eukaryotic genomes and to display eukaryotic gene structures. Further recent developments include whole genome views, genome list options and, for bacterial genome browsers, the display of horizontal gene transfer predictions. Two new GenColors-based databases for two fungal species (http://fgb.fli-leibniz.de) and for four social amoebas (http://sacgb.fli-leibniz.de) were set up. Both new resources open up a single entry point for related genomes for the amoebozoa and fungal research communities and other interested users. Comparative genomics approaches are greatly facilitated by these resources.

Transcription factor IID in the Archaea: sequences in the Thermococcus celer genome would encode a product closely related to the TATA-binding protein of eukaryotes

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Marsh, T. L.; Reich, C. I.; Whitelock, R. B.; Olsen, G. J.; Woese, C. R. (Principal Investigator)

1994-01-01

The first step in transcription initiation in eukaryotes is mediated by the TATA-binding protein, a subunit of the transcription factor IID complex. We have cloned and sequenced the gene for a presumptive homolog of this eukaryotic protein from Thermococcus celer, a member of the Archaea (formerly archaebacteria). The protein encoded by the archaeal gene is a tandem repeat of a conserved domain, corresponding to the repeated domain in its eukaryotic counterparts. Molecular phylogenetic analyses of the two halves of the repeat are consistent with the duplication occurring before the divergence of the archael and eukaryotic domains. In conjunction with previous observations of similarity in RNA polymerase subunit composition and sequences and the finding of a transcription factor IIB-like sequence in Pyrococcus woesei (a relative of T. celer) it appears that major features of the eukaryotic transcription apparatus were well-established before the origin of eukaryotic cellular organization. The divergence between the two halves of the archael protein is less than that between the halves of the individual eukaryotic sequences, indicating that the average rate of sequence change in the archael protein has been less than in its eukaryotic counterparts. To the extent that this lower rate applies to the genome as a whole, a clearer picture of the early genes (and gene families) that gave rise to present-day genomes is more apt to emerge from the study of sequences from the Archaea than from the corresponding sequences from eukaryotes.

Proton-pumping rhodopsins are abundantly expressed by microbial eukaryotes in a high-Arctic fjord.

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Vader, Anna; Laughinghouse, Haywood D; Griffiths, Colin; Jakobsen, Kjetill S; Gabrielsen, Tove M

2018-02-01

Proton-pumping rhodopsins provide an alternative pathway to photosynthesis by which solar energy can enter the marine food web. Rhodopsin genes are widely found in marine bacteria, also in the Arctic, and were recently reported from several eukaryotic lineages. So far, little is known about rhodopsin expression in Arctic eukaryotes. In this study, we used metatranscriptomics and 18S rDNA tag sequencing to examine the mid-summer function and composition of marine protists (size 0.45-10 µm) in the high-Arctic Billefjorden (Spitsbergen), especially focussing on the expression of microbial proton-pumping rhodopsins. Rhodopsin transcripts were highly abundant, at a level similar to that of genes involved in photosynthesis. Phylogenetic analyses placed the environmental rhodopsins within disparate eukaryotic lineages, including dinoflagellates, stramenopiles, haptophytes and cryptophytes. Sequence comparison indicated the presence of several functional types, including xanthorhodopsins and a eukaryotic clade of proteorhodopsin. Transcripts belonging to the proteorhodopsin clade were also abundant in published metatranscriptomes from other oceanic regions, suggesting a global distribution. The diversity and abundance of rhodopsins show that these light-driven proton pumps play an important role in Arctic microbial eukaryotes. Understanding this role is imperative to predicting the future of the Arctic marine ecosystem faced by a changing light climate due to diminishing sea-ice. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

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

Czech Academy of Sciences Publication Activity Database

Hatina, J.; Jansa, Petr; Forejt, Jiří

2001-01-01

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

Exploring the bZIP transcription factor regulatory network in Neurospora crassa.

Science.gov (United States)

Tian, Chaoguang; Li, Jingyi; Glass, N Louise

2011-03-01

Transcription factors (TFs) are key nodes of regulatory networks in eukaryotic organisms, including filamentous fungi such as Neurospora crassa. The 178 predicted DNA-binding TFs in N. crassa are distributed primarily among six gene families, which represent an ancient expansion in filamentous ascomycete genomes; 98 TF genes show detectable expression levels during vegetative growth of N. crassa, including 35 that show a significant difference in expression level between hyphae at the periphery versus hyphae in the interior of a colony. Regulatory networks within a species genome include paralogous TFs and their respective target genes (TF regulon). To investigate TF network evolution in N. crassa, we focused on the basic leucine zipper (bZIP) TF family, which contains nine members. We performed baseline transcriptional profiling during vegetative growth of the wild-type and seven isogenic, viable bZIP deletion mutants. We further characterized the regulatory network of one member of the bZIP family, NCU03905. NCU03905 encodes an Ap1-like protein (NcAp-1), which is involved in resistance to multiple stress responses, including oxidative and heavy metal stress. Relocalization of NcAp-1 from the cytoplasm to the nucleus was associated with exposure to stress. A comparison of the NcAp-1 regulon with Ap1-like regulons in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans and Aspergillus fumigatus showed both conservation and divergence. These data indicate how N. crassa responds to stress and provide information on pathway evolution.

Noise minimization in eukaryotic gene expression.

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Hunter B Fraser

2004-06-01

Full Text Available 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.

Noise minimization in eukaryotic gene expression

Energy Technology Data Exchange (ETDEWEB)

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.

Noise minimization in eukaryotic gene expression

International Nuclear Information System (INIS)

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

2004-01-01

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

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

Science.gov (United States)

Newton, Richard; Wernisch, Lorenz

2014-01-01

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

Gene name ambiguity of eukaryotic nomenclatures.

Science.gov (United States)

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

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.

On the dynamics of a gene regulatory network

International Nuclear Information System (INIS)

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

2006-01-01

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

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

Directory of Open Access Journals (Sweden)

Lien Huang-Chun

2009-03-01

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

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

Science.gov (United States)

Gazestani, Vahid H; Salavati, Reza

2015-01-01

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

Syndromes associated with Homo sapiens pol II regulatory genes.

Science.gov (United States)

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

2000-01-01

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

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

Science.gov (United States)

Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

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

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

Science.gov (United States)

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

2018-05-14

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

Genetic exchange in eukaryotes through horizontal transfer: connected by the mobilome.

Science.gov (United States)

Wallau, Gabriel Luz; Vieira, Cristina; Loreto, Élgion Lúcio Silva

2018-01-01

All living species contain genetic information that was once shared by their common ancestor. DNA is being inherited through generations by vertical transmission (VT) from parents to offspring and from ancestor to descendant species. This process was considered the sole pathway by which biological entities exchange inheritable information. However, Horizontal Transfer (HT), the exchange of genetic information by other means than parents to offspring, was discovered in prokaryotes along with strong evidence showing that it is a very important process by which prokaryotes acquire new genes. For some time now, it has been a scientific consensus that HT events were rare and non-relevant for evolution of eukaryotic species, but there is growing evidence supporting that HT is an important and frequent phenomenon in eukaryotes as well. Here, we will discuss the latest findings regarding HT among eukaryotes, mainly HT of transposons (HTT), establishing HTT once and for all as an important phenomenon that should be taken into consideration to fully understand eukaryotes genome evolution. In addition, we will discuss the latest development methods to detect such events in a broader scale and highlight the new approaches which should be pursued by researchers to fill the knowledge gaps regarding HTT among eukaryotes.

Comparative radiobiology of genetic loci of eukaryots as the basis of the general theory of mutations

International Nuclear Information System (INIS)

Aleksandrov, I.D.

1983-01-01

One of the fundamental problems of modern molecular cellular radiobiology is to reveal general and peculiar processes of the formation of gene mutations and chromosome aberrations in each stage of their formation in the irradiated genome of the higher eukaryots. The solution of the problems depends on the development of research within the framework of comparative radiobiology of genetic loci of the higher eukaryots that makes it possible to study quantitative regularities in the formation of gene (point) mutations and chromosome aberrations in one object and in the same experiment

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

Science.gov (United States)

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

2013-09-12

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

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

OpenAIRE

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

2009-01-01

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

Consequences of reductive evolution for gene expression in an obligate endosymbiont.

Science.gov (United States)

Wilcox, Jennifer L; Dunbar, Helen E; Wolfinger, Russell D; Moran, Nancy A

2003-06-01

The smallest cellular genomes are found in obligate symbiotic and pathogenic bacteria living within eukaryotic hosts. In comparison with large genomes of free-living relatives, these reduced genomes are rearranged and have lost most regulatory elements. To test whether reduced bacterial genomes incur reduced regulatory capacities, we used full-genome microarrays to evaluate transcriptional response to environmental stress in Buchnera aphidicola, the obligate endosymbiont of aphids. The 580 genes of the B. aphidicola genome represent a subset of the 4500 genes known from the related organism, Escherichia coli. Although over 20 orthologues of E. coli heat stress (HS) genes are retained by B. aphidicola, only five were differentially expressed after near-lethal heat stress treatments, and only modest shifts were observed. Analyses of upstream regulatory regions revealed loss or degradation of most HS (sigma32) promoters. Genomic rearrangements downstream of an intact HS promoter yielded upregulation of a functionally unrelated and an inactivated gene. Reanalyses of comparable experimental array data for E. coli and Bacillus subtilis revealed that genome-wide differential expression was significantly lower in B. aphidicola. Our demonstration of a diminished stress response validates reports of temperature sensitivity in B. aphidicola and suggests that this reduced bacterial genome exhibits transcriptional inflexibility.

RNA-Binding Proteins in Trichomonas vaginalis: Atypical Multifunctional Proteins Involved in a Posttranscriptional Iron Regulatory Mechanism

Science.gov (United States)

Figueroa-Angulo, Elisa E.; Calla-Choque, Jaeson S.; Mancilla-Olea, Maria Inocente; Arroyo, Rossana

2015-01-01

Iron homeostasis is highly regulated in vertebrates through a regulatory system mediated by RNA-protein interactions between the iron regulatory proteins (IRPs) that interact with an iron responsive element (IRE) located in certain mRNAs, dubbed the IRE-IRP regulatory system. Trichomonas vaginalis, the causal agent of trichomoniasis, presents high iron dependency to regulate its growth, metabolism, and virulence properties. Although T. vaginalis lacks IRPs or proteins with aconitase activity, possesses gene expression mechanisms of iron regulation at the transcriptional and posttranscriptional levels. However, only one gene with iron regulation at the transcriptional level has been described. Recently, our research group described an iron posttranscriptional regulatory mechanism in the T. vaginalis tvcp4 and tvcp12 cysteine proteinase mRNAs. The tvcp4 and tvcp12 mRNAs have a stem-loop structure in the 5'-coding region or in the 3'-UTR, respectively that interacts with T. vaginalis multifunctional proteins HSP70, α-Actinin, and Actin under iron starvation condition, causing translation inhibition or mRNA stabilization similar to the previously characterized IRE-IRP system in eukaryotes. Herein, we summarize recent progress and shed some light on atypical RNA-binding proteins that may participate in the iron posttranscriptional regulation in T. vaginalis. PMID:26703754

Eelgrass Leaf Surface Microbiomes Are Locally Variable and Highly Correlated with Epibiotic Eukaryotes

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Mia M. Bengtsson

2017-07-01

Full Text Available Eelgrass (Zostera marina is a marine foundation species essential for coastal ecosystem services around the northern hemisphere. Like all macroscopic organisms, it possesses a microbiome (here defined as an associated prokaryotic community which may play critical roles in modulating the interaction of eelgrass with its environment. For example, its leaf surface microbiome could inhibit or attract eukaryotic epibionts which may overgrow the eelgrass leading to reduced primary productivity and subsequent eelgrass meadow decline. We used amplicon sequencing of the 16S and 18S rRNA genes of prokaryotes and eukaryotes to assess the leaf surface microbiome (prokaryotes as well as eukaryotic epibionts in- and outside lagoons on the German Baltic Sea coast. Prokaryote microbiomes varied substantially both between sites inside lagoons and between open coastal and lagoon sites. Water depth, leaf area and biofilm chlorophyll a concentration explained a large amount of variation in both prokaryotic and eukaryotic community composition. The prokaryotic microbiome and eukaryotic epibiont communities were highly correlated, and network analysis revealed disproportionate co-occurrence between a limited number of eukaryotic taxa and several bacterial taxa. This suggests that eelgrass leaf surfaces are home to a mosaic of microbiomes of several epibiotic eukaryotes, in addition to the microbiome of the eelgrass itself. Our findings thereby underline that eukaryotic diversity should be taken into account in order to explain prokaryotic microbiome assembly and dynamics in aquatic environments.

Eukaryotic elongation factor 1-beta interacts with the 5' untranslated region of the M gene of Nipah virus to promote mRNA translation.

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Uchida, Shotaro; Sato, Hiroki; Yoneda, Misako; Kai, Chieko

2016-09-01

Nipah virus belongs to the genus Henipavirus in the family Paramyxoviridae, and its RNA genome is larger than those of other paramyxoviruses because it has long untranslated regions (UTRs) in each gene. However, the functions of these UTRs are not fully understood. In this study, we investigated the functions of the 5' UTRs and found that the 5' UTR of the M gene upregulated the translation of a reporter gene. Using an RNA pull-down assay, we showed that eukaryotic elongation factor 1-beta (EEF1B2) interacts with nucleotides 81-100 of the M 5' UTR and specifically enhances its translation efficiency. Our results suggest that the M 5' UTR promotes the production of M protein and viral budding by recruiting EEF1B2.

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

International Nuclear Information System (INIS)

Whittemore, L.A.; Maniatis, T.

1990-01-01

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

Predictive modelling of gene expression from transcriptional regulatory elements.

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

2015-07-01

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

Eukaryotic resistance to fluoride toxicity mediated by a widespread family of fluoride export proteins.

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Li, Sanshu; Smith, Kathryn D; Davis, Jared H; Gordon, Patricia B; Breaker, Ronald R; Strobel, Scott A

2013-11-19

Fluorine is an abundant element and is toxic to organisms from bacteria to humans, but the mechanisms by which eukaryotes resist fluoride toxicity are unknown. The Escherichia coli gene crcB was recently shown to be regulated by a fluoride-responsive riboswitch, implicating it in fluoride response. There are >8,000 crcB homologs across all domains of life, indicating that it has an important role in biology. Here we demonstrate that eukaryotic homologs [renamed FEX (fluoride exporter)] function in fluoride export. FEX KOs in three eukaryotic model organisms, Neurospora crassa, Saccharomyces cerevisiae, and Candida albicans, are highly sensitized to fluoride (>200-fold) but not to other halides. Some of these KO strains are unable to grow in fluoride concentrations found in tap water. Using the radioactive isotope of fluoride, (18)F, we developed an assay to measure the intracellular fluoride concentration and show that the FEX deletion strains accumulate fluoride in excess of the external concentration, providing direct evidence of FEX function in fluoride efflux. In addition, they are more sensitive to lower pH in the presence of fluoride. These results demonstrate that eukaryotic FEX genes encode a previously unrecognized class of fluoride exporter necessary for survival in standard environmental conditions.

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

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

2014-03-07

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

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

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

2014-01-01

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

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

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

2012-01-01

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

An SVD-based comparison of nine whole eukaryotic genomes supports a coelomate rather than ecdysozoan lineage

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Stuart Gary W

2004-12-01

Full Text Available Abstract Background Eukaryotic whole genome sequences are accumulating at an impressive rate. Effective methods for comparing multiple whole eukaryotic genomes on a large scale are needed. Most attempted solutions involve the production of large scale alignments, and many of these require a high stringency pre-screen for putative orthologs in order to reduce the effective size of the dataset and provide a reasonably high but unknown fraction of correctly aligned homologous sites for comparison. As an alternative, highly efficient methods that do not require the pre-alignment of operationally defined orthologs are also being explored. Results A non-alignment method based on the Singular Value Decomposition (SVD was used to compare the predicted protein complement of nine whole eukaryotic genomes ranging from yeast to man. This analysis resulted in the simultaneous identification and definition of a large number of well conserved motifs and gene families, and produced a species tree supporting one of two conflicting hypotheses of metazoan relationships. Conclusions Our SVD-based analysis of the entire protein complement of nine whole eukaryotic genomes suggests that highly conserved motifs and gene families can be identified and effectively compared in a single coherent definition space for the easy extraction of gene and species trees. While this occurs without the explicit definition of orthologs or homologous sites, the analysis can provide a basis for these definitions.

Communities of microbial eukaryotes in the mammalian gut within the context of environmental eukaryotic diversity

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Parfrey, Laura Wegener; Walters, William A.; Lauber, Christian L.; Clemente, Jose C.; Berg-Lyons, Donna; Teiling, Clotilde; Kodira, Chinnappa; Mohiuddin, Mohammed; Brunelle, Julie; Driscoll, Mark; Fierer, Noah; Gilbert, Jack A.; Knight, Rob

2014-06-19

Eukaryotic microbes (protists) residing in the vertebrate gut influence host health and disease, but their diversity and distribution in healthy hosts is poorly understood. Protists found in the gut are typically considered parasites, but many are commensal and some are beneficial. Further, the hygiene hypothesis predicts that association with our co-evolved microbial symbionts may be important to overall health. It is therefore imperative that we understand the normal diversity of our eukaryotic gut microbiota to test for such effects and avoid eliminating commensal organisms. We assembled a dataset of healthy individuals from two populations, one with traditional, agrarian lifestyles and a second with modern, westernized lifestyles, and characterized the human eukaryotic microbiota via high-throughput sequencing. To place the human gut microbiota within a broader context our dataset also includes gut samples from diverse mammals and samples from other aquatic and terrestrial environments. We curated the SILVA ribosomal database to reflect current knowledge of eukaryotic taxonomy and employ it as a phylogenetic framework to compare eukaryotic diversity across environment. We show that adults from the non-western population harbor a diverse community of protists, and diversity in the human gut is comparable to that in other mammals. However, the eukaryotic microbiota of the western population appears depauperate. The distribution of symbionts found in mammals reflects both host phylogeny and diet. Eukaryotic microbiota in the gut are less diverse and more patchily distributed than bacteria. More broadly, we show that eukaryotic communities in the gut are less diverse than in aquatic and terrestrial habitats, and few taxa are shared across habitat types, and diversity patterns of eukaryotes are correlated with those observed for bacteria. These results outline the distribution and diversity of microbial eukaryotic communities in the mammalian gut and across

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

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

2015-11-14

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

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

NARCIS (Netherlands)

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

2009-01-01

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

Precise regulation of gene expression dynamics favors complex promoter architectures.

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Dirk Müller

2009-01-01

Full Text Available Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure.

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

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

2007-11-01

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

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

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Lan Chung-Yu

2008-09-01

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

The BDGP gene disruption project: Single transposon insertions associated with 40 percent of Drosophila genes

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Bellen, Hugo J.; Levis, Robert W.; Liao, Guochun; He, Yuchun; Carlson, Joseph W.; Tsang, Garson; Evans-Holm, Martha; Hiesinger, P. Robin; Schulze, Karen L.; Rubin, Gerald M.; Hoskins, Roger A.; Spradling, Allan C.

2004-01-13

The Berkeley Drosophila Genome Project (BDGP) strives to disrupt each Drosophila gene by the insertion of a single transposable element. As part of this effort, transposons in more than 30,000 fly strains were localized and analyzed relative to predicted Drosophila gene structures. Approximately 6,300 lines that maximize genomic coverage were selected to be sent to the Bloomington Stock Center for public distribution, bringing the size of the BDGP gene disruption collection to 7,140 lines. It now includes individual lines predicted to disrupt 5,362 of the 13,666 currently annotated Drosophila genes (39 percent). Other lines contain an insertion at least 2 kb from others in the collection and likely mutate additional incompletely annotated or uncharacterized genes and chromosomal regulatory elements. The remaining strains contain insertions likely to disrupt alternative gene promoters or to allow gene mis-expression. The expanded BDGP gene disruption collection provides a public resource that will facilitate the application of Drosophila genetics to diverse biological problems. Finally, the project reveals new insight into how transposons interact with a eukaryotic genome and helps define optimal strategies for using insertional mutagenesis as a genomic tool.

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

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

2015-12-01

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

Genome-wide computational identification of microRNAs and their targets in the deep-branching eukaryote Giardia lamblia.

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Zhang, Yan-Qiong; Chen, Dong-Liang; Tian, Hai-Feng; Zhang, Bao-Hong; Wen, Jian-Fan

2009-10-01

Using a combined computational program, we identified 50 potential microRNAs (miRNAs) in Giardia lamblia, one of the most primitive unicellular eukaryotes. These miRNAs are unique to G. lamblia and no homologues have been found in other organisms; miRNAs, currently known in other species, were not found in G. lamblia. This suggests that miRNA biogenesis and miRNA-mediated gene regulation pathway may evolve independently, especially in evolutionarily distant lineages. A majority (43) of the predicted miRNAs are located at one single locus; however, some miRNAs have two or more copies in the genome. Among the 58 miRNA genes, 28 are located in the intergenic regions whereas 30 are present in the anti-sense strands of the protein-coding sequences. Five predicted miRNAs are expressed in G. lamblia trophozoite cells evidenced by expressed sequence tags or RT-PCR. Thirty-seven identified miRNAs may target 50 protein-coding genes, including seven variant-specific surface proteins (VSPs). Our findings provide a clue that miRNA-mediated gene regulation may exist in the early stage of eukaryotic evolution, suggesting that it is an important regulation system ubiquitous in eukaryotes.

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

Science.gov (United States)

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

2018-07-01

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

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

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

2006-07-01

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

Avian leukosis virus is a versatile eukaryotic platform for polypeptide display

International Nuclear Information System (INIS)

Khare, Pranay D.; Russell, Stephen J.; Federspiel, Mark J.

2003-01-01

Display technology refers to methods of generating libraries of modularly coded biomolecules and screening them for particular properties. Retroviruses are good candidates to be a eukaryotic viral platform for the display of polypeptides synthesized in eukaryotic cells. Here we demonstrate that avian leukosis virus (ALV) provides an ideal platform for display of nonviral polyaeptides expressed in a eukaryotic cell substrate. Different sizes of polypeptides were genetically fused to the extreme N-terminus of the ALV envelope glycoprotein in an ALV infectious clone containing an alkaline phosphatase reporter gene. The chimeric envelope glycoproteins were efficiently incorporated into virions and were stably displayed on the surface of the virions through multiple virus replication cycles. The foreign polypeptides did not interfere with the attachment and entry functions of the underlying ALV envelope glycoproteins. The displayed polypeptides were fully functional and could efficiently mediate attachment of the recombinant viruses to their respective cognate receptors. This study demonstrates that ALV is an ideal display platform for the generation and selection of libraries of polypeptides where there is a need for expression, folding, and posttranslational modification in the endoplasmic reticulum of eukaryotic cells

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

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

2014-01-01

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

Initiation of translation in bacteria by a structured eukaryotic IRES RNA.

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Colussi, Timothy M; Costantino, David A; Zhu, Jianyu; Donohue, John Paul; Korostelev, Andrei A; Jaafar, Zane A; Plank, Terra-Dawn M; Noller, Harry F; Kieft, Jeffrey S

2015-03-05

The central dogma of gene expression (DNA to RNA to protein) is universal, but in different domains of life there are fundamental mechanistic differences within this pathway. For example, the canonical molecular signals used to initiate protein synthesis in bacteria and eukaryotes are mutually exclusive. However, the core structures and conformational dynamics of ribosomes that are responsible for the translation steps that take place after initiation are ancient and conserved across the domains of life. We wanted to explore whether an undiscovered RNA-based signal might be able to use these conserved features, bypassing mechanisms specific to each domain of life, and initiate protein synthesis in both bacteria and eukaryotes. Although structured internal ribosome entry site (IRES) RNAs can manipulate ribosomes to initiate translation in eukaryotic cells, an analogous RNA structure-based mechanism has not been observed in bacteria. Here we report our discovery that a eukaryotic viral IRES can initiate translation in live bacteria. We solved the crystal structure of this IRES bound to a bacterial ribosome to 3.8 Å resolution, revealing that despite differences between bacterial and eukaryotic ribosomes this IRES binds directly to both and occupies the space normally used by transfer RNAs. Initiation in both bacteria and eukaryotes depends on the structure of the IRES RNA, but in bacteria this RNA uses a different mechanism that includes a form of ribosome repositioning after initial recruitment. This IRES RNA bridges billions of years of evolutionary divergence and provides an example of an RNA structure-based translation initiation signal capable of operating in two domains of life.

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

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Xin Lai

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Victoria L. Pritchard

2017-01-01

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

Heterologous gene expression in filamentous fungi.

Science.gov (United States)

Su, Xiaoyun; Schmitz, George; Zhang, Meiling; Mackie, Roderick I; Cann, Isaac K O

2012-01-01

Filamentous fungi are critical to production of many commercial enzymes and organic compounds. Fungal-based systems have several advantages over bacterial-based systems for protein production because high-level secretion of enzymes is a common trait of their decomposer lifestyle. Furthermore, in the large-scale production of recombinant proteins of eukaryotic origin, the filamentous fungi become the vehicle of choice due to critical processes shared in gene expression with other eukaryotic organisms. The complexity and relative dearth of understanding of the physiology of filamentous fungi, compared to bacteria, have hindered rapid development of these organisms as highly efficient factories for the production of heterologous proteins. In this review, we highlight several of the known benefits and challenges in using filamentous fungi (particularly Aspergillus spp., Trichoderma reesei, and Neurospora crassa) for the production of proteins, especially heterologous, nonfungal enzymes. We review various techniques commonly employed in recombinant protein production in the filamentous fungi, including transformation methods, selection of gene regulatory elements such as promoters, protein secretion factors such as the signal peptide, and optimization of coding sequence. We provide insights into current models of host genomic defenses such as repeat-induced point mutation and quelling. Furthermore, we examine the regulatory effects of transcript sequences, including introns and untranslated regions, pre-mRNA (messenger RNA) processing, transcript transport, and mRNA stability. We anticipate that this review will become a resource for researchers who aim at advancing the use of these fascinating organisms as protein production factories, for both academic and industrial purposes, and also for scientists with general interest in the biology of the filamentous fungi. Copyright © 2012 Elsevier Inc. All rights reserved.

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

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

2017-12-01

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

Different polyamine pathways from bacteria have replaced eukaryotic spermidine biosynthesis in ciliates Tetrahymena thermophila and Paramecium tetaurelia.

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Li, Bin; Kim, Sok Ho; Zhang, Yang; Hanfrey, Colin C; Elliott, Katherine A; Ealick, Steven E; Michael, Anthony J

2015-09-01

The polyamine spermidine is absolutely required for growth and cell proliferation in eukaryotes, due to its role in post-translational modification of essential translation elongation factor eIF5A, mediated by deoxyhypusine synthase. We have found that free-living ciliates Tetrahymena and Paramecium lost the eukaryotic genes encoding spermidine biosynthesis: S-adenosylmethionine decarboxylase (AdoMetDC) and spermidine synthase (SpdSyn). In Tetrahymena, they were replaced by a gene encoding a fusion protein of bacterial AdoMetDC and SpdSyn, present as three copies. In Paramecium, a bacterial homospermidine synthase replaced the eukaryotic genes. Individual AdoMetDC-SpdSyn fusion protein paralogues from Tetrahymena exhibit undetectable AdoMetDC activity; however, when two paralogous fusion proteins are mixed, AdoMetDC activity is restored and spermidine is synthesized. Structural modelling indicates a functional active site is reconstituted by sharing critical residues from two defective protomers across the heteromer interface. Paramecium was found to accumulate homospermidine, suggesting it replaces spermidine for growth. To test this concept, a budding yeast spermidine auxotrophic strain was found to grow almost normally with homospermidine instead of spermidine. Biosynthesis of spermidine analogue aminopropylcadaverine, but not exogenously provided norspermidine, correlated with some growth. Finally, we found that diverse single-celled eukaryotic parasites and multicellular metazoan Schistosoma worms have lost the spermidine biosynthetic pathway but retain deoxyhypusine synthase. © 2015 John Wiley & Sons Ltd.

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

Regulatory factors governing adenosine-to-inosine (A-to-I) RNA editing.

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Hong, HuiQi; Lin, Jaymie Siqi; Chen, Leilei

2015-03-31

Adenosine-to-inosine (A-to-I) RNA editing, the most prevalent mode of transcript modification in higher eukaryotes, is catalysed by the adenosine deaminases acting on RNA (ADARs). A-to-I editing imposes an additional layer of gene regulation as it dictates various aspects of RNA metabolism, including RNA folding, processing, localization and degradation. Furthermore, editing events in exonic regions contribute to proteome diversity as translational machinery decodes inosine as guanosine. Although it has been demonstrated that dysregulated A-to-I editing contributes to various diseases, the precise regulatory mechanisms governing this critical cellular process have yet to be fully elucidated. However, integration of previous studies revealed that regulation of A-to-I editing is multifaceted, weaving an intricate network of auto- and transregulations, including the involvement of virus-originated factors like adenovirus-associated RNA. Taken together, it is apparent that tipping of any regulatory components will have profound effects on A-to-I editing, which in turn contributes to both normal and aberrant physiological conditions. A complete understanding of this intricate regulatory network may ultimately be translated into new therapeutic strategies against diseases driven by perturbed RNA editing events. Herein, we review the current state of knowledge on the regulatory mechanisms governing A-to-I editing and propose the role of other co-factors that may be involved in this complex regulatory process.

Convergent evolution of RFX transcription factors and ciliary genes predated the origin of metazoans

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Chen Nansheng

2010-05-01

Full Text Available Abstract Background Intraflagellar transport (IFT genes, which are critical for the development and function of cilia and flagella in metazoans, are tightly regulated by the Regulatory Factor X (RFX transcription factors (TFs. However, how and when their evolutionary relationship was established remains unknown. Results We have identified evidence suggesting that RFX TFs and IFT genes evolved independently and their evolution converged before the first appearance of metazoans. Both ciliary genes and RFX TFs exist in all metazoans as well as some unicellular eukaryotes. However, while RFX TFs and IFT genes are found simultaneously in all sequenced metazoan genomes, RFX TFs do not co-exist with IFT genes in most pre-metazoans and thus do not regulate them in these organisms. For example, neither the budding yeast nor the fission yeast possesses cilia although both have well-defined RFX TFs. Conversely, most unicellular eukaryotes, including the green alga Chlamydomonas reinhardtii, have typical cilia and well conserved IFT genes but lack RFX TFs. Outside of metazoans, RFX TFs and IFT genes co-exist only in choanoflagellates including M. brevicollis, and only one fungus Allomyces macrogynus of the 51 sequenced fungus genomes. M. brevicollis has two putative RFX genes and a full complement of ciliary genes. Conclusions The evolution of RFX TFs and IFT genes were independent in pre-metazoans. We propose that their convergence in evolution, or the acquired transcriptional regulation of IFT genes by RFX TFs, played a pivotal role in the establishment of metazoan.

A recently transferred cluster of bacterial genes in Trichomonas vaginalis - lateral gene transfer and the fate of acquired genes

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2014-01-01

Background Lateral Gene Transfer (LGT) has recently gained recognition as an important contributor to some eukaryote proteomes, but the mechanisms of acquisition and fixation in eukaryotic genomes are still uncertain. A previously defined norm for LGTs in microbial eukaryotes states that the majority are genes involved in metabolism, the LGTs are typically localized one by one, surrounded by vertically inherited genes on the chromosome, and phylogenetics shows that a broad collection of bacterial lineages have contributed to the transferome. Results A unique 34 kbp long fragment with 27 clustered genes (TvLF) of prokaryote origin was identified in the sequenced genome of the protozoan parasite Trichomonas vaginalis. Using a PCR based approach we confirmed the presence of the orthologous fragment in four additional T. vaginalis strains. Detailed sequence analyses unambiguously suggest that TvLF is the result of one single, recent LGT event. The proposed donor is a close relative to the firmicute bacterium Peptoniphilus harei. High nucleotide sequence similarity between T. vaginalis strains, as well as to P. harei, and the absence of homologs in other Trichomonas species, suggests that the transfer event took place after the radiation of the genus Trichomonas. Some genes have undergone pseudogenization and degradation, indicating that they may not be retained in the future. Functional annotations reveal that genes involved in informational processes are particularly prone to degradation. Conclusions We conclude that, although the majority of eukaryote LGTs are single gene occurrences, they may be acquired in clusters of several genes that are subsequently cleansed of evolutionarily less advantageous genes. PMID:24898731

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

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

2011-05-01

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

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

DEFF Research Database (Denmark)

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

2015-01-01

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

Evolution of pH buffers and water homeostasis in eukaryotes: homology between humans and Acanthamoeba proteins.

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Baig, Abdul M; Zohaib, R; Tariq, S; Ahmad, H R

2018-02-01

This study intended to trace the evolution of acid-base buffers and water homeostasis in eukaryotes. Acanthamoeba castellanii  was selected as a model unicellular eukaryote for this purpose. Homologies of proteins involved in pH and water regulatory mechanisms at cellular levels were compared between humans and A. castellanii. Amino acid sequence homology, structural homology, 3D modeling and docking prediction were done to show the extent of similarities between carbonic anhydrase 1 (CA1), aquaporin (AQP), band-3 protein and H + pump. Experimental assays were done with acetazolamide (AZM), brinzolamide and mannitol to observe their effects on the trophozoites of  A. castellanii.  The human CA1, AQP, band-3 protein and H + -transport proteins revealed similar proteins in Acanthamoeba. Docking showed the binding of AZM on amoebal AQP-like proteins.  Acanthamoeba showed transient shape changes and encystation at differential doses of brinzolamide, mannitol and AZM.  Conclusion: Water and pH regulating adapter proteins in Acanthamoeba and humans show significant homology, these mechanisms evolved early in the primitive unicellular eukaryotes and have remained conserved in multicellular eukaryotes.

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

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

2017-12-15

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

Metabolic profiles of prokaryotic and eukaryotic communities in deep-sea sponge Neamphius huxleyi indicated by metagenomics

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Li, Zhi-Yong; Wang, Yue-Zhu; He, Li-Ming; Zheng, Hua-Jun

2014-01-01

The whole metabolism of a sponge holobiont and the respective contributions of prokaryotic and eukaryotic symbionts and their associations with the sponge host remain largely unclear. Meanwhile, compared with shallow water sponges, deep-sea sponges are rarely understood. Here we report the metagenomic exploration of deep-sea sponge Neamphius huxleyi at the whole community level. Metagenomic data showed phylogenetically diverse prokaryotes and eukaryotes in Neamphius huxleyi. MEGAN and gene enrichment analyses indicated different metabolic potentials of prokaryotic symbionts from eukaryotic symbionts, especially in nitrogen and carbon metabolisms, and their molecular interactions with the sponge host. These results supported the hypothesis that prokaryotic and eukaryotic symbionts have different ecological roles and relationships with sponge host. Moreover, vigorous denitrification, and CO2 fixation by chemoautotrophic prokaryotes were suggested for this deep-sea sponge. The study provided novel insights into the respective potentials of prokaryotic and eukaryotic symbionts and their associations with deep-sea sponge Neamphius huxleyi. PMID:24463735

Metabolic profiles of prokaryotic and eukaryotic communities in deep-sea sponge Lamellomorpha sp. indicated by metagenomics

Science.gov (United States)

Li, Zhi-Yong; Wang, Yue-Zhu; He, Li-Ming; Zheng, Hua-Jun

2014-01-01

The whole metabolism of a sponge holobiont and the respective contributions of prokaryotic and eukaryotic symbionts and their associations with the sponge host remain largely unclear. Meanwhile, compared with shallow water sponges, deep-sea sponges are rarely understood. Here we report the metagenomic exploration of deep-sea sponge Lamellomorpha sp. at the whole community level. Metagenomic data showed phylogenetically diverse prokaryotes and eukaryotes in Lamellomorpha sp.. MEGAN and gene enrichment analyses indicated different metabolic potentials of prokaryotic symbionts from eukaryotic symbionts, especially in nitrogen and carbon metabolisms, and their molecular interactions with the sponge host. These results supported the hypothesis that prokaryotic and eukaryotic symbionts have different ecological roles and relationships with sponge host. Moreover, vigorous denitrification, and CO2 fixation by chemoautotrophic prokaryotes were suggested for this deep-sea sponge. The study provided novel insights into the respective potentials of prokaryotic and eukaryotic symbionts and their associations with deep-sea sponge Lamellomorpha sp..

Eukaryotic translation initiation factor 2B-beta (eIF2Bβ), a new class of plant virus resistance gene.

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Shopan, Jannat; Mou, Haipeng; Zhang, Lili; Zhang, Changtong; Ma, Weiwei; Walsh, John A; Hu, Zhongyuan; Yang, Jinghua; Zhang, Mingfang

2017-06-01

Recessive resistances to plant viruses in the Potyvirus genus have been found to be based on mutations in the plant eukaryotic translation initiation factors, eIF4E and eIF4G or their isoforms. Here we report that natural, monogenic recessive resistance to the Potyvirus Turnip mosaic virus (TuMV) has been found in a number of mustard (Brassica juncea) accessions. Bulked segregant analysis and sequencing of resistant and susceptible plant lines indicated the resistance is controlled by a single recessive gene, recessive TuMV resistance 03 (retr03), an allele of the eukaryotic translation initiation factor 2B-beta (eIF2Bβ). Silencing of eIF2Bβ in a TuMV-susceptible mustard plant line and expression of eIF2Bβ from a TuMV-susceptible line in a TuMV-resistant mustard plant line confirmed the new resistance mechanism. A functional copy of a specific allele of eIF2Bβ is required for efficient TuMV infection. eIF2Bβ represents a new class of virus resistance gene conferring resistance to any pathogen. eIF2B acts as a guanine nucleotide exchange factor (GEF) for its GTP-binding protein partner eIF2 via interaction with eIF2·GTP at an early step in translation initiation. Further genotyping indicated that a single non-synonymous substitution (A120G) in the N-terminal region of eIF2Bβ was responsible for the TuMV resistance. A reproducible marker has been developed, facilitating marker-assisted selection for TuMV resistance in B. juncea. Our findings provide a new target for seeking natural resistance to potyviruses and new opportunities for the control of potyviruses using genome editing techniques targeted on eIF2Bβ. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

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

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Alexandra Saudemont

2010-12-01

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

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

OpenAIRE

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

2017-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

Insights into the diversity of eukaryotes in acid mine drainage biofilm communities.

Science.gov (United States)

Baker, Brett J; Tyson, Gene W; Goosherst, Lindsey; Banfield, Jillian F

2009-04-01

Microscopic eukaryotes are known to have important ecosystem functions, but their diversity in most environments remains vastly unexplored. Here we analyzed an 18S rRNA gene library from a subsurface iron- and sulfur-oxidizing microbial community growing in highly acidic (pH morphological characterization. Results revealed that the populations vary significantly with the habitat and no group is ubiquitous. Surprisingly, many of the eukaryotic lineages (with the exception of the APC) are closely related to neutrophiles, suggesting that they recently adapted to this extreme environment. Molecular analyses presented here confirm that the number of eukaryotic species associated with the acid mine drainage (AMD) communities is low. This finding is consistent with previous results showing a limited diversity of archaea, bacteria, and viruses in AMD environments and suggests that the environmental pressures and interplay between the members of these communities limit species diversity at all trophic levels.

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.

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

Science.gov (United States)

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

2017-01-05

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

Diversity of Eukaryotic Translational Initiation Factor eIF4E in Protists.

Science.gov (United States)

Jagus, Rosemary; Bachvaroff, Tsvetan R; Joshi, Bhavesh; Place, Allen R

2012-01-01

The greatest diversity of eukaryotic species is within the microbial eukaryotes, the protists, with plants and fungi/metazoa representing just two of the estimated seventy five lineages of eukaryotes. Protists are a diverse group characterized by unusual genome features and a wide range of genome sizes from 8.2 Mb in the apicomplexan parasite Babesia bovis to 112,000-220,050 Mb in the dinoflagellate Prorocentrum micans. Protists possess numerous cellular, molecular and biochemical traits not observed in "text-book" model organisms. These features challenge some of the concepts and assumptions about the regulation of gene expression in eukaryotes. Like multicellular eukaryotes, many protists encode multiple eIF4Es, but few functional studies have been undertaken except in parasitic species. An earlier phylogenetic analysis of protist eIF4Es indicated that they cannot be grouped within the three classes that describe eIF4E family members from multicellular organisms. Many more protist sequences are now available from which three clades can be recognized that are distinct from the plant/fungi/metazoan classes. Understanding of the protist eIF4Es will be facilitated as more sequences become available particularly for the under-represented opisthokonts and amoebozoa. Similarly, a better understanding of eIF4Es within each clade will develop as more functional studies of protist eIF4Es are completed.

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

Directory of Open Access Journals (Sweden)

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

Dose response relationship in anti-stress gene regulatory networks.

Science.gov (United States)

Zhang, Qiang; Andersen, Melvin E

2007-03-02

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

Dose response relationship in anti-stress gene regulatory networks.

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Qiang Zhang

2007-03-01

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

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

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Oka, Ayako; Shiroishi, Toshihiko

2014-01-01

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

The cell cycle-regulated genes of Schizosaccharomyces pombe.

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Oliva, Anna; Rosebrock, Adam; Ferrezuelo, Francisco; Pyne, Saumyadipta; Chen, Haiying; Skiena, Steve; Futcher, Bruce; Leatherwood, Janet

2005-07-01

Many genes are regulated as an innate part of the eukaryotic cell cycle, and a complex transcriptional network helps enable the cyclic behavior of dividing cells. This transcriptional network has been studied in Saccharomyces cerevisiae (budding yeast) and elsewhere. To provide more perspective on these regulatory mechanisms, we have used microarrays to measure gene expression through the cell cycle of Schizosaccharomyces pombe (fission yeast). The 750 genes with the most significant oscillations were identified and analyzed. There were two broad waves of cell cycle transcription, one in early/mid G2 phase, and the other near the G2/M transition. The early/mid G2 wave included many genes involved in ribosome biogenesis, possibly explaining the cell cycle oscillation in protein synthesis in S. pombe. The G2/M wave included at least three distinctly regulated clusters of genes: one large cluster including mitosis, mitotic exit, and cell separation functions, one small cluster dedicated to DNA replication, and another small cluster dedicated to cytokinesis and division. S. pombe cell cycle genes have relatively long, complex promoters containing groups of multiple DNA sequence motifs, often of two, three, or more different kinds. Many of the genes, transcription factors, and regulatory mechanisms are conserved between S. pombe and S. cerevisiae. Finally, we found preliminary evidence for a nearly genome-wide oscillation in gene expression: 2,000 or more genes undergo slight oscillations in expression as a function of the cell cycle, although whether this is adaptive, or incidental to other events in the cell, such as chromatin condensation, we do not know.

The Cell Cycle–Regulated Genes of Schizosaccharomyces pombe

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Oliva, Anna; Rosebrock, Adam; Ferrezuelo, Francisco; Pyne, Saumyadipta; Chen, Haiying; Skiena, Steve

2005-01-01

Many genes are regulated as an innate part of the eukaryotic cell cycle, and a complex transcriptional network helps enable the cyclic behavior of dividing cells. This transcriptional network has been studied in Saccharomyces cerevisiae (budding yeast) and elsewhere. To provide more perspective on these regulatory mechanisms, we have used microarrays to measure gene expression through the cell cycle of Schizosaccharomyces pombe (fission yeast). The 750 genes with the most significant oscillations were identified and analyzed. There were two broad waves of cell cycle transcription, one in early/mid G2 phase, and the other near the G2/M transition. The early/mid G2 wave included many genes involved in ribosome biogenesis, possibly explaining the cell cycle oscillation in protein synthesis in S. pombe. The G2/M wave included at least three distinctly regulated clusters of genes: one large cluster including mitosis, mitotic exit, and cell separation functions, one small cluster dedicated to DNA replication, and another small cluster dedicated to cytokinesis and division. S. pombe cell cycle genes have relatively long, complex promoters containing groups of multiple DNA sequence motifs, often of two, three, or more different kinds. Many of the genes, transcription factors, and regulatory mechanisms are conserved between S. pombe and S. cerevisiae. Finally, we found preliminary evidence for a nearly genome-wide oscillation in gene expression: 2,000 or more genes undergo slight oscillations in expression as a function of the cell cycle, although whether this is adaptive, or incidental to other events in the cell, such as chromatin condensation, we do not know. PMID:15966770

Pre-mRNA mis-splicing of sarcomeric genes in heart failure.

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Zhu, Chaoqun; Chen, Zhilong; Guo, Wei

2017-08-01

Pre-mRNA splicing is an important biological process that allows production of multiple proteins from a single gene in the genome, and mainly contributes to protein diversity in eukaryotic organisms. Alternative splicing is commonly governed by RNA binding proteins to meet the ever-changing demands of the cell. However, the mis-splicing may lead to human diseases. In the heart of human, mis-regulation of alternative splicing has been associated with heart failure. In this short review, we focus on alternative splicing of sarcomeric genes and review mis-splicing related heart failure with relatively well studied Sarcomeric genes and splicing mechanisms with identified regulatory factors. The perspective of alternative splicing based therapeutic strategies in heart failure has also been discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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

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

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

2005-07-15

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

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

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

1988-01-01

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

Using synthetic biology to distinguish and overcome regulatory and functional barriers related to nitrogen fixation.

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Xia Wang

Full Text Available Biological nitrogen fixation is a complex process requiring multiple genes working in concert. To date, the Klebsiella pneumoniae nif gene cluster, divided into seven operons, is one of the most studied systems. Its nitrogen fixation capacity is subject to complex cascade regulation and physiological limitations. In this report, the entire K. pneumoniae nif gene cluster was reassembled as operon-based BioBrick parts in Escherichia coli. It provided ~100% activity of native K. pneumoniae system. Based on the expression levels of these BioBrick parts, a T7 RNA polymerase-LacI expression system was used to replace the σ(54-dependent promoters located upstream of nif operons. Expression patterns of nif operons were critical for the maximum activity of the recombinant system. By mimicking these expression levels with variable-strength T7-dependent promoters, ~42% of the nitrogenase activity of the σ(54-dependent nif system was achieved in E. coli. When the newly constructed T7-dependent nif system was challenged with different genetic and physiological conditions, it bypassed the original complex regulatory circuits, with minor physiological limitations. Therefore, we have successfully replaced the nif regulatory elements with a simple expression system that may provide the first step for further research of introducing nif genes into eukaryotic organelles, which has considerable potentials in agro-biotechnology.

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

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Gerstein, Mark

2016-01-01

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

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

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Daifeng Wang

2016-10-01

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

Analysis of a Gene Regulatory Cascade Mediating Circadian Rhythm in Zebrafish

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Wang, Haifang; Du, Jiulin; Yan, Jun

2013-01-01

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

Metabolic profiles of prokaryotic and eukaryotic communities in deep-sea sponge Neamphius huxleyi [corrected]. indicated by metagenomics.

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Li, Zhi-Yong; Wang, Yue-Zhu; He, Li-Ming; Zheng, Hua-Jun

2014-01-27

The whole metabolism of a sponge holobiont and the respective contributions of prokaryotic and eukaryotic symbionts and their associations with the sponge host remain largely unclear. Meanwhile, compared with shallow water sponges, deep-sea sponges are rarely understood. Here we report the metagenomic exploration of deep-sea sponge Neamphius huxleyi [corrected] . at the whole community level. Metagenomic data showed phylogenetically diverse prokaryotes and eukaryotes in Neamphius huxleyi [corrected]. MEGAN and gene enrichment analyses indicated different metabolic potentials of prokaryotic symbionts from eukaryotic symbionts, especially in nitrogen and carbon metabolisms, and their molecular interactions with the sponge host. These results supported the hypothesis that prokaryotic and eukaryotic symbionts have different ecological roles and relationships with sponge host. Moreover, vigorous denitrification, and CO2 fixation by chemoautotrophic prokaryotes were suggested for this deep-sea sponge. The study provided novel insights into the respective potentials of prokaryotic and eukaryotic symbionts and their associations with deep-sea sponge Neamphius huxleyi [corrected].

Eukaryotic tRNAs fingerprint invertebrates vis-à-vis vertebrates.

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Mitra, Sanga; Das, Pijush; Samadder, Arpa; Das, Smarajit; Betai, Rupal; Chakrabarti, Jayprokas

2015-01-01

During translation, aminoacyl-tRNA synthetases recognize the identities of the tRNAs to charge them with their respective amino acids. The conserved identities of 58,244 eukaryotic tRNAs of 24 invertebrates and 45 vertebrates in genomic tRNA database were analyzed and their novel features extracted. The internal promoter sequences, namely, A-Box and B-Box, were investigated and evidence gathered that the intervention of optional nucleotides at 17a and 17b correlated with the optimal length of the A-Box. The presence of canonical transcription terminator sequences at the immediate vicinity of tRNA genes was ventured. Even though non-canonical introns had been reported in red alga, green alga, and nucleomorph so far, fairly motivating evidence of their existence emerged in tRNA genes of other eukaryotes. Non-canonical introns were seen to interfere with the internal promoters in two cases, questioning their transcription fidelity. In a first of its kind, phylogenetic constructs based on tRNA molecules delineated and built the trees of the vast and diverse invertebrates and vertebrates. Finally, two tRNA models representing the invertebrates and the vertebrates were drawn, by isolating the dominant consensus in the positional fluctuations of nucleotide compositions.

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

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Hyun-Eui Park

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

Regulatory Oversight of Cell and Gene Therapy Products in Canada.

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

2015-01-01

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

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

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

2016-06-01

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

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

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Liang Jinghang

2012-08-01

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

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

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Junhua Li

2014-01-01

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

The Roles and Evolutionary Patterns of Intronless Genes in Deuterostomes

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Ming Zou

2011-01-01

Full Text Available Genes without introns are a characteristic feature of prokaryotes, but there are still a number of intronless genes in eukaryotes. To study these eukaryotic genes that have prokaryotic architecture could help to understand the evolutionary patterns of related genes and genomes. Our analyses revealed a number of intronless genes that reside in 6 deuterostomes (sea urchin, sea squirt, zebrafish, chicken, platypus, and human. We also determined the conservation for each intronless gene in archaea, bacteria, fungi, plants, metazoans, and other eukaryotes. Proportions of intronless genes that are inherited from the common ancestor of archaea, bacteria, and eukaryotes in these species were consistent with their phylogenetic positions, with more proportions of ancient intronless genes residing in more primitive species. In these species, intronless genes belong to different cellular roles and gene ontology (GO categories, and some of these functions are very basic. Part of intronless genes is derived from other intronless genes or multiexon genes in each species. In conclusion, we showed that a varying number and proportion of intronless genes reside in these 6 deuterostomes, and some of them function importantly. These genes are good candidates for subsequent functional and evolutionary analyses specifically.

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

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

2016-07-11

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

Overexpression of maize anthocyanin regulatory gene Lc affects rice fertility.

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

2013-01-01

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

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

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Farré Domènec

2007-12-01

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

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

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Biswas, Surama; Acharyya, Sriyankar

2016-06-01

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

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

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

2017-05-01

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

Intermediary metabolism in protists: a sequence-based view of facultative anaerobic metabolism in evolutionarily diverse eukaryotes.

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Ginger, Michael L; Fritz-Laylin, Lillian K; Fulton, Chandler; Cande, W Zacheus; Dawson, Scott C

2010-12-01

Protists account for the bulk of eukaryotic diversity. Through studies of gene and especially genome sequences the molecular basis for this diversity can be determined. Evident from genome sequencing are examples of versatile metabolism that go far beyond the canonical pathways described for eukaryotes in textbooks. In the last 2-3 years, genome sequencing and transcript profiling has unveiled several examples of heterotrophic and phototrophic protists that are unexpectedly well-equipped for ATP production using a facultative anaerobic metabolism, including some protists that can (Chlamydomonas reinhardtii) or are predicted (Naegleria gruberi, Acanthamoeba castellanii, Amoebidium parasiticum) to produce H(2) in their metabolism. It is possible that some enzymes of anaerobic metabolism were acquired and distributed among eukaryotes by lateral transfer, but it is also likely that the common ancestor of eukaryotes already had far more metabolic versatility than was widely thought a few years ago. The discussion of core energy metabolism in unicellular eukaryotes is the subject of this review. Since genomic sequencing has so far only touched the surface of protist diversity, it is anticipated that sequences of additional protists may reveal an even wider range of metabolic capabilities, while simultaneously enriching our understanding of the early evolution of eukaryotes. Copyright © 2010 Elsevier GmbH. All rights reserved.

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

NARCIS (Netherlands)

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

2016-01-01

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

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

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Avraham E Mayo

2006-04-01

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

The cell cycle-regulated genes of Schizosaccharomyces pombe.

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Anna Oliva

2005-07-01

Full Text Available Many genes are regulated as an innate part of the eukaryotic cell cycle, and a complex transcriptional network helps enable the cyclic behavior of dividing cells. This transcriptional network has been studied in Saccharomyces cerevisiae (budding yeast and elsewhere. To provide more perspective on these regulatory mechanisms, we have used microarrays to measure gene expression through the cell cycle of Schizosaccharomyces pombe (fission yeast. The 750 genes with the most significant oscillations were identified and analyzed. There were two broad waves of cell cycle transcription, one in early/mid G2 phase, and the other near the G2/M transition. The early/mid G2 wave included many genes involved in ribosome biogenesis, possibly explaining the cell cycle oscillation in protein synthesis in S. pombe. The G2/M wave included at least three distinctly regulated clusters of genes: one large cluster including mitosis, mitotic exit, and cell separation functions, one small cluster dedicated to DNA replication, and another small cluster dedicated to cytokinesis and division. S. pombe cell cycle genes have relatively long, complex promoters containing groups of multiple DNA sequence motifs, often of two, three, or more different kinds. Many of the genes, transcription factors, and regulatory mechanisms are conserved between S. pombe and S. cerevisiae. Finally, we found preliminary evidence for a nearly genome-wide oscillation in gene expression: 2,000 or more genes undergo slight oscillations in expression as a function of the cell cycle, although whether this is adaptive, or incidental to other events in the cell, such as chromatin condensation, we do not know.

[Expression of mutation type GJA8 gene and wild type GJA8 gene of a congenital inherited nuclear cataract family in eukaryotic cells].

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Zheng, Jian-qiu; Liu, Ping; Wang, Jian-wen; Liu, Jian-ju

2010-04-20

To clone the sequence of mutation type GJA8 gene (mGJA8) and wild type GJA8 gene (wGJA8) of a congenital inherited nuclear cataract family and study their expression in eukaryotic cell lines in vitro. The mGJA8 and wGJA8 were amplified from this family's DNA and healthy people's DNA by PCR respectively. The mGJA8 and wGJA8 were recombined with plasmid pEGFP-N1 respectively. The accuracy of pEGFP-N1-GJA8 was confirmed by restriction enzyme digestion and DNA sequencing. Finally pEGFP-N1- mGJA8 and pEGFP-N1- wGJA8 and GFP protein were transfected into COS7 cells by lipofectin. The expression of pEGFP-N1-GJA8 and GFP fusion protein were to observe under fluorescence microscope, and to detect by Western-blotting and immunohistochemical staining. The mGJA8 and wGJA8 were cloned successfully. With restricting enzyme digestion analysis and DNA sequencing, recombinant plasmid pEGFP-N1-mGJA8 and pEGFP-N1-wGJA8 were constructed correctly and their GFP fusions were expressed in transfected COS7 cells. The expression of pEGFP-N1-mGJA8 and pEGFP-N1-wGJA8 fusion protein were observed under fluorescence microscope, and detected by Western-blotting and immunohistochemical staining successfully. The mGJA8 gene and wGJA8 gene are cloned successfully, and pEGFP-N1-mGJA8 and pEGFP-N1-mGJA8 fusion protein can be expressed in COS7 cells, which establish the foundation for further studying the mechanism of this congenital inherited nuclear cataract family.

Convergent use of RhoGAP toxins by eukaryotic parasites and bacterial pathogens.

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Dominique Colinet

2007-12-01

Full Text Available Inactivation of host Rho GTPases is a widespread strategy employed by bacterial pathogens to manipulate mammalian cellular functions and avoid immune defenses. Some bacterial toxins mimic eukaryotic Rho GTPase-activating proteins (GAPs to inactivate mammalian GTPases, probably as a result of evolutionary convergence. An intriguing question remains whether eukaryotic pathogens or parasites may use endogenous GAPs as immune-suppressive toxins to target the same key genes as bacterial pathogens. Interestingly, a RhoGAP domain-containing protein, LbGAP, was recently characterized from the parasitoid wasp Leptopilina boulardi, and shown to protect parasitoid eggs from the immune response of Drosophila host larvae. We demonstrate here that LbGAP has structural characteristics of eukaryotic RhoGAPs but that it acts similarly to bacterial RhoGAP toxins in mammals. First, we show by immunocytochemistry that LbGAP enters Drosophila immune cells, plasmatocytes and lamellocytes, and that morphological changes in lamellocytes are correlated with the quantity of LbGAP they contain. Demonstration that LbGAP displays a GAP activity and specifically interacts with the active, GTP-bound form of the two Drosophila Rho GTPases Rac1 and Rac2, both required for successful encapsulation of Leptopilina eggs, was then achieved using biochemical tests, yeast two-hybrid analysis, and GST pull-down assays. In addition, we show that the overall structure of LbGAP is similar to that of eukaryotic RhoGAP domains, and we identify distinct residues involved in its interaction with Rac GTPases. Altogether, these results show that eukaryotic parasites can use endogenous RhoGAPs as virulence factors and that despite their differences in sequence and structure, eukaryotic and bacterial RhoGAP toxins are similarly used to target the same immune pathways in insects and mammals.

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

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

2016-07-27

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

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

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Yoichiro Shibata

2012-06-01

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

diArk – a resource for eukaryotic genome research

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Kollmar Martin

2007-04-01

Full Text Available Abstract Background The number of completed eukaryotic genome sequences and cDNA projects has increased exponentially in the past few years although most of them have not been published yet. In addition, many microarray analyses yielded thousands of sequenced EST and cDNA clones. For the researcher interested in single gene analyses (from a phylogenetic, a structural biology or other perspective it is therefore important to have up-to-date knowledge about the various resources providing primary data. Description The database is built around 3 central tables: species, sequencing projects and publications. The species table contains commonly and alternatively used scientific names, common names and the complete taxonomic information. For projects the sequence type and links to species project web-sites and species homepages are stored. All publications are linked to projects. The web-interface provides comprehensive search modules with detailed options and three different views of the selected data. We have especially focused on developing an elaborate taxonomic tree search tool that allows the user to instantaneously identify e.g. the closest relative to the organism of interest. Conclusion We have developed a database, called diArk, to store, organize, and present the most relevant information about completed genome projects and EST/cDNA data from eukaryotes. Currently, diArk provides information about 415 eukaryotes, 823 sequencing projects, and 248 publications.

Mutation of a Nicotiana tabacum L. eukaryotic translation-initiation factor gene reduces susceptibility to a resistance-breaking strain of Potato Virus Y.

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Takakura, Yoshimitsu; Udagawa, Hisashi; Shinjo, Akira; Koga, Kazuharu

2018-04-06

Eukaryotic translation-initiation factors eIF4E and eIF(iso)4E in plants play key roles in infection by potyviruses and other plant RNA viruses. Mutations in the genes encoding these factors reduce susceptibility to the viruses, and are the basis of several recessive virus-resistance genes widely used in plant breeding. Because virus variants occasionally break such resistance, the molecular basis for this process must be elucidated. Although deletion mutants of eIF4E1-S of tobacco (Nicotiana tabacum L.) resist Potato virus Y (PVY; the type member of the genus Potyvirus), resistance-breaking strains of PVY threaten tobacco production worldwide. Here, we used RNA interference technology to knock down tobacco eIF4E2-S and eIF4E2-T genes or eIF(iso)4E-S and eIF(iso)4E-T genes. Transgenic plants with reduced transcript levels of both eIF(iso)4E-S and eIF(iso)4E-T showed reduced susceptibility to a resistance-breaking PVY strain with a K105E mutation in the viral genome-associated protein (VPg). By screening a population of chemically-induced mutants of eIF(iso)4E-S and eIF(iso)4E-T, we showed that plants with a nonsense mutation in eIF(iso)4E-T, but not eIF(iso)4E-S, showed reduced susceptibility to the resistance-breaking PVY strain. In a yeast two-hybrid assay, VPg of the resistance-breaking strain, but not wild-type PVY, physically interacted with the eIF(iso)4E-T protein. Thus, eIF4E1-S is required for infection by PVY, but eIF(iso)4E-T is required for infection by the resistance-breaking strain. Our study provides the first evidence for the involvement of a host eukaryotic translation-initiation factor in the infection cycle of a resistance-breaking virus strain. The eIF(iso)4E-T mutants will be useful in tobacco breeding to introduce resistance against resistance-breaking PVY strains. This article is protected by copyright. All rights reserved. © 2018 BSPP and John Wiley & Sons Ltd.

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

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

2018-07-03

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

Genome-wide analysis of eukaryote thaumatin-like proteins (TLPs with an emphasis on poplar

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Duplessis Sébastien

2011-02-01

Full Text Available Abstract Background Plant inducible immunity includes the accumulation of a set of defense proteins during infection called pathogenesis-related (PR proteins, which are grouped into families termed PR-1 to PR-17. The PR-5 family is composed of thaumatin-like proteins (TLPs, which are responsive to biotic and abiotic stress and are widely studied in plants. TLPs were also recently discovered in fungi and animals. In the poplar genome, TLPs are over-represented compared with annual species and their transcripts strongly accumulate during stress conditions. Results Our analysis of the poplar TLP family suggests that the expansion of this gene family was followed by diversification, as differences in expression patterns and predicted properties correlate with phylogeny. In particular, we identified a clade of poplar TLPs that cluster to a single 350 kb locus of chromosome I and that are up-regulated by poplar leaf rust infection. A wider phylogenetic analysis of eukaryote TLPs - including plant, animal and fungi sequences - shows that TLP gene content and diversity increased markedly during land plant evolution. Mapping the reported functions of characterized TLPs to the eukaryote phylogenetic tree showed that antifungal or glycan-lytic properties are widespread across eukaryote phylogeny, suggesting that these properties are shared by most TLPs and are likely associated with the presence of a conserved acidic cleft in their 3D structure. Also, we established an exhaustive catalog of TLPs with atypical architectures such as small-TLPs, TLP-kinases and small-TLP-kinases, which have potentially developed alternative functions (such as putative receptor kinases for pathogen sensing and signaling. Conclusion Our study, based on the most recent plant genome sequences, provides evidence for TLP gene family diversification during land plant evolution. We have shown that the diverse functions described for TLPs are not restricted to specific clades but seem

Ground rules of the pluripotency gene regulatory network.

KAUST Repository

Li, Mo

2017-01-03

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

Ground rules of the pluripotency gene regulatory network.

KAUST Repository

Li, Mo; Belmonte, Juan Carlos Izpisua

2017-01-01

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

Identifying Cis-Regulatory Changes Involved in the Evolution of Aerobic Fermentation in Yeasts

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Lin, Zhenguo; Wang, Tzi-Yuan; Tsai, Bing-Shi; Wu, Fang-Ting; Yu, Fu-Jung; Tseng, Yu-Jung; Sung, Huang-Mo; Li, Wen-Hsiung

2013-01-01

Gene regulation change has long been recognized as an important mechanism for phenotypic evolution. We used the evolution of yeast aerobic fermentation as a model to explore how gene regulation has evolved and how this process has contributed to phenotypic evolution and adaptation. Most eukaryotes fully oxidize glucose to CO2 and H2O in mitochondria to maximize energy yield, whereas some yeasts, such as Saccharomyces cerevisiae and its relatives, predominantly ferment glucose into ethanol even in the presence of oxygen, a phenomenon known as aerobic fermentation. We examined the genome-wide gene expression levels among 12 different yeasts and found that a group of genes involved in the mitochondrial respiration process showed the largest reduction in gene expression level during the evolution of aerobic fermentation. Our analysis revealed that the downregulation of these genes was significantly associated with massive loss of binding motifs of Cbf1p in the fermentative yeasts. Our experimental assays confirmed the binding of Cbf1p to the predicted motif and the activator role of Cbf1p. In summary, our study laid a foundation to unravel the long-time mystery about the genetic basis of evolution of aerobic fermentation, providing new insights into understanding the role of cis-regulatory changes in phenotypic evolution. PMID:23650209

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

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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.

Six subgroups and extensive recent duplications characterize the evolution of the eukaryotic tubulin protein family.

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Findeisen, Peggy; Mühlhausen, Stefanie; Dempewolf, Silke; Hertzog, Jonny; Zietlow, Alexander; Carlomagno, Teresa; Kollmar, Martin

2014-08-27

Tubulins belong to the most abundant proteins in eukaryotes providing the backbone for many cellular substructures like the mitotic and meiotic spindles, the intracellular cytoskeletal network, and the axonemes of cilia and flagella. Homologs have even been reported for archaea and bacteria. However, a taxonomically broad and whole-genome-based analysis of the tubulin protein family has never been performed, and thus, the number of subfamilies, their taxonomic distribution, and the exact grouping of the supposed archaeal and bacterial homologs are unknown. Here, we present the analysis of 3,524 tubulins from 504 species. The tubulins formed six major subfamilies, α to ζ. Species of all major kingdoms of the eukaryotes encode members of these subfamilies implying that they must have already been present in the last common eukaryotic ancestor. The proposed archaeal homologs grouped together with the bacterial TubZ proteins as sister clade to the FtsZ proteins indicating that tubulins are unique to eukaryotes. Most species contained α- and/or β-tubulin gene duplicates resulting from recent branch- and species-specific duplication events. This shows that tubulins cannot be used for constructing species phylogenies without resolving their ortholog-paralog relationships. The many gene duplicates and also the independent loss of the δ-, ε-, or ζ-tubulins, which have been shown to be part of the triplet microtubules in basal bodies, suggest that tubulins can functionally substitute each other. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

GFFview: A Web Server for Parsing and Visualizing Annotation Information of Eukaryotic Genome.

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Deng, Feilong; Chen, Shi-Yi; Wu, Zhou-Lin; Hu, Yongsong; Jia, Xianbo; Lai, Song-Jia

2017-10-01

Owing to wide application of RNA sequencing (RNA-seq) technology, more and more eukaryotic genomes have been extensively annotated, such as the gene structure, alternative splicing, and noncoding loci. Annotation information of genome is prevalently stored as plain text in General Feature Format (GFF), which could be hundreds or thousands Mb in size. Therefore, it is a challenge for manipulating GFF file for biologists who have no bioinformatic skill. In this study, we provide a web server (GFFview) for parsing the annotation information of eukaryotic genome and then generating statistical description of six indices for visualization. GFFview is very useful for investigating quality and difference of the de novo assembled transcriptome in RNA-seq studies.

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

OpenAIRE

Kristie, T M; Roizman, B

1986-01-01

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

Heterologous Expression of Toxins from Bacterial Toxin-Antitoxin Systems in Eukaryotic Cells: Strategies and Applications

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Yeo, Chew Chieng; Abu Bakar, Fauziah; Chan, Wai Ting; Espinosa, Manuel; Harikrishna, Jennifer Ann

2016-01-01

Toxin-antitoxin (TA) systems are found in nearly all prokaryotic genomes and usually consist of a pair of co-transcribed genes, one of which encodes a stable toxin and the other, its cognate labile antitoxin. Certain environmental and physiological cues trigger the degradation of the antitoxin, causing activation of the toxin, leading either to the death or stasis of the host cell. TA systems have a variety of functions in the bacterial cell, including acting as mediators of programmed cell death, the induction of a dormant state known as persistence and the stable maintenance of plasmids and other mobile genetic elements. Some bacterial TA systems are functional when expressed in eukaryotic cells and this has led to several innovative applications, which are the subject of this review. Here, we look at how bacterial TA systems have been utilized for the genetic manipulation of yeasts and other eukaryotes, for the containment of genetically modified organisms, and for the engineering of high expression eukaryotic cell lines. We also examine how TA systems have been adopted as an important tool in developmental biology research for the ablation of specific cells and the potential for utility of TA systems in antiviral and anticancer gene therapies. PMID:26907343

Heterologous Expression of Toxins from Bacterial Toxin-Antitoxin Systems in Eukaryotic Cells: Strategies and Applications

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Chew Chieng Yeo

2016-02-01

Full Text Available Toxin-antitoxin (TA systems are found in nearly all prokaryotic genomes and usually consist of a pair of co-transcribed genes, one of which encodes a stable toxin and the other, its cognate labile antitoxin. Certain environmental and physiological cues trigger the degradation of the antitoxin, causing activation of the toxin, leading either to the death or stasis of the host cell. TA systems have a variety of functions in the bacterial cell, including acting as mediators of programmed cell death, the induction of a dormant state known as persistence and the stable maintenance of plasmids and other mobile genetic elements. Some bacterial TA systems are functional when expressed in eukaryotic cells and this has led to several innovative applications, which are the subject of this review. Here, we look at how bacterial TA systems have been utilized for the genetic manipulation of yeasts and other eukaryotes, for the containment of genetically modified organisms, and for the engineering of high expression eukaryotic cell lines. We also examine how TA systems have been adopted as an important tool in developmental biology research for the ablation of specific cells and the potential for utility of TA systems in antiviral and anticancer gene therapies.

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

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Ruth Li

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

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

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

2013-10-01

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

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.

Directory of Open Access Journals (Sweden)

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.

Characterization and Evolution of the Cell Cycle-Associated Mob Domain-Containing Proteins in Eukaryotes

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Nicola Vitulo

2007-01-01

Full Text Available The MOB family includes a group of cell cycle-associated proteins highly conserved throughout eukaryotes, whose founding members are implicated in mitotic exit and co-ordination of cell cycle progression with cell polarity and morphogenesis. Here we report the characterization and evolution of the MOB domain-containing proteins as inferred from the 43 eukaryotic genomes so far sequenced. We show that genes for Mob-like proteins are present in at least 41 of these genomes, confi rming the universal distribution of this protein family and suggesting its prominent biological function. The phylogenetic analysis reveals fi ve distinct MOB domain classes, showing a progressive expansion of this family from unicellular to multicellular organisms, reaching the highest number in mammals. Plant Mob genes appear to have evolved from a single ancestor, most likely after the loss of one or more genes during the early stage of Viridiplantae evolutionary history. Three of the Mob classes are widespread among most of the analyzed organisms. The possible biological and molecular function of Mob proteins and their role in conserved signaling pathways related to cell proliferation, cell death and cell polarity are also presented and critically discussed.

Cooperative binding of transcription factors promotes bimodal gene expression response.

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Pablo S Gutierrez

Full Text Available In the present work we extend and analyze the scope of our recently proposed stochastic model for transcriptional regulation, which considers an arbitrarily complex cis-regulatory system using only elementary reactions. Previously, we determined the role of cooperativity on the intrinsic fluctuations of gene expression for activating transcriptional switches, by means of master equation formalism and computer simulation. This model allowed us to distinguish between two cooperative binding mechanisms and, even though the mean expression levels were not affected differently by the acting mechanism, we showed that the associated fluctuations were different. In the present generalized model we include other regulatory functions in addition to those associated to an activator switch. Namely, we introduce repressive regulatory functions and two theoretical mechanisms that account for the biphasic response that some cis-regulatory systems show to the transcription factor concentration. We have also extended our previous master equation formalism in order to include protein production by stochastic translation of mRNA. Furthermore, we examine the graded/binary scenarios in the context of the interaction energy between transcription factors. In this sense, this is the first report to show that the cooperative binding of transcription factors to DNA promotes the "all-or-none" phenomenon observed in eukaryotic systems. In addition, we confirm that gene expression fluctuation levels associated with one of two cooperative binding mechanism never exceed the fluctuation levels of the other.

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

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

2013-06-01

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

Identification of putative cis-regulatory elements in Cryptosporidium parvum by de novo pattern finding

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Kissinger Jessica C

2007-01-01

Full Text Available Abstract Background Cryptosporidium parvum is a unicellular eukaryote in the phylum Apicomplexa. It is an obligate intracellular parasite that causes diarrhea and is a significant AIDS-related pathogen. Cryptosporidium parvum is not amenable to long-term laboratory cultivation or classical molecular genetic analysis. The parasite exhibits a complex life cycle, a broad host range, and fundamental mechanisms of gene regulation remain unknown. We have used data from the recently sequenced genome of this organism to uncover clues about gene regulation in C. parvum. We have applied two pattern finding algorithms MEME and AlignACE to identify conserved, over-represented motifs in the 5' upstream regions of genes in C. parvum. To support our findings, we have established comparative real-time -PCR expression profiles for the groups of genes examined computationally. Results We find that groups of genes that share a function or belong to a common pathway share upstream motifs. Different motifs are conserved upstream of different groups of genes. Comparative real-time PCR studies show co-expression of genes within each group (in sub-sets during the life cycle of the parasite, suggesting co-regulation of these genes may be driven by the use of conserved upstream motifs. Conclusion This is one of the first attempts to characterize cis-regulatory elements in the absence of any previously characterized elements and with very limited expression data (seven genes only. Using de novo pattern finding algorithms, we have identified specific DNA motifs that are conserved upstream of genes belonging to the same metabolic pathway or gene family. We have demonstrated the co-expression of these genes (often in subsets using comparative real-time-PCR experiments thus establishing evidence for these conserved motifs as putative cis-regulatory elements. Given the lack of prior information concerning expression patterns and organization of promoters in C. parvum we

RNA Export through the NPC in Eukaryotes.

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Okamura, Masumi; Inose, Haruko; Masuda, Seiji

2015-03-20

In eukaryotic cells, RNAs are transcribed in the nucleus and exported to the cytoplasm through the nuclear pore complex. The RNA molecules that are exported from the nucleus into the cytoplasm include messenger RNAs (mRNAs), ribosomal RNAs (rRNAs), transfer RNAs (tRNAs), small nuclear RNAs (snRNAs), micro RNAs (miRNAs), and viral mRNAs. Each RNA is transported by a specific nuclear export receptor. It is believed that most of the mRNAs are exported by Nxf1 (Mex67 in yeast), whereas rRNAs, snRNAs, and a certain subset of mRNAs are exported in a Crm1/Xpo1-dependent manner. tRNAs and miRNAs are exported by Xpot and Xpo5. However, multiple export receptors are involved in the export of some RNAs, such as 60S ribosomal subunit. In addition to these export receptors, some adapter proteins are required to export RNAs. The RNA export system of eukaryotic cells is also used by several types of RNA virus that depend on the machineries of the host cell in the nucleus for replication of their genome, therefore this review describes the RNA export system of two representative viruses. We also discuss the NPC anchoring-dependent mRNA export factors that directly recruit specific genes to the NPC.

Evolutionary genomics of plant genes encoding N-terminal-TM-C2 domain proteins and the similar FAM62 genes and synaptotagmin genes of metazoans

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Craxton Molly

2007-07-01

Full Text Available Abstract Background Synaptotagmin genes are found in animal genomes and are known to function in the nervous system. Genes with a similar domain architecture as well as sequence similarity to synaptotagmin C2 domains have also been found in plant genomes. The plant genes share an additional region of sequence similarity with a group of animal genes named FAM62. FAM62 genes also have a similar domain architecture. Little is known about the functions of the plant genes and animal FAM62 genes. Indeed, many members of the large and diverse Syt gene family await functional characterization. Understanding the evolutionary relationships among these genes will help to realize the full implications of functional studies and lead to improved genome annotation. Results I collected and compared plant Syt-like sequences from the primary nucleotide sequence databases at NCBI. The collection comprises six groups of plant genes conserved in embryophytes: NTMC2Type1 to NTMC2Type6. I collected and compared metazoan FAM62 sequences and identified some similar sequences from other eukaryotic lineages. I found evidence of RNA editing and alternative splicing. I compared the intron patterns of Syt genes. I also compared Rabphilin and Doc2 genes. Conclusion Genes encoding proteins with N-terminal-transmembrane-C2 domain architectures resembling synaptotagmins, are widespread in eukaryotes. A collection of these genes is presented here. The collection provides a resource for studies of intron evolution. I have classified the collection into homologous gene families according to distinctive patterns of sequence conservation and intron position. The evolutionary histories of these gene families are traceable through the appearance of family members in different eukaryotic lineages. Assuming an intron-rich eukaryotic ancestor, the conserved intron patterns distinctive of individual gene families, indicate independent origins of Syt, FAM62 and NTMC2 genes. Resemblances

Biotransformation of arsenic by a Yellowstone thermoacidophilic eukaryotic alga.

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Qin, Jie; Lehr, Corinne R; Yuan, Chungang; Le, X Chris; McDermott, Timothy R; Rosen, Barry P

2009-03-31

Arsenic is the most common toxic substance in the environment, ranking first on the Superfund list of hazardous substances. It is introduced primarily from geochemical sources and is acted on biologically, creating an arsenic biogeocycle. Geothermal environments are known for their elevated arsenic content and thus provide an excellent setting in which to study microbial redox transformations of arsenic. To date, most studies of microbial communities in geothermal environments have focused on Bacteria and Archaea, with little attention to eukaryotic microorganisms. Here, we show the potential of an extremophilic eukaryotic alga of the order Cyanidiales to influence arsenic cycling at elevated temperatures. Cyanidioschyzon sp. isolate 5508 oxidized arsenite [As(III)] to arsenate [As(V)], reduced As(V) to As(III), and methylated As(III) to form trimethylarsine oxide (TMAO) and dimethylarsenate [DMAs(V)]. Two arsenic methyltransferase genes, CmarsM7 and CmarsM8, were cloned from this organism and demonstrated to confer resistance to As(III) in an arsenite hypersensitive strain of Escherichia coli. The 2 recombinant CmArsMs were purified and shown to transform As(III) into monomethylarsenite, DMAs(V), TMAO, and trimethylarsine gas, with a T(opt) of 60-70 degrees C. These studies illustrate the importance of eukaryotic microorganisms to the biogeochemical cycling of arsenic in geothermal systems, offer a molecular explanation for how these algae tolerate arsenic in their environment, and provide the characterization of algal methyltransferases.

Re-evaluating the green versus red signal in eukaryotes with secondary plastid of red algal origin

KAUST Repository

Burki, Fabien

2012-05-16

The transition from endosymbiont to organelle in eukaryotic cells involves the transfer of significant numbers of genes to the host genomes, a process known as endosymbiotic gene transfer (EGT). In the case of plastid organelles, EGTs have been shown to leave a footprint in the nuclear genome that can be indicative of ancient photosynthetic activity in present-day plastid-lacking organisms, or even hint at the existence of cryptic plastids. Here,we evaluated the impact of EGTon eukaryote genomes by reanalyzing the recently published EST dataset for Chromera velia, an interesting test case of a photosynthetic alga closely related to apicomplexan parasites. Previously, 513 genes were reported to originate from red and green algae in a 1:1 ratio. In contrast, by manually inspecting newly generated trees indicating putative algal ancestry, we recovered only 51 genes congruent with EGT, of which 23 and 9 were of red and green algal origin, respectively,whereas 19 were ambiguous regarding the algal provenance.Our approach also uncovered 109 genes that branched within a monocot angiosperm clade, most likely representing a contamination. We emphasize the lack of congruence and the subjectivity resulting from independent phylogenomic screens for EGT, which appear to call for extreme caution when drawing conclusions for major evolutionary events. 2012 The Author(s).

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

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Raza, Khalid; Alam, Mansaf

2016-10-01

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

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

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

2016-03-01

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

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

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

2018-01-01

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

A versatile selection system for folding competent proteins using genetic complementation in a eukaryotic host

DEFF Research Database (Denmark)

Lyngsø, C.; Kjaerulff, S.; Muller, S.

2010-01-01

in vivo selection system for folded proteins. It is based on genetic complementation of the Schizosaccharomyces pombe growth marker gene invertase fused C-terminally to a protein library. The fusion proteins are directed to the secretion system, utilizing the ability of the eukaryotic protein quality...

Characterization of an eukaryotic peptide deformylase from Plasmodium falciparum.

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Bracchi-Ricard, V; Nguyen, K T; Zhou, Y; Rajagopalan, P T; Chakrabarti, D; Pei, D

2001-12-15

Ribosomal protein synthesis in eubacteria and eukaryotic organelles initiates with an N-formylmethionyl-tRNA(i), resulting in N-terminal formylation of all nascent polypeptides. Peptide deformylase (PDF) catalyzes the subsequent removal of the N-terminal formyl group from the majority of bacterial proteins. Until recently, PDF has been thought as an enzyme unique to the bacterial kingdom. Searches of the genomic DNA databases identified several genes that encode proteins of high sequence homology to bacterial PDF from eukaryotic organisms. The cDNA encoding Plasmodium falciparum PDF (PfPDF) has been cloned and overexpressed in Escherichia coli. The recombinant protein is catalytically active in deformylating N-formylated peptides, shares many of the properties of bacterial PDF, and is inhibited by specific PDF inhibitors. Western blot analysis indicated expression of mature PfPDF in trophozoite, schizont, and segmenter stages of intraerythrocytic development. These results provide strong evidence that a functional PDF is present in P. falciparum. In addition, PDF inhibitors inhibited the growth of P. falciparum in the intraerythrocytic culture. (c)2001 Elsevier Science.

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

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

2016-01-01

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

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

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

2016-12-01

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

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

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Je-Hyuk Lee

2009-11-01

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

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

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

1987-12-08

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

Susceptibilities to DNA Structural Transitions within Eukaryotic Genomes

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Zhabinskaya, Dina; Benham, Craig; Madden, Sally

2012-02-01

We analyze the competitive transitions to alternate secondary DNA structures in a negatively supercoiled DNA molecule of kilobase length and specified base sequence. We use statistical mechanics to calculate the competition among all regions within the sequence that are susceptible to transitions to alternate structures. We use an approximate numerical method since the calculation of an exact partition function is numerically cumbersome for DNA molecules of lengths longer than hundreds of base pairs. This method yields accurate results in reasonable computational times. We implement algorithms that calculate the competition between transitions to denatured states and to Z-form DNA. We analyze these transitions near the transcription start sites (TSS) of a set of eukaryotic genes. We find an enhancement of Z-forming regions upstream of the TSS and a depletion of denatured regions around the start sites. We confirm that these finding are statistically significant by comparing our results to a set of randomized genes with preserved base composition at each position relative to the gene start sites. When we study the correlation of these transitions in orthologous mouse and human genes we find a clear evolutionary conservation of both types of transitions around the TSS.

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

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Huang Hsien-Da

2008-11-01

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

Large clusters of co-expressed genes in the Drosophila genome.

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Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

The Big Bang of picorna-like virus evolution antedates the radiation of eukaryotic supergroups.

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Koonin, Eugene V; Wolf, Yuri I; Nagasaki, Keizo; Dolja, Valerian V

2008-12-01

The recent discovery of RNA viruses in diverse unicellular eukaryotes and developments in evolutionary genomics have provided the means for addressing the origin of eukaryotic RNA viruses. The phylogenetic analyses of RNA polymerases and helicases presented in this Analysis article reveal close evolutionary relationships between RNA viruses infecting hosts from the Chromalveolate and Excavate supergroups and distinct families of picorna-like viruses of plants and animals. Thus, diversification of picorna-like viruses probably occurred in a 'Big Bang' concomitant with key events of eukaryogenesis. The origins of the conserved genes of picorna-like viruses are traced to likely ancestors including bacterial group II retroelements, the family of HtrA proteases and DNA bacteriophages.

Mixed heterolobosean and novel gregarine lineage genes from culture ATCC 50646: Long-branch artefacts, not lateral gene transfer, distort α-tubulin phylogeny.

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Cavalier-Smith, Thomas

2015-04-01

Contradictory and confusing results can arise if sequenced 'monoprotist' samples really contain DNA of very different species. Eukaryote-wide phylogenetic analyses using five genes from the amoeboflagellate culture ATCC 50646 previously implied it was an undescribed percolozoan related to percolatean flagellates (Stephanopogon, Percolomonas). Contrastingly, three phylogenetic analyses of 18S rRNA alone, did not place it within Percolozoa, but as an isolated deep-branching excavate. I resolve that contradiction by sequence phylogenies for all five genes individually, using up to 652 taxa. Its 18S rRNA sequence (GQ377652) is near-identical to one from stained-glass windows, somewhat more distant from one from cooling-tower water, all three related to terrestrial actinocephalid gregarines Hoplorhynchus and Pyxinia. All four protein-gene sequences (Hsp90; α-tubulin; β-tubulin; actin) are from an amoeboflagellate heterolobosean percolozoan, not especially deeply branching. Contrary to previous conclusions from trees combining protein and rRNA sequences or rDNA trees including Eozoa only, this culture does not represent a major novel deep-branching eukaryote lineage distinct from Heterolobosea, and thus lacks special significance for deep eukaryote phylogeny, though the rDNA sequence is important for gregarine phylogeny. α-Tubulin trees for over 250 eukaryotes refute earlier suggestions of lateral gene transfer within eukaryotes, being largely congruent with morphology and other gene trees. Copyright © 2015. Published by Elsevier GmbH.

Evolution of homeobox genes.

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Holland, Peter W H

2013-01-01

Many homeobox genes encode transcription factors with regulatory roles in animal and plant development. Homeobox genes are found in almost all eukaryotes, and have diversified into 11 gene classes and over 100 gene families in animal evolution, and 10 to 14 gene classes in plants. The largest group in animals is the ANTP class which includes the well-known Hox genes, plus other genes implicated in development including ParaHox (Cdx, Xlox, Gsx), Evx, Dlx, En, NK4, NK3, Msx, and Nanog. Genomic data suggest that the ANTP class diversified by extensive tandem duplication to generate a large array of genes, including an NK gene cluster and a hypothetical ProtoHox gene cluster that duplicated to generate Hox and ParaHox genes. Expression and functional data suggest that NK, Hox, and ParaHox gene clusters acquired distinct roles in patterning the mesoderm, nervous system, and gut. The PRD class is also diverse and includes Pax2/5/8, Pax3/7, Pax4/6, Gsc, Hesx, Otx, Otp, and Pitx genes. PRD genes are not generally arranged in ancient genomic clusters, although the Dux, Obox, and Rhox gene clusters arose in mammalian evolution as did several non-clustered PRD genes. Tandem duplication and genome duplication expanded the number of homeobox genes, possibly contributing to the evolution of developmental complexity, but homeobox gene loss must not be ignored. Evolutionary changes to homeobox gene expression have also been documented, including Hox gene expression patterns shifting in concert with segmental diversification in vertebrates and crustaceans, and deletion of a Pitx1 gene enhancer in pelvic-reduced sticklebacks. WIREs Dev Biol 2013, 2:31-45. doi: 10.1002/wdev.78 For further resources related to this article, please visit the WIREs website. The author declares that he has no conflicts of interest. Copyright © 2012 Wiley Periodicals, Inc.

MicroRNA-Mediated Gene Silencing in Plant Defense and Viral Counter-Defense

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Sheng-Rui Liu

2017-09-01

Full Text Available MicroRNAs (miRNAs are non-coding RNAs of approximately 20–24 nucleotides in length that serve as central regulators of eukaryotic gene expression by targeting mRNAs for cleavage or translational repression. In plants, miRNAs are associated with numerous regulatory pathways in growth and development processes, and defensive responses in plant–pathogen interactions. Recently, significant progress has been made in understanding miRNA-mediated gene silencing and how viruses counter this defense mechanism. Here, we summarize the current knowledge and recent advances in understanding the roles of miRNAs involved in the plant defense against viruses and viral counter-defense. We also document the application of miRNAs in plant antiviral defense. This review discusses the current understanding of the mechanisms of miRNA-mediated gene silencing and provides insights on the never-ending arms race between plants and viruses.

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

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

2016-01-01

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

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

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

2016-06-01

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

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

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Joshi NV

2009-01-01

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

Quantitative inference of dynamic regulatory pathways via microarray data

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Chen Bor-Sen

2005-03-01

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

Memory functions reveal structural properties of gene regulatory networks

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Perez-Carrasco, Ruben

2018-01-01

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

Remarkable interkingdom conservation of intron positions and massive, lineage-specific intron loss and gain in eukaryotic evolution.

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Rogozin, Igor B; Wolf, Yuri I; Sorokin, Alexander V; Mirkin, Boris G; Koonin, Eugene V

2003-09-02

Sequencing of eukaryotic genomes allows one to address major evolutionary problems, such as the evolution of gene structure. We compared the intron positions in 684 orthologous gene sets from 8 complete genomes of animals, plants, fungi, and protists and constructed parsimonious scenarios of evolution of the exon-intron structure for the respective genes. Approximately one-third of the introns in the malaria parasite Plasmodium falciparum are shared with at least one crown group eukaryote; this number indicates that these introns have been conserved through >1.5 billion years of evolution that separate Plasmodium from the crown group. Paradoxically, humans share many more introns with the plant Arabidopsis thaliana than with the fly or nematode. The inferred evolutionary scenario holds that the common ancestor of Plasmodium and the crown group and, especially, the common ancestor of animals, plants, and fungi had numerous introns. Most of these ancestral introns, which are retained in the genomes of vertebrates and plants, have been lost in fungi, nematodes, arthropods, and probably Plasmodium. In addition, numerous introns have been inserted into vertebrate and plant genes, whereas, in other lineages, intron gain was much less prominent.

Engineering nucleases for gene targeting: safety and regulatory considerations.

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

2014-01-25

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

How natural a kind is "eukaryote?".

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Doolittle, W Ford

2014-06-02

Systematics balances uneasily between realism and nominalism, uncommitted as to whether biological taxa are discoveries or inventions. If the former, they might be taken as natural kinds. I briefly review some philosophers' concepts of natural kinds and then argue that several of these apply well enough to "eukaryote." Although there are some sticky issues around genomic chimerism and when eukaryotes first appeared, if we allow for degrees in the naturalness of kinds, existing eukaryotes rank highly, higher than prokaryotes. Most biologists feel this intuitively: All I attempt to do here is provide some conceptual justification. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

Generic Properties of Random Gene Regulatory Networks.

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

2013-12-01

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

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.

Critical analysis of eukaryotic phylogeny: a case study based on the HSP70 family.

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Germot, A; Philippe, H

1999-01-01

Trichomonads, together with diplomonads and microsporidia, emerge at the base of the eukaryotic tree, on the basis of the small subunit rRNA phylogeny. However, phylogenies based on protein sequences such as tubulin are markedly different with these protists emerging much later. We have investigated 70 kDa heat-shock protein (HSP70), which could be a reliable phylogenetic marker. In eukaryotes, HSP70s are found in cytosol, endoplasmic reticulum, and organelles (mitochondria and chloroplasts). In Trichomonas vaginalis we identified nine different HSP70-encoding genes and sequenced three nearly complete cDNAs corresponding to cytosolic, endoplasmic reticulum, and mitochondrial-type HSP70. Phylogenies of eukaryotes were reconstructed using the classical methods while varying the number of species and characters considered. Almost all the undoubtedly monophyletic groups, defined by ultrastructural characters, were recovered. However, due to the long branch attraction phenomenon, the evolutionary rates were the main factor determining the position of species, even with the use of a close outgroup, which is an important advantage of HSP70 with respect to many other markers. Numerous variable sites are peculiar to Trichomonas and probably generated the artefactual placement of this species at the base of the eukaryotes or as the sister group of fast-evolving species. The inter-phyla relationships were not well supported and were sensitive to the reconstruction method, the number of species; and the quantity of information used. This lack of resolution could be explained by the very rapid diversification of eukaryotes, likely after the mitochondrial endosymbiosis.

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

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Walker Angela M

2009-04-01

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

The reduced kinome of Ostreococcus tauri: core eukaryotic signalling components in a tractable model species.

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Hindle, Matthew M; Martin, Sarah F; Noordally, Zeenat B; van Ooijen, Gerben; Barrios-Llerena, Martin E; Simpson, T Ian; Le Bihan, Thierry; Millar, Andrew J

2014-08-02

The current knowledge of eukaryote signalling originates from phenotypically diverse organisms. There is a pressing need to identify conserved signalling components among eukaryotes, which will lead to the transfer of knowledge across kingdoms. Two useful properties of a eukaryote model for signalling are (1) reduced signalling complexity, and (2) conservation of signalling components. The alga Ostreococcus tauri is described as the smallest free-living eukaryote. With less than 8,000 genes, it represents a highly constrained genomic palette. Our survey revealed 133 protein kinases and 34 protein phosphatases (1.7% and 0.4% of the proteome). We conducted phosphoproteomic experiments and constructed domain structures and phylogenies for the catalytic protein-kinases. For each of the major kinases families we review the completeness and divergence of O. tauri representatives in comparison to the well-studied kinomes of the laboratory models Arabidopsis thaliana and Saccharomyces cerevisiae, and of Homo sapiens. Many kinase clades in O. tauri were reduced to a single member, in preference to the loss of family diversity, whereas TKL and ABC1 clades were expanded. We also identified kinases that have been lost in A. thaliana but retained in O. tauri. For three, contrasting eukaryotic pathways - TOR, MAPK, and the circadian clock - we established the subset of conserved components and demonstrate conserved sites of substrate phosphorylation and kinase motifs. We conclude that O. tauri satisfies our two central requirements. Several of its kinases are more closely related to H. sapiens orthologs than S. cerevisiae is to H. sapiens. The greatly reduced kinome of O. tauri is therefore a suitable model for signalling in free-living eukaryotes.

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

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Lamprini G Kalampoki

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

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

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Yinyin Yuan

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

EuMicroSatdb: A database for microsatellites in the sequenced genomes of eukaryotes

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Grover Atul

2007-07-01

Full Text Available Abstract Background Microsatellites have immense utility as molecular markers in different fields like genome characterization and mapping, phylogeny and evolutionary biology. Existing microsatellite databases are of limited utility for experimental and computational biologists with regard to their content and information output. EuMicroSatdb (Eukaryotic MicroSatellite database http://ipu.ac.in/usbt/EuMicroSatdb.htm is a web based relational database for easy and efficient positional mining of microsatellites from sequenced eukaryotic genomes. Description A user friendly web interface has been developed for microsatellite data retrieval using Active Server Pages (ASP. The backend database codes for data extraction and assembly have been written using Perl based scripts and C++. Precise need based microsatellites data retrieval is possible using different input parameters like microsatellite type (simple perfect or compound perfect, repeat unit length (mono- to hexa-nucleotide, repeat number, microsatellite length and chromosomal location in the genome. Furthermore, information about clustering of different microsatellites in the genome can also be retrieved. Finally, to facilitate primer designing for PCR amplification of any desired microsatellite locus, 200 bp upstream and downstream sequences are provided. Conclusion The database allows easy systematic retrieval of comprehensive information about simple and compound microsatellites, microsatellite clusters and their locus coordinates in 31 sequenced eukaryotic genomes. The information content of the database is useful in different areas of research like gene tagging, genome mapping, population genetics, germplasm characterization and in understanding microsatellite dynamics in eukaryotic genomes.

Distribution and Diversity of Microbial Eukaryotes in Bathypelagic Waters of the South China Sea.

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Xu, Dapeng; Jiao, Nianzhi; Ren, Rui; Warren, Alan

2017-05-01

Little is known about the biodiversity of microbial eukaryotes in the South China Sea, especially in waters at bathyal depths. Here, we employed SSU rDNA gene sequencing to reveal the diversity and community structure across depth and distance gradients in the South China Sea. Vertically, the highest alpha diversity was found at 75-m depth. The communities of microbial eukaryotes were clustered into shallow-, middle-, and deep-water groups according to the depth from which they were collected, indicating a depth-related diversity and distribution pattern. Rhizaria sequences dominated the microeukaryote community and occurred in all samples except those from less than 50-m deep, being most abundant near the sea floor where they contributed ca. 64-97% and 40-74% of the total sequences and OTUs recovered, respectively. A large portion of rhizarian OTUs has neither a nearest named neighbor nor a nearest neighbor in the GenBank database which indicated the presence of new phylotypes in the South China Sea. Given their overwhelming abundance and richness, further phylogenetic analysis of rhizarians were performed and three new genetic clusters were revealed containing sequences retrieved from the deep waters of the South China Sea. Our results shed light on the diversity and community structure of microbial eukaryotes in this not yet fully explored area. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Heat degradation of eukaryotic and bacterial DNA: an experimental model for paleomicrobiology

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Nguyen-Hieu Tung

2012-09-01

Full Text Available Abstract Background Theoretical models suggest that DNA degradation would sharply limit the PCR-based detection of both eukaryotic and prokaryotic DNA within ancient specimens. However, the relative extent of decay of eukaryote and prokaryote DNA over time is a matter of debate. In this study, the murine macrophage cell line J774, alone or infected with Mycobacterium smegmatis bacteria, were killed after exposure to 90°C dry heat for intervals ranging from 1 to 48 h in order to compare eukaryotic cells, extracellular bacteria and intracellular bacteria. The sizes of the resulting mycobacterial rpoB and murine rpb2 homologous gene fragments were then determined by real-time PCR and fluorescent probing. Findings The cycle threshold (Ct values of PCR-amplified DNA fragments from J774 cells and the M. smegmatis negative controls (without heat exposure varied from 26–33 for the J774 rpb2 gene fragments and from 24–29 for M. smegmatis rpoB fragments. After 90°C dry heat incubation for up to 48 h, the Ct values of test samples increased relative to those of the controls for each amplicon size. For each dry heat exposure time, the Ct values of the 146-149-bp fragments were lower than those of 746-747-bp fragments. During the 4- to 24-h dry heat incubation, the non-infected J774 cell DNA was degraded into 597-bp rpb2 fragments. After 48 h, however, only 450-bp rpb2 fragments of both non-infected and infected J774 cells could be amplified. In contrast, the 746-bp rpoB fragments of M. smegmatis DNA could be amplified after the 48-h dry heat exposure in all experiments. Infected and non-infected J774 cell DNA was degraded more rapidly than M. smegmatis DNA after dry heat exposure (ANOVA test, p  Conclusion In this study, mycobacterial DNA was more resistant to dry-heat stress than eukaryotic DNA. Therefore, the detection of large, experimental, ancient mycobacterial DNA fragments is a suitable approach for paleomicrobiological studies.

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

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Chen, Dijun; Kaufmann, Kerstin

2017-01-01

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

Gene Therapy With Regulatory T Cells: A Beneficial Alliance

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Moanaro Biswas

2018-03-01

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

Small regulatory RNAs control the multi-cellular adhesive lifestyle of Escherichia coli

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Jørgensen, Mikkel Girke; Nielsen, Jesper Sejrup; Boysen, Anders

2012-01-01

Small regulatory RNA molecules have recently been recognized as important regulatory elements of developmental processes in both eukaryotes and bacteria. We here describe a striking example in Escherichia coli that can switch between a single-cell motile lifestyle and a multi-cellular, sessile....... Our demonstration that basal expression of each of the three RNA species is sufficient to downregulate CsgD synthesis and prevent curli formation indicates that all play a prominent role in the curli regulatory network. Our findings provide the first clue as to how the Rcs signalling pathway...... negatively regulates curli synthesis and increase the number of small regulatory RNAs that act directly on the csgD mRNA to five....

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

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

1991-12-20

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

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

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

2017-08-07

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

An algebra-based method for inferring gene regulatory networks.

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

2014-03-26

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

A versatile method to design stem-loop primer-based quantitative PCR assays for detecting small regulatory RNA molecules.

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Zsolt Czimmerer

Full Text Available Short regulatory RNA-s have been identified as key regulators of gene expression in eukaryotes. They have been involved in the regulation of both physiological and pathological processes such as embryonal development, immunoregulation and cancer. One of their relevant characteristics is their high stability, which makes them excellent candidates for use as biomarkers. Their number is constantly increasing as next generation sequencing methods reveal more and more details of their synthesis. These novel findings aim for new detection methods for the individual short regulatory RNA-s in order to be able to confirm the primary data and characterize newly identified subtypes in different biological conditions. We have developed a flexible method to design RT-qPCR assays that are very sensitive and robust. The newly designed assays were tested extensively in samples from plant, mouse and even human formalin fixed paraffin embedded tissues. Moreover, we have shown that these assays are able to quantify endogenously generated shRNA molecules. The assay design method is freely available for anyone who wishes to use a robust and flexible system for the quantitative analysis of matured regulatory RNA-s.

Functional and topological characteristics of mammalian regulatory domains

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

2014-01-01

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

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

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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.

Engineering a palette of eukaryotic chromoproteins for bacterial synthetic biology.

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Liljeruhm, Josefine; Funk, Saskia K; Tietscher, Sandra; Edlund, Anders D; Jamal, Sabri; Wistrand-Yuen, Pikkei; Dyrhage, Karl; Gynnå, Arvid; Ivermark, Katarina; Lövgren, Jessica; Törnblom, Viktor; Virtanen, Anders; Lundin, Erik R; Wistrand-Yuen, Erik; Forster, Anthony C

2018-01-01

Coral reefs are colored by eukaryotic chromoproteins (CPs) that are homologous to green fluorescent protein. CPs differ from fluorescent proteins (FPs) by intensely absorbing visible light to give strong colors in ambient light. This endows CPs with certain advantages over FPs, such as instrument-free detection uncomplicated by ultra-violet light damage or background fluorescence, efficient Förster resonance energy transfer (FRET) quenching, and photoacoustic imaging. Thus, CPs have found utility as genetic markers and in teaching, and are attractive for potential cell biosensor applications in the field. Most near-term applications of CPs require expression in a different domain of life: bacteria. However, it is unclear which of the eukaryotic CP genes might be suitable and how best to assay them. Here, taking advantage of codon optimization programs in 12 cases, we engineered 14 CP sequences (meffRed, eforRed, asPink, spisPink, scOrange, fwYellow, amilGFP, amajLime, cjBlue, meffBlue, aeBlue, amilCP, tsPurple and gfasPurple) into a palette of Escherichia coli BioBrick plasmids. BioBricks comply with synthetic biology's most widely used, simplified, cloning standard. Differences in color intensities, maturation times and fitness costs of expression were compared under the same conditions, and visible readout of gene expression was quantitated. A surprisingly large variation in cellular fitness costs was found, resulting in loss of color in some overnight liquid cultures of certain high-copy-plasmid-borne CPs, and cautioning the use of multiple CPs as markers in competition assays. We solved these two problems by integrating pairs of these genes into the chromosome and by engineering versions of the same CP with very different colors. Availability of 14 engineered CP genes compared in E. coli , together with chromosomal mutants suitable for competition assays, should simplify and expand CP study and applications. There was no single plasmid-borne CP that combined

Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

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Alina Sîrbu

2015-05-01

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

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

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

2015-05-14

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

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

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

2013-09-01

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

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

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

2016-03-12

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

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

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

2015-03-07

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

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

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Inoue, Masayo; Kaneko, Kunihiko

2013-04-01

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

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

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