scholarly journals Coherent Domains of Transcription Coordinate Gene Expression During Bacterial Growth and Adaptation

2019 ◽  
Vol 7 (12) ◽  
pp. 694 ◽  
Author(s):  
Georgi Muskhelishvili ◽  
Raphaël Forquet ◽  
Sylvie Reverchon ◽  
Sam Meyer ◽  
William Nasser
Keyword(s):  
Gene Expression ◽  
Bacterial Growth ◽  
Dna Sequences ◽  
Thermodynamic Stability ◽  
Spatial Organization ◽  
Genomic Sequence ◽  
Transcriptional Responses ◽  
Sequence Organization ◽  
Temporal Gene Expression ◽  
Coordinated Expression

Recent studies strongly suggest that in bacteria, both the genomic pattern of DNA thermodynamic stability and the order of genes along the chromosomal origin-to-terminus axis are highly conserved and that this spatial organization plays a crucial role in coordinating genomic transcription. In this article, we explore the relationship between genomic sequence organization and transcription in the commensal bacterium Escherichia coli and the plant pathogen Dickeya. We argue that, while in E. coli the gradient of DNA thermodynamic stability and gene order along the origin-to-terminus axis represent major organizational features orchestrating temporal gene expression, the genomic sequence organization of Dickeya is more complex, demonstrating extended chromosomal domains of thermodynamically distinct DNA sequences eliciting specific transcriptional responses to various kinds of stress encountered during pathogenic growth. This feature of the Dickeya genome is likely an adaptation to the pathogenic lifestyle utilizing differences in genomic sequence organization for the selective expression of virulence traits. We propose that the coupling of DNA thermodynamic stability and genetic function provides a common organizational principle for the coordinated expression of genes during both normal and pathogenic bacterial growth.

scholarly journals Structural insights into the role of architectural proteins in DNA looping deduced from computer simulations

2013 ◽  
Vol 41 (2) ◽  
pp. 559-564 ◽  
Author(s):  
Wilma K. Olson ◽  
Michael A. Grosner ◽  
Luke Czapla ◽  
David Swigon
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Genomic Sequence ◽  
Specific Binding ◽  
Double Helix ◽  
Lac Repressor ◽  
Dna Looping ◽  
Bacterial Gene ◽  
Architectural Proteins ◽  
Dna Double Helix

Bacterial gene expression is regulated by DNA elements that often lie far apart along the genomic sequence, but come close together during genetic processing. The intervening residues form loops, which are organized by the binding of various proteins. For example, the Escherichia coli Lac repressor protein binds DNA operators, separated by 92 or 401 bp, and suppresses the formation of gene products involved in the metabolism of lactose. The system also includes several highly abundant architectural proteins, such as the histone-like (heat-unstable) HU protein, which severely deform the double helix upon binding. In order to gain a better understanding of how the naturally stiff DNA double helix forms the short loops detected in vivo, we have developed new computational methods to study the effects of various non-specific binding proteins on the three-dimensional configurational properties of DNA sequences. The present article surveys the approach that we use to generate ensembles of spatially constrained protein-decorated DNA structures (minicircles and Lac repressor-mediated loops) and presents some of the insights gained from the correspondence between computation and experiment about the potential contributions of architectural and regulatory proteins to DNA looping and gene expression.

scholarly journals Exploring different sequence representations and classification methods for the prediction of nucleosome positioning

2018 ◽  
Author(s):  
Nikos Kostagiolas ◽  
Nikiforos Pittaras ◽  
Christoforos Nikolaou ◽  
George Giannakopoulos
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Large Scale ◽  
Genomic Sequence ◽  
Critical Role ◽  
Regulation Of Gene Expression ◽  
Nucleosome Positioning ◽  
Regulatory Elements ◽  
Machine Learning Algorithms ◽  
N Gram

Nucleosomes form the first level of DNA compaction and thus bear a critical role in the overall genome organization. At the same time, they modulate chromatin accessibility and, through a dynamic equilibrium with other DNA-binding proteins, may shape gene expression. A number of large-scale nucleosome positioning maps, obtained for various genomes, has compelled the importance of nucleosomes in the regulation of gene expression and has shown constraints in the relative positions of nucleosomes to be much stronger around regulatory elements (i.e. promoters, splice junctions and enhancers). At the same time, the great majority of nucleosome positions appears to be rather flexible. Various computational methods have in the past been used in order to capture the sequence determinants of nucleosome positioning but, as the extent to which DNA sequence preferences may guide nucleosome occupancy largely varies, this has proved to be rather difficult. In order to focus on highly specific sequence attributes, in this work we have analyzed two well-defined sets of nucleosome-occupied sites (NOS) and nucleosome-free-regions (NFR) from the genome of S. cerevisiae, with the use of textual representations. We employed 3 different genomic sequence representations (Hidden Markov Models, Bag-of-Words and N-gram Graphs) combined with a number of machine learning algorithms on the task of classifying genomic sequences as nucleosome-free (NFR) or nucleosome-occupied NOS (to be further amended based on updated results). We found that different approaches that involve the usage of different representations or algorithms can be more or less effective at predicting nucleosome positioning based on the textual data of the underlying genomic sequence. More interestingly, we show that N-gram Graphs, a sequence representation that takes into account both k-mer occurrences and relative positioning at various lengths scales is outperforming other methodologies and may thus be a choice of preference for the analysis of DNA sequences with subtle constraints.

Sequence-Based Deep Learning Frameworks on Enhancer-Promoter Interactions Prediction

2020 ◽  
Vol 26 ◽  
Author(s):  
Xiaoping Min ◽  
Fengqing Lu ◽  
Chunyan Li
Keyword(s):  
Gene Expression ◽  
Deep Learning ◽  
Dna Sequences ◽  
Experimental Methods ◽  
Learning Methods ◽  
Comprehensive Review ◽  
Genomic Features ◽  
Disease Mechanisms ◽  
Evaluation Strategies ◽  
Learning Frameworks

: Enhancer-promoter interactions (EPIs) in the human genome are of great significance to transcriptional regulation which tightly controls gene expression. Identification of EPIs can help us better deciphering gene regulation and understanding disease mechanisms. However, experimental methods to identify EPIs are constrained by the fund, time and manpower while computational methods using DNA sequences and genomic features are viable alternatives. Deep learning methods have shown promising prospects in classification and efforts that have been utilized to identify EPIs. In this survey, we specifically focus on sequence-based deep learning methods and conduct a comprehensive review of the literatures of them. We first briefly introduce existing sequence-based frameworks on EPIs prediction and their technique details. After that, we elaborate on the dataset, pre-processing means and evaluation strategies. Finally, we discuss the challenges these methods are confronted with and suggest several future opportunities.

scholarly journals Chromatin loop anchors contain core structural components of the gene expression machinery in maize

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Stéphane Deschamps ◽  
John A. Crow ◽  
Nadia Chaidir ◽  
Brooke Peterson-Burch ◽  
Sunil Kumar ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Transcriptional Activity ◽  
Spatial Organization ◽  
Regulatory Elements ◽  
Open Chromatin ◽  
Maize Genome ◽  
Chromatin Loop ◽  
Structural Components ◽  
Chromatin Loops

Abstract Background Three-dimensional chromatin loop structures connect regulatory elements to their target genes in regions known as anchors. In complex plant genomes, such as maize, it has been proposed that loops span heterochromatic regions marked by higher repeat content, but little is known on their spatial organization and genome-wide occurrence in relation to transcriptional activity. Results Here, ultra-deep Hi-C sequencing of maize B73 leaf tissue was combined with gene expression and open chromatin sequencing for chromatin loop discovery and correlation with hierarchical topologically-associating domains (TADs) and transcriptional activity. A majority of all anchors are shared between multiple loops from previous public maize high-resolution interactome datasets, suggesting a highly dynamic environment, with a conserved set of anchors involved in multiple interaction networks. Chromatin loop interiors are marked by higher repeat contents than the anchors flanking them. A small fraction of high-resolution interaction anchors, fully embedded in larger chromatin loops, co-locate with active genes and putative protein-binding sites. Combinatorial analyses indicate that all anchors studied here co-locate with at least 81.5% of expressed genes and 74% of open chromatin regions. Approximately 38% of all Hi-C chromatin loops are fully embedded within hierarchical TAD-like domains, while the remaining ones share anchors with domain boundaries or with distinct domains. Those various loop types exhibit specific patterns of overlap for open chromatin regions and expressed genes, but no apparent pattern of gene expression. In addition, up to 63% of all unique variants derived from a prior public maize eQTL dataset overlap with Hi-C loop anchors. Anchor annotation suggests that < 7% of all loops detected here are potentially devoid of any genes or regulatory elements. The overall organization of chromatin loop anchors in the maize genome suggest a loop modeling system hypothesized to resemble phase separation of repeat-rich regions. Conclusions Sets of conserved chromatin loop anchors mapping to hierarchical domains contains core structural components of the gene expression machinery in maize. The data presented here will be a useful reference to further investigate their function in regard to the formation of transcriptional complexes and the regulation of transcriptional activity in the maize genome.

scholarly journals Polycombs and microRNA-223 regulate human granulopoiesis by transcriptional control of target gene expression

Blood ◽  
2012 ◽  
Vol 119 (17) ◽  
pp. 4034-4046 ◽  
Author(s):  
Giuseppe Zardo ◽  
Alberto Ciolfi ◽  
Laura Vian ◽  
Linda M. Starnes ◽  
Monia Billi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Transcriptional Control ◽  
Transcriptional Level ◽  
Seed Region ◽  
Mrna Targets ◽  
Epigenetic Events ◽  
Evolutionarily Conserved ◽  
Lineage Decision ◽  
Chromatin Remodeling Complexes

Abstract Epigenetic modifications regulate developmental genes involved in stem cell identity and lineage choice. NFI-A is a posttranscriptional microRNA-223 (miR-223) target directing human hematopoietic progenitor lineage decision: NFI-A induction or silencing boosts erythropoiesis or granulopoiesis, respectively. Here we show that NFI-A promoter silencing, which allows granulopoiesis, is guaranteed by epigenetic events, including the resolution of opposing chromatin “bivalent domains,” hypermethylation, recruitment of polycomb (PcG)–RNAi complexes, and miR-223 promoter targeting activity. During granulopoiesis, miR-223 localizes inside the nucleus and targets the NFI-A promoter region containing PcGs binding sites and miR-223 complementary DNA sequences, evolutionarily conserved in mammalians. Remarkably, both the integrity of the PcGs-RNAi complex and DNA sequences matching the seed region of miR-223 are required to induce NFI-A transcriptional silencing. Moreover, ectopic miR-223 expression in human myeloid progenitors causes heterochromatic repression of NFI-A gene and channels granulopoiesis, whereas its stable knockdown produces the opposite effects. Our findings indicate that, besides the regulation of translation of mRNA targets, endogenous miRs can affect gene expression at the transcriptional level, functioning in a critical interface between chromatin remodeling complexes and the genome to direct fate lineage determination of hematopoietic progenitors.

Temporal gene expression profiling of maslinic acid-treated Raji cells

2021 ◽  
Author(s):  
Wai Meng Lau ◽  
Menaga Subramaniam ◽  
Hoe Han Goh ◽  
Yang Mooi Lim
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Raji Cells ◽  
Maslinic Acid ◽  
Temporal Gene Expression ◽  
Key Pathways

An hourly progression of gene expression profiling in maslinic acid treated Raji cells, which reported activation of several key pathways.

scholarly journals Yeast DNA sequences initiating gene expression in Escherichia coli

2004 ◽  
Vol 159 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Astrid Lewin ◽  
Thi Tuyen Tran ◽  
Daniela Jacob ◽  
Martin Mayer ◽  
Barbara Freytag ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Dna Sequences ◽  
Expression In Escherichia Coli

scholarly journals Assessment of the Role of Activator Protein-1 on Transcription of the Mouse Steroidogenic Acute Regulatory Protein Gene

2004 ◽  
Vol 18 (3) ◽  
pp. 558-573 ◽  
Author(s):  
Pulak R. Manna ◽  
Darrell W. Eubank ◽  
Douglas M. Stocco
Keyword(s):  
Binding Site ◽  
Gene Transcription ◽  
Dna Sequences ◽  
Regulatory Protein ◽  
Activator Protein 1 ◽  
Transcriptional Responses ◽  
Activator Protein ◽  
Steroidogenic Acute Regulatory ◽  
Star Gene

Abstract cAMP-dependent mechanisms regulate the steroidogenic acute regulatory (StAR) protein even though its promoter lacks a consensus cAMP response-element (CRE, TGACGTCA). Transcriptional regulation of the StAR gene has been demonstrated to involve combinations of DNA sequences that provide recognition motifs for sequence-specific transcription factors. We recently identified and characterized three canonical 5′-CRE half-sites within the cAMP-responsive region (−151/−1 bp) of the mouse StAR gene. Among these CRE elements, the CRE2 half-site is analogous (TGACTGA) to an activator protein-1 (AP-1) sequence [TGA(C/G)TCA]; therefore, the role of the AP-1 transcription factor was explored in StAR gene transcription. Mutation in the AP-1 element demonstrated an approximately 50% decrease in StAR reporter activity. Using EMSA, oligonucleotide probes containing an AP-1 binding site were found to specifically bind to nuclear proteins obtained from mouse MA-10 Leydig and Y-1 adrenocortical tumor cells. The integrity of the sequence-specific AP-1 element in StAR gene transcription was assessed using the AP-1 family members, Fos (c-Fos, Fra-1, Fra-2, and Fos B) and Jun (c-Jun, Jun B, and Jun D), which demonstrated the involvement of Fos and Jun in StAR gene transcription to varying degrees. Disruption of the AP-1 binding site reversed the transcriptional responses seen with Fos and Jun. EMSA studies utilizing antibodies specific to Fos and Jun demonstrated the involvement of several AP-1 family proteins. Functional assessment of Fos and Jun was further demonstrated by transfecting antisense c-Fos, Fra-1, and dominant negative forms of Fos (A-Fos) and c-Jun (TAM-67) into MA-10 cells, which significantly (P &lt; 0.01) repressed transcription of the StAR gene. Mutation of the AP-1 site in combination with mutations in other cis-elements resulted in a further decrease of StAR promoter activity, demonstrating a functional cooperation between these factors. Mammalian two-hybrid assays revealed high-affinity protein-protein interactions between c-Fos and c-Jun with steroidogenic factor 1, GATA-4, and CCAAT/enhancer binding protein-β. These findings demonstrate that Fos and Jun can bind to the TGACTGA element in the StAR promoter and provide novel insights into the mechanisms regulating StAR gene transcription.

Sign in / Sign up

Export Citation Format

Share Document