scholarly journals The yeast PHO5 promoter: from single locus to systems biology of a paradigm for gene regulation through chromatin

2014 ◽  
Vol 42 (17) ◽  
pp. 10888-10902 ◽  
Author(s):  
Philipp Korber ◽  
Slobodan Barbaric
Keyword(s):  
Gene Regulation ◽  
Systems Biology ◽  
Single Locus ◽  
Pho5 Promoter

Transcription in Living Cells: Molecular Mechanisms of Bursting

2020 ◽  
Vol 89 (1) ◽  
pp. 189-212 ◽  
Author(s):  
Joseph Rodriguez ◽  
Daniel R. Larson
Keyword(s):  
Gene Regulation ◽  
Rna Synthesis ◽  
Molecular Mechanisms ◽  
Gene Activation ◽  
Living Cells ◽  
Single Locus ◽  
Individual Gene ◽  
Technological Advances ◽  
Transcriptional Bursting ◽  
Cell Data

Transcription in several organisms from certain bacteria to humans has been observed to be stochastic in nature: toggling between active and inactive states. Periods of active nascent RNA synthesis known as bursts represent individual gene activation events in which multiple polymerases are initiated. Therefore, bursting is the single locus illustration of both gene activation and repression. Although transcriptional bursting was originally observed decades ago, only recently have technological advances enabled the field to begin elucidating gene regulation at the single-locus level. In this review, we focus on how biochemical, genomic, and single-cell data describe the regulatory steps of transcriptional bursts.

scholarly journals Chromatin is frequently unknotted at the megabase scale

2019 ◽  
Author(s):  
Dimos Goundaroulis ◽  
Erez Lieberman Aiden ◽  
Andrzej Stasiak
Keyword(s):  
Gene Regulation ◽  
Human Genome ◽  
Single Locus ◽  
Chromosome 21 ◽  
Cellular Processes ◽  
Potential Source ◽  
Localization Errors

Knots in the human genome would greatly impact diverse cellular processes ranging from transcription to gene regulation. To date, it has not been possible to directly examine the genome in vivo for the presence of knots. Recently, methods for serial fluorescent in situ hybridization have made it possible to measure the 3d position of dozens of consecutive genomic loci, in vivo. However, the determination of whether genomic trajectories are knotted remains challenging, because small errors in the localization of a single locus can transform an unknotted trajectory into a highly-knotted trajectory, and vice versa. Here, we use stochastic closure analysis to determine whether a genomic trajectory is knotted in the setting of experimental noise. We analyse 4727 deposited genomic trajectories of a 2Mb long chromatin interval from chromosome 21. For 243 of these trajectories, their knottedness could be reliably determined despite the possibility of localization errors. Strikingly, in each of these 243 cases, the trajectory was unknotted. We note a potential source of bias, insofar as knotted contours may be more difficult to reliably resolve. Nevertheless, our data is consistent with a model where, at the scales probed, the human genome is often free of knots.

scholarly journals Systems biology graphical notation markup language (SBGNML) version 0.3

2020 ◽  
Vol 17 (2-3) ◽  
Author(s):  
Frank T. Bergmann ◽  
Tobias Czauderna ◽  
Ugur Dogrusoz ◽  
Adrien Rougny ◽  
Andreas Dräger ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Systems Biology ◽  
Programming Languages ◽  
Biological Knowledge ◽  
Markup Language ◽  
Graphical Notation ◽  
Accurate Representation ◽  
Previous Version ◽  
Computer Scientists ◽  
Extensible Markup

AbstractThis document defines Version 0.3 Markup Language (ML) support for the Systems Biology Graphical Notation (SBGN), a set of three complementary visual languages developed for biochemists, modelers, and computer scientists. SBGN aims at representing networks of biochemical interactions in a standard, unambiguous way to foster efficient and accurate representation, visualization, storage, exchange, and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. SBGN is defined neutrally to programming languages and software encoding; however, it is oriented primarily towards allowing models to be encoded using XML, the eXtensible Markup Language. The notable changes from the previous version include the addition of attributes for better specify metadata about maps, as well as support for multiple maps, sub-maps, colors, and annotations. These changes enable a more efficient exchange of data to other commonly used systems biology formats (e. g., BioPAX and SBML) and between tools supporting SBGN (e. g., CellDesigner, Newt, Krayon, SBGN-ED, STON, cd2sbgnml, and MINERVA). More details on SBGN and related software are available at http://sbgn.org. With this effort, we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner.

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