Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA290333 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR2106930.fastq.gz | Fastqsanger.gz | |||
| SRR2106940.fastq.gz | Fastqsanger.gz | |||
| SRR2106950.fastq.gz | Fastqsanger.gz | |||
| SRR2106931.fastq.gz | Fastqsanger.gz | |||
| SRR2106941.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 30 |
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Project description:RNA interference (RNAi) technology is widely used in basic and translational research. By mimicking natural primary microRNA (pri-miRNA) cluster, multiple engineered hairpins can be transcribed as a single transcript from the same Pol-II promoter, enabling multiplex RNAi in mammalian cells 1-5. However, constructing synthetic miRNA cluster is still time-consuming, and the processing and function of miRNA cluster are incompletely understood. Here, we identified a miRNA precursor architecture that allowed precise miRNA maturation. We established a hierarchical cloning method for efficient construction of synthetic miRNA cluster harboring up to 18 miRNA precursors. We demonstrated that maturation and function of individual miRNA precursors were independent on their positions in the cluster. We then analyzed the integration efficiency of miRNA clusters with varying number of miRNA precursors by using CRISPR/Cas9 mediated integration, piggyBac transposon system, and lentiviral system. This synthetic miRNA cluster system provides an important tool for multiplex RNAi in mammalian cells. Different kinds of synthetic miRNAs or miRNA clusters, including the same synthetic miRNA precursor embedded in a series of derivative backbones, 18 synthetic miRNA precursors, miRNA precursors with various stem lengths and miRNA clusters carrying different numbers of different pri-miRNA hairpins, were expressed in HEK293 cells. The microRNA maturation pattern of individual miRNA precursors was detected by small RNA sequencing.
2016-09-01 | E-GEOD-71088 | biostudies-arrayexpress
Project description:RNA interference (RNAi) technology is widely used in basic and translational research. By mimicking natural primary microRNA (pri-miRNA) cluster, multiple engineered hairpins can be transcribed as a single transcript from the same Pol-II promoter, enabling multiplex RNAi in mammalian cells 1-5. However, constructing synthetic miRNA cluster is still time-consuming, and the processing and function of miRNA cluster are incompletely understood. Here, we identified a miRNA precursor architecture that allowed precise miRNA maturation. We established a hierarchical cloning method for efficient construction of synthetic miRNA cluster harboring up to 18 miRNA precursors. We demonstrated that maturation and function of individual miRNA precursors were independent on their positions in the cluster. We then analyzed the integration efficiency of miRNA clusters with varying number of miRNA precursors by using CRISPR/Cas9 mediated integration, piggyBac transposon system, and lentiviral system. This synthetic miRNA cluster system provides an important tool for multiplex RNAi in mammalian cells.
2016-09-01 | GSE71088 | GEO
Project description:This a model from the article:
Synthetic in vitro transcriptional oscillators.
Kim J, Winfree E Mol. Syst. Biol.
2011 Feb 1;7:465. 21283141
,
Abstract:
The construction of synthetic biochemical circuits from simple components illuminates how complex beha
viors can arise in chemistry and builds a foundation for future biological technologies. A simplified
analog of genetic regulatory networks, in vitro transcriptional circuits, provides a modular platform
for the systematic construction of arbitrary circuits and requires only two essential enzymes, bacteri
ophage T7 RNA polymerase and Escherichia coli ribonuclease H, to produce and degrade RNA signals. In t
his study, we design and experimentally demonstrate three transcriptional oscillators in vitro. First,
a negative feedback oscillator comprising two switches, regulated by excitatory and inhibitory RNA si
gnals, showed up to five complete cycles. To demonstrate modularity and to explore the design space fu
rther, a positive-feedback loop was added that modulates and extends the oscillatory regime. Finally,
a three-switch ring oscillator was constructed and analyzed. Mathematical modeling guided the design p
rocess, identified experimental conditions likely to yield oscillations, and explained the system's ro
bust response to interference by short degradation products. Synthetic transcriptional oscillators cou
ld prove valuable for systematic exploration of biochemical circuit design principles and for controll
ing nanoscale devices and orchestrating processes within artificial cells.
Note:
The paper describes 7 models (MODEL1012090000-6) and all these are submitted by the authors. This
model (MODEL1012090000) corresponds to the Simple model for both mode I and II (Design I and II).
The model reproduces timecourse figure plotted in the supplementary material (page 10 of Supplementary
material) of the reference publication.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2024-09-02 | BIOMD0000000322 | BioModels
Project description:This a model from the article:
Synthetic in vitro transcriptional oscillators.
Kim J, Winfree E Mol. Syst. Biol.
2011 Feb 1;7:465. 21283141
,
Abstract:
The construction of synthetic biochemical circuits from simple components illuminates how complex behaviors can arise in chemistry and builds a foundation for future biological technologies. A simplified analog of genetic regulatory networks, in vitro transcriptional circuits, provides a modular platform for the systematic construction of arbitrary circuits and requires only two essential enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H, to produce and degrade RNA signals. In this study, we design and experimentally demonstrate three transcriptional oscillators in vitro. First, a negative feedback oscillator comprising two switches, regulated by excitatory and inhibitory RNA signals, showed up to five complete cycles. To demonstrate modularity and to explore the design space further, a positive-feedback loop was added that modulates and extends the oscillatory regime. Finally, a three-switch ring oscillator was constructed and analyzed. Mathematical modeling guided the design process, identified experimental conditions likely to yield oscillations, and explained the system's robust response to interference by short degradation products. Synthetic transcriptional oscillators could prove valuable for systematic exploration of biochemical circuit design principles and for controlling nanoscale devices and orchestrating processes within artificial cells.
Notes:
The paper describes 7 models (MODEL1012090000-6) and all these are submitted by the authors. This model (MODEL1012090001) corresponds to the Simple model of the three-switch ring oscillator (Design III). The model reproduces figure 6 (central figures) of the reference publication. The time is rescaled by s=v_d/K_I*t where K_I=0.333 and v_d=1 (for alpha = 1) and v_d=0.5 (for alpha = 0.5). i.e. For alpha = 1, s = 0.003 * t (roughly 10 unitless time = 1hr; the time-course should be run for 60 timeunits (6hrs) to get figure 6a). For alpha = 2, s= 0.0015 * t (roughly 5 unitless time = 1hr; the time-course shoue be run for 100 timesunits (20hrs) to get figure 6b).
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
For more information see the terms of use
.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
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