Coupled pre-mRNA and mRNA dynamics unveil the operation strategies underlying transcriptional responses
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE24391 | GEO | 2011/08/31
SECONDARY ACCESSION(S): PRJNA132879
REPOSITORIES: GEO
Similar Datasets
Project description:Transcriptional responses to stimuli are regulated by tuning rates of transcript production and degradation. Here we show that stimulation-induced changes in transcript production and degradation rates can be inferred from simultaneously measured precursor mRNA (pre-mRNA) and mature mRNA profiles. Our studies on the transcriptome-wide responses to extracellular stimuli in different cellular model systems revealed hitherto unanticipated dynamics of transcript production and degradation rates. Intriguingly, genes with similar mRNA profiles often exhibit marked differences in the amplitude and onset of their production. Moreover, we identify a group of genes, which take advantage of the unexpectedly large dynamic range of production rates to expedite their induction by a transient production overshoot. These findings provide an unprecedented quantitative view on processes governing transcriptional responses, and may have broad implications for understanding their regulation at the transcriptional and post-transcriptional levels. MCF10A cells stimulated with EGF
2011-08-30 | E-GEOD-24391 | biostudies-arrayexpress
Project description:Transcriptional responses to stimuli are regulated by tuning rates of transcript production and degradation. Here we show that stimulation-induced changes in transcript production and degradation rates can be inferred from simultaneously measured precursor mRNA (pre-mRNA) and mature mRNA profiles. Our studies on the transcriptome-wide responses to extracellular stimuli in different cellular model systems revealed hitherto unanticipated dynamics of transcript production and degradation rates. Intriguingly, genes with similar mRNA profiles often exhibit marked differences in the amplitude and onset of their production. Moreover, we identify a group of genes, which take advantage of the unexpectedly large dynamic range of production rates to expedite their induction by a transient production overshoot. These findings provide an unprecedented quantitative view on processes governing transcriptional responses, and may have broad implications for understanding their regulation at the transcriptional and post-transcriptional levels. MCF10A cells stimulated with EGF, DEX, and their combination
2014-08-30 | E-GEOD-53405 | biostudies-arrayexpress
Project description:Transcriptional responses to stimuli are regulated by tuning rates of transcript production and degradation. Here we show that stimulation-induced changes in transcript production and degradation rates can be inferred from simultaneously measured precursor mRNA (pre-mRNA) and mature mRNA profiles. Our studies on the transcriptome-wide responses to extracellular stimuli in different cellular model systems revealed hitherto unanticipated dynamics of transcript production and degradation rates. Intriguingly, genes with similar mRNA profiles often exhibit marked differences in the amplitude and onset of their production. Moreover, we identify a group of genes, which take advantage of the unexpectedly large dynamic range of production rates to expedite their induction by a transient production overshoot. These findings provide an unprecedented quantitative view on processes governing transcriptional responses, and may have broad implications for understanding their regulation at the transcriptional and post-transcriptional levels.
2014-08-30 | GSE53405 | GEO
Project description:LlorénsRico2016 - Effects of cis-Encoded antisense RNAs (asRNAs) - Case1
Three
putative effects of the asRNAs were considered in this study: in
case 1
(this
model)
,
the binding of the asRNA to the corresponding mRNA induces
degradation of the duplex. In case 2, the binding of the asRNA to
the mRNA induces degradation of the mRNA, but not of the asRNA.
In case 3, the mRNA and the asRNA bind reversibly to form a
stable duplex, preventing translation of the mRNA. In all the
three cases, binding to the ribosome protects the mRNA from the
effect of the asRNA.
This model is described in the article:
Bacterial antisense RNAs are
mainly the product of transcriptional noise.
Lloréns-Rico V, Cano J,
Kamminga T, Gil R, Latorre A, Chen WH, Bork P, Glass JI, Serrano
L, Lluch-Senar M.
Sci Adv 2016 Mar; 2(3): e1501363
Abstract:
cis-Encoded antisense RNAs (asRNAs) are widespread along
bacterial transcriptomes. However, the role of most of these
RNAs remains unknown, and there is an ongoing discussion as to
what extent these transcripts are the result of transcriptional
noise. We show, by comparative transcriptomics of 20 bacterial
species and one chloroplast, that the number of asRNAs is
exponentially dependent on the genomic AT content and that
expression of asRNA at low levels exerts little impact in terms
of energy consumption. A transcription model simulating mRNA
and asRNA production indicates that the asRNA regulatory effect
is only observed above certain expression thresholds,
substantially higher than physiological transcript levels.
These predictions were verified experimentally by
overexpressing nine different asRNAs in Mycoplasma pneumoniae.
Our results suggest that most of the antisense transcripts
found in bacteria are the consequence of transcriptional noise,
arising at spurious promoters throughout the genome.
This model is hosted on
BioModels Database
and identified by:
MODEL1511170000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
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.
2017-05-18 | MODEL1511170000 | BioModels
Project description:LlorénsRico2016 - Effects of cis-Encoded
antisense RNAs (asRNAs) - Case3
Three putative
effects of the asRNAs were considered in this study: in case 1,
the binding of the asRNA to the corresponding mRNA induces
degradation of the duplex. In case 2, the binding of the asRNA
to the mRNA induces degradation of the mRNA, but not of the
asRNA. In case 3 (this model), the mRNA and the asRNA bind
reversibly to form a stable duplex, preventing translation of
the mRNA. In all the three cases, binding to the ribosome
protects the mRNA from the effect of the asRNA.
This model is described in the article:
Bacterial antisense RNAs are
mainly the product of transcriptional noise.
Lloréns-Rico V, Cano J,
Kamminga T, Gil R, Latorre A, Chen WH, Bork P, Glass JI, Serrano
L, Lluch-Senar M.
Sci Adv 2016 Mar; 2(3): e1501363
Abstract:
cis-Encoded antisense RNAs (asRNAs) are widespread along
bacterial transcriptomes. However, the role of most of these
RNAs remains unknown, and there is an ongoing discussion as to
what extent these transcripts are the result of transcriptional
noise. We show, by comparative transcriptomics of 20 bacterial
species and one chloroplast, that the number of asRNAs is
exponentially dependent on the genomic AT content and that
expression of asRNA at low levels exerts little impact in terms
of energy consumption. A transcription model simulating mRNA
and asRNA production indicates that the asRNA regulatory effect
is only observed above certain expression thresholds,
substantially higher than physiological transcript levels.
These predictions were verified experimentally by
overexpressing nine different asRNAs in Mycoplasma pneumoniae.
Our results suggest that most of the antisense transcripts
found in bacteria are the consequence of transcriptional noise,
arising at spurious promoters throughout the genome.
This model is hosted on
BioModels Database
and identified by:
MODEL1511170002.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
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.
2017-05-18 | MODEL1511170002 | BioModels
Project description:LlorénsRico2016 - Effects of cis-Encoded
antisense RNAs (asRNAs) - Case1
Three
putative effects of the asRNAs were considered in this study: in
case 1
,
the binding of the asRNA to the corresponding mRNA induces
degradation of the duplex. In case 2
(this
model)
the binding of the asRNA to the mRNA induces degradation of the
mRNA, but not of the asRNA. In case 3, the mRNA and the asRNA
bind reversibly to form a stable duplex, preventing translation
of the mRNA. In all the three cases, binding to the ribosome
protects the mRNA from the effect of the asRNA.
This model is described in the article:
Bacterial antisense RNAs are
mainly the product of transcriptional noise.
Lloréns-Rico V, Cano J,
Kamminga T, Gil R, Latorre A, Chen WH, Bork P, Glass JI, Serrano
L, Lluch-Senar M.
Sci Adv 2016 Mar; 2(3): e1501363
Abstract:
cis-Encoded antisense RNAs (asRNAs) are widespread along
bacterial transcriptomes. However, the role of most of these
RNAs remains unknown, and there is an ongoing discussion as to
what extent these transcripts are the result of transcriptional
noise. We show, by comparative transcriptomics of 20 bacterial
species and one chloroplast, that the number of asRNAs is
exponentially dependent on the genomic AT content and that
expression of asRNA at low levels exerts little impact in terms
of energy consumption. A transcription model simulating mRNA
and asRNA production indicates that the asRNA regulatory effect
is only observed above certain expression thresholds,
substantially higher than physiological transcript levels.
These predictions were verified experimentally by
overexpressing nine different asRNAs in Mycoplasma pneumoniae.
Our results suggest that most of the antisense transcripts
found in bacteria are the consequence of transcriptional noise,
arising at spurious promoters throughout the genome.
This model is hosted on
BioModels Database
and identified by:
MODEL1511170001.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
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.
2017-05-18 | MODEL1511170001 | BioModels
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Project description:Photo-inhibitory high-light stress induces damage to photosystems and changes a myriad of metabolic processes in plants. In Arabidopsis it leads to increased abundance of markers of protein degradation and transcriptional upregulation of proteases and proteolytic machinery, but proteostasis is largely maintained. To identify specific enzymes degrading at a faster rate under high light conditions, we developed a 13C partial labelling approach to measure rates of turnover of specific proteins in Arabidopsis rosettes. We identified 73 proteins with rates of protein degradation enhanced by high-light. In addition to the expected increase in degradation rate of the photosystem II (PSII) D1 subunit, we discovered significant increases in degradation rate for specific molecular chaperones, nitrate reductase, glyceraldehyde-3 phosphate dehydrogenase, and phosphoglycerate kinase. Significant increases in degradation of 65 other plastid, mitochondrial, peroxisomal, and cytosolic enzymes were also found, including factors involved in redox shuttles within and between organelles and the cytosol. Coupled analysis of protein degradation rate, transcriptional rate, and protein abundance revealed that 57% of the nuclear-encoded enzymes with higher degradation rates also had high light-induced transcriptional responses, ensuring proteostasis. In contrast, plastid-encoded proteins with enhanced turnover rates showed decreased transcript abundances and must maintain protein abundance by other processes. This analysis reveals a light-induced transcriptional program for nuclear-encoded genes, beyond the regulation of PSII D1 subunit and the function of PSII, to replace key protein degradation targets in plants and ensure proteostasis under high-light stress.
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