Bacterial antisense RNAs are mainly the product of transcriptional noise
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB11882 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR1145760.fastq.gz | Fastqsanger.gz | |||
| ERR1145770.fastq.gz | Fastqsanger.gz | |||
| ERR1145761.fastq.gz | Fastqsanger.gz | |||
| ERR1145771.fastq.gz | Fastqsanger.gz | |||
| ERR1145762.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:Cis-encoded antisense RNAs (asRNAs) are widespread along bacterial transcriptomes. However, the role of the vast majority 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 9 different asRNAs in M. 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.
2018-10-25 | PXD003231 | Pride
Project description:Cis-encoded antisense RNAs (asRNAs) are widespread along bacterial transcriptomes. However, the role of the vast majority 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 9 different asRNAs in M. 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.
2016-01-18 | E-MTAB-4081 | biostudies-arrayexpress
Project description: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.
| S-EPMC4783119 | biostudies-literature
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) - 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
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:Pervasive transcription generates mainly unstable non-coding transcripts. Although a few examples of pervasive antisense have been shown to mediate gene regulation by transcriptional interference, whether pervasive transcription has a general functional role or merely represents transcriptional noise remains to be determined. In a mutant context that revealed pervasive transcripts, we characterized more than 800 antisenses genome wide and analysed the corresponding sense mRNA behaviour. We observed that antisense non-coding transcription is commonly found associated with genes tightly repressed during the exponential phase with an opposite level of mRNA and the associated antisense. This suggested that antisense transcription might participate to a tight repression of genes during the exponential phase. We thus specifically interrupted the antisense transcription of a subset of genes, and found that it resulted in a de-repression of the corresponding mRNAs. We further validated that this repression acts in cis through a transcriptional interference mechanism, which involves several chromatin modification factors. Transcription interference is observed for the first time as a general mean of gene regulation between cellular states.
2018-07-23 | GSE101368 | GEO
Project description:Fuzziness and noise in nucleosomal architecture
| PRJEB4709 | ENA
Project description:Systemic sclerosis (SSc) is an autoimmune disease characterized by fibrosis of skin and multiple organs of which the pathogenesis is poorly understood. Here we studied differentially expressed coding and non-coding genes in relation to SSc pathogenesis with a specific focus on antisense non-coding RNAs. Skin biopsy-derived RNAs from fourteen early SSc patients and six healthy individuals were sequenced with ion-torrent and analysed using DEseq2. Overall, 4901 genes with a fold change >1.5 and a false discovery rate < 5% were detected in patients versus controls. Upregulated genes clustered in immunological, cell adhesion and keratin-related processes. Interestingly, 676 deregulated non-coding genes were detected, 257 of which were classified as antisense genes. Sense genes expressed opposite of these antisense genes were also deregulated in 42% of the observed sense-antisense gene pairs. The majority of the antisense genes had a similar effect sizes in an independent North American dataset with three genes (CTBP1-AS2, OTUD6B-AS1 and AGAP2-AS1) exceeding the study-wide Bonferroni-corrected ρ-value (PBonf<0.0023, Pcombined = 1.1x10-9, 1.4x10-8, 1.7x10-6, respectively). In this study, we highlight that together with coding genes, (antisense) long non-coding RNAs are deregulated in skin tissue of SSc patients suggesting a novel class of genes involved in pathogenesis of SSc.
| EGAS00001002751 | EGA