Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA198440 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR831695_1.fastq.gz | Fastqsanger.gz | |||
| SRR831695_2.fastq.gz | Fastqsanger.gz | |||
| SRR831696_1.fastq.gz | Fastqsanger.gz | |||
| SRR831696_2.fastq.gz | Fastqsanger.gz | |||
| SRR831697_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 16 |
Similar Datasets
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: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:MicroRNAs are important regulatory molecules in most eukaryotes and the identification of their mRNA targets is essential for their functional analysis. From inflorescence tissue of Arabidopsis, >28,000,000 signatures were sequenced from 5’ ends of polyadenylated products of mRNA decay. Within the set of ~27,000 transcripts included in the 3,500,000 non-redundant signatures, several previously predicted but non-validated miRNA targets were found. Like validated targets, most showed a single abundant signature at the miRNA cleavage site, particularly in libraries from a mutant deficient in the 5’ to 3’ exonuclease AtXRN4. Among the most unexpected miRNA targets discovered were miRNA precursor transcripts that are self-targeted by their own mature miRNA. Although the miRNAs of Arabidopsis have been extensively investigated, working in reverse from the cleaved targets, additional novel miRNAs were identified and validated. This deep and versatile approach will impact the study of other aspects of RNA processing beyond miRNA-target RNA pair analyses. Keywords: miRNA-target RNA pairs, Palallel analysis of RNA ends, PARE, SBS RNA from inflorescence tissue from wildtype Arabidopsis and xrn4 mutants was extracted. Following polyA RNA extraction, libraries for PARE were constructed. RNA from inflorescence tissue from wildtype Arabidopsis (Col-0), and rdr2 and dcl2,3,4 mutants was extracted. The material was submitted to Illumina and libraries were constructed for small RNAs. Individual small RNA libraries from inflorescences of Arabidopsis wildtype, rdr2, and dcl2/dcl3/dcl4 were sequenced with SBS at Illumina, Inc. The distribution of small RNA sizes in each library is in agreement with that published previously for the wild type or the respective mutants sequenced with MPSS or 454; however, the presence and abundances of some small RNAs may differ. This may be attributed to the use of different sequencing technologies with different depths, biological differences in the tissue used, or other unknown reasons. raw data requested but not provided for GSM280226 and GSM280227
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2013-08-01 | GSE46008 | GEO
Project description:MicroRNAs are important regulatory molecules in most eukaryotes and the identification of their mRNA targets is essential for their functional analysis. From inflorescence tissue of Arabidopsis, >28,000,000 signatures were sequenced from 5’ ends of polyadenylated products of mRNA decay. Within the set of ~27,000 transcripts included in the 3,500,000 non-redundant signatures, several previously predicted but non-validated miRNA targets were found. Like validated targets, most showed a single abundant signature at the miRNA cleavage site, particularly in libraries from a mutant deficient in the 5’ to 3’ exonuclease AtXRN4. Among the most unexpected miRNA targets discovered were miRNA precursor transcripts that are self-targeted by their own mature miRNA. Although the miRNAs of Arabidopsis have been extensively investigated, working in reverse from the cleaved targets, additional novel miRNAs were identified and validated. This deep and versatile approach will impact the study of other aspects of RNA processing beyond miRNA-target RNA pair analyses. Keywords: miRNA-target RNA pairs, Palallel analysis of RNA ends, PARE, SBS
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