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.
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.
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.
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
Project description:We report the mRNA and small RNA transcriptomes of Streptomyces coelicolor, Streptomyces avermitilis, and Streptomyces venezuelae. We identified dozens of new conserved sRNAs and antisense RNAs, including a prominent group of antisense RNAs termed ‘cutoRNAs’ that result from overlap of the 3′ ends of convergently transcribed mRNAs. In addition, we observed abundant unique ncRNAs, including many within secondary metabolic gene clusters.
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
Project description:<p>We use next generation sequencing to investigate the different transcriptomes of closely related CD4+ T-cells from healthy human donors to elucidate the genetic programs that underlie their specialized immune functions. Six cell types were included: Regulatory T-cells (CD25hiCD127low/neg with >95% FOXP3+ purity), regulatory T-cells activated using PMA/ionomycin, CD25-CD45RA+ ('naive' helper T-cells), CD25-CD45RO+ ('memory' helper T-cells), activated Th17 cells (>98% IL17A+ purity) and activated IL17-CD4+ T-cells (called 'ThPI'). Poly-T capture beads were used to isolate mRNA from total RNA, and fragment sizes of ~200 were sequenced from both ends on Illumina's genome analyzer. We confirm many of the canonical signature genes of T-cell populations, but also discover new genes whose expression is limited to specific CD4 T-cell lineages, including long non-coding RNAs. Additionally, we find that genes encoded at loci linked to multiple human autoimmune diseases are enriched for preferential expression upon T-cell activation, suggesting that an aberrant response to T-cell activation is fundamental to pathogenesis.</p>
Project description:The majority of clinical cancer specimens are preserved as formalin-fixed paraffin-embedded (FFPE) samples. In order for clinical molecular tests to have wide reaching impact, they must be applicable to FFPE material. Accurate quantitative measurements of RNA derived from FFPE specimens is challenging due to low yields and high amounts of degradation. Here we present FFPEcap-seq, a method specifically designed for sequencing capped 5’ ends of RNA derived from FFPE samples. FFPEcap-seq combines enzymatic enrichment of 5’ capped RNAs with template switching to create sequencing libraries. We find that FFPEcap-seq can faithfully capture mRNA expression levels in FFPE specimens while also detecting enhancer RNAs that arise from distal regulatory regions. FFPEcap-seq is a fast and straightforward method for making high quality 5’ end RNA-seq libraries from FFPE-derived RNA.
Project description:Yeast Npl3 is a highly abundant RNA binding protein, related to metazoan SR proteins, with reported functions including transcription elongation, splicing and RNA 3’ end processing. To identify direct targets and functions for Npl3, we used UV crosslinking and analysis of cDNA (CRAC) to map precise RNA binding sites. Npl3 binds diverse RNA species, at sites indicative of roles in both early pre-mRNA processing and 3’ end formation on mRNAs and ncRNAs. Consistent with this, tiling array and RNAPII binding data revealed 3’ extended mRNA and snoRNA transcripts in the absence of Npl3. This reflected transcriptional readthrough by RNAPII, and extension and stabilization of cryptic unstable transcript (CUT) long noncoding RNAs. Transcription readthrough was widespread, often resulting in down-regulation of neighboring genes. We conclude that Npl3 is required for the formation of a termination-competent RNA, affecting both coding and noncoding RNAs.
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.