High-throughput identification of miRNA targets using CLASH (crosslinking, ligation and sequencing of hybrids)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens Saccharomyces cerevisiae
PROVIDER: GSE50452 | GEO | 2013/08/30
SECONDARY ACCESSION(S): PRJNA217521
REPOSITORIES: GEO
Similar Datasets
Project description:Purpose: Identification of miRNA-mRNA interactions in human cells. Method: We used the CLASH technique with PTH-tagged AGO1 protein as a bait. Results: In 6 experiments we identified more than 18,000 miRNA-mRNA interactions in human HEK293 cells, corresponding to targets of 399 miRNAs. Conclusions: The binding of most miRNAs includes the 5' seed region, but around 60% of seed interactions are noncanonical, containing bulged or mismatched nucleotides. Moreover, seed interactions are generally accompanied by specific, non-seed basepairing. 18% of miRNA-mRNA interactions involve the miRNA 3' end, with little evidence for 5' contacts, and some of these were functionally validated. Analyses of miRNA:mRNA basepairing showed that miRNA species systematically differ in their target RNA interactions, and strongly overrepresented motifs were found in the interaction sites of several miRNAs. We speculate that these affect the response of RISC to miRNA-target binding. 6 samples (E1-E6) were prepared with comparable but not identical protocols, described in more detail in Helwak et al. Cell 2013. Samples E7-E10 were used for the determination of the background of the method resulting from RNA-RNA interactions formed after cell lysis.
2013-08-30 | E-GEOD-50452 | biostudies-arrayexpress
Project description:transcriptome profiling of miR-92a inhibitor treated and control cells with the aim of measuring miR-92a influence on its mRNA targets Abstract: MicroRNAs (miRNAs) play key roles in gene regulation, but reliable bioinformatic or experimental identification of their targets remains difficult. To provide an unbiased view of human miRNA targets we developed a technique for ligation and sequencing of miRNA-target RNA duplexes associated with human Ago1. Here we report datasets of more than 18,000 high-confidence miRNA-mRNA interactions. The binding of most miRNAs includes the 5' seed region, but around 60% of seed interactions are noncanonical, containing bulged or mismatched nucleotides. Moreover, seed interactions are generally accompanied by specific, non-seed basepairing. 18% of miRNA-mRNA interactions involve the miRNA 3' end, with little evidence for 5' contacts, and some of these were functionally validated. Analyses of miRNA:mRNA basepairing showed that miRNA species systematically differ in their target RNA interactions, and strongly overrepresented motifs were found in the interaction sites of several miRNAs. We speculate that these affect the response of RISC to miRNA-target binding. In total 10 samples were analyzed, 5 repeats for each experimental condition.
2013-04-26 | E-GEOD-46039 | biostudies-arrayexpress
Project description:transcriptome profiling of miR-92a inhibitor treated and control cells with the aim of measuring miR-92a influence on its mRNA targets Abstract: MicroRNAs (miRNAs) play key roles in gene regulation, but reliable bioinformatic or experimental identification of their targets remains difficult. To provide an unbiased view of human miRNA targets we developed a technique for ligation and sequencing of miRNA-target RNA duplexes associated with human Ago1. Here we report datasets of more than 18,000 high-confidence miRNA-mRNA interactions. The binding of most miRNAs includes the 5' seed region, but around 60% of seed interactions are noncanonical, containing bulged or mismatched nucleotides. Moreover, seed interactions are generally accompanied by specific, non-seed basepairing. 18% of miRNA-mRNA interactions involve the miRNA 3' end, with little evidence for 5' contacts, and some of these were functionally validated. Analyses of miRNA:mRNA basepairing showed that miRNA species systematically differ in their target RNA interactions, and strongly overrepresented motifs were found in the interaction sites of several miRNAs. We speculate that these affect the response of RISC to miRNA-target binding.
2013-04-26 | GSE46039 | GEO
Project description:By shaping gene expression profiles, small RNAs (sRNAs) enable bacteria to efficiently adapt to changes in their environment. To better understand how Escherichia coli acclimatizes to nutrient availability, we performed UV cross-linking, ligation and sequencing of hybrids (CLASH) to uncover Hfq-associated RNA-RNA interactions at specific growth stages. We demonstrate that Hfq CLASH robustly captures bona fide RNA-RNA interactions identified hundreds of novel sRNA base-pairing interactions, including many sRNA-sRNA interactions and involving 3’UTR-derived sRNAs. We rediscovered known and identified novel sRNA seed sequences. The sRNA-mRNA interactions identified by CLASH have strong base-pairing potential and are highly enriched for complementary sequence motifs, even those supported by only a few reads. Yet, steady state levels of most mRNA targets were not significantly affected upon over-expression of the sRNA regulator. Our results reinforce the idea that the reproducibility of the interaction, not base-pairing potential, is a stronger predictor for a regulatory outcome.
2020-05-01 | GSE123049 | GEO
Project description:By shaping gene expression profiles, small RNAs (sRNAs) enable bacteria to efficiently adapt to changes in their environment. To better understand how Escherichia coli acclimatizes to nutrient availability, we performed UV cross-linking, ligation and sequencing of hybrids (CLASH) to uncover Hfq-associated RNA-RNA interactions at specific growth stages. We demonstrate that Hfq CLASH robustly captures bona fide RNA-RNA interactions identified hundreds of novel sRNA base-pairing interactions, including many sRNA-sRNA interactions and involving 3’UTR-derived sRNAs. We rediscovered known and identified novel sRNA seed sequences. The sRNA-mRNA interactions identified by CLASH have strong base-pairing potential and are highly enriched for complementary sequence motifs, even those supported by only a few reads. Yet, steady state levels of most mRNA targets were not significantly affected upon over-expression of the sRNA regulator. Our results reinforce the idea that the reproducibility of the interaction, not base-pairing potential, is a stronger predictor for a regulatory outcome.
2020-05-01 | GSE123048 | GEO
Project description:Here we present the CLASH analysis of AGO2 in HEK293 cells to address the small RNA repertoire and uncover their physiological targets. We developed an optimized bioinformatics approach of chimeric read identification to detect chimeras of high confidence. We report thousands of Ago2 target sites driven by microRNAs, but also a substantial number of Ago2 ‘drivers’ derived from fragments of other small RNAs such as tRNAs, snoRNAs, rRNAs and others. Target validation of several miRNAs delivered by 3’ Quantseq RNA-Seq.
2023-12-24 | GSE221572 | GEO
Project description:Treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections is dependant on the efficacy of last-line antibiotics like vancomycin. Vancomycin treatment failure is most commonly linked to the emergence of vancomycin-intermediate resistance in clincal isolates (termed VISA). These isolates have not acquired resistance genes but appear to accumulate a heterogenous collection of single nucleotide polymerisms that collectively alter the physiology of the cell to increase vancomycin tolerance. Cell wall thickening is common among VISA isolates and is thought to decrease vancomycin permeability. Changes in regulatory sRNA expression have been correlated with antibiotic stress responses in VISA isolates however the functions of the vast majority of these RNA regulators is unknown. Here we have used the endoribonuclease RNase III to capture RNA-RNA interactions using an RNA proximity-dependant ligation technique termed CLASH. RNase III-CLASH uncovered hundreds of sRNA-mRNA interactions in vivo allowing functional characterisation of many sRNAs for the first time. Surprisingly, we find that an mRNA encoding an unusually long 3’UTR (here termed vigR) functions as a regulatory ‘hub’ within our RNA-RNA interaction network. We demonstrate vigR promotes expression of the cell wall lytic transglycosylase encoded by isaA through a direct mRNA-mRNA interaction. Further, we find that the vigR mRNA 3’UTR is required for cell wall thickening and that deletion of the vigR 3’UTR re-sensitises VISA to vancomycin. Our results demonstrate the utility of RNase III-CLASH for identifying new regulatory RNA functions and indicate that S. aureus may use mRNA-mRNA interactions to co-ordinate gene expression much more widely than previously appreciated.
2021-09-14 | GSE158830 | GEO
Project description:In an attempt to discover potential RNA-RNA interactions in mRNA 3’ processing regulation, we developed PAS-CLASH (PolyA Site-Crosslinking, Ligation and Sequencing of the Hybrid) method, which combines reported CLASH and poly(A) site sequencing protocols. Briefly, HeLa cells were treated with AMT, or without AMT as control, and irradiated at 365 nm for crosslinking. Following nuclear RNA fragmentation and purification, the potential proximate RNAs/PASs were ligated on the oligo d(T)25 beads, hybrids were reverse crosslinked and amplified with the QuantSeq Rev 3' mRNA sequencing library prep kit (Lexogen, Cat. 016.24) and sequenced with Hiseq, producing 150 bp paired end reads.
2019-01-22 | GSE125398 | GEO
Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir1_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Nature Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110000.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
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.
2017-09-26 | MODEL1704110000 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mir181_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110001.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
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.
2017-09-26 | MODEL1704110001 | BioModels