MiRNA expression profiling of stage specific monocyte derived dendritic cell differentiation
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Rattus norvegicus Homo sapiens
PROVIDER: GSE15644 | GEO | 2009/04/15
SECONDARY ACCESSION(S): PRJNA116657
REPOSITORIES: GEO
Similar Datasets
Project description:MicroRNAs (miRNAs, miRs) modulate a multitude of cellular events. Here, we identify functional miRNA-protein networks that regulate human monocyte-derived dendritic cell (MDDC) differentiation. MiRNA profiling revealed stage-specific differential expression of 20 miRNAs during days 1, 3 and 5 of MDDC differentiation. To identify and prioritize miRNA-protein networks for functional validation, we developed a target ranking algorithm that incorporates many features of miRNA regulatory networks. This system prioritized miR-21, miR-34a, and their cognate targets WNT1 and JAG1 for functional validation. Inhibition of both miR-21 and miR-34a stalled MDDC differentiation, as quantified by DC-SIGN/CD14 expression ratios, showing cooperative involvement of these miRNAs in MDDC differentiation. We confirmed that the 3â UTRs of WNT1 and JAG1 were functional targets of these miRNAs and provide evidence that these targets were translationally suppressed. Significantly, exogenously added Wnt-1 and Jagged-1 also stalled MDDC differentiation, suggesting that miRNA mediated inhibition of endogenous WNT1 and JAG1 expression was important for proper MDDC differentiation. Finally, inhibition of miR-21 and miR-34a, or addition of Wnt-1 and Jagged-1 led to a decrease in endocytic capacity, a key function of immature DCs. Thus, our novel approach identified and validated some miRNA-protein networks involved in phenotypic and functional MDDC differentiation. monocytes were cultured with GM-CSF and IL-4 for the indicated days (0,1, 3, and 5). Each timepoint was repeated in 3 independent donors (donor 1 , 2, and 3).
2010-06-19 | E-GEOD-15644 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs or miRs) are small, noncoding RNAs that are implicated in the regulation of nearly all biological processes. Global miRNA biogenesis is altered in many cancers and RNA-binding proteins (RBPs) have been shown to play a role in this process, presenting a promising avenue for targeting miRNA dysregulation in disease. miR-34a exhibits tumor-suppressive functions by targeting cell cycle regulators CDK4/6 and anti-apoptotic factor Bcl-2, among other regulatory pathways such as Wnt, TGF-, and Notch signaling. Many cancers show downregulation or loss of miR-34a, and synthetic miR-34a supplementation has been shown to inhibit tumor growth in vivo; however, the post-transcriptional mechanisms by which miR-34a is lost in cancer are not entirely understood. Here, we have used a proteomics-mediated approach to identify Squamous cell carcinoma antigen recognized by T-cells 3 (SART3) as a putative pre-miR-34a-binding protein. SART3 is a spliceosome recycling factor and nuclear RBP with no previously reported role in miRNA regulation. We demonstrate that SART3 binds pre-miR-34a with specificity over pre-let-7d and begin to elucidate a new functional role for this protein in non-small lung cancer cells. Overexpression of SART3 led to increased miR-34a levels, downregulation of the miR-34a target genes CDK4 and CDK6, and cell cycle arrest in the G1 phase. In vitro binding studies showed that the RNA-recognition motifs within the SART3 sequence are responsible for selective pre-miR-34a binding. Collectively, our results present evidence for an influential role of SART3 in miR-34a biogenesis and cell cycle progression.
2019-10-14 | PXD015278 | Pride
Project description:WNT signaling is fundamental to bone health and its aberrant activation leads to skeletal pathologies. A heterozygous missense mutation p.C218G in WNT1, a key WNT pathway ligand, leads to severe early-onset osteoporosis with multiple peripheral and spinal fractures. Despite the severe skeletal manifestations, conventional bone markers are normal in mutation-positive patients. The objective of this study was to find novel biomarkers that differentiate between WNT1 mutation-positive and -negative subjects. We evaluated serum levels of 192 miRNAs in 12 mutation-positive (median age 39 years, range 11-76 years) and 12 mutation-negative (35 years, range 9-59 years) subjects from two Finnish families. The results indicate significant differences in circulating miRNA profiles with 2 upregulated (miR-18a-3p, miR-223-3p) and 6 downregulated miRNAs (miR-22-3p, miR-31-5p, miR-34a-5p, miR-143-5p miR-423-5p, miR 423-3p) in the mutation-positive subjects. Three of these (miR-22-3p, miR-34a-5p, and miR-31-5p) are known inhibitors of WNT signaling: miR-22-3p and miR-34a-5p target WNT1 mRNA and miR-31-5p is predicted to bind to the WNT1 3’UTR. Our results suggest that the WNT1 mutation disrupts a feed-back regulation between these miRNAs and WNT1, providing new insights into the pathogenesis of WNT-related bone disorders. Future studies are warranted to explore the potential diagnostic and therapeutic applications of these findings in osteoporosis.
2018-03-29 | GSE103473 | GEO
Project description:The contribution of microRNA-mediated posttranscriptional regulation on the final proteome in differentiating cells remains elusive. Here, we evaluated the impact of microRNAs (miRNAs) on the proteome of human umbilical cord blood-derived unrestricted somatic stem cells (USSC) during retinoic acid (RA) differentiation by a systemic approach using next generation sequencing analysing mRNA and miRNA expression and quantitative mass spectrometry-based proteome analyses. Interestingly, regulation of mRNAs and their dedicated proteins highly correlated during RA-incubation. Additionally, RA-induced USSC demonstrated a clear separation from native USSC thereby shifting from a proliferating to a metabolic phenotype. Bioinformatic integration of up- and downregulated miRNAs and proteins initially implied a strong impact of the miRNome on the XXL-USSC proteome. However, quantitative proteome analysis of the miRNA contribution on the final proteome after ectopic overexpression of downregulated miR-27a-5p and miR-221-5p or inhibition of upregulated miR-34a-5p, respectively, followed by RA-induction revealed only minor proportions of differentially abundant proteins. In addition, only small overlaps of these regulated proteins with inversely abundant proteins in non-transfected RA-treated USSC were observed. Hence, mRNA transcription rather than miRNA-mediated regulation is the driving force for protein regulation upon RA-incubation, strongly suggesting that miRNAs are fine-tuning regulators rather than active primary switches during RA-induction of USSC.
2020-01-31 | PXD016915 | Pride
Project description:miR-34a is strongly induced upon TPA-induced megakaryocyte differentiation of K562 cells. To investigate the gene networks regulated by this miRNA during the process of differentiation we performed gene microarray analysis in K562 cells overexpressing miR-34a or a control sequence.
2009-07-13 | GSE16674 | GEO
Project description:Expression of the miR-34 family (miR-34a, -34b, -34c) is elevated in settings of heart disease, and inhibition with antimiR-34a/antimiR-34 has emerged as a promising therapeutic strategy. Under chronic cardiac disease settings, targeting the entire miR-34 family is more effective than targeting miR-34a alone. The identification of transcription factor (TF)-miRNA regulatory networks has added complexity to understanding the therapeutic potential miRNA-based therapies. Here, we sought to determine whether antimiR-34 targets secondary miRNAs via TFs which could contribute to antimiR-34-mediated protection. Using miRNA-Seq we identified differentially regulated miRNAs in hearts from mice with cardiac pathology due to transverse aortic constriction (TAC), and these miRNAs were also regulated by antimiR-34. Two clusters of stress-responsive miRNAs were classified as “pathological” and “cardioprotective”. Using ChIPBase we identified 45 TF binding sites on the promoters of “pathological” and “cardioprotective” miRNAs, and 5 represented direct targets of miR-34, with the capacity to regulate other miRNAs. The expression of two “pathological” miRNAs (let-7e and miR-31) was independently experimentally validated in hearts from antimiR-34 treated TAC mice, and may explain why targeting the entire miR-34 family is more effective than targeting miR-34a alone. AntimiR-34 regulates the expression of other miRNAs and this has significant implications for drug development.
2016-05-08 | GSE79050 | GEO
Project description:miR-34a is strongly induced upon TPA-induced megakaryocyte differentiation of K562 cells. To investigate the gene networks regulated by this miRNA during the process of differentiation we performed gene microarray analysis in K562 cells overexpressing miR-34a or a control sequence. Experiment Overall Design: K562 cells were transfected by nucleofection (Amaxa) with a miR-34a mimic (Dharmacon) or a control sequence with no homology to human genes. 24 hours post-transfection total RNA was extracted using trizol and hybridized on Affimetrix microarrays for comparing gene expression.
2009-07-19 | E-GEOD-16674 | biostudies-arrayexpress
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
Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir378_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:
MODEL1704110002.
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 | MODEL1704110002 | BioModels