MiRNA profiles in livers with different mass deficits after partial hepatectomy and miR-106b~25 cluster accelerating hepatocyte proliferation in rats
Ontology highlight
ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE79983 | GEO | 2016/04/06
SECONDARY ACCESSION(S): PRJNA317565
REPOSITORIES: GEO
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Project description:To query the relationship between miRNA profiles and deficits in liver mass after PH and the miRNAs linked to liver regeneration, we compared the miRNA expression profile after 2/3 PH, a standard procedure that leads to robust DNA synthesis, with that after 1/3 PH, a procedure that causes minimal replication. The patterns and dynamics of miRNA profiles after PH were featured, providing a rich resource of miRNAs underlying mechanisms of liver regeneration. We generated miRNA profiles from normal and remnant livers at 6, 12, 24, and 36 hours after 1/3 or 2/3PH using microarrays. Two or three rats were used at each time.
2016-04-06 | E-GEOD-79983 | biostudies-arrayexpress
Project description:Liver is one of the few organs that have the capacity to regenerate in response to injury. We carried out genome-wide miRNA microarray studies during liver regeneration in rats after 70% partial hepatectomy (PH) at early and mid-time points to more thoroughly understand their role. At 3, 12 and 18 hrs post-PH ~ 40% of the miRNAs tested were up-regulated. Conversely, at 24 hrs post-PH, ~ 70% of miRNAs were down-regulated. Further, we established that the genome-wide down-regulation of miRNA expression at 24 hrs was also correlated with decreased expression of genes such as Rnasen, Dgcr8, Dicer, Tarbp2 and Prkra that are associated with miRNA biogenesis. To determine if a potential negative feedback loop between miRNAs and their regulatory genes existed, 11 candidate miRNAs which were predicted to target the above genes were examined and found to be up-regulated at 3 hrs post-PH. Using reporter and functional assays, we determined that expression of these miRNA-processing genes could be regulated by a subset of miRNAs and some miRNAs could target multiple miRNA biogenesis genes simultaneously. We also demonstrated that over-expression of these miRNAs inhibited cell proliferation and modulated the cell cycle in both Huh-7 human hepatoma cells and primary rat hepatocytes. From these observations, we postulated that selective up-regulation of miRNAs in the early-phase after PH was involved in the priming and commitment to liver regeneration, while the subsequent genome-wide down-regulation of miRNAs was required for efficient recovery of liver cell mass. Conclusion: Our data suggest that miRNA changes are regulated by negative feedback loops between miRNAs and their regulatory genes that may play an important role in the steady-state regulation of liver regeneration. Sham and Partial Hepatectomized livers at various time points.
2011-06-01 | E-GEOD-28404 | biostudies-arrayexpress
Project description:Liver is one of the few organs that have the capacity to regenerate in response to injury. We carried out genome-wide miRNA microarray studies during liver regeneration in rats after 70% partial hepatectomy (PH) at early and mid-time points to more thoroughly understand their role. At 3, 12 and 18 hrs post-PH ~ 40% of the miRNAs tested were up-regulated. Conversely, at 24 hrs post-PH, ~ 70% of miRNAs were down-regulated. Further, we established that the genome-wide down-regulation of miRNA expression at 24 hrs was also correlated with decreased expression of genes such as Rnasen, Dgcr8, Dicer, Tarbp2 and Prkra that are associated with miRNA biogenesis. To determine if a potential negative feedback loop between miRNAs and their regulatory genes existed, 11 candidate miRNAs which were predicted to target the above genes were examined and found to be up-regulated at 3 hrs post-PH. Using reporter and functional assays, we determined that expression of these miRNA-processing genes could be regulated by a subset of miRNAs and some miRNAs could target multiple miRNA biogenesis genes simultaneously. We also demonstrated that over-expression of these miRNAs inhibited cell proliferation and modulated the cell cycle in both Huh-7 human hepatoma cells and primary rat hepatocytes. From these observations, we postulated that selective up-regulation of miRNAs in the early-phase after PH was involved in the priming and commitment to liver regeneration, while the subsequent genome-wide down-regulation of miRNAs was required for efficient recovery of liver cell mass. Conclusion: Our data suggest that miRNA changes are regulated by negative feedback loops between miRNAs and their regulatory genes that may play an important role in the steady-state regulation of liver regeneration.
2011-06-01 | GSE28404 | GEO
Project description:Liver regeneration has important implications because many therapeutic strategies for the surgical treatment of liver diseases, such as removal of liver tumors and liver transplantation, depend on the ability of the liver to regenerate physically and functionally. Recent studies reported that lncRNAs control cell proliferation in hepatocellular carcinoma (HCC). However, the role of lncRNAs in liver regeneration and the overall mechanisms remain largely unknown. To address this issue, we carried out a genome-wide lncRNA microarray analysis during liver regeneration in mice after 2/3 partial hepatectomy (PH) at various time points. The results revealed differential expression of thousands of lncRNAs during liver regeneration. Six-week-old male wildtype C57Bl/6 mouse liver samples were obtained at 0, 1.5, 12, and 24 hours after 2/3 PH, and three mice were analyzed for each time point. Total RNA was isolated using Trizol.Mouse Stringent LncRNA Array (4 x 44K, ArrayStar, Rockville, MD) were used to monitor the expression level of approximately 14000 lncRNAs identified from the NCBI RefSeq, UCSC, RNAdb2.0, NRED, Fantom3.0 and UCRs. LncRNAs differentially expressed were identified by comparing expression levels during liver regeneration in mice after 2/3 partial hepatectomy (PH) at various time points.
2013-04-24 | E-GEOD-43687 | biostudies-arrayexpress
Project description:The liver has extraordinary powers of regeneration after partial hepatectomy (PH). Changes of gene expression play a key role in cell proliferation and differentiation during liver regeneration (LR). To understand the molecular mechanisms underlying LR, this study was designed to assess the changes of rat hepatic gene expression in a timely manner. We used microarrays to further highlight the regulatory role of rat liver tissue in liver regeneration at gene transcription level.
2014-12-02 | GSE63742 | GEO
Project description:Liver regeneration has important implications because many therapeutic strategies for the surgical treatment of liver diseases, such as removal of liver tumors and liver transplantation, depend on the ability of the liver to regenerate physically and functionally. Recent studies reported that lncRNAs control cell proliferation in hepatocellular carcinoma (HCC). However, the role of lncRNAs in liver regeneration and the overall mechanisms remain largely unknown. To address this issue, we carried out a genome-wide lncRNA microarray analysis during liver regeneration in mice after 2/3 partial hepatectomy (PH) at various time points. The results revealed differential expression of thousands of lncRNAs during liver regeneration.
2013-04-24 | GSE43687 | GEO
Project description:The recovery of liver mass is mainly mediated by proliferation and enlargement of hepatocytes after partial hepatectomy. Studying the gene expression profiles of hepatocytes after partial hepatectomy will be helpful in exploring the mechanism of liver regeneration. We used microarrays to further highlight the regulatory role of hepatocyte in liver regeneration at gene transcription level. Rat liver regeneration after partial hepatectomy (PH) is a good model to study the regulation of cell proliferation. We isolated hepatocytes from regenerating liver at 9 time points (2, 6, 12,24, 30, 36, 72, 120, and 168h) after PH and measured gene expression profiles of hepatocytes from 2h to 168h with rat Genome 230 2.0 gene chip. Each sample corresponding to one time point was hybridized onto one array. The experiment was repeated 3 times for each time point. In total, 10 time points were measured and 0h was used control group. After careful quality control analyses of each chip, Affymetrix GCOS 2.0 software was used to analyze the data. The relevance of gene expression profiles and biological processes was analyzed by bioinformatics and systems biology.
2014-02-28 | E-GEOD-55434 | biostudies-arrayexpress
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 (Mirs_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:
MODEL1704110004.
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 | MODEL1704110004 | 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