Regulatory networks in prenatal porcine skeletal muscle development under nutrient restriction
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ABSTRACT:
ORGANISM(S): Sus scrofa
PROVIDER: GSE81751 | GEO | 2020/07/14
REPOSITORIES: GEO
Similar Datasets
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
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 (Mir143_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:
MODEL1704110003.
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 | MODEL1704110003 | BioModels
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:Purpose: MicroRNAs (miRNAs) are non-coding small miRNA ~22 nucleotides in length and play a vital role in muscle development by binding to messenger RNAs (mRNAs). Large White (LW, a lean type pig) and Meishan pigs (MS, a Chinese indigenous obese breed) have significant postnatal phenotype differences in growth rate, muscle mass and meat quality, and theses difference are programmed during prenatal muscle development.To shed directly light on the miRNA transcriptome difference in prenatal muscles between these two distinct pig breeds. Methods: skeletal musle miRNA profiles of Meishan pig and large white pig were generated by deep sequencing, in triplicate, using Illumina Hiseq2000 . The sequence reads that passed quality filters were analyzed at the mature miRNA level . qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: We measure the myofiber phenotypes of LW and MS at developmental stages of 35, 55 and 90 days post-conception (dpc). Results shows that the myogenesis process is more intense in MS than in LW at 35 dpc. To investigate the role of miRNAs involved in regulating muscle development at earlier stages of myogenesis and decipher the miRNAs transcriptome difference between LW and MS, here, the miRNAomes of longissimus dorsi muscle collected at 35 dpc from female LW and MS were analyzed by deep sequencing. Overall, we identified 1147 unique miRNAs comprising 434 known miRNAs, 239 conserved miRNAs and 474 candidate miRNAs. Expression analysis of the 10 most abundant miRANs in every library indicated that functional miRNAome may be smaller and tend to be highly expressed. These set of miRNA may play house keeping roles that were involved in myogenesis. A total of 87 miRNAs were significantly differentially expressed between LW and MS (reads > 1000, P < 0.05). Gene ontology (GO) and KEGG pathway enrichment analysis revealed that the differentially expressed miRNAs (DE miRNAs) were associated mainly with muscle contraction, WNT, mTOR, and MAPK signaling pathways. In addition, the expression patterns of myomiRs (miR-1,-133,-206) at three prenatal stages (35,55 and 90 dpc) were determined using qRT-PCR, Notably, ssc-miR-133 was significantly more highly expressed in LW pig skeletal muscle at all prenatal stages compared with its expression in LW pig skeletal muscle. We concluded that the higher expression levels of miR-133 in MS, possibly regulated by myoD, are potential strategies for improvement of myogenesis in earlier prenatal stages. Conclusions: our results add new information to existing data on porcine miRNAs and be helpful to investigate the dominant (main functional) muscle-related miRNAs sets in different pig breeds. In addition, this study provide a profound knowledge on the role of miRNAs in prenatal muscle development, which could provide great reference value for pork quality improvement.
2017-08-31 | GSE88860 | GEO
Project description:Studies have been done to search for changes in miRNA expression during the muscle development in different pigs. However, research in this area has largely focused on dissecting miRNAs that are important for fetal and young muscle development. Little is known about the role of miRNAs in adult muscle development. In this study, we performed a comprehensive study on miRNA expression pattern across the muscle developmental process from embryo to adult (E90-7Years). We identified a number of differentially expressed muscle development-associated miRNAs including new members during developmental stages.
2015-12-25 | GSE75223 | GEO
Project description:Purpose:To help identify the role miRNAs in molecular mechanisms and pathways potentially involved in the developmental toxicity for fish exposed to Deepwater Horizon (DWH) oil, miRNA-mRNA networks in mahi-mahi (Coryphaena hippurus) embryos exposed to different DWH oils (source and artificially weathered oil) were evaluated at different critical windows of development using High Throughput Sequencing (HTS). Methods:miRNA profiles of 24, 48, 96 hpf mahi-mah larvae after slick and source oil exposure were generated by deep sequencing, in triplicate, using Illumina NextSeq v2. qRT–PCR validation was performed using SYBR Green assays. Results: Exposure of embryos to slick oil resulted in more DE miRNAs than source oil at all developmental stages 24hpf, 48hpf, and 96hpf. There was also an increase in the number of DE miRNA as development progressed, with 96hpf having the highest number of DE miRNAs. The expression of miRNAs and their target mRNA was further compared using advanced bioinformatics with subsequent target organ predictions based on their interactions. Gene ontology (GO) analysis on the target mRNAs was consistent with pathway analysis of miRNAs, predicting disruption of cardiovascular system development after oil exposure and showed that specific miRNA–mRNA interactions may contribute to these effects.
2017-12-04 | GSE102966 | GEO
Project description:As the fetal heart develops, cardiomyocyte proliferation potential decreases while fatty acid oxidative capacity increases, a highly regulated transition known as cardiac maturation. Small noncoding RNAs, such as microRNAs (miRNAs), contribute to the establishment and control of tissue-specific transcriptional programs. However, small RNA expression dynamics and genome wide miRNA regulatory networks controlling maturation of the human fetal heart remain poorly understood. Transcriptome profiling of small RNAs revealed the temporal expression patterns of miRNA, piRNA, circRNA, snoRNA, snRNA and tRNA in the developing human heart between 8 and 19 weeks of gestation. Our analysis revealed that miRNAs were the most dynamically expressed small RNA species throughout mid-gestation. Cross-referencing differentially expressed miRNAs and mRNAs predicted 6,200 mRNA targets, 2134 of which were upregulated and 4066 downregulated as gestation progresses. Moreover, we found that downregulated targets of upregulated miRNAs predominantly control cell cycle progression, while upregulated targets of downregulated miRNAs are linked to energy sensing and oxidative metabolism. Furthermore, integration of miRNA and mRNA profiles with proteomes and reporter metabolites revealed that proteins encoded in mRNA targets, and their associated metabolites, mediate fatty acid oxidation and are enriched as the heart develops.This study revealed the small RNAome of the maturing human fetal heart. Furthermore, our findings suggest that coordinated activation and repression of miRNA expression throughout mid-gestation is essential to establish a dynamic miRNA-mRNA-protein network that decreases cardiomyocyte proliferation potential while increasing the oxidative capacity of the maturing human fetal heart.
2024-01-26 | PXD044936 | Pride
Project description:To investigate the upstream regulatory networks in myogenesis that lead to the establishment of the myogenic lineage and subsequent differentiation, we proformed scATAC-seq of pig somite and myotome cells from Tibetan pigs (ZZ) and Duroc×Tibetan pigs (DZ) at several embryonic stages (E18, E21, and E28).
2023-01-15 | GSE206913 | GEO