Dataset Information

MicroRNA-mRNA expression profiles and functional networks of Submandibular Gland in type 2 diabetic db/db mice [array]

ABSTRACT: Abstract: Background: Hyposalivation is one of the common symptoms of diabetes. Although the micro ribonucleic acid (miRNA) has recently been identified to play a role in the pathogenesis of diabetes, the specific effects of miRNAs on diabetic salivary glands remain unclear. This work was aimed to investigate the expression profiles of miRNAs and identify miRNA‐mRNA network in submandibular gland (SMG) in db/db mice. Methods: miRNA and mRNA expressional profiles were analyzed by microarray technology from the SMG of db/db mice and db/m mice. Significant fold changes in miRNAs and mRNAs were confirmed by real-time quantitative reverse transcription-polymerase chain reaction. Bioinformatic analyses were performed to identify the critical biological functions and signaling pathways involved in diabetes-mediated hyposalivation and to identify the functional networks formed between differentially expressed (DE) miRNAs and mRNAs. Results: A total of 28 DE miRNAs and 1146 DE mRNAs were identified of the SMG in db/db mice and db/m mice. Gene ontology (GO) analysis and KEGG pathway analysis demonstrated that DE miRNAs were highly associated with terms related to diverse biological processes and signaling pathways. Of the related pathways, TGF-beta signaling pathway and tight junction pathway were notable. The constructed network indicated interactions between 11 miRNAs and 42 mRNAs. Autophagy pathway is worth studying, especially the dynamic network of miRNA and mRNA. In addition, AKT3 and PIK3CD may play important roles in the development of diabetes-mediated hyposalivation. Conclusions: Our research describes the miRNA and mRNA expression profiles and functional networks involved in SMGs from db/db mice. These results provide possible molecular mechanisms and may help to elucidate possible molecular therapeutic targets for the treatment of diabetes-induced hyposalivation. Key words: diabetes, submandibular gland, miRNA, mRNA, miRNA–mRNA network, microarray

ORGANISM(S): Mus musculus

PROVIDER: GSE141411 | GEO | 2021/12/01

REPOSITORIES: GEO

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Project description:Abstract: Background: Hyposalivation is one of the common symptoms of diabetes. Although the micro ribonucleic acid (miRNA) has recently been identified to play a role in the pathogenesis of diabetes, the specific effects of miRNAs on diabetic salivary glands remain unclear. This work was aimed to investigate the expression profiles of miRNAs and identify miRNA‐mRNA network in submandibular gland (SMG) in db/db mice. Methods: miRNA and mRNA expressional profiles were analyzed by microarray technology from the SMG of db/db mice and db/m mice. Significant fold changes in miRNAs and mRNAs were confirmed by real-time quantitative reverse transcription-polymerase chain reaction. Bioinformatic analyses were performed to identify the critical biological functions and signaling pathways involved in diabetes-mediated hyposalivation and to identify the functional networks formed between differentially expressed (DE) miRNAs and mRNAs. Results: A total of 28 DE miRNAs and 1146 DE mRNAs were identified of the SMG in db/db mice and db/m mice. Gene ontology (GO) analysis and KEGG pathway analysis demonstrated that DE miRNAs were highly associated with terms related to diverse biological processes and signaling pathways. Of the related pathways, TGF-beta signaling pathway and tight junction pathway were notable. The constructed network indicated interactions between 11 miRNAs and 42 mRNAs. Autophagy pathway is worth studying, especially the dynamic network of miRNA and mRNA. In addition, AKT3 and PIK3CD may play important roles in the development of diabetes-mediated hyposalivation. Conclusions: Our research describes the miRNA and mRNA expression profiles and functional networks involved in SMGs from db/db mice. These results provide possible molecular mechanisms and may help to elucidate possible molecular therapeutic targets for the treatment of diabetes-induced hyposalivation. Key words: diabetes, submandibular gland, miRNA, mRNA, miRNA–mRNA network, microarray

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.

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.

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.

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.

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MicroRNA-mRNA expression profiles and functional networks of Submandibular Gland in type 2 diabetic db/db mice [array]

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