Integrative analysis of microRNA-mRNA of muscle tissues in Qianhua Mutton Merino and Small Tail Han sheep
Ontology highlight
ABSTRACT:
ORGANISM(S): Ovis aries
PROVIDER: GSE113173 | GEO | 2021/04/16
REPOSITORIES: GEO
Similar Datasets
Project description:In this study, we selected differentially expressed miRNAs through construcing and analyzing the miRNA expression profile during 2-, 6-, and 12- month-old Small Tail Han Sheep ovaries, which provided a theoretical basis for the study of miRNAs regulating the reproduction of Small Tail Han Sheep. RNASeq techniques were used to perform profile analysis for these ovaries. The results showed that 11, 13 and 19 DE miRNAs were identified in 2- vs 6-, 6- vs 12-, and 2- vs 12-month-old ovaries, respectively. In total, 54, 37, and 198 predicted target genes of DE miRNAs were obtained from these three groups, respectively. GO and KEGG analyses showed that, in 2- vs 6-month-olds, the target genes of DE known sheep miRNAs were involved in 102 GO terms and 7 signaling pathways; in 6- vs 12-month-olds, the target genes of DE known sheep miRNAs were involved in 52 GO terms and 3 signaling pathways; and in 2- vs 12-month-olds, the target genes of DE known sheep miRNAs were involved in 88 GO terms and 6 signaling pathways. Three miR–target regulatory networks were constructed based on these DE miRNA–targets. 9 miRNAs were selected to validate the accuracy of miRNA sequencing data by qRT-PCR. The binding sites of oar-miR-432 with RPS6KA1 was validated by a dual luciferase reporter gene detection system. This is the first integrative analysis of miRNA and mRNA expression profiles in Small Tail Han Sheep ovarian development. These data help elucidate the molecular regulatory mechanisms in sheep ovarian development and identify the biomarkers that influence reproductive performance of Small Tail Han Sheep ewe.
2018-11-16 | GSE122607 | GEO
Project description:Effective management and control of parasitic infections on farms depends on their early detection. Traditional serological diagnostic methods for Fasciola hepatica infection in livestock are specific and sensitive, but currently the earliest detection of the parasite only occurs at approximately three weeks post-infection. At this timepoint, parasites have already entered the liver and caused the tissue damage and immunopathology that results in reduced body weight and loss in productivity. Here, we investigated whether the differential abundance of micro(mi)miRNAs in sera of F. hepatica-infected sheep has potential as a tool for the early diagnosis of infection. Using miRNA sequencing analysis, we discovered specific profiles of sheep miRNAs at both the pre-hepatic and hepatic infection phases in comparison to non-infected sheep. In addition, six F. hepatica-derived miRNAs were specifically identified in sera from infected sheep. Thus, a panel of differentially expressed miRNAs comprising four sheep (miR-3231-3p; miR133-5p; 3957-5p; 1197-3p) and two parasite miRNAs (miR-124-3p; miR-Novel-11-5p) were selected as potential biomarkers. The expression of these candidates in sera samples from longitudinal sheep infection studies collected between 7 days and 23 weeks was quantified using RT-qPCR and compared to samples from age-matched non-infected sheep. We identified oar-miR-133-5p and oar-miR-3957-5p as promising biomarkers of fasciolosis, detecting infection as early as 7 days. The differential expression of the other selected miRNAs was not sufficient to diagnose infection; however, our analysis found that the most abundant forms of fhe-miR-124-3p in sera were sequence variants (IsomiRs) of the canonical miRNA, highlighting the critical importance of primer design for accurate diagnostic RT-qPCR. Accordingly, this investigative study suggests that certain miRNAs are biomarkers of F. hepatica infection and validates miRNA-based diagnostics for the detection of fasciolosis in sheep.
2024-04-15 | GSE254115 | 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
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 (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 (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:MicroRNAs (miRNAs) are short endogenous, single-stranded, non-coding small RNA molecules of about 22 nucleotides in length. They regulate gene expression post-transcriptionally by silencing mRNA molecules and they regulate many physiological processes. Visna-Maedi virus (VMV) is a lentivirus that causes Visna-Maedi disease (VM) in sheep characterised by pneumonia, mastitis, arthritis and encephalitis; and affects cells of the monocyte/macrophage lineage. So far, there are no studies in the role of miRNAs in this viral disease. Using RNAseq technology and bioinformatics analysis the expression of miRNAs in different phases of the disease were studied. A total of 212 miRNAs were found, of which 46 were conserved sequences found for the first time in sheep and 12 were completely novel. Differential expression analysis showed changes in several miRNAs comparing uninfected and seropositive groups, but did not detect significant differences between seropositive asymptomatic and diseased sheep. The high increase in expression of oar-miR-21 agrees with the increase of the same miRNA detected in other viral diseases. In addition, the target prediction of dysregulated miRNAs revealed that they control genes involved in proliferation-related signalling pathways like PI3K-Akt, AMPK and ErbB.
2018-12-19 | GSE115415 | GEO
Project description:Cancer cachexia is a multifactorial metabolic syndrome defined by the rapid loss of skeletal muscle mass and the loss of fat mass. Up 80% of cancer patients at the late stage with cachexia suffer from progressive atrophy of adipose tissue. Unlike studies on skeletal muscle wasting, there is limited research on fat loss in cachexia. It was noted that most patients suffer from fat loss as cancer progress. Fat loss precedes muscle loss, is associated with shorter survival, and is variable to timing and intensity in various cancer populations. Increased lipolysis may be the leading cause of fat loss in cancer cachexia. miRNAs are a class of non-coding RNAs of 19~25 nucleotides that regulate gene silencing by interacting with the 3’ untranslated region (UTR) of target mRNA to cause mRNA degradation and translational repression. miRNAs play multifaceted roles in pancreatic cancer proliferation, survival, metastasis, and chemoresistance. Aberrant expression of miRNA in circulating exosomes may play potential roles in modulating fat loss in cancer cachexia. We identified 2 miRNAs, miR-16 and miR-29, which have 2-fold higher expression existed in at PDAC cells. To explore which genes in adipogenesis and lipolysis were directly affected by miR-16-5p or/and miR-29a-3p, we analyzed the targets which were down-regulated in both miR-16-5p and miR-29a-3p-transfected 3T3-L1 cells by mass analysis.
2024-06-13 | PXD037998 | Pride
Project description:Cancer cachexia is a multifactorial metabolic syndrome defined by the rapid loss of skeletal muscle mass and the loss of fat mass. Up 80% of cancer patients at the late stage with cachexia suffer from progressive atrophy of adipose tissue. Unlike studies on skeletal muscle wasting, there is limited research on fat loss in cachexia. It was noted that most patients suffer from fat loss as cancer progress. Fat loss precedes muscle loss, is associated with shorter survival, and is variable to timing and intensity in various cancer populations. Increased lipolysis may be the leading cause of fat loss in cancer cachexia. miRNAs are a class of non-coding RNAs of 19~25 nucleotides that regulate gene silencing by interacting with the 3’ untranslated region (UTR) of target mRNA to cause mRNA degradation and translational repression. miRNAs play multifaceted roles in pancreatic cancer proliferation, survival, metastasis, and chemoresistance. Aberrant expression of miRNA in circulating exosomes may play potential roles in modulating fat loss in cancer cachexia. We identified 2 miRNAs, miR-16 and miR-29, which have 2-fold higher expression existed in at PDAC cells. To explore which genes in adipogenesis and lipolysis were directly affected by miR-16-5p or/and miR-29a-3p, we analyzed the targets which were down-regulated in both miR-16-5p and miR-29a-3p-transfected 3T3-L1 cells by mass analysis.
2024-06-13 | PXD037862 | Pride