A burst of miRNA innovation in the early evolution of butterflies and moths
Ontology highlight
ABSTRACT:
ORGANISM(S): Cameraria ohridella
SUBMITTER: Peter Holland
PROVIDER: E-GEOD-63644 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:MicroRNAs (miRNAs) are involved in post-transcriptional regulation of gene expression. Since several miRNAs are known to affect the stability or translation of developmental regulatory genes, the origin of novel miRNAs may have contributed to the evolution of developmental processes and morphology. Lepidoptera (butterflies and moths) is a species-rich clade with a well-established phylogeny and abundant genomic resources, thereby representing an ideal system in which to study miRNA evolution. We sequenced small RNA libraries from developmental stages of two divergent lepidopterans, Cameraria ohridella (Horse chestnut Leafminer) and Pararge aegeria (Speckled Wood butterfly), discovering 90 and 81 conserved miRNAs respectively, and many species-specific miRNA sequences. Mapping miRNAs onto the lepidopteran phylogeny reveals rapid miRNA turnover and an episode of miRNA fixation early in lepidopteran evolution, implying that miRNA acquisition accompanied the early radiation of the Lepidoptera. One lepidopteran-specific miRNA gene, miR-2768, is located within an intron of the homeobox gene invected, involved in insect segmental and wing patterning. We identified cubitus interruptus (ci) as a likely direct target of miR-2768, and validated this suppression using a luciferase assay system. We propose a model by which miR-2768 modulates expression of ci in the segmentation pathway and in patterning of lepidopteran wing primordia.
2014-11-26 | GSE63644 | GEO
Project description:Background: Heliconius butterflies are an excellent model system for studies of adaptive convergent and divergent phenotypic traits. Wing colour patterns are used as signals to both predators and potential mates and are inherited in a Mendelian manner. The underlying genetic mechanisms of pattern formation have been studied for many years and shed light on broad issues, such as the repeatability of evolution. In Heliconius melpomene, the yellow hindwing bar is controlled by the HmYb locus and several genes in this region show expression pattern differences across races. MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression that have key roles in many biological processes, including development. It seems likely that miRNAs could act as downstream regulators of genes involved in wing development, patterning and pigmentation. For this reason we characterised miRNAs in developing butterfly wings and examined differences in their expression between colour pattern races. Results: We sequenced small RNA libraries from two colour pattern races and detected 142 Heliconius miRNAs with homology to others found in miRBase. Several highly abundant miRNAs appeared to be differentially expressed between colour pattern races and this was tested further in different developing pupal wing stages using Northern blots. These revealed that differences in expression were due to developmental stage rather than colour pattern. Assembly of sequenced reads to the HmYb region identified miR-193 and miR-2788; located 2380bp apart in an intergenic region. A search for miRNAs in all available H. melpomene BAC sequences (~2.5Mb) did not reveal any other miRNA genes and no novel miRNAs were predicted. There were several regions where other small RNA sequences assembled to the HmYb region and appeared to be differentially expressed.These might represent other regulatory RNAs. Conclusions: Here we describe the first butterfly miRNAs and characterise their expression in developing wings. Some show differences in expression across developing pupal stages. Two miRNAs were located in the HmYb region. Future work will examine the expression of these miRNAs in different colour pattern races and identify miRNA targets among wing patterning genes.
2011-06-02 | GSE23292 | GEO
Project description:Background: Heliconius butterflies are an excellent model system for studies of adaptive convergent and divergent phenotypic traits. Wing colour patterns are used as signals to both predators and potential mates and are inherited in a Mendelian manner. The underlying genetic mechanisms of pattern formation have been studied for many years and shed light on broad issues, such as the repeatability of evolution. In Heliconius melpomene, the yellow hindwing bar is controlled by the HmYb locus and several genes in this region show expression pattern differences across races. MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression that have key roles in many biological processes, including development. It seems likely that miRNAs could act as downstream regulators of genes involved in wing development, patterning and pigmentation. For this reason we characterised miRNAs in developing butterfly wings and examined differences in their expression between colour pattern races. Results: We sequenced small RNA libraries from two colour pattern races and detected 142 Heliconius miRNAs with homology to others found in miRBase. Several highly abundant miRNAs appeared to be differentially expressed between colour pattern races and this was tested further in different developing pupal wing stages using Northern blots. These revealed that differences in expression were due to developmental stage rather than colour pattern. Assembly of sequenced reads to the HmYb region identified miR-193 and miR-2788; located 2380bp apart in an intergenic region. A search for miRNAs in all available H. melpomene BAC sequences (~2.5Mb) did not reveal any other miRNA genes and no novel miRNAs were predicted. There were several regions where other small RNA sequences assembled to the HmYb region and appeared to be differentially expressed.These might represent other regulatory RNAs. Conclusions: Here we describe the first butterfly miRNAs and characterise their expression in developing wings. Some show differences in expression across developing pupal stages. Two miRNAs were located in the HmYb region. Future work will examine the expression of these miRNAs in different colour pattern races and identify miRNA targets among wing patterning genes. High-throughput sequencing of Heliconius melpomene endogenous small RNAs. Size fractionated small RNA from total RNA extracts of two different Heliconius melpomene races (Heliconius melpomene melpomene and Heliconius melpomene rosina) were isolated from wing tissue using miRVana kit. 100µg RNA from 11 individuals of different developmental stages was pooled for each race as follows: 4.1% larval stage <1; 2% larval stage 1-1.75; 2.9% larval stage 2-2.5; 22% larval stage 2.75-3; 19% larval stage > 3; 25% early pupae; 25% mid-melanin pupae. Sequences were ligated to adapters, purified again and reverse transcribed. After PCR amplification the sample was subjected to Solexa/Illumina high throughput pyrosequencing. Please see www.illumina.com for details of the sequencing technology.
2011-06-02 | E-GEOD-23292 | biostudies-arrayexpress
Project description:We characterized sperm from the seminal vesicles of male monarch butterflies (Danaus plexippus), in triplicate, identifying 548 high confidence proteins. As with all but the most basal lepidopteran species male monarch butterflies are sperm heteromorphic, producing fertilization competent and anucleate fertilization incompetent sperm morphs. Comparing this data to the sperm proteomes of the Carolina sphinx moth (Manduca sexta) and the fruit fly (Drosophila melanogaster) demonstrated high levels of functional coherence across proteomes, and conservation at the level of protein abundance and post-translational modification within Lepidoptera. Comparative genomic analyses revealed a significant reduction in orthology among Monarch sperm genes relative to the remainder of the genome in non-Lepidopteran insects. A substantial number of sperm proteins were found to be specific to Lepidoptera, lacking detectable homology outside this taxa. These findings are consistent with a burst of genetic novelty in the sperm proteome concurrent with the origin of heteromorphic spermatogenesis early in Lepidoptera evolution.
2017-10-26 | PXD006454 | Pride
Project description:The aim of the presented study was to define tissue and plasma miRNA signatures, which could potentially serve as diagnostic and prognostic markers in endometrioid endometrial cancer (EEC), and to investigate miRNA profiles in regard to clinicopathological characteristics of the tumors. Results: qPCR validation revealed regulation of 14 miRNAs in EEC tissues (miR-9, miR-141,miR-205,miR-203,miR-183,miR-200a*,miR-200b*,miR-200a,miR-200c,miR-429,miR-200b,miR-410,miR-92a,miR-1305) and 9 in plasma samples (miR-449a,miR-1290,miR-1228,miR-203,miR-200a,miR-141,miR-92a, miR-9, miR-301b). Expression of certain miRNAs showed association with FIGO stage, grade and relapse. Two miRNA signatures, miR-205/miR-410 and miR-410/miR-429/miR-92a, classified tumor tissues with higher accuracy in comparison to single miRNAs (AUC 0.972, 95% CI 0.919-0.995 and 0.991, 95% CI 0.948-1.000, resepctively). miRNA signature composed of miR-205 and miR-200a predicted relapse with AUC of 0.854 (95% CI 0.691-0.951). Tissue miRNA signatures were independent prognostic markers of overall (miR-1228/miR-200c/miR-429, HR 2.98) and progression-free survival (miR-1228/miR-429, HR 4.149). Plasma miRNA signatures classified EEC plasma samples with high accuracy. Conclusions: We conclude that miRNA signatures hold great promise for becoming non-invasive biomarkers for early EEC detection and prognosis. Tissue samples were collected from 122 women (77 EEC and 45 controls). Expression profiling of 866 human miRNAs and 89 human viral miRNAs was performed in 24 samples and was followed by qPCR validation in 104 patients. Of 24 samples analyzed by microarrays, 22 (18 EEC, 4 normal controls) were available for final analysis. Expression of 14 miRNAs was analysed in 48 plasma samples by qPCR.
2012-05-31 | E-GEOD-35794 | biostudies-arrayexpress
Project description:The aim of the presented study was to define tissue and plasma miRNA signatures, which could potentially serve as diagnostic and prognostic markers in endometrioid endometrial cancer (EEC), and to investigate miRNA profiles in regard to clinicopathological characteristics of the tumors. Results: qPCR validation revealed regulation of 14 miRNAs in EEC tissues (miR-9, miR-141,miR-205,miR-203,miR-183,miR-200a*,miR-200b*,miR-200a,miR-200c,miR-429,miR-200b,miR-410,miR-92a,miR-1305) and 9 in plasma samples (miR-449a,miR-1290,miR-1228,miR-203,miR-200a,miR-141,miR-92a, miR-9, miR-301b). Expression of certain miRNAs showed association with FIGO stage, grade and relapse. Two miRNA signatures, miR-205/miR-410 and miR-410/miR-429/miR-92a, classified tumor tissues with higher accuracy in comparison to single miRNAs (AUC 0.972, 95% CI 0.919-0.995 and 0.991, 95% CI 0.948-1.000, resepctively). miRNA signature composed of miR-205 and miR-200a predicted relapse with AUC of 0.854 (95% CI 0.691-0.951). Tissue miRNA signatures were independent prognostic markers of overall (miR-1228/miR-200c/miR-429, HR 2.98) and progression-free survival (miR-1228/miR-429, HR 4.149). Plasma miRNA signatures classified EEC plasma samples with high accuracy. Conclusions: We conclude that miRNA signatures hold great promise for becoming non-invasive biomarkers for early EEC detection and prognosis.
2012-06-01 | GSE35794 | GEO
Project description:Clear cell renal cell carcinomas (ccRCC) are characterized by arm-wide chromosomal alterations. Loss at 14q is associated with disease aggressiveness in ccRCC, which responds poorly to chemotherapeutics. The 14q locus contains one of the largest miRNA clusters in the human genome; however, little is known about the contribution of these miRNAs to ccRCC pathogenesis. In this regard, we investigated the expression pattern of selected miRNAs at the 14q32 locus in TCGA kidney tumors and in ccRCC cell lines. We validated that the miRNA cluster is downregulated in ccRCC (and cell lines) as well as in papillary kidney tumors relative to normal kidney tissues and primary renal proximal tubule epithelial (RPTEC) cells. We demonstrated that agents modulating expression of DNMT1 (e.g., 5-Aza-deoxycytidine) could modulate miRNA expression in ccRCC cell lines. Lysophosphatidic acid (LPA, a Lysophospholipid mediator elevated in ccRCC) not only increased labile iron content but also modulated expression of 14q32 miRNAs. Through an overexpression approach targeting a subset of 14q32 miRNAs (specifically at subcluster A: miR-431, miR-432, miR-127, and miR-433) in 769-P cells, we uncovered changes in cellular viability and claudin-1, a tight junction marker. A global proteomic approach was implemented using these miRNA overexpressing cell lines which uncovered ATXN2 as a highly downregulated target, which has a role in chronic kidney disease pathogenesis. Collectively, these findings support a contribution of miRNAs at 14q32 in ccRCC pathogenesis.
2023-05-10 | PXD036428 | Pride
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 (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