Source 1review2019Frontiers in Plant Science
Toolkit/root-specific transcriptomic dataset comparison for ethylene responses
root-specific transcriptomic dataset comparison for ethylene responses
Also known as: root-specific transcriptomic datasets
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Root-specific transcriptomic dataset comparison is a comparative transcriptomic assay approach used to identify transcripts that respond consistently to elevated ethylene across multiple root datasets. In the cited review, this approach defined a core set of 139 ethylene-responsive root transcripts.
Usefulness & Problems
Why this is useful
This approach is useful for extracting a robust root ethylene-response signature from multiple transcriptomic datasets rather than relying on a single experiment. The resulting gold-standard transcript set includes genes linked to ethylene signaling and synthesis as well as previously uncharacterized gene products that may contribute to ethylene response phenotypes.
Problem solved
It addresses the problem of distinguishing reproducible root-specific ethylene-responsive transcripts from dataset-specific variation. The review specifically used cross-dataset comparison to identify a consistent core response to elevated ethylene in roots.
Problem links
Need conditional control of signaling activity
DerivedRoot-specific transcriptomic dataset comparison is a comparative transcriptomic assay approach used to identify transcripts that respond consistently to elevated ethylene across multiple root datasets. In the cited review, this approach defined a core set of 139 ethylene-responsive root transcripts.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete measurement method used to characterize an engineered system.
Techniques
Functional AssayTarget processes
signalingImplementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: sensor
Implementation requires access to at least three root-specific transcriptomic datasets collected under elevated ethylene conditions, because the reported core set was defined by comparison across three datasets. No details are provided here on organism, transcriptomic platform, normalization strategy, or downstream validation workflow.
The available evidence comes from a review summary and does not provide experimental design details, statistical thresholds, or platform-specific methods for the underlying datasets. Validation is limited in the supplied evidence to transcript-level consistency, with no direct functional confirmation of the uncharacterized genes described here.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
core transcript count 139root-specific dataset count 3
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Comparison and meta-analysis of transcriptomic datasets can identify both light-dependent and light-independent transcriptional responses to ethylene.
One powerful method to identify similarities and differences in these important regulatory processes is through comparison of transcriptomic datasets resulting from manipulation of ethylene levels or signaling under varying light conditions. We performed a meta-analysis of multiple transcriptomic datasets to uncover transcriptional responses to ethylene that are both light-dependent and light-independent.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Ethylene levels and responses diverge between light and dark environmental conditions.
After a seedling's emergence from the soil, light signaling pathways elicit a switch in developmental programming and the hormonal circuitry that controls it. Accordingly, ethylene levels and responses diverge under these different environmental conditions.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Hypocotyl elongation-based screens in dark-grown seedlings were valuable for identifying and molecularly characterizing major components of the ethylene signaling and response pathway.
This simple approach proved invaluable for identification and molecular characterization of major players in the ethylene signaling and response pathway, including receptors and downstream signaling proteins, as well as transcription factors that mediate the extensive transcriptional remodeling observed in response to elevated ethylene.
Approval Evidence
1 source2 linked approval claimsfirst-pass slug root-specific-transcriptomic-dataset-comparison-for-ethylene-responses
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
Source:
dataset summarysupports
The gold standard ethylene-regulated transcript set includes genes encoding proteins involved in ethylene signaling and synthesis and also includes previously uncharacterized gene products that may contribute to ethylene response phenotypes.
This "gold standard" group of ethylene-regulated transcripts includes mRNAs encoding numerous proteins that function in ethylene signaling and synthesis, but also reveals a number of previously uncharacterized gene products that may contribute to ethylene response phenotypes.
Source:
dataset summarysupports
The review reports a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
We identified a core set of 139 transcripts with robust and consistent responses to elevated ethylene across three root-specific datasets.
Source:
Comparisons
Source-backed strengths
A key strength is that the output was defined by consistency across three root-specific datasets, yielding a core set of 139 transcripts with robust responses to elevated ethylene. The identified set spans known ethylene signaling and synthesis genes and also captures uncharacterized genes, supporting both validation of known biology and hypothesis generation.
Compared with 3D microelectrode arrays
root-specific transcriptomic dataset comparison for ethylene responses and 3D microelectrode arrays address a similar problem space because they share signaling.
Shared frame: same top-level item type; shared target processes: signaling
Compared with multicomponent, ligand-functionalized microarrays
root-specific transcriptomic dataset comparison for ethylene responses and multicomponent, ligand-functionalized microarrays address a similar problem space because they share signaling.
Shared frame: same top-level item type; shared target processes: signaling
Compared with ProKAS
root-specific transcriptomic dataset comparison for ethylene responses and ProKAS address a similar problem space because they share signaling.
Shared frame: same top-level item type; shared target processes: signaling
Ranked Citations
- 1.