Source 1review2019Frontiers in Plant Science
Toolkit/meta-analysis of transcriptomic datasets under varying light conditions
meta-analysis of transcriptomic datasets under varying light conditions
Also known as: comparison of transcriptomic datasets, transcriptomic meta-analysis
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
This computational method compares and meta-analyzes transcriptomic datasets generated after manipulation of ethylene levels or signaling under varying light conditions. It is used to identify ethylene-responsive transcriptional programs that are light-dependent versus light-independent.
Usefulness & Problems
Why this is useful
The method is useful for extracting shared and distinct transcriptional responses across multiple ethylene-related transcriptomic datasets collected under different light regimes. In the cited analysis, it supported definition of a gold-standard ethylene-regulated transcript set and a core set of 139 transcripts with robust, consistent responses to elevated ethylene across three root-specific datasets.
Problem solved
It addresses the problem of disentangling how light modulates ethylene-driven transcriptional networks. Specifically, it helps separate ethylene-responsive genes whose regulation depends on light context from those that respond independently of light.
Problem links
Need conditional control of signaling activity
DerivedThis computation method performs comparison and meta-analysis of transcriptomic datasets generated under varying light conditions and ethylene perturbations. It is used to identify transcriptional responses to ethylene that are either light-dependent or light-independent.
Need precise spatiotemporal control with light input
DerivedThis computation method performs comparison and meta-analysis of transcriptomic datasets generated under varying light conditions and ethylene perturbations. It is used to identify transcriptional responses to ethylene that are either light-dependent or light-independent.
Need tighter control over gene expression timing or amplitude
DerivedThis computation method performs comparison and meta-analysis of transcriptomic datasets generated under varying light conditions and ethylene perturbations. It is used to identify transcriptional responses to ethylene that are either light-dependent or light-independent.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
comparative transcriptomic analysiscomparative transcriptomic analysismeta-analysismeta-analysisTechniques
Computational DesignTarget processes
signalingtranscriptionInput: Light
Implementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationimplementation constraint: spectral hardware requirementoperating role: builder
The method requires transcriptomic datasets generated from ethylene level or signaling perturbations under varying light conditions. The available evidence indicates application to multiple datasets, including three root-specific datasets, but does not specify software, code availability, preprocessing steps, or organism-specific implementation beyond the plant ethylene context.
The supplied evidence describes the analytical goal and resulting transcript sets but does not provide methodological details such as statistical framework, normalization strategy, dataset inclusion criteria, or benchmarking against alternative methods. Validation described here is limited to transcript-level consistency in the reviewed datasets, with no independent experimental confirmation included in the evidence provided.
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 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 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
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
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.
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.
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.
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.
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.
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.
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.
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.
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 meta-analysis-of-transcriptomic-datasets-under-varying-light-conditions
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.
Source:
method summarysupports
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.
Source:
review summarysupports
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.
Source:
Comparisons
Source-backed strengths
A reported strength is integration of multiple transcriptomic datasets to identify similarities and differences in regulatory responses under ethylene and light perturbations. The approach yielded a gold-standard ethylene-regulated transcript set containing genes involved in ethylene signaling and synthesis, and it also highlighted previously uncharacterized gene products that may contribute to ethylene response phenotypes.
Compared with iLID/SspB
meta-analysis of transcriptomic datasets under varying light conditions and iLID/SspB address a similar problem space because they share signaling, transcription.
Shared frame: shared target processes: signaling, transcription; same primary input modality: light
Relative tradeoffs: appears more independently replicated.
Compared with LOVpep/ePDZb
meta-analysis of transcriptomic datasets under varying light conditions and LOVpep/ePDZb address a similar problem space because they share signaling, transcription.
Shared frame: shared target processes: signaling, transcription; same primary input modality: light
Relative tradeoffs: appears more independently replicated.
Compared with UVB-inducible expression system
meta-analysis of transcriptomic datasets under varying light conditions and UVB-inducible expression system address a similar problem space because they share signaling, transcription.
Shared frame: shared target processes: signaling, transcription; same primary input modality: light
Strengths here: looks easier to implement in practice.
Ranked Citations
- 1.