Toolkit/meta-analysis of transcriptomic datasets under varying light conditions

meta-analysis of transcriptomic datasets under varying light conditions

Computational Method·Research·Since 2019

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.

Taxonomy & Function

Primary hierarchy

Technique Branch

Method: A concrete computational method used to design, rank, or analyze an engineered system.

Target processes

signalingtranscription

Input: Light

Implementation Constraints

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

Claim 1dataset summarysupports2019Source 1needs review

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.
Claim 2dataset summarysupports2019Source 1needs review

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.
Claim 3dataset summarysupports2019Source 1needs review

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.
Claim 4dataset summarysupports2019Source 1needs review

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.
Claim 5dataset summarysupports2019Source 1needs review

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.
Claim 6dataset summarysupports2019Source 1needs review

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.
Claim 7dataset summarysupports2019Source 1needs review

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.
Claim 8dataset summarysupports2019Source 1needs review

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
Claim 9dataset summarysupports2019Source 1needs review

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
Claim 10dataset summarysupports2019Source 1needs review

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
Claim 11dataset summarysupports2019Source 1needs review

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
Claim 12dataset summarysupports2019Source 1needs review

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
Claim 13dataset summarysupports2019Source 1needs review

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
Claim 14dataset summarysupports2019Source 1needs review

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
Claim 15method summarysupports2019Source 1needs review

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.
Claim 16method summarysupports2019Source 1needs review

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.
Claim 17method summarysupports2019Source 1needs review

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.
Claim 18method summarysupports2019Source 1needs review

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.
Claim 19method summarysupports2019Source 1needs review

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.
Claim 20method summarysupports2019Source 1needs review

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.
Claim 21method summarysupports2019Source 1needs review

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.
Claim 22review summarysupports2019Source 1needs review

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.
Claim 23review summarysupports2019Source 1needs review

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.
Claim 24review summarysupports2019Source 1needs review

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.
Claim 25review summarysupports2019Source 1needs review

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.
Claim 26review summarysupports2019Source 1needs review

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.
Claim 27review summarysupports2019Source 1needs review

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.
Claim 28review summarysupports2019Source 1needs review

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.
Claim 29review summarysupports2019Source 1needs review

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.
Claim 30review summarysupports2019Source 1needs review

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.
Claim 31review summarysupports2019Source 1needs review

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.
Claim 32review summarysupports2019Source 1needs review

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.
Claim 33review summarysupports2019Source 1needs review

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.
Claim 34review summarysupports2019Source 1needs review

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.
Claim 35review summarysupports2019Source 1needs review

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.

Ranked Citations

  1. 1.
    StructuralSource 1Frontiers in Plant Science2019Claim 1Claim 2Claim 3

    Seeded from load plan for claim claim_2. Extracted from this source document.