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Cell Signaling in Plants

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Plant cells communicate to coordinate their cycle of growth, flowering and fruiting, and activities in roots, shoots, and leaves in response to the changing environmental conditions. Plant signaling is distinct from animal signaling. Plants primarily utilize enzyme-linked receptors, whereas the largest class of cell-surface receptors in animals are G-protein coupled receptors (GPCRs). Unlike animals, receptor tyrosine kinases are rare in plants. Instead, plants have a diverse class of...

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Updated: Jan 16, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

Detection of Ethylene Signaling Using Bioinformatics Tools in Plants.

Yogeshwar Vikram Dhar^1,2, Priyamvada Mishra^1,2, Garima Saxena^1,2

¹CSIR-National Botanical Research Institute (CSIR-NBRI), Lucknow, Uttar Pradesh, India.

Methods in Molecular Biology (Clifton, N.J.)

|October 1, 2025

Summary

This summary is machine-generated.

Ethylene, a key plant hormone, regulates growth and stress responses. Analyzing its complex signaling machinery requires specialized databases and workflows to interpret large omics datasets effectively.

Keywords:

Bioinformatics Cis-regulatory elements Ethylene signaling Gene mining Plant hormones Promoter analysis Transcriptomics miRNA analysis

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A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

Area of Science:

Plant Biology
Molecular Biology
Genomics

Background:

Ethylene is a crucial gaseous hormone regulating diverse plant processes like growth, development, stress responses, fruit ripening, and senescence.
Ethylene signaling involves complex multigene families with dynamic spatial and temporal expression, alongside evolutionary divergence and expansion.
High-throughput technologies have enabled comprehensive profiling of ethylene-regulated genes, generating vast omics data.

Purpose of the Study:

To address the challenges in interpreting large omics datasets for ethylene signaling research.
To present methods and workflows for detecting ethylene signaling machinery using public databases.
To facilitate comparative analysis across different studies and platforms despite data variances.

Main Methods:

Utilizing public databases such as TAIR, BGH, CGD, OneKP, miRDeep-2, miRDP, psRNATarget, AHD, and GSHR.
Employing online and offline methods for data analysis and gene mining.
Establishing basic workflows for the detection of ethylene signaling machinery.

Main Results:

Identification of numerous public databases and tools for ethylene genomics, transcriptomics, and regulatory mechanisms.
Development of analytical approaches to handle large and variable omics data.
Facilitation of gene mining and biological insight extraction from ethylene signaling data.

Conclusions:

Effective analysis of ethylene signaling requires tailored databases and workflows.
Public omics data resources are valuable but necessitate careful interpretation.
Standardized methods are essential for advancing our understanding of ethylene's role in plants.