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Updated: Jun 8, 2026

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

Published on: April 30, 2011

Dissection of intercellular communication using the transcriptome-based framework ICELLNET.

Floriane Noël^1,2,3, Lucile Massenet-Regad^1,4, Irit Carmi-Levy^2,3

¹Université de Paris, INSERM U976, Equipe labellisée par la Ligue Nationale contre le Cancer, F-75006 Paris, France.

Nature Communications

|February 18, 2021

Summary

This summary is machine-generated.

ICELLNET is a new framework for analyzing cell-to-cell communication using transcriptomic data. It integrates ligand-receptor interactions to reveal biological insights and has been experimentally validated for dendritic cell communication.

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Area of Science:

Immunology
Computational Biology
Genomics

Background:

Cell-to-cell communication is crucial for biological processes.
Transcriptomic data offers insights into cellular interactions but faces challenges in integration and interpretation.
Existing methods struggle with global analysis and application to diverse transcriptomic profiles.

Purpose of the Study:

To develop a comprehensive transcriptomic-based framework, ICELLNET, for analyzing cell-to-cell communication.
To integrate ligand-receptor interactions, quantify communication scores, and enable connections with reference cell types.
To facilitate biological interpretation through visualization tools for individual and multiple cell populations.

Main Methods:

Development of ICELLNET, a framework integrating an expert-curated ligand-receptor database.
Quantification of cell communication scores based on gene expression.
Application to RNA-seq, single-cell RNA-seq, and microarray datasets.
Connection of cell populations to 31 reference human cell types with advanced visualization.

Main Results:

ICELLNET successfully integrated and analyzed cell communication from diverse transcriptomic datasets.
The framework revealed autocrine Interleukin-10 (IL-10) control in human dendritic cell communication.
Specific interactions with T cells, keratinocytes, neutrophils, and plasmacytoid dendritic cells (pDC) were identified and experimentally validated.

Conclusions:

ICELLNET provides a global, versatile, and user-friendly approach to dissect cell communication from transcriptomic data.
The framework enhances biological interpretation and application for individual and multiple cell populations.
Experimental validation confirms the reliability and utility of ICELLNET in uncovering cell communication networks.