Peking University, August 18, 2025: A research team led by Professor Wang Yangming from the Institute of Molecular Medicine, College of Future Technology, and the Beijing Advanced Center of RNA Biology (BEACON) at Peking University has published a landmark study in Nature Methods titled "Co-profiling of in situ RNA-protein interactions and transcriptome in single cells and tissues."
Quick Overview (What is MAPIT-seq in 3 points)
1.What it does: Captures both RNA–protein interactions and the full transcriptome from very small or preserved samples.
2.Why it matters: Works without genetic engineering, works in fixed or frozen tissues, and offers single-cell and long-read resolution.
3.What’s next: The team aims to integrate it with spatial transcriptomics for high-resolution mapping of RNA-binding proteins in organs.
Breaking Through Technical Barriers
MAPIT-seq (Modification Added to RBP Interacting Transcript sequencing) is an innovative method that simplifies how scientists study RNA-binding proteins (RBPs)—key regulators of RNA splicing, stability, movement, and translation, and vital to processes like stem cell development, neural function, and cancer. Traditional methods are often slow, require large samples and complex steps, and lack the ability to capture both interactions and transcriptome data at high resolution.
How It Works
MAPIT-seq uses an “antibody plus RNA editing” strategy: antibodies guide a fusion protein containing two RNA editors—ADAR and APOBEC1—to RBP-bound RNAs. These editors leave clear signals near binding sites within hours, which are then identified by sequencing (Figure 1).
● No genetic engineering required
● Works with fixed cells and frozen tissues
● Enables simultaneous mapping of RNA–protein interactions and full-transcriptome profiling
Demonstrated Strengths Across the Board
The technology showed robust performance in multiple contexts:
● Detected interactions at sequencing depths similar to standard RNA-seq—efficient and reliable.
● Uncovered targets, binding motifs, and regulatory features of RBPs like YTHDF2, RBFOX2, PTBP1, and PUM1.
● Mapped G3BP1 binding during fetal brain development in mouse tissues—offering fresh insights into neurological roles.
● When combined with the 10x Genomics single-cell platform, it enabled dual profiling of RBP binding and cellular states, revealing how targets change across the cell cycle.
● Integration with PacBio long-read sequencing added isoform-level resolution—clarifying how RBPs regulate different RNA variants.
A Toolkit Built to Grow
MAPIT-seq comes in three adaptable versions tailored to different sample types and sequencing setups (Figure 2). Its genetic engineering–free design opens doors for primary tissue and clinical studies, while its high-resolution capabilities push RBP research into single-cell and isoform-specific territories.
Looking ahead, the team plans to:
● Integrate MAPIT-seq with spatial transcriptomics,
● Expand the enzyme toolbox and data analysis pipeline,
● Map RBP dynamics with fine spatial and base resolution in complex organs,
● Accelerate applications in disease research, drug target validation, and translational medicine.
*This article is featured in PKU News "Why It Matters" series. More from this series.
Read More: https://www.nature.com/articles/s41592-025-02774-4
Source: College of Future Technology, Peking University
Edited by: Chen Shizhuo