Researchers from Peking University have developed an innovative technique called MAPIT-seq that offers scientists a powerful new way to study how proteins interact with RNA inside cells. These proteins, known as RNA-binding proteins (RBPs), play a crucial role in controlling the fate of RNA molecules, from how they are processed to how long they survive, and ultimately help determine how genes are expressed in living organisms. Understanding these interactions is key to unlocking how cells function in health and disease.

One of the biggest challenges in studying RBPs has been capturing a complete and accurate picture of their RNA partners within the highly dynamic environment of cells, especially in single-cell experiments or in complex tissues like the brain. Traditional methods often fall short because they either lack the resolution to examine individual cells or cannot be applied to real tissue samples without damaging them.

MAPIT-seq, short for modification added to RBP interacting transcript-sequencing, addresses this problem by combining molecular tagging with advanced RNA sequencing. The method uses antibodies, specialized molecules that can recognize and bind to specific RBPs, to direct a chemical “mark” onto the RNA molecules that the protein is interacting with. This mark acts like a flag, allowing researchers to easily identify these RNA molecules during sequencing.

Cells or tissue sections (not depicted) are fixed with formaldehyde (FA) to preserve native RBP–RNA interactions. After permeabilization, samples are sequentially incubated with a primary antibody specific for the target RBP and a secondary antibody to recruit the dual deaminase fusion protein (rAPOBEC1-pAG-hADAR2dd) to RBP-binding sites. Unbound enzymes are removed with rigorous washes, and efficient RNA editing is activated by incubation in a Zn²⁺-containing buffer. Following crosslink reversal, total RNA is extracted for library preparation and sequencing to measure gene expression alongside RBP-binding profiles defined by editing events. 

One of the most impressive features of MAPIT-seq is its versatility. The team demonstrated that it works reliably with multiple RBPs and can even be used on frozen tissue samples. This is especially valuable for studying archived clinical specimens or delicate tissues, such as those from the developing brain, where the spatial arrangement of cells is important for understanding biological processes.

To take the technology even further, the researchers developed a high-throughput single-cell version, scMAPIT-seq. This allows them to study not just which RNA molecules a protein binds to, but also how those interactions change depending on the cell type or stage of development. For example, they applied the method to explore the activity of RBPs that are part of the polycomb repressive complex 2 (PRC2), a group of proteins known to regulate gene expression and play roles in development and disease.

By capturing both the protein–RNA interaction map and the overall gene activity profile in the same experiment, MAPIT-seq opens up new possibilities for multi-omics research, integrating different layers of biological data to gain a more complete understanding of how cells operate. This approach could help scientists uncover new regulatory mechanisms in processes like brain development, cancer progression, or response to treatments.

Availability – Codes for processing MAPIT-seq data are available in the following GitHub repository: https://github.com/WangLabPKU/MAPIT-seq.