NCI Division of Cancer Biology Junior Investigators Meeting (Abstract): Submission #13

Submission information
Submission Number: 13
Submission ID: 194194
Submission UUID: 697e8c2a-ff76-4f4c-af5d-d7bbe3ad885c
Submission URI: /dcb/ji-meeting/abstract

Created: Tue, 09/08/2026 - 13:53
Completed: Tue, 09/08/2026 - 13:53
Changed: Tue, 09/08/2026 - 13:53

Remote IP address: 10.208.24.147
Submitted by: Anonymous
Language: English

Is draft: No
First Name Sai
Middle Initial
Last Name Ma
Degree(s) Ph.D.
Position/Title/Career Status Assistant Professor
Organization Icahn School of Medicine at Mount Sinai
Organization Address New York
Email sai.ma2@mssm.edu
Abstract Category Consider my abstract for a Methodology/Technology presentation
Abstract Keywords Single-cell, multi-comics, gene regulation
Abstract Title Scalable Single-Cell Multimodal Genomics for Mapping Regulatory State Transitions
Abstract Understanding how regulatory programs change during cell-state transitions requires technologies that can measure multiple layers of genome regulation in the same cell and at sufficient scale to capture rare and transient states. We are developing a suite of scalable single-cell multimodal genomic technologies designed to connect epigenetic regulation, genome organization, and transcription within individual cells. These methods enable ultra-high-throughput profiling of 100,000 to 1 million cells per assay, providing the statistical power and cellular resolution needed to resolve rare populations, reconstruct continuous state transitions, and systematically interrogate regulatory heterogeneity.
A major focus is ME-seq, a combinatorial-indexing platform that jointly profiles DNA methylation, chromatin accessibility, and gene expression from the same cell. By integrating enzymatic methylation profiling with highly scalable indexing, ME-seq enables trimodal measurements across hundreds of thousands of cells while preserving regulatory information. We have applied ME-seq across developmental, hematopoietic, aging, and disease systems, where same-cell measurements allow us to distinguish regulatory changes that precede transcriptional state transitions from those that accompany or follow them.
We are also extending this framework to incorporate three-dimensional genome organization through technologies that jointly measure chromatin contacts and transcription at single-cell resolution. These approaches are being optimized for increased molecular recovery, high-throughput processing, and compatibility with targeted enrichment strategies, enabling scalable interrogation of genome architecture in heterogeneous primary cell populations.
Together, these technology-development efforts aim to move single-cell genomics beyond parallel molecular atlases toward direct measurement of regulatory coupling within the same cell. By combining ultra-high throughput with increasingly comprehensive multimodal measurements, these platforms enable analysis of rare cellular states, regulatory trajectories, cell-to-cell heterogeneity, and coordinated molecular changes that would be difficult to resolve using conventional-scale single-cell assays. These capabilities provide new opportunities to identify early regulatory events preceding phenotypic change and dissect mechanisms of cellular transitions in development and cancer.