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

serial: '13'
sid: '194194'
uuid: 697e8c2a-ff76-4f4c-af5d-d7bbe3ad885c
uri: /dcb/ji-meeting/abstract
created: '1788890032'
completed: '1788890032'
changed: '1788890032'
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data:
  category: 'Consider my abstract for a Methodology/Technology presentation'
  degree_s_: Ph.D.
  email: sai.ma2@mssm.edu
  first_name: Sai
  keywords_abstracts: 'Single-cell, multi-comics, gene regulation'
  last_name: Ma
  middle_initial: ''
  organization: 'Icahn School of Medicine at Mount Sinai'
  organization_address:
    address: ''
    address_2: ''
    city: 'New York'
    country: ''
    postal_code: ''
    state_province: ''
  summary: |-
    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.
  title: 'Assistant Professor'
  ttile: 'Scalable Single-Cell Multimodal Genomics for Mapping Regulatory State Transitions'