Unraveling Biology One Cell at a Time
Integrating transcriptomics, epigenomics, proteomics, and metabolomics at the single-cell level to decode complexity in health and disease.
📈 Why Single-Cell Multiomics Matters
Traditional "bulk" sequencing masks cellular heterogeneity by averaging signals across millions of cells. Single-cell multiomics enables researchers to:
- Capture the true diversity of cell states
- Discover rare cell populations (e.g., stem-like cancer cells)
- Understand how genomic, transcriptomic, and epigenetic programs interact
- Build cell atlases for organs and diseases
"Every cell tells a story. Multiomics lets us read every chapter."
📊 Key Modalities in Single-Cell Multiomics
scRNA-seq: Single-Cell Transcriptomics
- Measures gene expression in thousands to millions of individual cells.
- Useful for identifying cell types, cell states, and developmental trajectories.
scATAC-seq: Chromatin Accessibility
- Reveals which parts of the genome are open and active in each cell.
- Helps in linking enhancers to target genes and understanding epigenetic regulation.
CITE-seq: Protein + RNA Quantification
- Uses oligo-tagged antibodies to quantify surface proteins and RNA in parallel.
- Bridges the gap between transcriptome and proteome.
Multiome-seq / SNARE-seq
- Captures both RNA and chromatin accessibility from the same cell.
- Enables integrative models of gene regulation.
Spatial Transcriptomics (Optional Integration)
- Localizes gene expression within tissue architecture.
- Can be integrated with scRNA-seq for spatial context.
🌍 Applications Across the Biomedical Landscape
Cancer Research
- Identifying tumor subclones
- Understanding therapy resistance
- Mapping tumor-immune microenvironments
Developmental Biology
- Tracing lineage trajectories
- Mapping differentiation in embryos
- Studying tissue morphogenesis
Immunology
- Profiling immune responses to infection or vaccination
- Understanding autoimmune disease at the cellular level
- Defining T-cell receptor and B-cell receptor diversity
Neuroscience
- Deconstructing brain cell types and regional variation
- Linking gene expression to function in health and disease
- Studying neurodevelopmental and neurodegenerative disorders