Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity

Area of Science:

• Single-cell biology
• Genomics
• Molecular biology

Background:

• Dissecting cell-to-cell variation requires integrative multi-omics analysis at the single-cell level.
• Understanding regulatory relationships is key to defining cell states and heterogeneity.

Purpose of the Study:

• To introduce scCAT-seq, a technique for simultaneous assaying of chromatin accessibility and transcriptome in single cells.
• To demonstrate the utility of integrated single-cell omics data for constructing regulatory relationships and defining cell states.

Main Methods:

• Development of scCAT-seq for paired chromatin accessibility and transcriptome profiling.
• Application of scCAT-seq to early embryonic cells.
• Analysis of integrated multi-omics data for regulatory pattern discovery.

Main Results:

• scCAT-seq enables accurate construction of cis-regulatory element-gene relationships at single-cell resolution.
• The first single-cell integrated map of chromatin accessibility and transcriptome in early embryos was generated.
• scCAT-seq precisely dissects master transcription factors in distinct cell states.

Conclusions:

• scCAT-seq provides a powerful tool for dissecting regulatory heterogeneity in complex cell populations.
• Simultaneous multi-omics data enhances the definition of single-cell states.
• This technique facilitates the discovery of cell-identity-specific regulatory patterns.