Advances in single-cell multiomic profiling

Single-cell transcriptomic approaches have revolutionised the study of complex biological systems, with the routine measurement of gene expression in thousands of cells enabling construction of whole-organism cell atlases. However, the transcriptome is just one layer amongst many that coordinate to define cell type and state and, ultimately, function. In parallel with the widespread uptake of single-cell RNA-seq (scRNA-seq), there has been a rapid emergence of methods that enable multiomic profiling of individual cells, enabling parallel measurement of intercellular heterogeneity in the genome, epigenome, transcriptome, and proteomes. Researchers from the Earlham Institute discuss how linking measurements from each of these layers has the potential to reveal regulatory and functional mechanisms underlying cell behaviour in healthy development and disease.

Capturing multiple layers of information from the same single cell

Various approaches have emerged to extract distinct layers of omic information from the same single cell. (A) G&T-seq, and those methods based on it, perform physical separation of genomic DNA and mRNA following capture on magnetic beads. (B) An alternative approach involves physical separation of the nucleus and cytoplasm of the cell. These methods allow both genome sequencing and methylation sequencing to be performed on the isolated DNA. High-throughput combinatorial indexing has been applied in (C) sci-CAR and (D) SHARE-seq to obtain linked transcriptome and chromatin accessibility from the same cell, while droplet-based microfluidic approaches (E) have enabled parallel capture of these modalities using SNARE-seq and the 10X Genomics Chromium platform. (F) Droplet microfluidics has also been used to sequence DNA from accessible and compacted chromatin using GET-seq. (G) CITE-seq and REAP-seq take advantage of polyadenylated oligonucleotide tags attached to antigen-specific antibodies to capture protein expression information in parallel with mRNA expression. 

Ogbeide S, Giannese F, Mincarelli L, Macaulay IC. (2022) Into the multiverse: advances in single-cell multiomic profiling. Trends in Genetics [Epub ahead of print]. [article]

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