Machine-learning-optimized Cas12a barcoding enables the recovery of single-cell lineages and transcriptional profiles

The development of CRISPR-based barcoding methods creates an exciting opportunity to understand cellular phylogenies. We present a compact, tunable, high-capacity Cas12a barcoding system called dual acting inverted site array (DAISY). We combined high-throughput screening and machine learning to predict and optimize the 60-bp DAISY barcode sequences. After optimization, top-performing barcodes had similar to 10-fold increased capacity relative to the best random-screened designs and performed reliably across diverse cell types. DAISY barcode arrays generated similar to 12 bits of entropy and similar to 66,000 unique barcodes. Thus, DAISY barcodes-at a fraction of the size of Cas9 barcodes-achieved high-capacity barcoding. We coupled DAISY barcoding with single-cell RNA-seq to recover lineages and gene expression profiles from similar to 47,000 human melanoma cells. A single DAISY barcode recovered up to similar to 700 lineages from one parental cell. This analysis revealed heritable single-cell gene expression and potential epigenetic modulation of memory gene transcription. Overall, Cas12a DAISY barcoding is an efficient tool for investigating cell-state dynamics.

Automated summary

The development of CRISPR-based barcoding methods has provided an exciting opportunity to understand cellular phylogenies. A compact, tunable, high-capacity Cas12a barcode system called DAISY has been introduced. DAISY barcode arrays can generate a large number of unique markers and, when combined with single-cell RNA sequencing, can recover lineages and gene expression profiles from human melanoma cells.