Genotype-phenotype single-cell transcriptomics for massive parallel assessment of genetic variants

Predicting the pathogenic effect of rare genetic variants is significantly hampered by the limited cohort of diagnosed patients and the difficulty in functionally evaluating the effect of existing and novel variants. To address this issue, we leveraged a protein Multiplexed Assay of Variants Effect (MAVE) to functionally assess the effect of ~ 2200 missense variants of the TP63 gene, some of which cause autosomal dominant developmental disorders. The activity of each variant was measured using an optimized fibroblast-to-keratinocyte conversion protocol, and a subset of mutants was validated through multiple orthogonal biochemical and genomics functional assays to assess consistency and robustness. To systematically expand MAVEs beyond predefined assay, we here introduce SCRAMseq (Single Cell RNAseq Associated with MAVEs by sequencing). This generalizable platform leverages full-length scRNAseq for high-throughput, single-cell genotype-to-phenotype mapping. We validate SCRAMseq across different experimental and genetic contexts to demonstrate its reproducibility and accuracy. SCRAMseq provides a robust and versatile workflow poised to accelerate the discovery and dissection of gene variant effects on any potential disease-driving pathway, thereby significantly broadening MAVEs applicability to virtually any possible disease-driving gene. This work introduces SCRAMseq, a generalizable single-cell platform that pairs full-length transcriptomics with genotyping to test the functional effect of thousands of genetic variants simultaneously, bypassing the need for gene-specific functional assays.