Linking zygosity and allelic balance to phenotype with programmable heterozygous editing and allele-specific single-cell RNA sequencing 2307550

Abstract

Abstract Introduction Heterozygous single-nucleotide variants cause many inborn errors of immunity (IEI), yet most functional genomics tools generate homozygous edits, limiting insight into dominant-negative (DN) and dosage-dependent variant effects. Expression imbalance of the mutant and wild-type alleles can further complicate genotype—phenotype relationships, and has been nearly impossible to interrogate experimentally. To overcome this, we built a scalable platform to engineer heterozygous variants in primary immune cells and directly link allelic expression bias to phenotype. Methods We harnessed an innovative CRISPR-based editing system, helicase-assisted continuous editing (HACE), in primary human T cells to engineer heterozygous variants across CARD11, a key regulator of immune signaling, in which heterozygous variants cause diverse IEI with variable penetrance. In parallel, we developed single-cell Allele-Integrated Multi-omics sequencing (sc-AIMseq), which integrates transcriptomics, surface proteomics, and quantification of mutant and wild-type allele expression at single cell resolution. Results HACE screens recovered known pathogenic DN variants in CARD11 and revealed novel DN and haploinsufficient variants not evident in homozygous models. sc-AIMseq of HACE-edited T cells uncovered marked cell-to-cell variability in CARD11 allelic expression bias, which dramatically influenced T cell phenotype. We also performed sc-AIMseq on PBMCs from multiple patients with DN CARD11 mutations, which revealed that CARD11 allelic expression bias is cell-type dependent, providing a mechanistic basis for variable penetrance. Conclusion This work establishes a scalable strategy to model heterozygous genetic disorders in primary and patient-derived immune cells, and dissect their variable penetrance. By directly coupling heterozygous variant engineering, allelic expression bias, and phenotype at single-cell resolution, our approach enables unprecedented functional variant interpretation and advances precision immunology. Funding Source Z.H.W. has received research funding from NCI F30CA298572 and the Melanoma Research Foundation. Topic Categories Technological Innovations in Immunology (TECH)