SRA

Advances in genetics and sequencing have lead to a deluge of disease-associated and disease-causing genetic alterations. Resolving causality between genetics and disease requires generating accurate models for molecular dissection; however, the rapid expansion of single-cell landscapes presents a major challenge to accurate comparisons between mutants and their wild type equivalents. Here, we generated mouse models of human severe congenital neutropenia (SCN) using patient-derived mutations in the Growth factor independent-1 (GFI1) transcription factor. To delineate the impact of SCN mutations, we first generated single-cell references for granulopoietic genomic states with linked epitopes, then developed a new computational approach to align mutant cells to their wild-type equivalent and derive differentially expressed genes. Surprisingly, the majority of differentially expressed GFI1-target genes are sequentially altered as cells traverse successive states. These cell-state-specific insights facilitated genetic rescue of granulocytic specification but not post-commitment defects in the expression of innate-immune effectors, providing regulatory insights into granulocyte dysfunction. Overall design: Single cell RNA seq of Gfi1-R412X mutant GMP subpopulations