Webinar: A Single-Cell Multiomics Workflow: Impact of Human Disease Variants on Relevant Cell States
Description: Advances in genetics and sequencing have identified a plethora of disease-associated genetic alterations. To determine causality between genetics and disease, accurate models for molecular dissection are required; however, the rapid expansion of transcriptional populations identified through single-cell analyses presents a major challenge for accurate mutant/wild-type comparisons.To address this, a team at Cincinnati Children’s Hospital Medical Center explored a single-cell multiomics workflow to analyze newly generated mouse models of human severe congenital neutropenia (SCN) bearing patient-derived mutations in the GFI1 transcription factor. In this webinar, David Muench, post-doctoral research scientist, describes the work the team did to generate single-cell references for granulopoietic genomic states using CITE-Seq before aligning mutant cells to their wild-type equivalents to ultimately identify differentially expressed genes and epigenetic loci.Dr. Muench also talks about their findings, including that they found that GFI1-target genes are altered sequentially, through successive states of differentiation. These insights facilitated the genetic rescue of granulocytic specification but not post-commitment defects in innate immune effector function while underscoring the importance of evaluating the effects of mutations and therapy within each relevant cell state.