Project description: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.
Project description: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.
Project description: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.
Project description: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.
Project description:Advances in genetics and sequencing have identified a plethora of disease-associated and disease-causing 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 comparisons between mutant and wild-type cells. Here we generate mouse models of human severe congenital neutropenia (SCN) using patient-derived mutations in the GFI1 transcription factor. To determine the effects of SCN mutations, we generated single-cell references for granulopoietic genomic states with linked epitopes1, aligned mutant cells to their wild-type equivalents and identified differentially expressed genes and epigenetic loci. We find that GFI1-target genes are altered sequentially, as cells go through successive states of differentiation. These insights facilitated the genetic rescue of granulocytic specification but not post-commitment defects in innate immune effector function, and underscore the importance of evaluating the effects of mutations and therapy within each relevant cell state.
Project description:In animal models, Nipbl-deficiency phenocopies gene expression changes and birth defects seen in Cornelia de Lange Syndrome (CdLS), the most common cause of which is Nipbl-haploinsufficiency. Previous studies in Nipbl+/- mice identified aberrant gene expression and heart defects as early as cardiac crescent (CC) stage. Here, we performed single-cell RNA-sequencing on wildtype (WT) and Nipbl+/- mouse embryos at CC- and earlier (gastrulation) stages. Nipbl+/- embryos had fewer mesoderm cells than WT and altered proportions of mesodermal cell subpopulations. These findings were associated with an underexpression of genes implicated in driving specific mesodermal lineages. Nipbl+/- embryos also misexpressed developmentally-critical genes, including the transcription factor, Nanog, and genes governing left-right and anterior-posterior patterning. These events of cell misallocation and transcriptional dysregulation foreshadowed defects in tissue composition and patterning that arise later in Nipbl+/- mice, offering insights into early developmental contributions to birth defects in CdLS.