Project description:New technologies that profile chromatin modifications at single-cell resolution offer enormous promise for functional genomic characterization. However, the sparsity of these measurements and the challenge of integrating multiple binding maps represent significant challenges. Here we introduce scCUT&Tag-pro, a multimodal assay for profiling protein-DNA interactions coupled with the abundance of surface proteins in single cells. In addition, we introduce scChromHMM, which integrates data from multiple experiments to infer and annotate chromatin states based on combinatorial histone modification patterns. We apply these tools to perform an integrated analysis across nine different molecular modalities in circulating human immune cells. We demonstrate how these two approaches can characterize dynamic changes in the function of individual genomic elements across both discrete cell states and continuous developmental trajectories, nominate associated motifs and regulators that establish chromatin states, and identify extensive and cell type-specific regulatory priming. Finally, we demonstrate how our integrated reference can serve as a scaffold to map and improve the interpretation of additional scCUT&Tag datasets.
Project description:Acute myeloid and lymphoid leukemias often harbor chromosomal translocations involving the Mixed Lineage Leukemia-1 gene, which encodes the KMT2A lysine methyltransferase. The most common translocations produce in-frame fusions of KMT2A to trans-activation domains of chromatin regulatory proteins. Here we develop a strategy to map the genome-wide occupancy of oncogenic KMT2A fusion proteins in primary patient samples regardless of fusion partner. By modifying the versatile CUT&Tag method for full automation we identify common and tumor-specific patterns of aberrant chromatin regulation induced by different KMT2A fusion proteins. Integration of automated and single-cell CUT&Tag uncovers lineage heterogeneity within patient samples and provides an attractive avenue for future diagnostics.
Project description:The extent of transcriptional diversity in mouse NPCs is likely to be influenced by a variety of unexamined factors that include programmed cell death, genomic mosaicism as well as a variety of âenvironmentalâ influences such as changes in exposure to signaling lipids. We therefore used scRNA-seq to assess a cohort of cortical NPCs from an embryonic mouse. We demonstrate that PAGODA (Pathway And Geneset OverDispersion Analysis) effectively recovers the known neuroanatomical and functional organization of NPCs, identifying multiple aspects of transcriptional heterogeneity within the developing mouse cortex that are difficult to discern by the existing heterogeneity analysis approaches. Examination of mouse NPC transcriptional heterogeneity via single cell RNA-seq