6 research outputs found

    Transcript-indexed ATAC-seq for precision immune profiling.

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    T cells create vast amounts of diversity in the genes that encode their T cell receptors (TCRs), which enables individual clones to recognize specific peptide-major histocompatibility complex (MHC) ligands. Here we combined sequencing of the TCR-encoding genes with assay for transposase-accessible chromatin with sequencing (ATAC-seq) analysis at the single-cell level to provide information on the TCR specificity and epigenomic state of individual T cells. By using this approach, termed transcript-indexed ATAC-seq (T-ATAC-seq), we identified epigenomic signatures in immortalized leukemic T cells, primary human T cells from healthy volunteers and primary leukemic T cells from patient samples. In peripheral blood CD4+ T cells from healthy individuals, we identified cis and trans regulators of naive and memory T cell states and found substantial heterogeneity in surface-marker-defined T cell populations. In patients with a leukemic form of cutaneous T cell lymphoma, T-ATAC-seq enabled identification of leukemic and nonleukemic regulatory pathways in T cells from the same individual by allowing separation of the signals that arose from the malignant clone from the background T cell noise. Thus, T-ATAC-seq is a new tool that enables analysis of epigenomic landscapes in clonal T cells and should be valuable for studies of T cell malignancy, immunity and immunotherapy

    Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma

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    Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures. We infer that most cancer cells are differentiated along two specialized glial programs, whereas a rare subpopulation of cells is undifferentiated and associated with a neural stem cell expression program. Cells with expression signatures for proliferation are highly enriched in this rare subpopulation, consistent with a model in which CSCs are primarily responsible for fuelling the growth of oligodendroglioma in humans. Analysis of copy number variation (CNV) shows that distinct CNV sub-clones within tumours display similar cellular hierarchies, suggesting that the architecture of oligodendroglioma is primarily dictated by developmental programs. Subclonal point mutation analysis supports a similar model, although a full phylogenetic tree would be required to definitively determine the effect of genetic evolution on the inferred hierarchies. Our single-cell analyses provide insight into the cellular architecture of oligodendrogliomas at single-cell resolution and support the cancer stem cell model, with substantial implications for disease management

    Dynamic regulatory network controlling T[subscript H]17 cell differentiation

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    Despite their importance, the molecular circuits that control the differentiation of naive T cells remain largely unknown. Recent studies that reconstructed regulatory networks in mammalian cells have focused on short-term responses and relied on perturbation-based approaches that cannot be readily applied to primary T cells. Here we combine transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based perturbation tools to systematically derive and experimentally validate a model of the dynamic regulatory network that controls the differentiation of mouse T[subscript H]17 cells, a proinflammatory T-cell subset that has been implicated in the pathogenesis of multiple autoimmune diseases. The T[subscript H]17 transcriptional network consists of two self-reinforcing, but mutually antagonistic, modules, with 12 novel regulators, the coupled action of which may be essential for maintaining the balance between T[subscript H]17 and other CD4[superscript +] T-cell subsets. Our study identifies and validates 39 regulatory factors, embeds them within a comprehensive temporal network and reveals its organizational principles; it also highlights novel drug targets for controlling T[subscript H]17 cell differentiation.National Human Genome Research Institute (U.S.) (1P50HG006193-01)National Institutes of Health (U.S.). Pioneer Award (DP1OD003958-01)Howard Hughes Medical InstituteKlarman Cell Observator
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