209 research outputs found

    High-resolution mapping of cancer cell networks using co-functional interactions.

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    Powerful new technologies for perturbing genetic elements have recently expanded the study of genetic interactions in model systems ranging from yeast to human cell lines. However, technical artifacts can confound signal across genetic screens and limit the immense potential of parallel screening approaches. To address this problem, we devised a novel PCA-based method for correcting genome-wide screening data, bolstering the sensitivity and specificity of detection for genetic interactions. Applying this strategy to a set of 436 whole genome CRISPR screens, we report more than 1.5 million pairs of correlated "co-functional" genes that provide finer-scale information about cell compartments, biological pathways, and protein complexes than traditional gene sets. Lastly, we employed a gene community detection approach to implicate core genes for cancer growth and compress signal from functionally related genes in the same community into a single score. This work establishes new algorithms for probing cancer cell networks and motivates the acquisition of further CRISPR screen data across diverse genotypes and cell types to further resolve complex cellular processes

    Improvement of E-Commerce

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    Semaphores must work. In our research, authors verify the analysis of context-free grammar, which embodies the essential principles of robotics. In order to achieve this intent, we discover how scatter/gather I/O can be applied to the improvement of Markov models

    High-throughput chromatin accessibility profiling at single-cell resolution.

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    Here we develop a high-throughput single-cell ATAC-seq (assay for transposition of accessible chromatin) method to measure physical access to DNA in whole cells. Our approach integrates fluorescence imaging and addressable reagent deposition across a massively parallel (5184) nano-well array, yielding a nearly 20-fold improvement in throughput (up to ~1800 cells/chip, 4-5 h on-chip processing time) and library preparation cost (~81¢ per cell) compared to prior microfluidic implementations. We apply this method to measure regulatory variation in peripheral blood mononuclear cells (PBMCs) and show robust, de novo clustering of single cells by hematopoietic cell type

    Single-cell epigenomic variability reveals functional cancer heterogeneity.

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    BackgroundCell-to-cell heterogeneity is a major driver of cancer evolution, progression, and emergence of drug resistance. Epigenomic variation at the single-cell level can rapidly create cancer heterogeneity but is difficult to detect and assess functionally.ResultsWe develop a strategy to bridge the gap between measurement and function in single-cell epigenomics. Using single-cell chromatin accessibility and RNA-seq data in K562 leukemic cells, we identify the cell surface marker CD24 as co-varying with chromatin accessibility changes linked to GATA transcription factors in single cells. Fluorescence-activated cell sorting of CD24 high versus low cells prospectively isolated GATA1 and GATA2 high versus low cells. GATA high versus low cells express differential gene regulatory networks, differential sensitivity to the drug imatinib mesylate, and differential self-renewal capacity. Lineage tracing experiments show that GATA/CD24hi cells have the capability to rapidly reconstitute the heterogeneity within the entire starting population, suggesting that GATA expression levels drive a phenotypically relevant source of epigenomic plasticity.ConclusionSingle-cell chromatin accessibility can guide prospective characterization of cancer heterogeneity. Epigenomic subpopulations in cancer impact drug sensitivity and the clonal dynamics of cancer evolution

    Joint single-cell DNA accessibility and protein epitope profiling reveals environmental regulation of epigenomic heterogeneity.

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    Here we introduce Protein-indexed Assay of Transposase Accessible Chromatin with sequencing (Pi-ATAC) that combines single-cell chromatin and proteomic profiling. In conjunction with DNA transposition, the levels of multiple cell surface or intracellular protein epitopes are recorded by index flow cytometry and positions in arrayed microwells, and then subject to molecular barcoding for subsequent pooled analysis. Pi-ATAC simultaneously identifies the epigenomic and proteomic heterogeneity in individual cells. Pi-ATAC reveals a casual link between transcription factor abundance and DNA motif access, and deconvolute cell types and states in the tumor microenvironment in vivo. We identify a dominant role for hypoxia, marked by HIF1α protein, in the tumor microvenvironment for shaping the regulome in a subset of epithelial tumor cells

    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

    Effects of habitat composition and landscape structure on worker foraging distances of five bumblebee species

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    Bumblebees (Bombus spp.) are important pollinators of both crops and wild flowers. Their contribution to this essential ecosystem service has been threatened over recent decades by changes in land use, which have led to declines in their populations. In order to design effective conservation measures it is important to understand the effects of variation in landscape composition and structure on the foraging activities of worker bumblebees. This is because the viability of individual colonies is likely to be affected by the trade-off between the energetic costs of foraging over greater distances and the potential gains from access to additional resources. We used field surveys, molecular genetics and fine resolution remote sensing to estimate the locations of wild bumblebee nests and to infer foraging distances across a 20 km2 agricultural landscape in southern England. We investigated five species, including the rare B. ruderatus and ecologically similar but widespread B. hortorum. We compared worker foraging distances between species and examined how variation in landscape composition and structure affected foraging distances at the colony level. Mean worker foraging distances differed significantly between species. Bombus terrestris, B. lapidarius and B. ruderatus exhibited significantly greater mean foraging distances (551 m, 536 m, 501 m, respectively) than B. hortorum and B. pascuorum (336 m, 272 m, respectively). There was wide variation in worker foraging distances between colonies of the same species, which was in turn strongly influenced by the amount and spatial configuration of available foraging habitats. Shorter foraging distances were found for colonies where the local landscape had high coverage and low fragmentation of semi-natural vegetation, including managed agri-environmental field margins. The strength of relationships between different landscape variables and foraging distance varied between species, for example the strongest relationship for B. ruderatus being with floral cover of preferred forage plants. Our findings suggest that favourable landscape composition and configuration has the potential to minimise foraging distances across a range of bumblebee species. There is thus potential for improvements in the design and implementation of landscape management options, such as agri-environment schemes, aimed at providing foraging habitat for bumblebees and enhancing crop pollination services
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