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1.
Nature ; 523(7561): 486-90, 2015 Jul 23.
Article in English | MEDLINE | ID: mdl-26083756

ABSTRACT

Cell-to-cell variation is a universal feature of life that affects a wide range of biological phenomena, from developmental plasticity to tumour heterogeneity. Although recent advances have improved our ability to document cellular phenotypic variation, the fundamental mechanisms that generate variability from identical DNA sequences remain elusive. Here we reveal the landscape and principles of mammalian DNA regulatory variation by developing a robust method for mapping the accessible genome of individual cells by assay for transposase-accessible chromatin using sequencing (ATAC-seq) integrated into a programmable microfluidics platform. Single-cell ATAC-seq (scATAC-seq) maps from hundreds of single cells in aggregate closely resemble accessibility profiles from tens of millions of cells and provide insights into cell-to-cell variation. Accessibility variance is systematically associated with specific trans-factors and cis-elements, and we discover combinations of trans-factors associated with either induction or suppression of cell-to-cell variability. We further identify sets of trans-factors associated with cell-type-specific accessibility variance across eight cell types. Targeted perturbations of cell cycle or transcription factor signalling evoke stimulus-specific changes in this observed variability. The pattern of accessibility variation in cis across the genome recapitulates chromosome compartments de novo, linking single-cell accessibility variation to three-dimensional genome organization. Single-cell analysis of DNA accessibility provides new insight into cellular variation of the 'regulome'.


Subject(s)
Cells/metabolism , Chromatin/genetics , Chromatin/metabolism , Epigenomics , Single-Cell Analysis/methods , Animals , Cell Compartmentation , Cell Cycle/genetics , Cell Line , Cells/classification , DNA/genetics , DNA/metabolism , Epigenesis, Genetic , Genome, Human/genetics , Humans , Microfluidics , Signal Transduction , Transcription Factors/metabolism , Transposases/metabolism
2.
Clin Chem ; 65(2): 272-281, 2019 02.
Article in English | MEDLINE | ID: mdl-30523199

ABSTRACT

BACKGROUND: The comeasurement of both genomic and transcriptomic signatures in single cells is of fundamental importance to accurately assess how the genetic information correlates with the transcriptomic phenotype. However, existing technologies have low throughput and laborious work flows. METHODS: We developed a new method for concurrent sequencing of the transcriptome and targeted genomic regions (CORTAD-seq) within the same single cell on an automated microfluidic platform. The method was compatible with the downstream library preparation, allowing easy integration into existing next-generation sequencing work flows. We incorporated a single-cell bioinformatics pipeline for transcriptome and mutation analysis. RESULTS: As proof of principle, we applied CORTAD-seq to lung cancer cell lines to dissect the cellular consequences of mutations that result in resistance to targeted therapy. We obtained a mean detection of 6000 expressed genes and an exonic rate of 50%. The targeted DNA-sequencing data achieved a 97.8% detection rate for mutations and allowed for the identification of copy number variations and haplotype construction. We detected expression signatures of tyrosine kinase inhibitor (TKI) resistance, epidermal growth factor receptor (EGFR) amplification, and expansion of the T790M mutation among resistant cells. We also identified characteristics for TKI resistance that were independent of EGFR T790M, indicating that other alterations are required for resistance in this context. CONCLUSIONS: CORTAD-seq allows assessment of the interconnection between genetic and transcriptomic changes in single cells. It is operated on an automated, commercially available single-cell isolation platform, making its implementation straightforward.


Subject(s)
Genomics , High-Throughput Nucleotide Sequencing/methods , RNA/chemistry , Sequence Analysis, DNA/methods , Automation , Cell Line, Tumor , DNA Copy Number Variations , Drug Resistance, Neoplasm/genetics , ErbB Receptors/genetics , Gene Library , Humans , Lung Neoplasms/drug therapy , Lung Neoplasms/genetics , Lung Neoplasms/pathology , Microfluidics , Protein Kinase Inhibitors/therapeutic use , RNA/metabolism , Single-Cell Analysis , Transcriptome
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