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Tumour evolution inferred by single-cell sequencing

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TLDR
It is shown that with flow-sorted nuclei, whole genome amplification and next generation sequencing the authors can accurately quantify genomic copy number within an individual nucleus and indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.
Abstract
Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.

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SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Glenn Tesler
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Journal ArticleDOI

Comprehensive Integration of Single-Cell Data.

TL;DR: A strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities.
Journal ArticleDOI

Cancer Genome Landscapes

TL;DR: This work has revealed the genomic landscapes of common forms of human cancer, which consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of "hills" (Genes altered infrequently).
References
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Technical Advance Whole Genome Amplification for Array Comparative Genomic Hybridization Using DNA Extracted from Formalin-Fixed, Paraffin-Embedded Histological Sections

TL;DR: In this paper, a ligation step before WGA is used to generate sufficient DNA with minimum amplification bias, which is important because it allows a short reaction time with Phi29 to generate WGA-DNA with greatly decreased amplification bias.
Journal ArticleDOI

Whole Genome Amplification for Array Comparative Genomic Hybridization Using DNA Extracted from Formalin-Fixed, Paraffin-Embedded Histological Sections

TL;DR: The results suggest that genetic analyses are possible using WGA-DNA extracted from paraffin sections, but that they should be performed with a carefully optimized and controlled protocol.
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