文献_2011-Tumour evolution inferred by single-cell sequencing.pdfVIP

LETTER doi:10.1038/nature09807 Tumour evolution inferred by single-cell sequencing 1,2 1 1 1 1 1 1 Nicholas Navin , Jude Kendall , Jennifer Troge , Peter Andrews , Linda Rodgers , Jeanne McIndoo , Kerry Cook , Asya Stepansky1 1 1 3 1 1 1 , Dan Levy , Diane Esposito , Lakshmi Muthuswamy , Alex Krasnitz , W. Richard McCombie , James Hicks Michael Wigler1 Genomic analysis provides insights into the role of copy number progression, our data indicate that tumours grow by punctuated variation in disease, but most methods are not designed to resolve clonal expansions with few persistent intermediates. mixed populations of cells. In tumours, where genetic heterogeneity In single-nucleus sequencing (SNS), we isolate nuclei by flow-sort- is common1–3, very important information may be lost that would be ing and amplify DNA using whole genome amplification (WGA) for useful for reconstructing evolutionary history. Here we show that massively parallel sequencing (Supplementary Fig. 1). We achieve low with flow-sorted nuclei, whole genome amplification and next coverage (,6%) of the genome of a single cell, sufficient to quantify generation sequencing we can accurately quantify genomic copy copy number from sequence read depth. Several features of our data number within an individual nucleus. We apply single-nucleus analysis were designed for SNS and differ from previous met