clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers

Genome Biol. 2019 Mar 12;20(1):54. doi: 10.1186/s13059-019-1645-z.

Abstract

Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods to simultaneously assay DNA and RNA from the same single cell, parallel single-cell DNA and RNA measurements from independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns gene expression states to cancer clones using single-cell RNA and DNA sequencing independently sampled from a heterogeneous population. We apply clonealign to triple-negative breast cancer patient-derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either sequencing method alone.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biomarkers, Tumor / genetics*
  • Clone Cells
  • Cystadenocarcinoma, Serous / genetics*
  • Cystadenocarcinoma, Serous / pathology
  • Female
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Mice, Inbred NOD
  • Mice, SCID
  • Models, Statistical*
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / pathology
  • Single-Cell Analysis / methods*
  • Software*
  • Triple Negative Breast Neoplasms / genetics*
  • Triple Negative Breast Neoplasms / pathology
  • Tumor Cells, Cultured
  • Xenograft Model Antitumor Assays

Substances

  • Biomarkers, Tumor