Inferring expressed genes by whole-genome sequencing of plasma DNA

Peter Ulz, Gerhard G Thallinger, Martina Auer, Ricarda Graf, Karl Kashofer, Stephan W Jahn, Luca Abete, Gunda Pristauz, Edgar Petru, Jochen B Geigl, Ellen Heitzer, Michael R Speicher*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing of plasma DNA and identified two discrete regions at transcription start sites (TSSs) where nucleosome occupancy results in different read depth coverage patterns for expressed and silent genes. By employing machine learning for gene classification, we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In patients with cancer having metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We were able to determine the expressed isoform of genes with several TSSs, as confirmed by RNA-seq analysis of the matching primary tumor. Our analyses provide functional information about cells releasing their DNA into the circulation.

Original languageEnglish
Pages (from-to)1273-8
Number of pages6
JournalNature Genetics
Volume48
Issue number10
DOIs
Publication statusPublished - Oct 2016

Keywords

  • Journal Article

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