Abstract

Next-generation sequencing has generated a need for a broadly applicable method to remove unwanted high-abundance species prior to sequencing. We introduce DASH (Depletion of Abundant Sequences by Hybridization). Sequencing libraries are ‘DASHed’ with recombinant Cas9 protein complexed with a library of guide RNAs targeting unwanted species for cleavage, thus preventing them from consuming sequencing space. We demonstrate a more than 99 % reduction of mitochondrial rRNA in HeLa cells, and enrichment of pathogen sequences in patient samples. We also demonstrate an application of DASH in cancer. This simple method can be adapted for any sample type and increases sequencing yield without additional cost.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0904-5) contains supplementary material, which is available to authorized users.

Highlights

  • The challenge of extracting faint signals from abundant noise in molecular diagnostics is a recurring theme across a broad range of applications

  • We demonstrate deletion of unwanted mitochondrial Ribosomal RNA (rRNA) using Depletion of Abundant Sequences by Hybridization (DASH) first on HeLa cell line RNA (Fig. 2) and on cerebrospinal fluid (CSF) RNA from patients with pathogens in their CSF (Fig. 3), in order to increase sequencing bandwidth of useful data

  • Selection of rRNA Single guide RNA (sgRNA) targets was based on examining coverage plots for standard RNA sequencing (RNA-Seq) experiments on HeLa cells as well as on several patient CSF samples

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Summary

Introduction

The challenge of extracting faint signals from abundant noise in molecular diagnostics is a recurring theme across a broad range of applications. The fraction of the mutant tumor-derived species may be vastly outnumbered by wild-type species due to the abundance of immune cells or the interspersed nature of some tumors throughout normal tissue This problem is profoundly exaggerated in the case of cell-free DNA/RNA diagnostics, whether from malignant [2, 3], transplant [4], or fetal sources [5, 6], and relies on brute force counting by either sequencing or digital PCR (dPCR) [7] to yield a detectable signal. A technique to deplete specific unwanted sequences that is independent of sample preparation protocols and agnostic to measurement technology is highly desired

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