Using RNA-seq and targeted nucleases to identify mechanisms of drug resistance in acute myeloid leukemia

Susan K. Rathe, Branden S. Moriarity, Christopher B. Stoltenberg, Morito Kurata, Natalie K. Aumann, Eric P. Rahrmann, Natashay J. Bailey, Ellen G. Melrose, Dominic A. Beckmann, Chase R. Liska, David A. Largaespada

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

The evolution from microarrays to transcriptome deep-sequencing (RNA-seq) and from RNA interference to gene knockouts using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and Transcription Activator-Like Effector Nucleases (TALENs) has provided a new experimental partnership for identifying and quantifying the effects of gene changes on drug resistance. Here we describe the results from deep-sequencing of RNA derived from two cytarabine (Ara-C) resistance acute myeloid leukemia (AML) cell lines, and present CRISPR and TALEN based methods for accomplishing complete gene knockout (KO) in AML cells. We found protein modifying loss-of-function mutations in Dck in both Ara-C resistant cell lines. CRISPR and TALEN-based KO of Dck dramatically increased the IC50 of Ara-C and introduction of a DCK overexpression vector into Dck KO clones resulted in a significant increase in Ara-C sensitivity. This effort demonstrates the power of using transcriptome analysis and CRISPR/TALEN-based KOs to identify and verify genes associated with drug resistance.

Original languageEnglish (US)
Article number6048
JournalScientific reports
Volume4
DOIs
StatePublished - Aug 13 2014

Bibliographical note

Funding Information:
Funding for this project was provided by The Leukemia & Lymphoma Society (grant 7019-04). We extend our thanks to the many University of Minnesota resources involved in our project. The BioMedical Genomics Center provided services for RNA sequencing, oligo preparation, and Sanger sequencing. The Minnesota Supercomputing Institute maintains the Galaxy Software, as well as provides data management services and training. The Masonic Cancer Center Bioinformatics Core provided guidance in the analysis of the RNA-seq data. We would also like to express our thanks to the assistance provided by Willemijn Veldhuijzen.

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