학술논문
Identification of cancer-related mutations in human pluripotent stem cells using RNA-seq analysis
Document Type
Report
Author
Source
Nature Protocols. September 2021, Vol. 16 Issue 9, p4522, 16 p.
Subject
Language
English
ISSN
1754-2189
Abstract
Author(s): Elyad Lezmi [sup.1] , Nissim Benvenisty [sup.1] Author Affiliations: (1) The Azrieli Center for Stem Cells and Genetic Research, The Hebrew University of Jerusalem, Jerusalem, Israel Introduction Genetic stability [...]
Human pluripotent stem cells (hPSCs) are known to acquire genetic aberrations during in vitro propagation. In addition to recurrent chromosomal aberrations, it has recently been shown that these cells also gain point mutations in cancer-related genes, predominantly in TP53. The need for routine quality control of hPSCs is critical for both basic research and clinical applications. Here we discuss the relevance of detecting mutations for various hPSCs applications, and present a detailed protocol to identify cancer-related point mutations using data from RNA sequencing, an assay commonly performed during the growth and differentiation of hPSCs. In this protocol, we describe how to process and align the sequencing data, analyze it and conservatively interpret the results in order to generate an accurate estimation of mutations in tumor-related genes. This pipeline is designed to work in high throughput and is available as a software container at https://github.com/elyadlezmi/RNA2CM. The protocol requires minimal command-line skills and can be carried out in 1-2 d. Human pluripotent stem cells acquire cancer-related mutations during culture, which can impact their use in the clinic or in basic research. This protocol describes a computational pipeline to detect such mutations using RNA sequencing data.
Human pluripotent stem cells (hPSCs) are known to acquire genetic aberrations during in vitro propagation. In addition to recurrent chromosomal aberrations, it has recently been shown that these cells also gain point mutations in cancer-related genes, predominantly in TP53. The need for routine quality control of hPSCs is critical for both basic research and clinical applications. Here we discuss the relevance of detecting mutations for various hPSCs applications, and present a detailed protocol to identify cancer-related point mutations using data from RNA sequencing, an assay commonly performed during the growth and differentiation of hPSCs. In this protocol, we describe how to process and align the sequencing data, analyze it and conservatively interpret the results in order to generate an accurate estimation of mutations in tumor-related genes. This pipeline is designed to work in high throughput and is available as a software container at https://github.com/elyadlezmi/RNA2CM. The protocol requires minimal command-line skills and can be carried out in 1-2 d. Human pluripotent stem cells acquire cancer-related mutations during culture, which can impact their use in the clinic or in basic research. This protocol describes a computational pipeline to detect such mutations using RNA sequencing data.