TY - JOUR
T1 - Identification of cancer-related mutations in human pluripotent stem cells using RNA-seq analysis
AU - Lezmi, Elyad
AU - Benvenisty, Nissim
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/9
Y1 - 2021/9
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85112046707&partnerID=8YFLogxK
U2 - 10.1038/s41596-021-00591-5
DO - 10.1038/s41596-021-00591-5
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.systematicreview???
C2 - 34363070
AN - SCOPUS:85112046707
SN - 1754-2189
VL - 16
SP - 4522
EP - 4537
JO - Nature Protocols
JF - Nature Protocols
IS - 9
ER -