Protocol for genome-wide analysis of somatic variants at single-cell resolution using primary template-directed DNA amplification

Lucca L.M. Derks; Anaïs J.C.N. van Leeuwen; Alexander S. Steemers; Laurianne Trabut; Markus J. van Roosmalen; Vera M. Poort; Rico Hagelaar; Mark Verheul; Sjors Middelkamp; Ruben van Boxtel

doi:10.1016/j.xpro.2024.103499

Protocol for genome-wide analysis of somatic variants at single-cell resolution using primary template-directed DNA amplification

Lucca L.M. Derks, Anaïs J.C.N. van Leeuwen, Alexander S. Steemers, Laurianne Trabut, Markus J. van Roosmalen, Vera M. Poort, Rico Hagelaar, Mark Verheul, Sjors Middelkamp, Ruben van Boxtel^*

^*Corresponding author for this work

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Abstract

The study of somatic mutations in single cells provides insights into aging and carcinogenesis, which is complicated by the dependency on whole-genome amplification (WGA). Here, we describe a detailed workflow starting from single-cell isolation to WGA by primary template-directed amplification (PTA), sequencing, quality control, and downstream analyses. A machine learning approach, the PTA Analysis Toolkit (PTATO), is used to filter the hundreds to thousands of artificial variants induced by WGA from true mutations at high sensitivity and accuracy. For complete details on the use and execution of this protocol, please refer to Middelkamp et al.¹

Original language	English
Article number	103499
Journal	STAR protocols
Volume	6
Issue number	1
Early online date	20 Dec 2024
DOIs	https://doi.org/10.1016/j.xpro.2024.103499
Publication status	Published - 21 Mar 2025

Keywords

bioinformatics
cancer
molecular biology
sequence analysis
sequencing

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10.1016/j.xpro.2024.103499Licence: CC BY-NC

1-s2.0-S2666166724006646-mainFinal published version, 7.53 MBLicence: CC BY-NC

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Derks, L. L. M., van Leeuwen, A. J. C. N., Steemers, A. S., Trabut, L., van Roosmalen, M. J., Poort, V. M., Hagelaar, R., Verheul, M., Middelkamp, S., & van Boxtel, R. (2025). Protocol for genome-wide analysis of somatic variants at single-cell resolution using primary template-directed DNA amplification. STAR protocols, 6(1), Article 103499. https://doi.org/10.1016/j.xpro.2024.103499

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abstract = "The study of somatic mutations in single cells provides insights into aging and carcinogenesis, which is complicated by the dependency on whole-genome amplification (WGA). Here, we describe a detailed workflow starting from single-cell isolation to WGA by primary template-directed amplification (PTA), sequencing, quality control, and downstream analyses. A machine learning approach, the PTA Analysis Toolkit (PTATO), is used to filter the hundreds to thousands of artificial variants induced by WGA from true mutations at high sensitivity and accuracy. For complete details on the use and execution of this protocol, please refer to Middelkamp et al.1",

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AU - Derks, Lucca L.M.

AU - van Leeuwen, Anaïs J.C.N.

AU - Steemers, Alexander S.

AU - Trabut, Laurianne

AU - van Roosmalen, Markus J.

AU - Poort, Vera M.

AU - Hagelaar, Rico

AU - Verheul, Mark

AU - Middelkamp, Sjors

AU - van Boxtel, Ruben

PY - 2025/3/21

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N2 - The study of somatic mutations in single cells provides insights into aging and carcinogenesis, which is complicated by the dependency on whole-genome amplification (WGA). Here, we describe a detailed workflow starting from single-cell isolation to WGA by primary template-directed amplification (PTA), sequencing, quality control, and downstream analyses. A machine learning approach, the PTA Analysis Toolkit (PTATO), is used to filter the hundreds to thousands of artificial variants induced by WGA from true mutations at high sensitivity and accuracy. For complete details on the use and execution of this protocol, please refer to Middelkamp et al.1

AB - The study of somatic mutations in single cells provides insights into aging and carcinogenesis, which is complicated by the dependency on whole-genome amplification (WGA). Here, we describe a detailed workflow starting from single-cell isolation to WGA by primary template-directed amplification (PTA), sequencing, quality control, and downstream analyses. A machine learning approach, the PTA Analysis Toolkit (PTATO), is used to filter the hundreds to thousands of artificial variants induced by WGA from true mutations at high sensitivity and accuracy. For complete details on the use and execution of this protocol, please refer to Middelkamp et al.1

KW - bioinformatics

KW - cancer

KW - molecular biology

KW - sequence analysis

KW - sequencing

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SN - 2666-1667

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JO - STAR protocols

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Protocol for genome-wide analysis of somatic variants at single-cell resolution using primary template-directed DNA amplification

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