Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Sjors Middelkamp; Freek Manders; Flavia Peci; Markus J. van Roosmalen; Diego Montiel González; Eline J.M. Bertrums; Inge van der Werf; Lucca L.M. Derks; Niels M. Groenen; Mark Verheul; Laurianne Trabut; Cayetano Pleguezuelos-Manzano; Arianne M. Brandsma; Evangelia Antoniou; Dirk Reinhardt; Marc Bierings; Mirjam E. Belderbos; Ruben van Boxtel

doi:10.1016/j.xgen.2023.100389

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Sjors Middelkamp, Freek Manders, Flavia Peci, Markus J. van Roosmalen, Diego Montiel González, Eline J.M. Bertrums, Inge van der Werf, Lucca L.M. Derks, Niels M. Groenen, Mark Verheul, Laurianne Trabut, Cayetano Pleguezuelos-Manzano, Arianne M. Brandsma, Evangelia Antoniou, Dirk Reinhardt, Marc Bierings, Mirjam E. Belderbos, Ruben van Boxtel^*

^*Corresponding author for this work

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Abstract

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

Original language	English
Article number	100389
Number of pages	23
Journal	Cell genomics
Volume	3
Issue number	9
DOIs	https://doi.org/10.1016/j.xgen.2023.100389
Publication status	Published - 13 Sept 2023

Keywords

cancer
Fanconi anemia
hematopoietic stem cells
mutational signatures
primary template-directed amplification
single-cell sequencing
somatic mutations
structural variants
whole-genome amplification
whole-genome sequencing

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1-s2.0-S2666979X23001866-mainFinal published version, 3.46 MBLicence: CC BY

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Middelkamp, S., Manders, F., Peci, F., van Roosmalen, M. J., González, D. M., Bertrums, E. J. M., van der Werf, I., Derks, L. L. M., Groenen, N. M., Verheul, M., Trabut, L., Pleguezuelos-Manzano, C., Brandsma, A. M., Antoniou, E., Reinhardt, D., Bierings, M., Belderbos, M. E., & van Boxtel, R. (2023). Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox. Cell genomics, 3(9), Article 100389. https://doi.org/10.1016/j.xgen.2023.100389

@article{47c09e9c1a4d4f3a9fea47209e31207d,

title = "Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox",

abstract = "Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90\%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.",

keywords = "cancer, Fanconi anemia, hematopoietic stem cells, mutational signatures, primary template-directed amplification, single-cell sequencing, somatic mutations, structural variants, whole-genome amplification, whole-genome sequencing",

author = "Sjors Middelkamp and Freek Manders and Flavia Peci and \{van Roosmalen\}, \{Markus J.\} and Gonz{\'a}lez, \{Diego Montiel\} and Bertrums, \{Eline J.M.\} and \{van der Werf\}, Inge and Derks, \{Lucca L.M.\} and Groenen, \{Niels M.\} and Mark Verheul and Laurianne Trabut and Cayetano Pleguezuelos-Manzano and Brandsma, \{Arianne M.\} and Evangelia Antoniou and Dirk Reinhardt and Marc Bierings and Belderbos, \{Mirjam E.\} and \{van Boxtel\}, Ruben",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

month = sep,

day = "13",

doi = "10.1016/j.xgen.2023.100389",

language = "English",

volume = "3",

journal = "Cell genomics",

issn = "2666-979X",

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Middelkamp, S, Manders, F, Peci, F, van Roosmalen, MJ, González, DM, Bertrums, EJM, van der Werf, I, Derks, LLM, Groenen, NM, Verheul, M, Trabut, L, Pleguezuelos-Manzano, C, Brandsma, AM, Antoniou, E, Reinhardt, D, Bierings, M, Belderbos, ME & van Boxtel, R 2023, 'Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox', Cell genomics, vol. 3, no. 9, 100389. https://doi.org/10.1016/j.xgen.2023.100389

TY - JOUR

T1 - Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

AU - Middelkamp, Sjors

AU - Manders, Freek

AU - Peci, Flavia

AU - van Roosmalen, Markus J.

AU - González, Diego Montiel

AU - Bertrums, Eline J.M.

AU - van der Werf, Inge

AU - Derks, Lucca L.M.

AU - Groenen, Niels M.

AU - Verheul, Mark

AU - Trabut, Laurianne

AU - Pleguezuelos-Manzano, Cayetano

AU - Brandsma, Arianne M.

AU - Antoniou, Evangelia

AU - Reinhardt, Dirk

AU - Bierings, Marc

AU - Belderbos, Mirjam E.

AU - van Boxtel, Ruben

PY - 2023/9/13

Y1 - 2023/9/13

N2 - Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

AB - Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

KW - cancer

KW - Fanconi anemia

KW - hematopoietic stem cells

KW - mutational signatures

KW - primary template-directed amplification

KW - single-cell sequencing

KW - somatic mutations

KW - structural variants

KW - whole-genome amplification

KW - whole-genome sequencing

UR - https://www.scopus.com/pages/publications/85170679896

U2 - 10.1016/j.xgen.2023.100389

DO - 10.1016/j.xgen.2023.100389

M3 - Article

AN - SCOPUS:85170679896

SN - 2666-979X

VL - 3

JO - Cell genomics

JF - Cell genomics

IS - 9

M1 - 100389

ER -

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

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