Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox.
Fanconi anemia
cancer
hematopoietic stem cells
mutational signatures
primary template-directed amplification
single-cell sequencing
somatic mutations
structural variants
whole-genome amplification
whole-genome sequencing
Journal
Cell genomics
ISSN: 2666-979X
Titre abrégé: Cell Genom
Pays: United States
ID NLM: 9918284260106676
Informations de publication
Date de publication:
13 Sep 2023
13 Sep 2023
Historique:
received:
01
02
2023
revised:
30
05
2023
accepted:
02
08
2023
medline:
18
9
2023
pubmed:
18
9
2023
entrez:
18
9
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37719152
doi: 10.1016/j.xgen.2023.100389
pii: S2666-979X(23)00186-6
pmc: PMC10504672
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100389Informations de copyright
© 2023 The Author(s).
Déclaration de conflit d'intérêts
The authors declare no competing interests.
Références
Bioinformatics. 2009 Jul 15;25(14):1754-60
pubmed: 19451168
Mutat Res. 2009 Jul 31;668(1-2):73-91
pubmed: 19464302
Haematologica. 2018 Nov;103(11):1806-1814
pubmed: 29976742
Front Aging. 2021 Dec 17;2:802407
pubmed: 35822044
Bioinformatics. 2014 Jul 15;30(14):2076-8
pubmed: 24681907
Nat Biotechnol. 2011 Jan;29(1):24-6
pubmed: 21221095
Nat Cancer. 2021 Jun;2(6):643-657
pubmed: 34164627
Nat Methods. 2015 Oct;12(10):966-8
pubmed: 26258291
Nat Rev Mol Cell Biol. 2016 Jun;17(6):337-49
pubmed: 27145721
Blood Cancer Discov. 2021 Sep;2(5):484-499
pubmed: 34642666
Nucleic Acids Res. 2014 Dec 16;42(22):e168
pubmed: 25300484
Cell Genom. 2022 Mar 22;2(4):100112
pubmed: 36776527
Nature. 2016 Oct 13;538(7624):260-264
pubmed: 27698416
Nat Rev Genet. 2016 Mar;17(3):175-88
pubmed: 26806412
Trends Genet. 2018 Jul;34(7):545-557
pubmed: 29731376
BMC Genomics. 2012 Nov 04;13:591
pubmed: 23442169
Cell. 2012 Jul 20;150(2):264-78
pubmed: 22817890
Cell. 2012 May 25;149(5):979-93
pubmed: 22608084
Cell. 2020 Jul 9;182(1):12-23
pubmed: 32649873
Nat Rev Genet. 2019 Jul;20(7):404-416
pubmed: 30918367
Nat Rev Dis Primers. 2019 Sep 19;5(1):64
pubmed: 31537806
Cell Rep. 2018 Nov 27;25(9):2308-2316.e4
pubmed: 30485801
Nature. 2012 Sep 27;489(7417):571-5
pubmed: 22922648
Gigascience. 2021 Feb 16;10(2):
pubmed: 33590861
Nat Protoc. 2021 Feb;16(2):841-871
pubmed: 33318691
Genome Biol. 2021 Jul 12;22(1):202
pubmed: 34253237
Genome Res. 2009 Sep;19(9):1639-45
pubmed: 19541911
Nucleic Acids Res. 2020 Jan 8;48(D1):D682-D688
pubmed: 31691826
Nat Genet. 2011 May;43(5):491-8
pubmed: 21478889
Nature. 2020 Feb;578(7793):94-101
pubmed: 32025018
Nat Rev Cancer. 2018 Mar;18(3):168-185
pubmed: 29376519
Nucleic Acids Res. 2011 Jan;39(Database issue):D19-21
pubmed: 21062823
Science. 2017 Oct 13;358(6360):234-238
pubmed: 28912133
Nature. 2019 Nov;575(7781):210-216
pubmed: 31645765
Nat Genet. 2019 Apr;51(4):749-754
pubmed: 30886424
PLoS One. 2016 Oct 5;11(10):e0163962
pubmed: 27706213
Genome Biol. 2020 Aug 17;21(1):208
pubmed: 32807205
Annu Rev Cancer Biol. 2018 Mar;2:313-336
pubmed: 30345412
Nat Commun. 2019 Aug 29;10(1):3908
pubmed: 31467286
Genome Res. 2002 Jun;12(6):996-1006
pubmed: 12045153
Cell. 2019 Mar 21;177(1):101-114
pubmed: 30901533
Nature. 2018 Jan 11;553(7687):171-177
pubmed: 29323295
Cell. 2019 May 2;177(4):821-836.e16
pubmed: 30982602
Nat Genet. 2022 Oct;54(10):1564-1571
pubmed: 36163278
Nat Biotechnol. 2017 Apr 11;35(4):316-319
pubmed: 28398311
Science. 2015 Sep 25;349(6255):1483-9
pubmed: 26404825
BMC Genomics. 2022 Feb 15;23(1):134
pubmed: 35168570
Cell Stem Cell. 2021 Oct 7;28(10):1726-1739.e6
pubmed: 34496298
Nat Commun. 2018 May 1;9(1):1744
pubmed: 29717121
Nat Protoc. 2013 Nov;8(11):2281-2308
pubmed: 24157548
Nature. 2022 Dec;612(7940):495-502
pubmed: 36450981
Nature. 2022 Apr;604(7907):714-722
pubmed: 35444284
Bioinformatics. 2010 Mar 15;26(6):841-2
pubmed: 20110278
Cell. 2012 May 25;149(5):994-1007
pubmed: 22608083
Proc Natl Acad Sci U S A. 2021 Jun 15;118(24):
pubmed: 34099548
Mol Cell. 2020 Dec 17;80(6):1013-1024.e6
pubmed: 33338401
Bioinformatics. 2015 Jun 15;31(12):2032-4
pubmed: 25697820
Blood Adv. 2017 Oct 24;1(23):2088-2104
pubmed: 29296856
Nat Protoc. 2021 Oct;16(10):4633-4649
pubmed: 34381208
Cell Stem Cell. 2023 Feb 2;30(2):153-170.e9
pubmed: 36736290
Nat Commun. 2019 Nov 28;10(1):5436
pubmed: 31780650