Evaluation of Single-Molecule Sequencing Technologies for Structural Variant Detection in Two Swedish Human Genomes.


Journal

Genes
ISSN: 2073-4425
Titre abrégé: Genes (Basel)
Pays: Switzerland
ID NLM: 101551097

Informations de publication

Date de publication:
30 11 2020
Historique:
received: 12 10 2020
revised: 24 11 2020
accepted: 26 11 2020
entrez: 3 12 2020
pubmed: 4 12 2020
medline: 27 7 2021
Statut: epublish

Résumé

Long-read single molecule sequencing is increasingly used in human genomics research, as it allows to accurately detect large-scale DNA rearrangements such as structural variations (SVs) at high resolution. However, few studies have evaluated the performance of different single molecule sequencing platforms for SV detection in human samples. Here we performed Oxford Nanopore Technologies (ONT) whole-genome sequencing of two Swedish human samples (average 32× coverage) and compared the results to previously generated Pacific Biosciences (PacBio) data for the same individuals (average 66× coverage). Our analysis inferred an average of 17k and 23k SVs from the ONT and PacBio data, respectively, with a majority of them overlapping with an available multi-platform SV dataset. When comparing the SV calls in the two Swedish individuals, we find a higher concordance between ONT and PacBio SVs detected in the same individual as compared to SVs detected by the same technology in different individuals. Downsampling of PacBio reads, performed to obtain similar coverage levels for all datasets, resulted in 17k SVs per individual and improved overlap with the ONT SVs. Our results suggest that ONT and PacBio have a similar performance for SV detection in human whole genome sequencing data, and that both technologies are feasible for population-scale studies.

Identifiants

pubmed: 33266238
pii: genes11121444
doi: 10.3390/genes11121444
pmc: PMC7760597
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Références

Genome Res. 2020 Sep;30(9):1258-1273
pubmed: 32887686
Front Genet. 2019 May 07;10:426
pubmed: 31134132
Cell. 2019 Jan 24;176(3):663-675.e19
pubmed: 30661756
Front Genet. 2020 Mar 09;11:159
pubmed: 32211024
Nat Rev Genet. 2006 Feb;7(2):85-97
pubmed: 16418744
Indian J Microbiol. 2016 Dec;56(4):394-404
pubmed: 27784934
Nat Biotechnol. 2019 Oct;37(10):1155-1162
pubmed: 31406327
Eur J Hum Genet. 2017 Nov;25(11):1253-1260
pubmed: 28832569
Nat Commun. 2019 Apr 23;10(1):1869
pubmed: 31015479
Science. 2015 Sep 25;349(6255):1483-9
pubmed: 26404825
Bioinformatics. 2018 Sep 15;34(18):3094-3100
pubmed: 29750242
Genome Biol. 2019 Nov 14;20(1):239
pubmed: 31727106
Cancer Biol Ther. 2016;17(3):246-53
pubmed: 26787508
PLoS Genet. 2011 Nov;7(11):e1002334
pubmed: 22102821
Nat Rev Genet. 2020 Oct;21(10):597-614
pubmed: 32504078
Genome Res. 2019 Jul;29(7):1178-1187
pubmed: 31186302
Genome Res. 2017 May;27(5):677-685
pubmed: 27895111
Genet Med. 2018 Jan;20(1):159-163
pubmed: 28640241
Nat Methods. 2018 Jun;15(6):461-468
pubmed: 29713083
Nature. 2020 May;581(7809):434-443
pubmed: 32461654
Bioinformatics. 2016 Jan 15;32(2):292-4
pubmed: 26428292
Genes (Basel). 2018 Oct 09;9(10):
pubmed: 30304863
Genome Biol. 2019 May 20;20(1):97
pubmed: 31104630
Bioinformatics. 2019 Sep 1;35(17):2907-2915
pubmed: 30668829
Nat Commun. 2017 Nov 6;8(1):1326
pubmed: 29109544
Nature. 2020 May;581(7809):444-451
pubmed: 32461652
Genome Res. 2015 Jun;25(6):792-801
pubmed: 25883321
Nat Commun. 2018 Oct 2;9(1):4038
pubmed: 30279509
Nat Rev Genet. 2016 May 17;17(6):333-51
pubmed: 27184599
Genome Res. 2017 May;27(5):849-864
pubmed: 28396521
Nat Biotechnol. 2020 Sep;38(9):1044-1053
pubmed: 32686750
Hereditas. 2018 Sep 28;155:32
pubmed: 30279644
Nature. 2008 Nov 6;456(7218):53-9
pubmed: 18987734
Bioinformatics. 2018 Aug 1;34(15):2666-2669
pubmed: 29547981
Nat Commun. 2017 Jan 24;8:14061
pubmed: 28117401
Genome Biol. 2020 Aug 3;21(1):189
pubmed: 32746918
Genome Res. 2014 Dec;24(12):2066-76
pubmed: 25373144
Hum Genome Var. 2016 Jun 30;3:16016
pubmed: 27408750
Nat Rev Genet. 2018 Jun;19(6):329-346
pubmed: 29599501
Nat Genet. 2004 Sep;36(9):949-51
pubmed: 15286789
Nature. 2020 Jul;583(7814):83-89
pubmed: 32460305
Nat Commun. 2019 Apr 16;10(1):1784
pubmed: 30992455
Trends Genet. 2018 Sep;34(9):666-681
pubmed: 29941292
Bioinformatics. 2009 Aug 15;25(16):2078-9
pubmed: 19505943
Curr Drug Discov Technol. 2015;12(1):3-20
pubmed: 26033233
Bioinformatics. 2015 Jun 15;31(12):2032-4
pubmed: 25697820
BMC Bioinformatics. 2011 Jan 26;12:35
pubmed: 21269502

Auteurs

Nazeefa Fatima (N)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 752 36 Uppsala, Sweden.

Anna Petri (A)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 752 36 Uppsala, Sweden.

Ulf Gyllensten (U)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 752 36 Uppsala, Sweden.

Lars Feuk (L)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 752 36 Uppsala, Sweden.

Adam Ameur (A)

Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 752 36 Uppsala, Sweden.
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Clayton, VIC 3800, Australia.

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Classifications MeSH