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Whole-genome sequencing with AVITI and NovaSeq X Plus reveals comparable performance with contextual biases
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-8010-4755
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.ORCID iD: 0000-0002-2467-008X
National Genomics Infrastructure, Science for Life Laboratory, Stockholm University, Stockholm, 171 65 Solna, Sweden.
Department of Medical Sciences, Uppsala University, Uppsala, 751 85 Uppsala, Sweden; National Genomics Infrastructure, Science for Life Laboratory, Uppsala University, Uppsala, 752 37 Uppsala, Sweden.
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2026 (English)In: NAR Genomics and Bioinformatics, E-ISSN 2631-9268, Vol. 8, no 2, article id lqag053Article in journal (Refereed) Published
Abstract [en]

Element Biosciences’ avidity sequencing has emerged as a competing technology to Illumina’s short-read sequencing platform. Prior benchmarks of avidity sequencing have not included the latest Illumina NovaSeq X/X Plus instruments with XLEAP chemistry. Here, we have run polymerase chain reaction-free whole-genome sequencing on four human tumor cell lines using both Illumina NovaSeq X Plus and Element AVITI instruments. AVITI showed low duplication rates and reported higher base qualities; the latter contributed to improved mapping confidence and fewer spurious variant candidates. Both platforms were found to be highly comparable when benchmarking variant calling, with AVITI only providing a minor improvement on INDELs at lower coverages. Stratifying by genomic context revealed further differences, where AVITI genome coverage and variant calls were superior in high-GC regions while being inferior in GC homopolymers. Error-rate analysis highlighted further differences between the platforms; in particular, AVITI in some instances displayed an increased error rate on read 2 related to short fragments. AVITI error rate was also found to be more stable downstream of repetitive regions, except for GC homopolymers. We further found that AVITI sequencing was sensitive to G-quadruplex motifs. Overall, despite these identified differences, both platforms performed highly comparable for variant analysis.

Place, publisher, year, edition, pages
Oxford University Press (OUP) , 2026. Vol. 8, no 2, article id lqag053
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Bioinformatics and Computational Biology
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URN: urn:nbn:se:kth:diva-383066DOI: 10.1093/nargab/lqag053ISI: 001773612000001PubMedID: 42206012Scopus ID: 2-s2.0-105040003595OAI: oai:DiVA.org:kth-383066DiVA, id: diva2:2066424
Note

QC 20260605

Available from: 2026-06-05 Created: 2026-06-05 Last updated: 2026-06-05Bibliographically approved

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Höjer, PontusAlneberg, JohannesNatanaelsson, ChristianAmeur, AdamNordlund, JessicaMånsson Welinder, Robert
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