Cost-efficient whole genome-sequencing using novel mostly natural sequencing-by-synthesis chemistry and open fluidics platform

Gilad Almogy, Mark Pratt, Florian C. Oberstrass, Linda Lee, Dan Mazur, Nate Beckett, Omer Barad, Ilya Soifer, Eddie Perelman, Yoav Etzioni, Martín Sosa, April Jung, Tyson A. Clark, Eliane Trepagnier, Gila Lithwick‐Yanai, Sarah Pollock, Gil Hornung, Maya Levy, Matthew Coole(Broad Institute), Tom Howd(Broad Institute), Megan Shand(Broad Institute), Yossi Farjoun(Broad Institute), James Emery(Broad Institute), Giles Hall(Broad Institute), Sam Lee(Broad Institute), Takuto Sato(Broad Institute), Ricky Magner(Broad Institute), S C Low(Broad Institute), Andrew Bernier(Broad Institute), Bharathi Gandi(Broad Institute), Jack Stohlman(Broad Institute), Corey Nolet(Broad Institute), Siobhan Donovan(Broad Institute), Brendan Blumenstiel(Broad Institute), Michelle Cipicchio(Broad Institute), Sheila Dodge(Broad Institute), Eric Banks(Broad Institute), Niall J. Lennon(Broad Institute), Stacey Gabriel(Broad Institute), Doron Lipson
bioRxiv (Cold Spring Harbor Laboratory)
May 30, 2022
Cited by 74Open Access
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Abstract

Abstract We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length (∼300bp) and fast runs times (<20hrs) with high base accuracy (Q30 > 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data.


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