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A Combinatorial PCR Method for Efficient, Selective Oligo Retrieval from Complex Oligo Pools

Claris Winston, Lee Organick, Luis Ceze, Karin Strauss, Yuan-Jyue Chen
doi: https://doi.org/10.1101/2021.08.25.457714
Claris Winston
1University of Washington, Paul G. Allen School of Computer Science and Engineering, Seattle, 98195, USA
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Lee Organick
1University of Washington, Paul G. Allen School of Computer Science and Engineering, Seattle, 98195, USA
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Luis Ceze
1University of Washington, Paul G. Allen School of Computer Science and Engineering, Seattle, 98195, USA
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Karin Strauss
1University of Washington, Paul G. Allen School of Computer Science and Engineering, Seattle, 98195, USA
2Microsoft Research, Redmond, 98052, USA
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Yuan-Jyue Chen
1University of Washington, Paul G. Allen School of Computer Science and Engineering, Seattle, 98195, USA
2Microsoft Research, Redmond, 98052, USA
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  • For correspondence: yuanjc@microsoft.com
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ABSTRACT

With the rapidly decreasing cost of array-based oligo synthesis, large-scale oligo pools offer significant benefits for advanced applications, including gene synthesis, CRISPR-based gene editing, and DNA data storage. Selectively retrieving specific oligos from these complex pools traditionally uses Polymerase Chain Reaction (PCR), in which any selected oligos are exponentially amplified to quickly outnumber non-selected ones. In this case, the number of orthogonal PCR primers is limited due to interactions between them. This lack of specificity presents a serious challenge, particularly for DNA data storage, where the size of an oligo pool (i.e., a DNA database) is orders of magnitude larger than it is for other applications. Although a nested file address system was recently developed to increase the number of accessible files for DNA storage, it requires a more complicated lab protocol and more expensive reagents to achieve high specificity. Instead, we developed a new combinatorial PCR method that outperforms prior work without compromising the fidelity of retrieved material or complicating wet lab processes. Our method quadratically increases the number of accessible oligos while maintaining high specificity. In experiments, we accessed three arbitrarily chosen files from a DNA prototype database that contained 81 different files. Initially comprising only 1% of the original database, the selected files were enriched to over 99.9% using our combinatorial primer method. Our method thus provides a viable path for scaling up DNA data storage systems and has broader utility whenever scientists need access to a specific target oligo and can design their own primer regions.

Competing Interest Statement

Y.J.C. and K.S. are currently employed at Microsoft. The remaining authors declare no conflict of interest.

Footnotes

  • https://github.com/uwmisl/combinatorial_primer_project

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted August 25, 2021.
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A Combinatorial PCR Method for Efficient, Selective Oligo Retrieval from Complex Oligo Pools
Claris Winston, Lee Organick, Luis Ceze, Karin Strauss, Yuan-Jyue Chen
bioRxiv 2021.08.25.457714; doi: https://doi.org/10.1101/2021.08.25.457714
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A Combinatorial PCR Method for Efficient, Selective Oligo Retrieval from Complex Oligo Pools
Claris Winston, Lee Organick, Luis Ceze, Karin Strauss, Yuan-Jyue Chen
bioRxiv 2021.08.25.457714; doi: https://doi.org/10.1101/2021.08.25.457714

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