Developing an Efficient and Replicable Single-Guide RNA Synthesis Protocol for Targeted Enrichment of Perfect Assemblies
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Date
2023
Authors
Gaudreault, Yukiko
Journal Title
Journal ISSN
Volume Title
Publisher
University of Oregon
Abstract
Inexpensive large-scale de novo gene synthesis technologies are in high demand for protein characterization and engineering as they enable the testing of many complex hypotheses. One such technology is DropSynth, which can assemble array-derived oligos within emulsion droplets to synthesize libraries of up to 1536 genes in one reaction pool. However, this approach propagates oligo errors, resulting in 20-30% perfect assemblies for 500 bp genes. To address this limitation, we are developing a method to directly extract these perfect assemblies using deactivated CRISPR Cas9 (dCas9). This enrichment method can effectively target the unique barcode sequences corresponding to perfect assemblies as determined from next generation sequencing (NGS) mapping. Here, we show the development of a highly efficient and replicable single guide RNA (sgRNA) synthesis protocol for DropSynth dCas9 enrichment which minimizes the length of oligos required. As a proof-of-concept, we synthesized a 2.2 µg pool of 18 sgRNAs via iterative design based on existing Golden Gate Assembly (GGA) and in vitro RNA transcription protocols. Targeted enrichment verified the functionality of these sgRNAs resulting in 6-fold enrichment of 18 targets. This scalable workflow was also used to synthesize 10 libraries of sgRNAs with ~11,000 unique spacers. Finally, we developed an RNA-seq pipeline to assess sgRNA pools for mutations and biases, highlighting the presence of many mutated off-target spacers in the final population as well as significant inequality in their distribution. We anticipate that this method will allow for the streamlined synthesis of any number of unique sgRNAs for dCas9 enrichment to ultimately allow for the extraction of a pool of perfectly synthesized DNA.
Description
41 pages
Keywords
Gene synthesis, Targeted enrichment, DropSynth, sgRNA, CRISPR Cas9