Quantification and Mechanistic Analysis of Plant Genome Editing Outcomes using Nanopore Sequencing

Abstract

Precise genome modification via homologous recombination, or gene targeting (GT), allows crop genomes to be tailored to any application or environment. While GT’s potential is immense, it tends to be inefficient and technically challenging in plants. These problems are compounded by the slow and low-throughput nature of plant transformation, drastically hindering optimization. More insidiously, these issues result in dependence upon proxies and reporter readouts for estimating GT frequencies that vary between groups and delivery platform making it difficult to compare experimental outcomes. To enable widespread optimization of plant GT, a universal platform for directly measuring genome editing outcomes at the molecular level that accommodates plant-specific technical constraints is urgently needed. Here I develop such a platform, an amplicon-based analysis pipeline using Oxford Nanopore Sequencing (ONS). ONS has several valuable qualities for a plant GT optimization pipeline, namely its accessibility, speed, and read length, making it feasible for even the smallest labs to perform on-demand sequencing with their own equipment. These strengths are accompanied by a major shortcoming – sequencing error. I mitigate this problem using several approaches in a novel bioinformatics pipeline to minimize the effect of ONS error on estimates of targeted mutagenesis and virtually eliminating its effect on estimates of GT frequencies. Using this pipeline, I observed a significant impact of both geminiviral replicons (GVRs) and donor sequence divergence on gene targeting frequencies. Additionally, I was able to observe the conversion tracts of hundreds of gene targeting events, revealing their deposition by multiple DNA repair pathways and the prevalence of extremely short tracts, which will inform future optimization efforts. This work establishes a universal pipeline for quantifying plant gene targeting events, facilitating future optimization and communication of results between disparate experimental systems within the plant community.