Kinetic sequencing (k-Seq) as a massively parallel assay for ribozyme kinetics: utility and critical parameters

Abstract

Characterization of genotype-phenotype relationships of genetically encoded molecules (e.g., ribozymes) requires accurate quantification of activity for a large set of molecules. Kinetic measurement using high-throughput sequencing (e.g., k-Seq) is an emerging assay applicable in various domains that potentially scales up measurement throughput to 105 ~ 106 unique sequences. However, technical challenges introduced by sequence heterogeneity and DNA sequencing must be understood to realize the utility and limitations of such assays. We characterized the k-Seq method in terms of model identifiability, effects of sequencing error, accuracy and precision using simulated datasets and experimental data from a variant pool constructed from previously identified ribozymes. Relative abundance, kinetic coefficients, and measurement noise were found to affect the measurement of each sequence. We introduced bootstrapping to robustly quantify the uncertainty in estimating model parameters and proposed interpretable metrics to quantify model identifiability. These efforts enabled the rigorous reporting of data quality for individual sequences in k-Seq experiments. Critical experimental factors were examined, and general guidelines are proposed to maximize the number of sequences having precisely estimated and identifiable kinetic coefficients from k-Seq data. Practices analogous to those laid out here could be applied to improve the rigor of similar sequencing-based assays.