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

Characterizing genotype-phenotype relationships of biomolecules (e.g.,
ribozymes) requires accurate ways to measure 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 over 106 unique nucleic acid
sequences. However, maximizing the return of such assays requires
understanding the technical challenges introduced by sequence
heterogeneity and DNA sequencing. 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. Here we present detailed protocols, define critical
experimental factors, and identify general guidelines to maximize the
number of sequences and their measurement accuracy from k-Seq data.
Analogous practices could be applied to improve the rigor of other
sequencing-based assays.