EditR: A Method to Quantify Base Editing from Sanger Sequencing

Abstract

CRISPR-Cas9-Cytidine deaminase fusion enzymes-termed "base editors"-allow targeted editing of genomic deoxycytidine to deoxythymidine (C:G→T:A) without the need for double-stranded break induction. Base editors represent a paradigm shift in gene editing technology due to their unprecedented efficiency to mediate targeted, single-base conversion. However, current analysis of base editing outcomes rely on methods that are either imprecise or expensive and time-consuming. To overcome these limitations, we developed a simple, cost-effective, and accurate program to measure base editing efficiency from fluorescence-based Sanger sequencing, termed "EditR." We provide EditR as a free online tool or downloadable desktop application requiring a single Sanger sequencing file and guide RNA sequence. EditR is more accurate than enzymatic assays, and provides added insight to the position, type, and efficiency of base editing. Furthermore, EditR is likely amenable to quantify base editing from the recently developed adenosine deaminase base editors that act on either DNA (adenosine deaminase base editors [ABEs]) or RNA (REPAIRs) (catalyzes A:T→G:C). Collectively, we demonstrate that EditR is a robust, inexpensive tool that will facilitate the broad application of base editing technology, thereby fostering further innovation in this burgeoning field.

FIG. 1.

Analysis of base editing by capillary Sanger sequencing trace quantification. (A) Following treatment with base editor and guide RNA (gRNA), Cs (antisense Gs) within the editing window are converted to Ts (antisense As), producing a heterogeneous population of edited cells. (B) Workflow of EditR steps with summary plots. (1) The first and last portions of the file are removed due to poor quality. The signal–noise plot allows users to visualize the amount of fluorescence at each basecall that is deemed signal (purple) versus noise (orange). A chromatogram of the protospacer is also produced for users to validate their results qualitatively. (2) A zero-adjusted gamma distribution is fit to the percent area noise of each trace (A, C, G, and T) to generate four null distribution to which the traces in the hypothesized sites of editing (i.e., the protospacer) are compared. (3) Percent composition of traces measured to be significantly different from noise are plotted in a colored heat map proportional to magnitude (red is low, blue is high).

FIG. 2.

In vitro validation of EditR as an accurate and sensitive method. (A) EditR data presented as the mean of independent triplicates ± 1 standard deviation. See Supplementary Figs. S2 and S3 for an additional titration series. Surveyor assay data presented as the mean of triplicate measurement ± 1 standard error of gel fluorescence densitometry, as previously described. When the expected editing rate is >50%, the observed editing is calculated as 100%–calculated editing, as the T-containing product shifted from the minor to major PCR product. See Supplementary Fig. S2 for gel image. (B) EditR can detect 2.5% differences in C→T down to 2.5% C→T. Individual red dots represent a replicate. ^†p < 0.05; *p < 0.01; **p < 0.001; ***p < 0.0001; n.s., not significant.

FIG. 3.

Validation of EditR in base-edited cells with target mutations. (A) Output graphic showing the distribution of signal and noise in the sequencing file with peaks in the gRNA region. (B) Output plots of traces by base identity and significance. (C) Output editing table color-coded by proportionality showing editing of G→A at two bases. (D) Comparison of EditR to Surveyor assay, height of bars is the mean of triplicate measurement ± 1 standard error of gel fluorescence densitometry, as previously described. WT negative control not shown (0% editing). See Supplementary Fig. S2 for gel image. (E–H) Additional EditR-generated table plots of base-edited samples with target mutations.

FIG. 4.

Validation of EditR in base-edited cells with non-target mutations. (A) Output graphic showing the distribution of signal and noise in the sequencing file with peaks in the gRNA region. (B) Output plots of traces by base identity and significance. (C) Output editing table color-coded by proportionality showing significant C→T and C→G mutations. (D) Comparison of EditR to Surveyor assay, height of bars is the mean ± 1 standard deviation of fluorescence densitometry from independent surveyor assays. Similarity in the percent editing suggests linked mutations. See Supplementary Fig. S2 for gel image. (E–H) Additional EditR-generated table plots of base-edited samples with target mutations.

FIG. 5.

Validation of EditR compared to next-generation deep sequencing (NGS) across multiple guide sites. (A) Base editing guides used to compare EditR to NGS. (B) Comparison of measured editing by EditR and NGS. Solid black bars denote the mean of each group. Red lines drawn between points indicate which samples are paired. (C) Distribution of differences between EditR and NGS. Positive values indicate editing measured by EditR was larger. (D) Table summary of paired t-test performed on data. N = 43, comprised of 8 amplicons, 14 unique guides, 26 unique bases, and 21 unique edits with one or two independent replicates per guide. A single unique base may produce multiple unique edits via non-target editing, that is, one unique C edited to T, G, or A.