Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair

Abstract

Non-homologous end-joining (NHEJ) plays an important role in double-strand break (DSB) repair of DNA. Recent studies have shown that the error patterns of NHEJ are strongly biased by sequence context, but these studies were based on relatively few templates. To investigate this more thoroughly, we systematically profiled ∼1.16 million independent mutational events resulting from CRISPR/Cas9-mediated cleavage and NHEJ-mediated DSB repair of 6872 synthetic target sequences, introduced into a human cell line via lentiviral infection. We find that: (i) insertions are dominated by 1 bp events templated by sequence immediately upstream of the cleavage site, (ii) deletions are predominantly associated with microhomology and (iii) targets exhibit variable but reproducible diversity with respect to the number and relative frequency of the mutational outcomes to which they give rise. From these data, we trained a model that uses local sequence context to predict the distribution of mutational outcomes. Exploiting the bias of NHEJ outcomes towards microhomology mediated events, we demonstrate the programming of deletion patterns by introducing microhomology to specific locations in the vicinity of the DSB site. We anticipate that our results will inform investigations of DSB repair mechanisms as well as the design of CRISPR/Cas9 experiments for diverse applications including genome-wide screens, gene therapy, lineage tracing and molecular recording.

Inference of Single-Cell Phylogenies from Lineage Tracing Data

“…(b-c) Nested, expanded views of 7 the phylogram and character matrices. As expected, Cassiopeia correctly relates cells with similar 8 character states, and closely related cells are found within the same culture plate. consistency between tree reconstructions are evaluated with respect to the first split, represented 12 in (a).…”

“…Not only does Cas-5 siopeia provide a scalable and accurate inference approach, but also our benchmarking resources 6 enable the systematic exploration of stronger algorithms as well as more robust single-cell lineage 7 tracing technologies. Taken together, this work forms the foundation for future efforts in building 8 detailed cell fate maps in a variety of biological applications. workflow of a lineage tracing experiment.…”

“…7 Finally, the character matrix is used to infer phylogenies by one of various methods. (b) The Cas- 8 siopeia framework. Cassiopeia takes as input a "character matrix," summarizing the mutations 9 seen at heritable target sites across cells.…”

“…true number of occurrences of a mutation is estimated well by the observed frequency at leaves. 8 We use a Linear Least Squares Estimate to quantify the relationship between the expected number 9 of times a mutation occurred given the observed frequency at the leaves (Eq. 3).…”

“…3 4 The triple-sgRNA-BFP-PuroR lentivector, PCT61 (to be added to Addgene), is derived from 5 pBA392 (to be added to Addgene) as previously described [1,29] containing three sgRNA cas-6 settes driven by distinct U6 promoters and constitutive BFP and puromycin-resistance markers 7 for selection. Importantly, the three PCT61 sgRNAs are complementary to the three cut-sites in 8 the PCT48 Target Site. To slow the cutting kinetics of the sgRNAs to best match the timescale 9 involved in the in vitro lineage tracing experiments [7], the sgRNAs contain precise single-basepair 10 mismatches that decrease their avidity for the cognate cut-sites [21].…”