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We present ampliCan, an analysis tool for genome editing that unites highly precise quantification and visualization of genuine genome editing events. ampliCan features nuclease-optimized alignments, filtering of experimental artifacts, event-specific normalization, and off-target read detection and quantifies insertions, deletions, HDR repair, as well as targeted base editing. It is scalable to thousands of amplicon sequencing-based experiments from any genome editing experiment, including CRISPR. It enables automated integration of controls and accounts for biases at every step of the analysis. We benchmarked ampliCan on both real and simulated data sets against other leading tools, demonstrating that it outperformed all in the face of common confounding factors., (© 2019 Labun et al.; Published by Cold Spring Harbor Laboratory Press.)

Lineage relationships among the large number of heterogeneous cell types generated during development are difficult to reconstruct in a high-throughput manner. We recently established a method, scGESTALT, that combines cumulative editing of a lineage barcode array by CRISPR-Cas9 with large-scale transcriptional profiling using droplet-based single-cell RNA sequencing (scRNA-seq). The technique generates edits in the barcode array over multiple timepoints using Cas9 and pools of single-guide RNAs (sgRNAs) introduced during early and late zebrafish embryonic development, which distinguishes it from similar Cas9 lineage-tracing methods. The recorded lineages are captured, along with thousands of cellular transcriptomes, to build lineage trees with hundreds of branches representing relationships among profiled cell types. Here, we provide details for (i) generating transgenic zebrafish; (ii) performing multi-timepoint barcode editing; (iii) building scRNA-seq libraries from brain tissue; and (iv) concurrently amplifying lineage barcodes from captured single cells. Generating transgenic lines takes 6 months, and performing barcode editing and generating single-cell libraries involve 7 d of hands-on time. scGESTALT provides a scalable platform to map lineage relationships between cell types in any system that permits genome editing during development, regeneration, or disease.

The lineage relationships among the hundreds of cell types generated during development are difficult to reconstruct. A recent method, GESTALT, used CRISPR-Cas9 barcode editing for large-scale lineage tracing, but was restricted to early development and did not identify cell types. Here we present scGESTALT, which combines the lineage recording capabilities of GESTALT with cell-type identification by single-cell RNA sequencing. The method relies on an inducible system that enables barcodes to be edited at multiple time points, capturing lineage information from later stages of development. Sequencing of ∼60,000 transcriptomes from the juvenile zebrafish brain identified >100 cell types and marker genes. Using these data, we generate lineage trees with hundreds of branches that help uncover restrictions at the level of cell types, brain regions, and gene expression cascades during differentiation. scGESTALT can be applied to other multicellular organisms to simultaneously characterize molecular identities and lineage histories of thousands of cells during development and disease.

Multicellular systems develop from single cells through distinct lineages. However, current lineage-tracing approaches scale poorly to whole, complex organisms. Here, we use genome editing to progressively introduce and accumulate diverse mutations in a DNA barcode over multiple rounds of cell division. The barcode, an array of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 target sites, marks cells and enables the elucidation of lineage relationships via the patterns of mutations shared between cells. In cell culture and zebrafish, we show that rates and patterns of editing are tunable and that thousands of lineage-informative barcode alleles can be generated. By sampling hundreds of thousands of cells from individual zebrafish, we find that most cells in adult organs derive from relatively few embryonic progenitors. In future analyses, genome editing of synthetic target arrays for lineage tracing (GESTALT) can be used to generate large-scale maps of cell lineage in multicellular systems for normal development and disease., (Copyright © 2016, American Association for the Advancement of Science.)

In just 3 years CRISPR genome editing has transformed biology, and its popularity and potency continue to grow. New CRISPR effectors and rules for locating optimum targets continue to be reported, highlighting the need for computational CRISPR targeting tools to compile these rules and facilitate target selection and design. CHOPCHOP is one of the most widely used web tools for CRISPR- and TALEN-based genome editing. Its overarching principle is to provide an intuitive and powerful tool that can serve both novice and experienced users. In this major update we introduce tools for the next generation of CRISPR advances, including Cpf1 and Cas9 nickases. We support a number of new features that improve the targeting power, usability and efficiency of CHOPCHOP. To increase targeting range and specificity we provide support for custom length sgRNAs, and we evaluate the sequence composition of the whole sgRNA and its surrounding region using models compiled from multiple large-scale studies. These and other new features, coupled with an updated interface for increased usability and support for a continually growing list of organisms, maintain CHOPCHOP as one of the leading tools for CRISPR genome editing. CHOPCHOP v2 can be found at http://chopchop.cbu.uib.no., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The CRISPR-Cas9 system has the potential to revolutionize genome editing in human pluripotent stem cells (hPSCs), but its advantages and pitfalls are still poorly understood. We systematically tested the ability of CRISPR-Cas9 to mediate reporter gene knockin at 16 distinct genomic sites in hPSCs. We observed efficient gene targeting but found that targeted clones carried an unexpectedly high frequency of insertion and deletion (indel) mutations at both alleles of the targeted gene. These indels were induced by Cas9 nuclease, as well as Cas9-D10A single or dual nickases, and often disrupted gene function. To overcome this problem, we designed strategies to physically destroy or separate CRISPR target sites at the targeted allele and developed a bioinformatic pipeline to identify and eliminate clones harboring deleterious indels at the other allele. This two-pronged approach enables the reliable generation of knockin hPSC reporter cell lines free of unwanted mutations at the targeted locus., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Major advances in genome editing have recently been made possible with the development of the TALEN and CRISPR/Cas9 methods. The speed and ease of implementing these technologies has led to an explosion of mutant and transgenic organisms. A rate-limiting step in efficiently applying TALEN and CRISPR/Cas9 methods is the selection and design of targeting constructs. We have developed an online tool, CHOPCHOP (https://chopchop.rc.fas.harvard.edu), to expedite the design process. CHOPCHOP accepts a wide range of inputs (gene identifiers, genomic regions or pasted sequences) and provides an array of advanced options for target selection. It uses efficient sequence alignment algorithms to minimize search times, and rigorously predicts off-target binding of single-guide RNAs (sgRNAs) and TALENs. Each query produces an interactive visualization of the gene with candidate target sites displayed at their genomic positions and color-coded according to quality scores. In addition, for each possible target site, restriction sites and primer candidates are visualized, facilitating a streamlined pipeline of mutant generation and validation. The ease-of-use and speed of CHOPCHOP make it a valuable tool for genome engineering., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)