Search

Prime editing systems have enabled the incorporation of precise edits within a genome without introducing double strand breaks. Previous studies defined an optimal primer binding site (PBS) length for the pegRNA of ∼13 nucleotides depending on the sequence composition. However, optimal PBS length characterization has been based on prime editing outcomes using plasmid or lentiviral expression systems. In this study, we demonstrate that for prime editor (PE) ribonucleoprotein complexes, the auto-inhibitory interaction between the PBS and the spacer sequence affects pegRNA binding efficiency and target recognition. Destabilizing this auto-inhibitory interaction by reducing the complementarity between the PBS-spacer region enhances prime editing efficiency in multiple prime editing formats. In the case of end-protected pegRNAs, a shorter PBS length with a PBS-target strand melting temperature near 37°C is optimal in mammalian cells. Additionally, a transient cold shock treatment of the cells post PE-pegRNA delivery further increases prime editing outcomes for pegRNAs with optimized PBS lengths. Finally, we show that prime editor ribonucleoprotein complexes programmed with pegRNAs designed using these refined parameters efficiently correct disease-related genetic mutations in patient-derived fibroblasts and efficiently install precise edits in primary human T cells and zebrafish.

Type V CRISPR–Cas12a systems provide an alternate nuclease platform to Cas9, with potential advantages for specific genome editing applications. Here we describe improvements to the Cas12a system that facilitate efficient targeted mutagenesis in mammalian cells and zebrafish embryos. We show that engineered variants of Cas12a with two different nuclear localization sequences (NLS) on the C terminus provide increased editing efficiency in mammalian cells. Additionally, we find that pre-crRNAs comprising a full-length direct repeat (full-DR-crRNA) sequence with specific stem-loop G-C base substitutions exhibit increased editing efficiencies compared with the standard mature crRNA framework. Finally, we demonstrate in zebrafish embryos that the improved LbCas12a and FnoCas12a nucleases in combination with these modified crRNAs display high mutagenesis efficiencies and low toxicity when delivered as ribonucleoprotein complexes at high concentration. Together, these results define a set of enhanced Cas12a components with broad utility in vertebrate systems.

The eastern North American monarch butterfly, Danaus plexippus, is an emerging model system to study the neural, molecular, and genetic basis of animal long-distance migration and animal clockwork mechanisms. While genomic studies have provided new insight into migration-associated and circadian clock genes, the general lack of simple and versatile reverse-genetic methods has limited in vivo functional analysis of candidate genes in this species. Here, we report the establishment of highly efficient and heritable gene mutagenesis methods in the monarch butterfly using transcriptional activator-like effector nucleases (TALENs) and CRISPR-associated RNA-guided nuclease Cas9 (CRISPR/Cas9). Using two clock gene loci, cryptochrome 2 and clock (clk), as candidates, we show that both TALENs and CRISPR/Cas9 generate high-frequency nonhomologous end-joining (NHEJ)-mediated mutations at targeted sites (up to 100%), and that injecting fewer than 100 eggs is sufficient to recover mutant progeny and generate monarch knockout lines in about 3 months. Our study also genetically defines monarch CLK as an essential component of the transcriptional activation complex of the circadian clock. The methods presented should not only greatly accelerate functional analyses of many aspects of monarch biology, but are also anticipated to facilitate the development of these tools in other nontraditional insect species as well as the development of homology-directed knock-ins.

Regulation of eukaryotic gene transcription is often combinatorial in nature, with multiple transcription factors (TFs) regulating common target genes, often through direct or indirect mutual interactions. Many individual examples of cooperative binding by directly interacting TFs have been identified, but it remains unclear how pervasive this mechanism is during animal development. Cooperative TF binding should be manifest in genomic sequences as biased arrangements of TF-binding sites. Here, we explore the extent and diversity of such arrangements related to gene regulation during Drosophila embryogenesis. We used the DNA-binding specificities of 322 TFs along with chromatin accessibility information to identify enriched spacing and orientation patterns of TF-binding site pairs. We developed a new statistical approach for this task, specifically designed to accurately assess inter-site spacing biases while accounting for the phenomenon of homotypic site clustering commonly observed in developmental regulatory regions. We observed a large number of short-range distance preferences between TF-binding site pairs, including examples where the preference depends on the relative orientation of the binding sites. To test whether these binding site patterns reflect physical interactions between the corresponding TFs, we analyzed 27 TF pairs whose binding sites exhibited short distance preferences. In vitro protein–protein binding experiments revealed that >65% of these TF pairs can directly interact with each other. For five pairs, we further demonstrate that they bind cooperatively to DNA if both sites are present with the preferred spacing. This study demonstrates how DNA-binding motifs can be used to produce a comprehensive map of sequence signatures for different mechanisms of combinatorial TF action.

Motivation: Recognition models for protein-DNA interactions, which allow the prediction of specificity for a DNA-binding domain based only on its sequence or the alteration of specificity through rational design, have long been a goal of computational biology. There has been some progress in constructing useful models, especially for C2H2 zinc finger proteins, but it remains a challenging problem with ample room for improvement. For most families of transcription factors the best available methods utilize k-nearest neighbor (KNN) algorithms to make specificity predictions based on the average of the specificities of the k most similar proteins with defined specificities. Homeodomain (HD) proteins are the second most abundant family of transcription factors, after zinc fingers, in most metazoan genomes, and as a consequence an effective recognition model for this family would facilitate predictive models of many transcriptional regulatory networks within these genomes. Results: Using extensive experimental data, we have tested several machine learning approaches and find that both support vector machines and random forests (RFs) can produce recognition models for HD proteins that are significant improvements over KNN-based methods. Cross-validation analyses show that the resulting models are capable of predicting specificities with high accuracy. We have produced a web-based prediction tool, PreMoTF (Predicted Motifs for Transcription Factors) (http://stormo.wustl.edu/PreMoTF), for predicting position frequency matrices from protein sequence using a RF-based model. Contact: stormo@wustl.edu

FlyFactorSurvey (http://pgfe.umassmed.edu/TFDBS/) is a database of DNA binding specificities for Drosophila transcription factors (TFs) primarily determined using the bacterial one-hybrid system. The database provides community access to over 400 recognition motifs and position weight matrices for over 200 TFs, including many unpublished motifs. Search tools and flat file downloads are provided to retrieve binding site information (as sequences, matrices and sequence logos) for individual TFs, groups of TFs or for all TFs with characterized binding specificities. Linked analysis tools allow users to identify motifs within our database that share similarity to a query matrix or to view the distribution of occurrences of an individual motif throughout the Drosophila genome. Together, this database and its associated tools provide computational and experimental biologists with resources to predict interactions between Drosophila TFs and target cis-regulatory sequences.

Zinc finger nucleases (ZFNs) facilitate tailor-made genomic modifications in vivo through the creation of targeted double-stranded breaks. They have been employed to modify the genomes of plants and animals, and cell-based therapies utilizing ZFNs are undergoing clinical trials. However, many ZFNs display dose-dependent toxicity presumably due to the generation of undesired double-stranded breaks at off-target sites. To evaluate the parameters influencing the functional specificity of ZFNs, we compared the in vivo activity of ZFN variants targeting the zebrafish kdrl locus, which display both high on-target activity and dose-dependent toxicity. We evaluated their functional specificity by assessing lesion frequency at 141 potential off-target sites using Illumina sequencing. Only a minority of these off-target sites accumulated lesions, where the thermodynamics of zinc finger-DNA recognition appear to be a defining feature of active sites. Surprisingly, we observed that both the specificity of the incorporated zinc fingers and the choice of the engineered nuclease domain could independently influence the fidelity of these ZFNs. The results of this study have implications for the assessment of likely off-target sites within a genome and point to both zinc finger-dependent and -independent characteristics that can be tailored to create ZFNs with greater precision.