Patent Application
20240368633
The present disclosure relates to genome editing. More specifically, the present disclosure provides an improved method to boost precision genome editing efficiencies, particularly in systems suffering from low HDR frequencies, such as mammalian cells or mouse germline transformations. The improved genome editing method also improves any CRISPR-based gene drive efficiency by recycling resistance alleles, such improved gene drive also efficiently spreads in caged populations.
The detailed background information related to the state of art genome editing is described in the introductions under EXAMPLES 1 and 2, respectively, of the present disclosure.
The present disclosure provides an improved method of CRISPR-based gene editing. The method disclosed herein, termed “double-tap”, uses additional gRNAs (called secondary or tertiary gRNAs, or multiple secondary or tertiary gRNAs) to target high frequency indel products created by end joining pathways during an attempted HDR event (
In certain embodiments, the double tap method was tested in multiple human cell lines at 15 different genomic loci. Secondary gRNAs were designed and tested to targeted indel sequences with a wide range of frequencies and larger improvements in HDR-mediated genome editing efficiencies were observed when targeting higher frequency indel sequences, with no increases in indel rates (in many instances, decreases in indel rates were in fact observed). The present disclosure demonstrates the ability of the double tap method to improve HDR-mediated genome editing efficiencies for the installation of point mutations, small insertions, and deletions with ssODNs, as well as for gene knock-in using dsDNA donor templates. The double tap method disclosed herein can be easily integrated into any routine HDR experiment to boost precision editing efficiencies by characterizing the sequences of the most common indel products and incorporating secondary or tertiary or subsequent gRNAs to target these sequences. Therefore, the double tap method could be implemented in a subject, such as any animals (fly, mice, rats, etc.), plants, or fungi, that has HDR as a DNA repair mechanism and/or a system where HDR conversion is less efficient, such as primary human cells or other mammalian cells, and/or mouse embryos or germline transformations, to boost efficient gene editing for human diseases and/or agriculture.
The present disclosure further provides the double tap homing gene-drive strategy to combat the prevalent resistance alleles that prevent drive spread. In certain embodiments, the double tap gene drive method uses additional, secondary or tertiary or multiple secondary or tertiary gRNAs targeting the resistance alleles to recycle them as new templates for an additional round of gene conversation, ultimately, improving gene drive efficiency. Therefore, the double tap method disclosed herein could be universally applied to increase the efficiency of CRISPR-based gene-drive systems suffering from resistance allele generation. In other embodiments, the double tap gene drive method also improves the ability of the drive to spread in a population.
Other systems, methods, features, and advantages of the present disclosure will be or become apparent to one with skill in the art upon examination of the following drawings and detailed description. It is intended that all such additional systems, methods, features, and advantages be included within this description, be within the scope of the present disclosure, and be protected by the accompanying claims. In addition, all optional and preferred features and modifications of the described embodiments are usable in all aspects of the disclosure taught herein. Furthermore, the individual features of the dependent claims, as well as all optional and preferred features and modifications of the described embodiments are combinable and interchangeable with one another.
Additional aspects and advantages of the present disclosure will become readily apparent to those skilled in this art from the following detailed description, wherein only illustrative embodiments of the present disclosure are shown and described. As will be realized, the present disclosure is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the disclosure. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.
All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. To the extent publications and patents or patent applications incorporated by reference contradict the disclosure contained in the specification, the specification is intended to supersede and/or take precedence over any such contradictory material.
Many aspects of the present disclosure can be better understood with reference to the drawings. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Moreover, in the drawings, like reference numerals designate corresponding parts throughout the several views. A better understanding of the features and advantages of the invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings (also “Figure” and “FIG.” herein), of which:
Many modifications and other embodiments disclosed herein will come to mind to one skilled in the art to which the disclosed compositions and methods pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the disclosures are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. The skilled artisan will recognize many variants and adaptations of the aspects described herein. These variants and adaptations are intended to be included in the teachings of this disclosure and to be encompassed by the claims herein.
Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure.
Any recited method can be carried out in the order of events recited or in any other order that is logically possible. That is, unless otherwise expressly stated, it is in no way intended that any method or aspect set forth herein be construed as requiring that its steps be performed in a specific order. Accordingly, where a method claim does not specifically state in the claims or descriptions that the steps are to be limited to a specific order, it is no way intended that an order be inferred, in any respect. This holds for any possible non-express basis for interpretation, including matters of logic with respect to arrangement of steps or operational flow, plain meaning derived from grammatical organization or punctuation, or the number or type of aspects described in the specification.
All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided herein can be different from the actual publication dates, which can require independent confirmation.
While aspects of the present disclosure can be described and claimed in a particular statutory class, such as the system statutory class, this is for convenience only and one of skill in the art will understand that each aspect of the present disclosure can be described and claimed in any statutory class.
It is also to be understood that the terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the disclosed compositions and methods belong. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and relevant art and should not be interpreted in an idealized or overly formal sense unless expressly defined herein.
Prior to describing the various aspects of the present disclosure, the following definitions are provided and should be used unless otherwise indicated. Additional terms may be defined elsewhere in the present disclosure.
As used herein, “comprising” is to be interpreted as specifying the presence of the stated features, integers, steps, or components as referred to, but does not preclude the presence or addition of one or more features, integers, steps, or components, or groups thereof. Moreover, each of the terms “by”, “comprising,” “comprises”, “comprised of,” “including,” “includes,” “included,” “involving,” “involves,” “involved,” and “such as” are used in their open, non-limiting sense and may be used interchangeably. Further, the term “comprising” is intended to include examples and aspects encompassed by the terms “consisting essentially of” and “consisting of.” Similarly, the term “consisting essentially of” is intended to include examples encompassed by the term “consisting of.
As used in the specification and the appended claims, the singular forms “a,” “an” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a catalyst,” “a metal,” or “a substrate,” includes, but are not limited to, mixtures or combinations of two or more such catalysts, metals, or substrates, and the like.
It should be noted that ratios, concentrations, amounts, and other numerical data can be expressed herein in a range format. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. It is also understood that there are a number of values disclosed herein, and that each value is also herein disclosed as “about” that particular value in addition to the value itself. For example, if the value “10” is disclosed, then “about 10” is also disclosed. Ranges can be expressed herein as from “about” one particular value, and/or to “about” another particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms a further aspect. For example, if the value “about 10” is disclosed, then “10” is also disclosed.
When a range is expressed, a further aspect includes from the one particular value and/or to the other particular value. For example, where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure, e.g. the phrase “x to y” includes the range from ‘x’ to ‘y’ as well as the range greater than ‘x’ and less than ‘y’. The range can also be expressed as an upper limit, e.g. ‘about x, y, z, or less’ and should be interpreted to include the specific ranges of ‘about x’, ‘about y’, and ‘about z’ as well as the ranges of ‘less than x’, less than y’, and ‘less than z’. Likewise, the phrase ‘about x, y, z, or greater’ should be interpreted to include the specific ranges of ‘about x’, ‘about y’, and ‘about z’ as well as the ranges of ‘greater than x’, greater than y’, and ‘greater than z’. In addition, the phrase “about ‘x’ to ‘y’”, where ‘x’ and ‘y’ are numerical values, includes “about ‘x’ to about ‘y’”.
It is to be understood that such a range format is used for convenience and brevity, and thus, should be interpreted in a flexible manner to include not only the numerical values explicitly recited as the limits of the range, but also to include all the individual numerical values or sub-ranges encompassed within that range as if each numerical value and sub-range is explicitly recited. To illustrate, a numerical range of “about 0.1% to 5%” should be interpreted to include not only the explicitly recited values of about 0.1% to about 5%, but also include individual values (e.g., about 1%, about 2%, about 3%, and about 4%) and the sub-ranges (e.g., about 0.5% to about 1.1%; about 5% to about 2.4%; about 0.5% to about 3.2%, and about 0.5% to about 4.4%, and other possible sub-ranges) within the indicated range.
As used herein, the terms “about,” “approximate,” “at or about,” and “substantially” mean that the amount or value in question can be the exact value or a value that provides equivalent results or effects as recited in the claims or taught herein. That is, it is understood that amounts, sizes, formulations, parameters, and other quantities and characteristics are not and need not be exact, but may be approximate and/or larger or smaller, as desired, reflecting tolerances, conversion factors, rounding off, measurement error and the like, and other factors known to those of skill in the art such that equivalent results or effects are obtained. In some circumstances, the value that provides equivalent results or effects cannot be reasonably determined. In such cases, it is generally understood, as used herein, that “about” and “at or about” mean the nominal value indicated ±10% variation unless otherwise indicated or inferred. In general, an amount, size, formulation, parameter or other quantity or characteristic is “about,” “approximate,” or “at or about” whether or not expressly stated to be such. It is understood that where “about,” “approximate,” or “at or about” is used before a quantitative value, the parameter also includes the specific quantitative value itself, unless specifically stated otherwise.
As used herein, the terms “optional” or “optionally” means that the subsequently described event or circumstance can or cannot occur, and that the description includes instances where said event or circumstance occurs and instances where it does not.
Unless otherwise expressly stated, it is in no way intended that any method set forth herein be construed as requiring that its steps be performed in a specific order. Accordingly, where a method claim does not actually recite an order to be followed by its steps or it is not otherwise specifically stated in the claims or descriptions that the steps are to be limited to a specific order, it is no way intended that an order be inferred, in any respect. This holds for any possible non-express basis for interpretation, including: matters of logic with respect to arrangement of steps or operational flow; plain meaning derived from grammatical organization or punctuation; and the number or type of embodiments described in the specification.
Unless otherwise specified, temperatures referred to herein are based on atmospheric pressure (i.e., one atmosphere).
In certain embodiments, the present disclosure provides a general strategy (the “double tap” method) to improve HDR-mediated precision genome editing efficiencies that takes advantage of the reproducible nature of indel sequences. The method simply involves the use of multiple gRNAs: a primary gRNA that targets the wild-type genomic sequence, and one or more secondary or tertiary or multiple secondary or tertiary gRNAs that target the most common indel sequence(s), which in effect provides a “second chance” at HDR-mediated editing. The studies described herein, particularly in EXAMPLE 1 below presents the double tap method as a simple yet effective option for enhancing precision editing in mammalian cells.
Homing CRISPR gene drives could aid in curbing the spread of vector-borne diseases and controlling crop pest and invasive species populations due to an inheritance rate that surpasses Mendelian laws. However, this technology suffers from resistance alleles formed when the drive-induced DNA break is repaired by error-prone pathways, which creates mutations that disrupt the gRNA recognition sequence and prevent further gene-drive propagation. To counteract this, the present disclosure, particularly in EXAMPLE 2, provides that the double tap method disclosed herein improves drive efficiency by encoding additional gRNAs into the gene drive that target the most commonly generated resistance alleles, allowing a second or third or subsequent opportunity at gene-drive conversion and recycling resistance alleles. The double tap drive also efficiently spreads in caged populations, outperforming the control drive. Overall, the double tap method disclosed herein can be readily implemented in any CRISPR-based gene drive to improve performance, and similar approaches could benefit other systems suffering from low HDR frequencies, such as mammalian cells or mouse germline transformations.
Now having described the aspects of the present disclosure, in general, the following Examples describe some additional aspects of the present disclosure. While aspects of the present disclosure are described in connection with the following examples and the corresponding text and figures, there is no intent to limit aspects of the present disclosure to this description. On the contrary, the intent is to cover all alternatives, modifications, and equivalents included within the spirit and scope of the present disclosure.
The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how the compounds, compositions, articles, devices and/or methods claimed herein are made and evaluated and are intended to be purely exemplary of the disclosure and are not intended to limit the scope of what the inventors regard as their disclosure. Efforts have been made to ensure accuracy with respect to numbers (e.g., amounts, temperature, etc.), but some errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, temperature is in ° C. or is at ambient temperature, and pressure is at or near atmospheric.
Targeting Double-Strand Break Indel Byproducts with Secondary Guide RNAs Improves Cas9 HDR-Mediated Genome Editing Efficiencies
Clustered regularly interspaced short palindromic repeat (CRISPR) systems have revolutionized the genome editing field over the past decade. The most widely used type II CRISPR system consists of two main elements: an engineered chimeric single guide RNA (gRNA) and the DNA endonuclease protein Cas9 (CRISPR-associated protein 9)1. The gRNA is easily programmed as it facilitates Cas9 to bind to a target site of interest via sequence complementarity with the target DNA sequence (called the protospacer), which must be directly next to a protospacer adjacent motif (PAM). In the Streptococcus pyogenes (Sp) system (used in this work), the protospacer is 20 bases long, and the PAM sequence is NGG (
The DSB can be repaired via two main pathways: either re-ligation of the broken ends by end-joining pathways, or templated repair via homology-directed repair (HDR). Re-ligation is mainly mediated by non-homologous end joining (NHEJ) or microhomology-mediated end joining (MMEJ), which result in insertion and deletion (indel) sequences at the site of the DSB under genome editing conditions. In contrast, HDR uses a sister chromatid as a template to repair the DSB in a precise manner2. The endogenous HDR pathway can be manipulated to precisely insert DNA sequences by providing the cell with an artificial donor template harboring modifications of interest. Under typical genome editing conditions, both pathways are active and compete to process the DSB intermediate, resulting in mixtures of precision HDR-mediated products as well as end-joining-mediated indel products.
Since the initial demonstration of HDR-mediated genome editing using Cas9 in human cells3-6, there have been numerous studies that have improved the ratio of HDR-mediated to end-joining-mediated genome editing products.7, 8 Specifically, a variety of strategies involving donor template modifications have improved HDR-mediated editing efficiencies, including: (1) phosphorothioate end modification of the template, potentially due to the longer residence time within the cells of the template when modified9; (2) optimization of homology arm length of the donor template when using a single-stranded oligodeoxynucleotide (ssODN) template, both with symmetric10 and asymmetric homology arms11; (3) fusion of the ssODN donor template to the Cas9 protein, potentially due to enhanced nuclear import of the donor template when covalently attached to Cas912, 13; and (4) installation of silent mutations in the PAM or PAM-proximal regions of the protospacer, which prevents the Cas9:gRNA complex from binding and re-cutting the genomic DNA following a successful HDR event14. Additionally, as HDR is primarily limited to the synthesis (S) and gap 2 (G2) phases of the cell cycle, methods to manipulate cell cycle phases have been shown to impact HDR outcomes15,16. In addition, small molecules have been used to inhibit end-joining pathways (by targeting key end-joining repair proteins such as DNA Ligase IV17, DNA-PKcs18, and 53BP119) to increase relative HDR to end-joining ratios as well. Finally, fusion of Cas9 to different DNA repair proteins, such as CtIP20 and Rad5121, have also been shown to enhance HDR-mediated editing efficiencies.
Motivated by this need to enhance the efficiency of precision genome editing outcomes, other CRISPR-based genome editing technologies have emerged recently, such as base editing22,23 and prime editing24. Although these technologies enable genome editing with greatly enhanced precision, they have certain restrictions and limitations that are not an issue with traditional HDR-based methods. For example, base editors can only install transition mutations and have strict protospacer design requirements that prevent certain bases from being viable base editor targets. Furthermore, if multiple target bases are present within the “base editing window” for a given protospacer, they may all become edited at once, reducing the precision of base editing (referred to as bystander editing). Although prime editing can overcome these issues, editing efficiency is often low without use of additional “nicking gRNAs,” which has the undesired side effect of increasing indel formation at the target site. Additionally, the sheer possible number of prime editing gRNA (pegRNA)-nicking gRNA combinations for a given modification of interest makes finding the optimal construct cumbersome. Finally, neither base editing nor prime editing can facilitate the insertion of large DNA sequences such as gene knock-ins25-27, and certain specialized applications, such as gene drive technologies28, explicitly require HDR and therefore cannot be performed with base editing or prime editing.
It has recently been acknowledged that indel sequences arising from a given DSB are generally reproducible and depend on the sequence surrounding the DSB. Sites with low microhomology (<4-nt of homology) are thought to be mainly processed by NHEJ, which often generates one base pair insertions29,30. In contrast, sites with high microhomology (5- to 25-nt of microhomology) are efficiently processed by MMEJ, which results in well-defined deletions of the bases between the microhomology sites. Inspired by these observations, researchers have developed algorithms to predict indel products. One such software, “Microhomology-Predictor,” can predict MMEJ deletion outcomes, and was developed to help researchers identify optimal cut sites that avoid MMEJ-mediated deletions that do not result in frame-shift mutations31. Another, inDelphi, was generated using machine learning based off a dataset of 2,000 gRNA-DNA target site pairs and corresponding indel sequences and can predict indel sequence outcomes (including both NHEJ-mediated insertions and deletions, as well as MMEJ-mediated deletions) in different cell lines32. In addition, inDelphi can predict the distribution frequency of indel products. While for many sites, indel products are heterogenous, it is estimated that 5-11% of gRNAs produce a single repair outcome that represents more than 50% of repair products, and 27-47% of gRNAs produce a single repair outcome that represents more than 30% of repair products. Therefore, it is needed to develop a method that takes advantage of the reproducible and predictable nature of these high frequency indel sequences to improve HDR-mediated genome editing.
JDS246 (NGG-WT-Cas9, Addgene plasmid #43861), pCMV_ABEmax_P2A_GFP (Addgene plasmid #112101), pCMV-PE2 (Addgene plasmid #132775), pFYF1320 (gRNA expression plasmid, Addgene plasmid #47511), pX330 (Addgene plasmid #42230), pCas9-HE (Addgene plasmid #109400), and the donor plasmid for the ACTB knock-in experiments (AICSDP-15:ACTB-mEGFP, Addgene plasmid #87425) were obtained from Addgene. pCMV_ABEmax_P2A_GFP was used as a template to create Cas9-P2A-GFP and Cas9-NG-P2A-GFP constructs using USER cloning, following New England Biolabs (NEB) protocols52.
Two Bsmbl (a type IIS restriction enzyme) recognition sites were installed into the spacer region of the pFYF1320 plasmid using USER cloning, following NEB protocols, to produce the gRNA destination vector pU6-sgRNA-Bsmbl. Custom guide RNA plasmids for each target site were then generated from pU6-sgRNA-Bsmbl using Golden Gate assembly protocols as described by NEB. Briefly, pU6-sgRNA-Bsmbl was digested with BsMBI-v2 (NEB #0739) overnight following the manufacturer's instructions. The digested backbone was gel purified using a QIAquick Gel Extraction kit (#QIAGEN 28704), and inserts encoding custom spacer sequences were annealed and ligated into the backbone with T4 DNA ligase (NEB #M0202) following the manufacturer's instructions. As GFP tagging of LMNA was previously done in our lab, those plasmids were cloned into a different backbone. The LMNA primary gRNA was cloned into the pX330 backbone (which has Bbsl recognition sites), creating pU6_LMNA_SpCas9. Briefly, the pX330 backbone was digested with Bbsl (NEB #R3539S) following the manufacturer's instructions, gel extracted, and the annealed inserts encoding custom spacer sequences were ligated into the digested, purified backbone with T4 DNA ligase. pLMNA_HA_donor_GFP plasmid was cloned in multiple steps: first the LMNA homology arms were amplified from genomic DNA using primers, then the PCR product was TOPO cloned into the pCR2.1 TOPO backbone (ThermoFisher #K450002) to make a pLMNA_reservoir plasmid following the manufacturer's instructions. The entirety of the pLMNA_reservoir plasmid was then amplified by PCR using primers, which created a linearized DNA product. The linearized product was assembled with TurboGFP (synthesized gene block) using Gibson assembly following the NEB protocol #E2611.
Prime editing gRNAs were generated in two steps. First the spacer sequence was incorporated into the pU6-sgRNA-Bsmbl plasmid as previously described to generate a stepping-stone plasmid, followed by incorporation of the reverse transcriptase template (RTT) and primer binding sequence (PBS) sequences using site directed mutagenesis. Site directed mutagenesis primers designed to install the RTT and PBS sequences were obtained from integrated DNA technologies, and 5′ phosphorylated using T4 Polynucleotide Kinase (NEB #M0201) following the manufacturer's instructions. PCR was then performed with Phusion High-Fidelity DNA Polymerase (NEB #M0530) with the phosphorylated primers and the stepping-stone plasmid as a template. PCR products were purified using the QIAquick PCR purification kit (QIAGEN #28104) following the manufacturer's instructions. PCR products were ligated using Quick Ligase (NEB #M2200), and ligation products were transformed into NEB 10-beta (NEB #C3019H) cells following the manufacturer's instructions. Endotoxin-free plasmids were prepared using either the Zymo mini (Zymo #D4037) or midiprep (Zymo #11-550B) kit following the manufacturer's instructions. Plasmids generated using USER cloning were fully sequenced with Sanger sequencing, while gRNA plasmids generated using Golden Gate cloning were sequenced around the insert to confirm correct ligation. Protospacer sequences for all gRNA plasmids are available. The selected primary gRNAs were either previously used in prior publications22, 24, 25, 27, 32 or designed to have cut sites within 15 bp of the intended mutation and to be “high precision” protospacers by inDelphi (i.e. those predicted to produce outcomes in which the top three indel sequences would represent >40% of products).
All cells were cultured at 37° C. with 5% CO2 in a humidified environment. HEK293T (ATCC CRL-3216), HeLa (ATCC CCL-2), and K562 (ATCC CCL-243) cells were obtained from ATCC. HEK293T and HeLa cells were maintained in Dulbecco's Modified Eagle's Medium (DMEM, Gibco #10566-016) supplemented with 10% (V/V) fetal bovine serum (FBS, Gibco #10437-028), while K562 cells were maintained in Roswell Park Memorial Institute 1640 (RPMI 1640, Gibco #11875-093) media supplemented with 10% (V/V) FBS. HEK293T and HeLa cells were plated at a density of 100,000 cells per well in 48-well plates in a total volume of 250 μL per well and transfected four hours after plating using 1.5 μl Lipofectamine 2000 (Invitrogen #11668-019) and a custom DNA mixture (described below) in 25 μL total volume, made up with Opti-MEM (Gibco #31985-070). For PE2 experiments, 750 ng of PE2 plasmid and 250 ng of pegRNA plasmid were used per transfection. For PE3 experiments, 750 ng of PE2 plasmid, 250 ng of pegRNA plasmid, and 83 ng of nicking gRNA plasmid were used per transfection. For ssODN double tap experiments, 750 ng of Cas9-P2A-GFP plasmid (except for experiments involving the SEC61B, HEXA, and HBB loci, in which case Cas9-NG-P2A-GFP was used) or 750 ng of Cas9-HE plasmid, 300 ng of gRNA plasmid, and 10 nM final concentration of ssODN were used per transfection. The gRNA plasmid mixture was comprised of 200 ng of primary gRNA and 100 ng of non-targeting gRNA or secondary gRNA(s), except for non-targeting negative control samples, in which case 300 ng of non-targeting gRNA was used. For the LMNA knock-in experiment, Cas9 and primary gRNA were expressed from the same plasmid (pU6_LMNA_SpCas9). In this case, 1,000 ng of pU6_LMNA_SpCas9, 100 ng of non-targeting or secondary gRNA plasmid, and 300 ng dsDNA donor plasmid (pLMNA_HA_donor_GFP) was used. For the ACTB knock-in experiment, 750 ng of JDS246 plasmid (Cas9 expression without GFP), 300 ng of gRNA plasmid, and 300 ng of dsDNA donor plasmid was used. The gRNA plasmid mixture was comprised of 200 ng primary gRNA and 100 ng non-targeting or secondary gRNA. For off-target analysis experiments, 750 ng of Cas9-P2A-GFP plasmid and 200 ng of gRNA plasmid (either non-targeting gRNA, primary gRNA, or secondary gRNA only) was used. K562 cells were plated at a density of 1×106 cells per well in 6-well plates in a total volume of 2.5 mL per well and transfected four hours after plating using 15 μl Lipofectamine 2000 (Invitrogen #11668-019) and a custom DNA mixture (described below) in 250 μL total volume, made up with Opti-MEM (Gibco #31985-070). For these experiments, 3750 ng Cas9-P2A-GFP plasmid, 1500 ng gRNA plasmid, and 10 nM final concentration of ssODN were used per transfection. The gRNA plasmid mixture was comprised of 1,000 ng primary gRNA and 500 ng non-targeting or secondary gRNA. When the small molecule Alt-R™ HDR Enhancer V2 (Integrated DNA Technologies IDT #10007910) was tested, 0.435 μl of the Alt-R enhancer was diluted in Opti-MEM (Gibco #31985-070) to 25 μl and added immediately after the transfection. The same volume of DMSO was diluted in Opti-MEM (Gibco #31985-070) and added to a separate well as a control. The media was replaced 24 hours after transfection to reduce cytotoxicity.
For the RNP transfections, Cas9 (TrueCut v2, #A36497) and custom TrueGuide synthetic sgRNAs (with the same spacer sequences that were used with the plasmid-based delivery samples) were purchased from Thermo Fisher. Transfection was performed into HEK293T cells plated in 48 well as described above. First 750 ng TrueCut Cas9 was complexed with 4.5 pmoles TrueGuide gRNA. The gRNA mixture was comprised of 3 pmoles of primary gRNA and 1.5 pmoles of non-targeting gRNA or secondary gRNA(s). After RNP complex generation, ssODNs were added as described above (10 nM final concentration) and transfected with 1.5 μl Lipofectamine 2000 (Invitrogen #11668-019) with Opti-MEM (Gibco #31985-070) as described above. Samples from the ssODN experiments were harvested three days after transfection and processed for NGS analysis while GFP knock-in experiments were continuously passaged for fourteen days followed by flow cytometry analysis.
HEK293T cells were analyzed via flow cytometry to assess GFP knock-in efficiency fourteen days after transfection. Cells were washed with 250 μL phosphate buffered saline (PBS, Gibco #10010-023) in the plate and then detached from the plate with Accumax (Innovative-Cell Technology #AM-105) according to the manufacturer's instructions. After harvesting, cells were resuspended in 500 μL PBS. Samples were filtered into FACS tubes (Falcon, #352235) and kept on ice until analysis. A S3e cell sorter (Bio-Rad) equipped with 488 nm, 561 nm and 640 nm lasers was used for all analysis. The instrument was calibrated and quality control checked before each flow cytometry or FACS experiment. GFP positive samples were quantified using the 525/30 nm channel. Single color (pool of the transfected samples for each group) and no color (untransfected cells) control cell populations were used to set up gating. Single color (GFP positive cells for knock-in) had higher intensity than the untransfected cells for the corresponding channels (GFP channel for knock-in). The GFP population was selected based on untransfected cells. Gates were set up or checked with the untransfected and single color controls for each flow cytometry or FACS experiment. Example of the gates are shown in
Isogenic cells for the zygosity experiment were generated using FACS. Cells were prepared for sorting as described above. Samples were gated against untransfected samples as described above. Single GFP positive cells (cells expressing Cas9) were sorted into 96 well plates 48 hours post transfection using a BD Ariall cell sorter. Prior to sorting, wells were filled with 200 μL of 30% (V/V) FBS DMEM media and incubated at 37° C. After sorting, plates were kept in the incubator for 3 weeks for clonal expansion, then harvested for NGS analysis.
All HeLa and K562 cell experiments required FACS (using GFP fluorescence) before NGS analysis. HeLa cells were prepared the same as the HEK293T cells described above. For K562 cells, cells were spun down at 300 g for 5 minutes, the supernatant was decanted, and cells were washed with another 500 μL PBS. Following the second wash, the cell pellets were resuspended in 500 μL PBS and kept on ice until sorting. The 525/30 nm channel was used to identify cells with GFP fluorescence, and untransfected cells were used as negative controls to set up gating. Doublets were gated out using forward and side scattering width against area, and 40,000 GFP positive cells were collected using purity mode. K562 cells were collected into RPMI 1640 supplemented with 20% (V/V) FBS, and HeLa cells were collected into DMEM supplemented with 20% (V/V) FBS. Both cell lines were then spun down, washed with 500 μL PBS, and then prepped for NGS.
After 72 hours of editing, cells were washed with PBS either on the plate (HEK239T cells) or after FACS (HeLa and K562 cells), followed by proteinase K digestion (in a buffer made up of 10 mM Tris, pH 7.5; 0.05% SDS, and 25 μg/mL freshly added proteinase K) at 37° C. for 1 hour, followed by an 80° C. heat treatment for 30 minutes. HEK293T cells were digested in 100 μL total volume of buffer while the sorted HeLa and K562 cells were digested in 50 μL total volume of buffer. After the lysis, genomic loci of interest were PCR amplified using locus-specific primers. These primers were designed to contain an adapter sequence, allowing for sample barcoding with a second round of PCR. PCR reactions were performed using Phusion High-Fidelity DNA Polymerase following the manufacturer's instructions with the following modifications: all PCR reactions were performed using GC buffer, 3% DMSO was utilized, and 25% of the recommended primer amount was used to reduce the amount of primer dimers. 25 cycles of amplification were used for round one PCRs, while 15 cycles of amplification were used for round two PCRs. An annealing temperature of 61° C., and an extension time of 45 seconds was used for both rounds. 0.5 μL of genomic DNA was used a template for round one PCRs, and 0.5 μL of round one PCR product was used as a template for round two PCRs at 10 μL total reaction volume. Second round PCR products were pooled together based on the amplicon size and purified from a 2% agarose gel using the QIAGEN gel extraction kit (QIAGEN #28704) following the manufacturer's instructions. The resulting purified libraries were quantified with the Qubit dsDNA high sensitivity kit (Thermo Fisher #Q32851) and diluted to 1.8 pM following Illumina's sample preparation guidelines. The final library was mixed with 1.8 pM PhiX in a nine to one ratio. Samples were then sequenced on a MiniSeq (Illumina) via paired end sequencing.
NGS samples were processed in CRISPResso253 (version 2.0.20b) using the default and HDR outputs. Values from the CRISPResso2 were further processed in R Studio (version 1.4.1717) and plotted with the “ggplot2” 54 package. Univariate statistics were performed in R Studio using the “ggpubr” package. FACS data was analyzed with FlowJo (version 10.7.2) to assess knock-in efficiencies. InDelphi32 (version 0.18.1) was used to predict insertions and deletions at the Cas9 cut site. Indel frequency values and errors were calculated as follows: values represent the mean of the number of sequencing reads with the indel sequence of interest (or any indel, when calculating total indel rates) divided by the total number of sequencing reads ±standard deviation (SD) for n=3 biological replicates. For biological replicates, cells were plated into three different wells on the same day. Transfection reagents were prepared in three different tubes and transfected into independent replicates. Day to day transfection variability (from different splits of the same HEK293T cells) is demonstrated in
Fold-change values and errors were calculated as follows: values represent the mean of the number of sequencing reads with perfect HDR outcomes divided by the total number of sequencing reads for double tap samples divided by that of the samples with primary and non-targeting gRNA±propagation of uncertainty of the SD for n=3 biological replicates.
Percent decrease values and errors were calculated as follows: The mean total indel rates were first calculated for the sample with primary and non-targeting gRNA and for the sample with primary and secondary gRNA(s) (as described above). Then the difference of these two values were calculated and then divided by the mean total indel rate of the primary and non-targeting gRNA sample, multiplied by 100±propagation of uncertainty of the SD for n=3 biological replicates.
The high-throughput sequencing data generated in this study have been deposited in the NCBI Sequencing Read Archive database under Accession Number PRJNA819982.
Four well-characterized genomic loci were first selected to test that targeting reproducible indel sequences with secondary gRNAs could boost HDR-mediated genome editing efficiencies. Specifically, previously validated protospacers that target loci within the APOB, MMACHC, RNF2, and FANCF genes (hereafter referred to as the APOB1, MMACHC, RNF2, and FANCF loci or sites, respectively)22,32 were chosen. To characterize the most common indel sequences introduced using these primary gRNAs, human embryonic kidney (HEK293T) cells were transfected with plasmids encoding Cas9 and primary gRNA. After 72 hours, cells were lysed, genomic DNA (gDNA) was extracted, and loci of interest were amplified, sequenced using next-generation sequencing (NGS), and analyzed with CRISPResso2 to identify recurrent indels. The experimentally determined and predicted indel sequences (using inDelphi) are shown in
ssODN templates to install either a point mutation (for the RNF2 and MMACHC sites) or a small insertion (for the FANCFand APOB1 sites) were then designed so that editing efficiencies could be monitored. Unless explicitly noted otherwise, all the ssODNs were designed symmetrically, with 50 or 70-nt homology arms. HEK293T cells with ssODN and plasmids encoding Cas9, primary gRNA, and either non-targeting gRNA (to keep the total amount of gRNA plasmid constant when comparing to the double tap experiments) or secondary gRNA(s) were transfected. After 72 hours, cells were lysed and analyzed via NGS and CRISPResso2 to determine HDR and indel introduction efficiencies. Increases in absolute HDR-mediated genome editing efficiencies were observed in all cases, with the relative size of the increase roughly correlated to the initial rates of the indel sequences that were targeted with the secondary gRNAs (expand dataset and further analysis of this relationship are shown in
For further characterization and validation, the double tap method was tested at seven additional protospacers (within the LOC1 10120638, LINC01509, HIRA, PSMB2, PCSK9, APOB, and SEC61B genes, hereinafter referred to as the HEK2, HEK3, HIRA, PSMB, PCSK, APOB2, and SEC61Bloci or sites, respectively), using HDR to install point mutations, small deletions, and small insertions. Again, the double tap method increased HDR-mediated genome editing efficiencies at all tested sites, with larger fold-change values when using secondary gRNAs targeted to indel sequences with larger initial rates (
Furthermore, decreases in the total absolute indel rates were also observed when using the double tap method in ten out of eleven cases (
C. Additive Effects Combining Double Tap with Other Methods to Improve Precision Editing Outcomes
The use of blocking mutations at the PAM or the PAM-proximal region of the protospacer has been shown to improve HDR-mediated genome editing yields14, and combine this method with the double tap method may improve HDR efficiencies even further. Therefore, the double tap method was tested at the FANCF, APOB1, and MMACHC sites (which were previously tested without blocking mutations,
To further investigate potential synergistic effects of the double tap method with existing methods to improve HDR:NHEJ ratios, the double tap method was compared and combined with a small molecule inhibitor of NHEJ and a Cas9-CtIP fusion construct. Specifically, IDT's “Alt-R™ HDR Enhancer V2” (which hereinafter referred to as Alt-R) and the Cas9-HE fusion protein (wherein Cas9 is tethered to the HDR enhancer domain of the CtIP protein) were used and tested at the MMACHC site using primary gRNA with additional non-targeting or secondary gRNA to compare them to and evaluate their additive effects with the double tap method. Both the Alt-R molecule and the Cas9-HE increased HDR rates relative to the wild-type Cas9 (wtCas9) with primary and non-targeting gRNA sample with no additives or dimethyl sulfoxide (DMSO) added (the Alt-R molecule is dissolved in a DMSO solution,
The Cas9:gRNA complex is often delivered into cells as a ribonucleoprotein (RNP) complex due to lower toxicity, decreased off-target editing efficiencies, and enhanced on-target editing efficiencies. To assess if RNP delivery is compatible with the double tap method, HEK293T cells were transfected with purified Cas9 RNP complexes targeting the HEK3, RNF2, or MMACHC sites (using the same primary gRNA and non-targeting or secondary gRNA(s) as used previously) and the same ssODNs as used previously. Similar results were observed when utilizing RNP delivery as those when using plasmid-based delivery; HDR rates increased and rates of indel products decreased (
Isogenic cell lines are useful model systems with which to study the effects of mutations. Generation of such models can often be hampered by “hemizygous-like” clones, in which one allele contains the edit of interest, and the other an indel14. Therefore, the zygosity of cell lines generated using the double tap method were characterized. HEK293T cells were transfected with ssODN, Cas9-p2A-GFP plasmid, and gRNA plasmids (primary gRNA with non-targeting or secondary gRNA plasmid) to target the MMACHC locus. After 72 hours, individual GFP-positive cells were sorted into separate wells of a well-plate using fluorescence activated cell sorting (FACS) and clonally expanded. Cells were expanded for 21 days, and 41 colonies per experiment (non-targeting or secondary gRNA) were genotyped via NGS. As the HEK293T cell line is pseudotriploid35,36 (the MMACHC locus resides on chromosome 1, which is triploid), a variety of zygosities were observed and simplified into the categories of homozygous (all copies have the HDR edit, with no indels), heterozygous (mixture of wild-type and HDR edits, with no indels), HDR/indel products (mixture of HDR edits and indels), indel mixtures (all copies have indels), WT/indel (mixture of wild-type and indels), and WT (all copies unedited). The breakdown can be seen in
F. Double Tap Using dsDNA Donor Templates to Perform Gene Knock-In
The installation of small modifications is typically carried out using ssODNs as a donor template. However, the introduction of larger (typically, >100 bps) modifications, such as knocking-in a gene to a targeted locus, is usually carried out using dsDNA donor templates. These two precision genome editing methods have been shown to function via different mechanisms (ssODN-mediated knock-in occurs in a Rad51-independent manner, while dsDNA donor-mediated knock-in occurs in a Rad51-dependent manner7). To determine if the double tap method was compatible with both, the double tap method was used to knock-in the green fluorescent protein (GFP) gene just after the start codon of two different genes (ACTB and LMNA) using dsDNA donor plasmids. Donor template and primary gRNA designs that had been described previously for ACTB25 were used, as well as for LMNA27. To design secondary gRNAs, HEK293T cells were first transfected with plasmids encoding Cas9 and primary gRNA, then the genomic loci of interest was analyzed with NGS after 72 hours to determine the indel product distribution (
The double tap method was also tested in human erythroleukemic (K562) and human cervical cancer (HeLa) cell lines using the APOB1 and MMACHC primary gRNAs and secondary gRNAs that previously validated in HEK293T cells. Cells were transfected with ssODN, Cas9-p2A-GFP plasmid, and gRNA plasmids. After 72 hours, GFP positive cells were enriched using fluorescence activated cell sorting (FACS) and analyzed by NGS (FACS enrichment was used due to the significantly lower transfection efficiencies of these cell lines as compared to HEK293T cells).
At the MMACHC site, the average HDR-mediated genome editing efficiency improved 1.6±0.04-fold in K562 cells and 2.4±0.3-fold in HeLa cells (compared to 1.6±0.1-fold in HEK239T cells,
The ability of the double tap method to install two disease-relevant mutations to demonstrate its utility for generating disease models and to compare its performance with that of prime editing was also tested. The sickle cell-relevant mutation E6V in hemoglobin, which is an A to T transversion mutation in the HBB gene, and the Tay-Sachs disease-relevant TATC 4-bp insertion in the HEXA gene were chosen as pegRNA-nicking gRNA combinations have already been optimized to introduce these mutations with prime editing. Five potential primary gRNAs (referred to as HBB1, HBB2, etc. and HEXA1, HEXA2, etc. primary gRNAs) were designed for each site using inDelphi to aid in identifying “high precision” protospacers (i.e., those predicted to produce outcomes in which the top three indel sequences would represent >40% of products) with cut sites within 15 bp of the intended mutation (
One secondary gRNA was then designed for both HEXA primary gRNAs, one secondary gRNA was designed for the HBB1 primary gRNA, and three secondary gRNAs were designed for the HBB5 primary gRNA (
To further compare the performance of the double tap method to that of prime editing, previously reported pegRNAs and nicking gRNAs to install these mutations24 were used. It is important to mention that these two pegRNA-nicking gRNA combinations were extensively optimized; specifically, to identify the HEXA combination, 43 pegRNAs and three nicking gRNAs were tested (for a total of 129 different combinations tested). In contrast, for the double tap method, only five primary gRNAs were screened per site, and all double tap experiments that were performed displayed improvements in HDR efficiency. HEK293T cells were transfected with plasmids encoding PE2 and pegRNA only (PE2 sample), or pegRNA and nicking gRNA (PE3 sample). After 72 hours, cells were lysed and analyzed via NGS and CRISPResso2 to determine the efficiency of introduction of the intended edit. We found that intended edit introduction efficiencies with PE2 were lower than that with the double tap method (10.8±1.3% at the HBB site, and 7±0.3% at the HEXA site), while those with PE3 were similar at the HEXA site (20.9±2.6%), and higher at the HBB site (30.8±2.1%,
It was recognized that a potential drawback of the double tap method is the possibility of introducing DSBs at additional off-target sites compared to when only a single gRNA is used. Indeed, the introduction of multiple DSBs within a given cell can cause cytotoxicity and chromosomal rearrangements38-41. Therefore, all secondary gRNAs used in this study were first analyzed for potential full matches with other sites in the human genome. It was found only one secondary gRNA (one of the RNF2 secondary gRNAs) that fully matched a location in the human reference genome that is directly next to an NGG PAM sequence (this locus is labeled RNF2_DT_OT1). To quantify editing at this site, HEK293T cells were transfected with plasmids encoding Cas9 and either a non-targeting gRNA, the RNF2 primary gRNA, or the RNF2 secondary gRNA, then cells were lysed after 72 hours, and the primary on-target and the secondary matched loci of all samples were analyzed for indel frequencies using NGS and CRISPResso2. Unsurprisingly, a 30% indel introduction efficiency was observed with the RNF2 secondary gRNA at its fully matched locus (
Additionally, all secondary gRNAs were analyzed for putative off-targets containing a single mismatch using Cas-OFFinder42, as these types of off-targets are the most common43. It was found that only one secondary gRNA (one of the HBB5 secondary gRNAs) had a potential off-target with a single mismatch (this locus is labeled as HBB5_DT_OT1). Two additional sets of primary and secondary gRNAs (those for the APOB1 and MMACHC sites) were then chosen and their predicted off-target sites in silico were identified and analyzed using a combination of Cas-OFFinder (to identify putative off-target sites with up to five mismatches and three bulges)42 and Benchling44 (to assess their predicted off-target scores). The MMACHC primary gRNA had the highest predicted off-target site (labelled as MMACHC_OG_OT1) with only a single mismatch, and a predicted off-target score of 100 (out of a highest possible score of 100). All other putative off-target sites had predicted off-target scores of less than 6 (the closest predicted off-target sites had at least two mismatches). Nevertheless, three predicted off-target sites were selected for each gRNA based off these two analyses for both the primary gRNAs (which were called as the original guide off-target sites, or OG_OT), as well as for the secondary gRNAs (which were called as the double tap guide off-target sites, or DT_OT,
Since as previously stated, multiplexed DSB introduction can cause cytotoxicity, if the use of secondary gRNAs causes significant off-target editing, reduced viability of the cells would be observed. Therefore, to further qualify cell viability, primary and secondary gRNAs for the RNF2 (in which case all three secondary gRNAs, including the one that has a fully matched site in the genome were used), HBB5, APOB1 and MMACHC sites were chosen, as these had been previously evaluated for indel introduction efficiencies at putative off-target sites. HEK293T cells were then transfected with plasmids encoding Cas9-P2A-GFP (to allow for identification of transfected cells using GFP fluorescence) and gRNA (non-targeting gRNA only as a control, primary and secondary gRNA, or primary and non-targeting gRNA) and stained the cells with propidium iodide to monitor cell viability after 72 hours (
Off-target editing remains a key challenge for all genome editing agents, and the use of high-fidelity Cas enzymes has been shown to alleviate off-target editing by CRISPR nucleases46-51. The use of these high-fidelity variants in combination with off-target score prediction software could minimize unwanted off-target editing for the double tap method. However, in silico off-target identification has major limitations, and thus in cases where off-target editing must be completely eliminated, the use of unbiased experimental methods to identify putative off-target edits would be required.
The studies in EXAMPLE 1 of the present disclosure describe the development and characterization of the double tap method to improve HDR-mediated genome editing efficiencies in human cell lines. The double tap method takes advantage of the modularity of the Cas9 system and the reproducibility of indel sequences by using additional secondary gRNAs that target unwanted, high-frequency indel sequences generated during the end-joining repair of DSBs. In this manner, the double tap method provides researchers with a second chance at a successful HDR event when performing precision genome editing at a locus of interest. Importantly, the double tap method does not perturb the cell by modulating gene expression levels or synchronizing the cell cycle phase which may introduction additional artifacts to the system being studied.
In this EXAMPLE 1, the impact of the double tap method was characterized by first quantifying the improvements in HDR-mediated genome editing efficiencies following the use of secondary gRNAs targeted to indel sequences with a wide range of frequencies (ranging from 4.8±0.2% to 49.2±3.7%). A direct correlation was found between the fold-improvement afforded by this method and the collective frequencies of the indels targeted by secondary gRNAs; this correlation allows a user to estimate a fold-change in HDR efficiency for the double tap method following analysis of indel distribution frequencies for a particular gRNA of interest. It is noted that initial HDR efficiencies can vary drastically depending on the primary gRNA used, and thus this value needs to be balanced with the estimated fold-change to identify the ideal conditions to maximize absolute HDR efficiencies. Overall indel rates were found to be decreased when using the double tap method, mostly driven by large decreases in the frequencies of the indels that were targeted by secondary gRNAs. Overall, this led to enhancements in HDR:NHEJ ratios up to 3.8-fold. However, the targeted amplicon sequencing methods may miss larger deletion products that occur outside the sequencing primer binding sites.
The double tap method was found to be compatible with multiple cell lines, RNP delivery, and with both small modifications (using ssODN donors) and large insertions (using dsDNA donors). The design of secondary gRNAs is straight-forward when 1-bp insertions or deletions are targeted, in which case the original PAM can be used, and the resulting secondary gRNA will rarely match the original sequence. However, in certain instances when small deletions (likely facilitated by MMEJ) were targeted, using the original PAM would result in a secondary gRNA that could target the original DNA sequence, but with an unwanted alternate cut site (
Overall, this EXAMPLE 1 describes that the double tap method was tested with 23 different primary protospacer sequences and compared their experimentally determined indel sequence distribution outcomes with their inDelphi predictions (
EXAMPLE 1 further demonstrates that the double tap method can be combined with existing HDR-enhancing methods to further improve precision genome editing efficiencies. Combining the use of secondary gRNAs with additional blocking mutations on the ssODN (to prevent Cas9 from re-cutting the target site after a successful HDR event) was found to produce additive improvements in HDR efficiencies. As neither of these methods disturb the cell cycle or DNA repair protein levels, this represents a simple and robust non-perturbative method for improving precision editing outcomes. Further, it is also demonstrated that the double tap method can be combined with DNA repair pathway alteration methods to achieve higher HDR:NHEJ ratios compared to using any of these strategies in isolation. The double tap method represents a simple yet effective strategy that can be effortlessly implemented into existing HDR-enhancing pipelines to further improve genome editing outcomes.
Moreover, the utility of the double tap method for generating of isogenic cell lines was also demonstrated. Overall success rates of generating homozygous and heterozygous cell lines were improved, as the secondary gRNAs provides a “second chance” to convert indel-containing alleles into the desired edit. This improvement would allow for a decrease in the number of colonies screened during isogenic cell line generation, as well as an increase in the throughput of cell line generation, which is incredibly valuable for laboratories studying the functional effects of genetic variants. This method could be particularly useful for genome editing in organisms with high chromosomal copy numbers such as plants or applications that cannot take advantage of precision editing-enhancing strategies such as base editing, prime editing, and cell cycle/DNA repair manipulation, including gene drive applications. In fact, the double tap method has been applied to improve gene drive efficiencies by recycling resistance alleles.
It was also demonstrated the utility of the double tap method by installing two disease-relevant mutations (an A to T point mutation in the HBB gene that causes sickle cell disease, and a 4-bp insertion in the HEXA gene that causes Tay-Sachs disease). For both mutations, secondary gRNAs were identified to boost HDR efficiencies. The double tap method can therefore be easily integrated into researchers' current HDR experiments by simply analyzing their DNA sequencing data to identify high-frequency indel products. For experiments such as disease modeling (particularly for the generation of isogenic cell lines), absolute HDR rates are often the most important factor, and dictate whether homozygous variants can be obtained. The double tap method was shown to improve HDR yields up to 2.4-fold in the present disclosure, and because fold-changes can be estimated based on the initial indel frequencies, HDR rates can potentially be modulated if heterozygous models are desired. The decrease in indel rates facilitated by the double tap method of the present disclosure is also an important factor and can help to avoid generating cells in which the mutation of interest is present at one allele and an indel is present at the other. Enhancements in absolute HDR efficiencies are invaluable for modeling of polygenic disorders, in which the introduction of multiple mutations is necessary. In these cases, the increase in likelihood of successfully generating the model is proportional to the product of the individual increases in HDR rates for each mutation.
Off-target editing is always a factor to consider with genome editing experiments and the usage of additional gRNAs increases the number of potential off-target edits, and therefore the possibility of translocations, large-scale deletions, and chromothripsis. This scales with the number of gRNAs, thus experiments that require multiple secondary or tertiary gRNAs have an increased probability of suffering from off-target issues. While in silico off-target prediction tools have been developed and can identify certain putative off-target loci for a given gRNA (including secondary gRNAs), for experiments in which off-target editing is unacceptable, each gRNA needs to be individually assessed using unbiased methods. High-fidelity Cas9 variants have also been used to reduce or eliminate off-target editing in DSB-reliant genome editing experiments, and these mutants could also be used successfully with the double tap method. It is imperative to analyze secondary gRNAs to assess if they are a perfect match with other sites in the genome prior to using them. If this is the case, re-designing the secondary gRNA to use a different PAM nearby is recommended if this is possible (
There are now a variety of “next-generation” genome editing tools for researchers to choose from, such as base editors and prime editors, and each editor comes with its own unique pros and cons. When directly compared the double tap method to prime editing to introduce small modifications, it was found that with minimal optimization, the double tap method can be used to approach PE3 efficiencies and surpass PE2 efficiencies. A drawback of prime editing is the requirement of extensive optimization of the length of the primer binding region and the reverse transcription template portions of the peg RNAs to find a combination with satisfactory efficiency for each protospacer option (and there are often multiple protospacer options for a given modification of interest). Additionally, again with minimal optimization, the efficiencies of GFP knock-in with the double tap method were improved up to 90%. Next-generation genome editing technologies such as base editing and prime editing are unable to facilitate such large insertions. Overall, a major benefit of the double tap method disclosed herein is the simplicity of its implementation; a handful of candidate primary gRNAs can be tested and analyzed for initial HDR efficiencies and indel distributions, and fold-changes can then be estimated to identify the optimal primary-secondary gRNA combination to maximize HDR yields. Overall, this significantly reduces the time and resources required for construct optimization as compared to prime editing.
In summary, the double tap method disclosed in EXAMPLE 1 presents researchers with an easily implemented method to increase HDR-mediated genome editing efficiencies using a combination of a primary gRNA that produces high frequency indel products with a secondary gRNA that targets these indel sequences. A major benefit of the double tap method disclosed herein is its ease of integration with any previously developed HDR system; minimal optimization is required. The double tap method disclosed herein can be used for boosting efficient genome editing in agriculture, plants, animals (e.g., fruit fly, mice, rats, etc.), fungi, mammalian cells, animal germlines and embryos, and/or in vivo animal models for human diseases.
The rapid spread of homing CRISPR-based gene drives through populations can help curb the impact of vector-borne diseases worldwide 1-3. For example, mosquitos can be modified with beneficial genes to prevent carried pathogens 4-6 or with detrimental gene alterations to suppress the vector population 7-9. Gene drives also offer promising solutions in crop pest population control 10 and invasive species suppression 11,12, such as for the rodents 13,14 currently impacting island conservation efforts 15. Briefly, CRISPR gene drives operate by biasing their own inheritance from Mendelian (˜50%) toward super-Mendelian (>50%) by converting heterozygous germline cells to homozygosity. Gene-drive constructs encode both a Cas9 endonuclease and a guide RNA (gRNA) that targets the precise location where the gene-drive transgene is integrated in the genome. In a heterozygous individual, resulting from a gene-drive individual mating with a wildtype, the Cas9/gRNA complex cleaves the wildtype allele opposing the gene drive. The endogenous cell machinery repairs this double-stranded DNA break, which copies the drive element from the drive chromosome to the cleaved wildtype one 16,17. When this process occurs in the germline of an individual, the inheritance is strongly biased towards the gene-drive transgene.
To repair the double-stranded DNA break, the germline has a bias towards the efficient and highly accurate homology-directed repair (HDR) repair pathway, which uses the intact strand—in this case, the strand containing the gene-drive—as a template for repair. In some cases, however, alternative, error-prone DNA-repair pathways, such as non-homologous end-joining (NHEJ) and microhomology-mediated end-joining (MMEJ), can instead generate small insertions or deletions (indels) near the gRNA cleavage site, disrupting the gRNA recognition sequence and rendering these indels resistant to further cleavage 4, 18, 19. Since such mutations can no longer be targeted by the drive and are passed on to the progeny, they can effectively counteract the spread of a gene drive through a population and obstruct field applications of these tools 20. Additionally, when a gene drive is inherited from the mother, it has been shown that in both the fruit fly 19 and in Anopheles mosquitoes 4,5, the Cas9/gRNA complexes deposited in the egg can prematurely target the incoming wildtype male allele, before it can reach the proximity of the female chromosome which would be used as a template for HDR. This dynamic leads to the early generation of indels that prevent further gene-drive conversion during later germline development. In extreme instances, the offspring of these animals will carry ˜50% gene drive and ˜50% resistance alleles 19, making this maternal effect a substantial and problematic source of resistance alleles as a gene drive progresses within a population.
Previously, a trans-complementing gene drive (tGD) was built in Drosophila melanogaster (D.mel) that inserts a Cas9 transgene within the coding sequence of the yellow gene and a tandem-gRNA cassette at the white locus 19. The gRNA transgene encodes two gRNAs, one targeting yellow (y1-gRNA) at the location where Cas9 is inserted, and the other targeting white (w2-gRNA) at the gRNA cassette insertion site. When the separate Cas9 and gRNA lines are crossed, the Cas9 protein can complex with the two gRNAs to cleave the wildtype yellow and white alleles, which leads to each of the transgenes being copied onto the opposing chromosome by HDR. While this action leads to super-Mendelian inheritance of both transgenes, it was observed resistance alleles generated by the end-joining alternative repair pathways. In this previous work, these resistance alleles were analyzed by sequencing ˜500 flies containing mutations at either the yellow or white locus, and it was observed that there were specific indels that appeared at a higher frequency than others, consistent with other findings in human cells 21-23.
To circumvent this phenomenon a CRISPR-based homing gene drive was supplemented with additional gRNAs targeting the most common resistance alleles generated by the drive process. This modification should provide a second opportunity for allelic conversion through HDR by allowing the drive element to also cut a subset of the resistance alleles, improving gene-drive inheritance. To do this, the “double-tap” trans-complementing gene drive (DT-tGD) was built, which contains two extra gRNAs, one for yellow and one for white, each targeting one of the most prevalent resistance alleles formed at each locus by our original tGD(y1,w2) 19. The DT-tGD system was tested and its ability to improve drive efficiency at both loci was shown. The data further show that the DT-tGD can specifically target the resistance alleles using the added gRNAs, and that this targeting results in efficient HDR conversion. Further, the data show that the DT-tGD spreads more efficiently in caged populations than the tGD control, supporting its potential use for counteracting resistance alleles in field applications of this technology.
All the studies presented in EXAMPLE 2 followed procedures and protocols approved by the Institutional Biosafety Committee from University of California San Diego, complying with all relevant ethical regulations for animal testing and research. Gene-drive experiments were performed in a high-security Arthropod Containment Level 2 (ACL2) barrier facility.
All plasmids were cloned using standard molecular biology techniques. Plasmids were constructed by Gibson assembly using NEBuilder HiFi DNA Assembly Master Mix (New England BioLabs Cat. #E2621) and transformed into NEB 10-beta electrocompetent E. coli (New England BioLabs Cat. #3020). Plasmid DNA was prepared using a Qiagen Plasmid Midi Kit (Qiagen Cat. #12143) and sequences were confirmed by Sanger sequencing at Genewiz. Primers used for cloning can be found in Table 2 and the validated sequences of all constructs have been deposited in the GenBank database; accession numbers are provided in the Data availability Statement.
Constructs were sent to Rainbow Transgenic Flies, Inc. for injection. All constructs were injected into our lab's isogenized Oregon-R (Or-R) strain to ensure consistent genetic background throughout experiments. Constructs were co-injected with a Cas9-expressing plasmid29 expressing previously validated gRNA-w230. Injected G0 animals were mailed back, then outcrossed to Or-R in small batches (3-5 males×3-5 females) and screened the G1 flies for a fluorescent marker (GFP expressed in the eyes), which was indicative of transgene insertion. homozygous lines from single transformants were generated by crossing to Or-R and the white phenotype was identified in subsequent generations. Stocks were sequenced by PCR and Sanger sequencing to ensure correct transgene insertion.
All flies were kept on standard cornmeal food with a 12/12 hour day/night cycle. Fly stocks were kept at 18° C., and all experimental crosses were conducted at 25° C. To phenotype and cross flies, they were anesthetized using CO2. For all crosses, virgin females were crossed the same day that they eclosed. F0 crosses were made in small batches of 3-5 virgin females crossed to 3-5 males. F1 crosses were made in single pairs, left for 5 days, then the adults were removed. F2 flies were counted as male or female and scored for fluorescent marker (DsRed and/or GFP) using a Leica M165 F2 Stereomicroscope with fluorescence. DsRed or GFP expression was used as indicative of transgene inheritance. All gene drive experiments were performed in a high-security ACL2 (Arthropod Containment Level 2) facility built for gene drive purposes in the Division of Biological Sciences at the University of California, San Diego. Crosses were made in shatter-proof polypropylene vials (Genesee Scientific Cat. #32-120) and all flies and vials were frozen for 48 hours before being removed from the facility, autoclaved, and discarded as biohazardous waste.
To sequence resistance alleles, genomic DNA was extracted from individual males following the protocol described by Gloor and colleagues31: flies were mashed in 50 μl squishing buffer (10 mM Tris-CI pH 8.2, 1 mM EDTA, 25 mM NaCl, and 200 μg/ml freshly diluted Proteinase K), then incubated at 37° C. for 30 min, then 95° C. for 2 min to inactivate the Proteinase K. Each sample was diluted with 200 μL of water, then 1-5 uL was used in a 25 uL PCR reaction spanning the gRNA cut site in either the yellow or white gene. The amplicon was then sequenced by Sanger sequencing to determine the resistance allele present. Primers used for resistance allele sequencing can be found in Table 2.
For the population experiments, bottles were seeded with 100 flies each: 1) 50 yEX1, wEX1 virgin females; 2) 40 yEX1 wEX1 males; and 3) 10 males from a homozygous stock containing the vasa-Cas9-DsRed construct and either the tGD(y1,w2) control or the DT-gRNA(y1,w2, y1b, w2b). Each condition was performed in triplicate. Adult flies were left in the bottles for 5 days before being removed. The remaining eggs and larvae were allowed to develop until day 18 at which point all flies were anesthetized with CO2, removed, and approximately 200 were chosen at random to seed the next generation. The remaining flies were phenotypically scored as male or female and for GFP and/or DsRed expression using a Leica M165 F2 Stereomicroscope with fluorescence, with the fluorescent markers being indicative of transgene inheritance. The bottles were maintained on this schedule for 15 generations. All experiments were done at 25° C. and flies were kept on standard cornmeal food with a 12/12 hour day/night cycle. Experiments were conducted in shatter-proof polypropylene bottles (Genesee Scientific Cat #: 32-129F) within the high-security ACL2 facility, maintaining the same precautions as previous other gene drive experiments.
To perform deep sequencing of the caged populations, 50 GFP−, DsRed− males were isolated from each cage at the generations F4, F8, and F15. For two samples additional GFP−, DsRed+ flies were supplemented (F8, Cage 2: 30 GFP−, DsRed−males and 12 GFP−, DsRed+males; F8, Cage 3: 39 GFP−, DsRed− males and 11 GFP−, DsRed+males). 50 OregonR WT males were used as an indel baseline control. Genomic DNA was extracted from each fly pool following the standard protocol in the DNeasy® Blood and Tissue Kit (Cat. No. 69504). After extraction, each sample was eluted with 300 uL of water, and about ˜500 ng of the extracted DNA was then used in a 25 uL PCR reaction as a template to amplify either the yellow or white targeted region using specific primers for each locus:
1 μL of the resulting PCR reaction was used as a template for the subsequent PCR reaction to attach Illumina barcodes. 3 μL of the barcoding PCR product was then run on a gel, and the amplicon band was first gel extracted using QIAquick® Gel Extraction Kit (Cat. No. 28704) and then further purified using Monarch@ PCR & DNA Cleanup Kit (5 μg) (Cat. No. T1030L). The pooled and purified DNA amplicons were quantified with the Qubit dsDNA high sensitivity kit (Thermo Fisher). Equal amounts of amplicon from each sample were pooled together and prepared based on the Illumina sequencing protocol. 1.8 pM of the pooled libraries were mixed with 1.8 pM PhiX with nine to one ratio and loaded on an Illumnina MiniSeq instrument using a mid output kit of 300 cycles. Data was analyzed using CRISPResso232 to determine the frequency of resistance alleles across different generations.
Using as a reference the data obtained from the OregonR wild type males to consider any indel occurrence with less than 100 occurrences as background and removed these sequences from downstream analysis. The frequency observed for the different alleles (wild-type, y1b or w2b, and other indels) was then used to estimate the number of flies present in the sampled pool. The easimate was done by first dividing the frequency of a specific allele by the sum of all the frequencies of the alleles above background (i.e. true alleles), then multiplying this number by the number of male flies that contributed an allele to the pool, and then rounding this number to the closest integer. The resulting estimates (i.e. number of flies contributing an allele to the pool) was used to generate the graphs in
GraphPad Prism 9 and Adobe Illustrator were used to generate all the graphs. Statistical analyses were done using GraphPad Prism 9 and the StatKey analysis tool, version 2.1.1. For
The plasmid sequences of the constructs generated are either deposited into the GenBank database. GenBank accession numbers for the deposited plasmids are the following: pVG182 vasa-Cas9 (MN551085)33, pVG185 tGD(y1,w2) (MN551090)19, pVMG127 DT-tGD(y1,w2, y1b) (OL630771), pVMG128 DT-tGD(y1,w2,w2b) (OL630772), pVMG129 DT-tGD(y1,w2, y1 b, w2b) (OL630773), pVMG130 C-tGD(w2, y1 b) (OL630774), pVMG131 C-tGD(y1,w2b) (OL630775), pVMG138 C-tGD(y1, y1 b) (OL630776). All raw and source data and information are available upon request.
To evaluate whether an additional gRNA would improve inheritance by recycling indels generated by the primary gRNA, double-tap versions (DT-tGD) of the previously-tested tGD targeting the genes yellow and white 19 was designed. Compared to tGD, this new arrangement includes two additional gRNAs within the construct inserted in the white gene (
To test the DT-tGD system, three gRNA-constructs were made to compare to the tGD(y1,w2) control (
To test these three double-tap constructs, genetic crosses were performed to combine the two tGD components by mating Cas9-expressing males to gRNA-expressing females. From their progeny, trans-heterozygous F1 virgin females were then collected that should display gene-drive conversion in their germline and single-pair crossed them to wildtype (Oregon-R) males (
For the tGD(y1,w2) control, it was observed 89% inheritance of the Cas9-DsRed transgene and 96% inheritance of the gRNA-GFP transgene, in line with the previous characterization of this arrangement19. For the DT-tGD(y1,w2, y1b), Cas9-DsRed transgene inheritance improved significantly to 97% (compared to 89% for the control, p <0.0001, Mann Whitney test), suggesting that the additional y1b-gRNA increases inheritance of the transgene. No increase was observed for the inheritance of the gRNA-GFP transgene, which contained no secondary gRNA for this position and therefore displayed an average inheritance comparable with the control of 96%. For the DT-tGD(y1,w2,w2b), which instead carries an additional gRNA for white, an average inheritance of 97% was observed for the gRNA-GFP transgene (compared to 96% in the control). For this condition, the Cas9-DsRed transgene acted instead as an internal control displaying an average inheritance rate of 91% which is comparable with the control (89%). The four-gRNA DT-tGD(y1,w2, y1b, w2b) were also tested and improved inheritance rates of both transgenes were expected. Indeed, a significantly higher inheritance was observed for the Cas9-DsRed in yellow (97% compared to 89% for the control, p<0.0001, Mann Whitney test) and the gRNA-GFP transgene in white (98% compared to 96% for the control, p=0.1179, Mann Whitney test). From this analysis, it was concluded that the double-tap arrangement can improve drive efficiency at the yellow locus. Given that the w2-gRNA has, on its own, very high conversion rates (˜96%), the small range available for improvement did not allow to observe statistically significant differences in these experiments.
The double-tap should also increase the overall number of crosses generating 100% inheritance due to its two-step action. The fraction of vials (i.e., germlines) producing 100% inheritance for each transgene was compared. For DT-tGD(y1,w2, y1b), the fraction of vials producing 100% inheritance of the DsRed transgene climbed significantly from the tGD(y1, w2) control value of 3% to 48% (p<0.0001, randomization test for a difference in proportions). For DT-tGD(y1,w2,w2b), the fraction of vials displaying 100% GFP inheritance grew from 38% (control) to 48% with the double-tap (p=0.277, randomization test for a difference in proportions). Similarly for the four-gRNA DT-tGD(y1,w2, y1b, w2b), it was observed a consistent increase in both transgenes, with the fraction of crosses at 100% DsRed inheritance significantly increased from 3% for the control to 33% (p=0.0006, randomization test for a difference in proportions), and at 100% GFP inheritance increased from 38% for the control to 53% (p=0.133, randomization test for a difference in proportions). This additional analysis confirms that the double-tap can significantly improve inheritance at the yellow locus and, while all the observations are consistent with an improvement of inheritance at white, statistical significances for these comparisons were not observed.
To tested whether the double-tap drive would similarly improve inheritance when both the Cas9 and the g RNAs are co-inherited from the same parent, in a condition similar to a full gene drive19, a homozygous fruit fly strain containing both the vasa-Cas9 and DT-tGD(y1,w2, y1b, w2b)-gRNAs on the same chromosome was generated (
The propagation of engineered gene-drive systems can suffer from a maternal effect caused by Cas9 protein and gRNA deposition in the egg by transgenic females, leading to the high frequency generation of indels4,5, 19. To evaluate if the double-tap system could alleviate this effect by recycling some of the generated indels, F0 females from the Cas9+gRNA homozygous stock were crossed with wildtype males to obtain heterozygous F1 females (
C. Double Tap Secondary gRNAs Specifically Target Indels for Conversion
To rule out an unexpected mechanism contributing to the increased rate of transgene inheritance in the double-tap system, the makeup of the indels and the prevalence of the y1b and w2b sequences in the F2 were evaluated. To do this, several DsRed− or GFP− F2 males from the experiments performed in
To further show that the secondary gRNAs in the double-tap system specifically target the intended indels, the wildtype alleles were challenged with constructs lacking one of the primary gRNAs (
To demonstrate that the y1b- and w2b-gRNAs can specifically target the intended alleles to generate a gene drive via the conversion of these indels, a fruit fly line termed “y1b, w2b” was generated, which carries the two indel alleles (y1b, w2b) generated at the respective loci by previous rounds of gene drive using the primary gRNAs. These alleles in this fruit fly line should be efficiently cleaved by the secondary gRNAs of the same name. Homozygous lines combining each of the C-tGDs with vasa-Cas9 on the same chromosome were separately generated. Males from these vasa-Cas9,C-tGD stocks were then crossed to y1b, w2b females; from their offspring F1 heterozygous virgins were collected and single-pair crossed to wildtype males to evaluate the transgene transmission to their F2 progeny (
D. Double Tap Improves Drive when the Number of gRNAs in the System is Held Constant
Given that the DT-tGD carries four gRNA-expressing genes while the control tGD(y1,w2) has only two, it was tested whether differences in the total number of gRNA-expressing genes could affect gene-drive efficiency and therefore the interpretation of our double-tap results. Since the effect of the double-tap strategy is stronger on the transgene inserted in yellow, this transgene was focused on for this analysis. To control the number of gRNA genes, an additional C-tGD carrying only two gRNAs, y1 and y1b, analogous to the tGD(y1,w2) was generated (
To perform this experimental analysis, males from the Cas9, wΔ13 line were crossed to virgins from either the tGD(y1,w2) or tGD(y1, y1b) lines, F1 virgins were collected and crossed to wildtype males to evaluate the inheritance of the respective constructs in the F2 by scoring the fluorescent markers (
E. DT-tGD Outperforms Regular tGD when Spread in a Population
Because the double-tap strategy improved gene-drive performance, it was then tested whether the addition of secondary gRNAs would improve spread of the DT-tGD in a population. Given that the DT transgenes are inserted in either the yellowor white genes, to eliminate a fitness difference between the gene drive and the wildtype alleles a homozygous yellow-, white-fly line were used as the target population. For this purpose, a mutant line was generated by injecting gRNA- and Cas9-expressing plasmids targeting the first exon of yellow and white. These null alleles, yEX1 and wEX1 were generated at a considerable distance from the gene-drive insertion site so as to not influence the sequence-homology-dependent gene-drive process (
To test the performance of the double-tap strategy in a caged population setting, three bottles were seeded with: 1) 50 yEX1 wEX1 virgin females; 2) 40 yEX1 wEX1 males; and 3) 10 males from a homozygous stock containing the vasa-Cas9-DsRed construct and either the tGD(y1,w2) control or the DT-gRNA(y1,w2, y1b, w2b) (
In the caged population experiments, the percentage of transgenic alleles in each condition seemed to level off at different values much lower than 100%. Indeed, this behavior was observed given the strong maternal effect previously characterized at both loci19. This effect was more pronounced for w2 than for y1, consistent with the observations described in
To confirm this was due to maternal effects and simultaneously evaluate the generation of indels as the tGDs spread, the targeted loci from pools of male individuals were deep sequenced, again for their simpler makeup of one allele per individual. Three time points: during the initial exponential spread (F4), when the gene-drive spread began to slow (F8), and at the end of the experiment to evaluate the final population makeup (F15) were sampled. It was found that the frequency of wildtype alleles diminished over time in all cages, reaching levels in the 0-26% range in the F15 generation, and indel alleles accumulated (
Surprisingly, the y1b and w2b alleles accumulate in the tGD(y1,w2) populations to a much lower frequency than expected, given that in above Table 1, these alleles were observed appearing with 49% (y1b) and 63% (w2b) in single-pair crosses. This may be explained by a qualitative difference between indel alleles generated through NHEJ/MMEJ in the late germline (see Table 1) and indel alleles generated in population experiments. In the latter case, the major source of indel generation is the maternal effect which acts in early embryos, as seen in the previous study19. Altogether these results suggest that the double-tap strategy can improve gene-drive performance as it spreads in a population by specifically recycling indel alleles for a second round of gene-drive conversion.
This EXAMPLE 2 provides the double-tap homing gene-drive strategy to combat the most prevalent resistance alleles that prevent drive spread. This strategy uses an additional, secondary gRNA targeting these resistance alleles to recycle them as new templates for an additional round of gene conversion, ultimately improving gene-drive efficiency. A double-tap version of a previously tested trans-complementing gene drive targeting the yellow and white loci of fruit flies19 showed that the secondary gRNAs are specific in their targeting and improve the drive efficiency at both loci tested. The double-tap also improves the ability of the drive to spread in a population, with the double-tap reaching higher frequencies than the control.
Studies presented in EXAMPLE 2 confirms that the efficiency of the drive depends on the locus and gRNAs used. Of the two loci tested in EXAMPLE 2, the double-tap strategy performed better at yellow, likely due to the lower baseline conversion efficiency of yl-gRNA (89%) than w2-gRNA (96%). This generates more resistance alleles that can be further converted, which results in a more readily observable phenomenon for yellow. Additionally, this study employed only one additional secondary gRNA, yet a modest improvement in efficiency is observed. In the drive process, several resistance alleles are generated consistently, which could be targeted by the addition of multiple secondary or tertiary gRNAs to further improve conversion rates and approximate 100% efficiency.
The double-tap strategy also improves upon other proposed strategies that relied on the multiplexing of gRNAs to overcome resistance alleles. For example, two or more adjacent gRNA target sites have been employed to increase drive efficiency when either one of them would fail25,26. While this strategy allows for recycling resistance alleles, it also has the potential to generate non-homologous overhangs that can affect HDR rates, as shown in previous work19. The double-tap acts instead as a multiplexing system “in time” instead of “in space” and creates no homology mismatches while still allowing the drive element multiple chances to convert the wildtype allele. This feature of the double-tap system allows it to be seamlessly implemented in existing gene-drive systems to further boost their effectiveness.
Though this work addresses the drawback of indel formation slowing drive spread, another drawback of gene-drive systems in insects stems from the maternal effect caused by Cas9 and gRNA deposition in the egg which severely impairs drive efficiency. The double-tap does not seem to reduce this maternal effect, at least using the gRNAs tested in this study. It was believed that the strong maternal effect observed in this study is due to the highly efficient gRNAs employed. Use of less efficient gRNAs may lead to lessened maternal effect and should also greatly benefit from a double-tap approach.
While the main scope of the studies presented in EXAMPLE 2 was to demonstrate the feasibility of the strategy, the constructs were also evaluated for their potential to spread in caged population experiments to test their potential for field use. While the strong maternal effect in both the double-tap and control populations rapidly generated resistance alleles that stifled the spread of either drive, a higher level of spread for the double-tap than the control was nonetheless observed, further supporting the beneficial effect of the secondary gRNAs. This suggests that the double-tap strategy could be universally applied to increase the efficiency of CRISPR-based gene-drive systems suffering from resistance allele generation. For example, several mosquito systems4, 5, 7, 8 can partially circumvent the generation of resistance alleles by different strategies; implementing a double-tap approach should further increase their spread in a population. Additionally, secondary gRNAs could be used to specifically target problematic resistance alleles, such as those retaining target gene function and thus not suffering an imposed fitness disadvantage from the gene drive5.
Further, a double-tap strategy could be implemented in systems where HDR conversion is less efficient, such as primary human cells or mouse embryos. The delivery of secondary gRNAs in human cells could increase HDR-based transgenesis and perhaps benefit therapeutic uses requiring the HDR-based delivery of beneficial cargos27, while its use in mice could further boost transgenesis efficiency beyond the latest improvements28. Overall, the double-tap strategy can be widely applicable to diverse situations that could benefit from the use of secondary gRNAs to boost HDR efficiency or eliminate unwanted indels.
It should be emphasized that the above-described embodiments of the present disclosure are merely possible examples of implementations set forth for a clear understanding of the principles of the disclosure. Many variations and modifications may be made to the above-described embodiment(s) without departing substantially from the spirit and principles of the disclosure. All such modifications and variations are intended to be included herein within the scope of this disclosure and protected by the following claims.
This application claims the benefit of U.S. Provisional Application No. 63/243,260, filed Sep. 13, 2021, the entire content of which is incorporated herein by reference.
This invention was made with government support under OD023098 and AI162911 awarded by the National Institutes of Health and under MCB-2048207 awarded by the National Science Foundation. The government has certain rights in the invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2022/043004 | 9/9/2022 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63243260 | Sep 2021 | US |
