Cell and Gene Engineering
Comment
Stakeholder Type
GESDA
"The inner workings of a dividing cell" by Joana Delgado Martins, University of Zurich
Photo: "The inner workings of a dividing cell" by Joana Delgado Martins, University of Zurich

Topic

Cell and Gene Engineering

Anticipation Committee Chair:

Robin Lovell-Badge

Principal Group Leader, Stem Cell Biology and Developmental Genetics Laboratory

Francis Crick Institute

Anticipation Committee:

Alejandro Chavez, Isabelle Mansuy, Kelly Ormond, Philip M. Kim, Samira Kiani
Topic Brief

Cell and Gene Engineering

Gene editing has achieved significant successes in a range of areas and has gained regulatory approval for targeting cancer, 1,2,3 eye diseases4 and blood diseases.5 Its next act will be to move from rare and difficult diseases into more common disorders and cancers, and from there into cracking the fundamentals of ageing.
Gene editing has achieved significant successes in a range of areas and has gained regulatory approval for targeting cancer, 1,2,3 eye diseases4 and blood diseases.5 Its next act will be to move from rare and difficult diseases into more common disorders and cancers, and from there into cracking the fundamentals of ageing.

The ultimate goal for gene editing is a one-shot wonder drug — a one-time injection that cures heritable or acquired disease for the rest of the patient’s life. However, it is becoming increasingly clear that the gene-editing tool that has underpinned most clinical and research breakthroughs will not be the main way forward. CRISPR, an editor that can snip DNA to alter its sequence, also creates dangerous and irreversible breaks in DNA.6 The future of gene editing will rely on new, more efficient, more accurate techniques now under investigation and in early trials, along with novel ideas about how to manipulate the genome indirectly, transiently and even perhaps reversibly.

They will also rely on improved delivery methods. Today, most gene editing is not applied to living embryos or directly done on patients, but is ex vivo: as, for example, in treatments for sickle-cell anaemia.7 But this limits the number of diseases that can be targeted. Targeted payload delivery is being developed to be more precise and less toxic, thereby creating fewer side effects and immune reactions. This could deliver the editor into tissues that are traditionally hard to reach. Better diagnostics, editors and delivery methods could be a result of advances in machine learning. AI could make it easier to diagnose and even predict heritable disorders.

It is generally agreed that future research needs to move forward with an eye to lowering the staggering costs of gene therapy. Currently, the biggest barriers to making gene editing a medical reality are not only technological: they also include public-health messaging, infrastructure and cost. Recently approved haemophilia and sickle-cell disease therapies cost $2 million to $3 million.8 The expense is multifactorial, but new initiatives are under way to make them cheaper and more accessible.9 Crucial to the future of scientific success will be public acceptance and understanding that this is not always led by the West.10 As this therapeutic modality moves into more medical interventions, more infrastructure needs to be developed to address the interpretability of the science (for example, genetic counsellors are needed to interpret genetic test results but are in short supply).

KEY TAKEAWAYS

Editing human genetics is a promising route towards disease prevention and reduction. Work to improve Diagnostics tools for reading and interpreting the genome has achieved fast identification of pathogens and promises to enable insight into the most suitable gene therapies for an individual. This will be complemented by developments in Next-generation editors and delivery, which will manipulate the genome in ways that avoid unwanted immune-system responses. A number of processes will benefit from Engineered organisms and AI-based tools, such as testing of proposed therapies on synthetic organisms and accelerated reading of whole genomes through the use of AI. Researchers are exploring Alternatives to direct gene editing, including epigenome editing, which might facilitate the fine-grained control of gene expression.

Topic:

Anticipation Potential

Cell and Gene Engineering

Sub-Fields:

Diagnostics
Next-generation editors and delivery
Engineered organisms and AI-based tools
Alternatives to direct gene editing
The relatively low Anticipation Potential scores for the sub-topics covered in the Cell and Gene Engineering topic are linked to lower transformative effects scores and the high awareness they benefit from. The ability to use AI to engineer new organisms is still in its early phase and will require more than 10 years of further research before transformative effects on society and the economy start to be seen. Combined with the high uncertainty, this explains the higher Anticipation Potential score for this field.

Anticipatory Impact:

Three fundamental questions guide GESDA’s mission and drive its work: Who are we, as humans? How can we all live together? How can we ensure the well-being of humankind and the sustainable future of our planet? We asked researchers from the field to anticipate what impact future breakthroughs could have on each of these dimensions. This wheel summarises their opinions when considering each of these questions, with a higher score indicating high anticipated impact, and vice versa.

  • Anticipated impact on who we are as humans
  • Anticipated impact on how we will all live together
  • Anticipated impact on the well-being of humankind and sustainable future of our planet
SubField

Diagnostics

Reading and interpreting the genome — whole-genome sequencing of patient DNA — is increasingly common in medical practice for developing and adequately deploying therapeutics. Better reading technologies have already helped to diagnose disease, genetic predispositions to disease and even infections.11 For example, the CRISPR-Cas system is enabling the fast detection of pathogens: Cas12a has detected hepatitis B in less than 30 minutes.12 More typically, sequencing is now possible in hours to days.13 Costs are also falling.14

Future Horizons:

×××

5-yearhorizon

Faster, cheaper, better diagnostics become available

CRISPR-based diagnostic methods are developed for a variety of targets, including cancer, viruses and other pathogens. Rapid, reliable, widespread whole-genome sequencing shortens rare-disease diagnosis and cancer diagnosis, prognosis and management. Cost drops to $100 to $200 a genome.17 Therapeutic investment explodes. Genome targeting for pathogen diagnosis comes to point-of-care settings, including pharmacogenomics when drugs are prescribed. AI interprets sequencing.

10-yearhorizon

Genome-reading finds a broad range of applications

The time for whole-human-genome sequencing drops to an hour. Same-day diagnosis of cancers and rare diseases shortens time to treatment. Genome sequencing influences retirement plans and insurance. AI helps fill unmet need for genetic counsellors.

25-yearhorizon

Gene-reading goes mainstream

Rapid diagnostics enable to-go or home-based devices for pathogen detection and better prediction of complex diseases. Editing technology, combined with AI, obviates most genetic concerns over partner choice. Heritability and environmental conditions are included in assessments of polygenic risk scores for everything from cancer to obesity.

Faster, better and cheaper diagnostics coming into the mainstream will act as a fact-checker on the new generations of genome editors, detecting and preventing DNA-editing errors. These technologies need to be further refined to ensure every laboratory can easily adopt them when in vivo editing becomes mainstream.

Much progress will be thanks to the new ability to do long-read sequencing, more accurate than the previously more common usage of short-read sequencing. This could identify more clinically relevant gene variants and it could also provide epigenetic information that can bring epigenome editing to the clinic.15 Diagnostics will be able to tell patients what kind of gene therapy they are suited for, or even which interventions and lifestyle changes will most affect their chances of expressing a genetic disease. However, analysis and interpretation are a major bottleneck: a shortage of genetic counsellors is an increasing problem.16

Diagnostics - Anticipation Scores

The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:

  1. The uncertainty related to future science breakthroughs in the field
  2. The transformative effect anticipated breakthroughs may have on research and society
  3. The scope for action in the present in relation to anticipated breakthroughs.

This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.

SubField

Next-generation editors and delivery

CRISPR-Cas9 is now the most widely used gene-editing technology in the world, successfully treating blood diseases, cancers and eye diseases.18 Several therapies have been approved for clinical use and many more are in trials. However, CRISPR’s ability to correct gene defects depends on making double-strand breaks that are repaired by cellular processes. It is increasingly accepted that such double-strand breaks are dangerous,19 resulting in potential chromosomal rearrangements or loss.20 Drugs in the pipeline will not be abandoned, but future therapies will rely on more efficient and accurate techniques.

Future Horizons:

×××

5-yearhorizon

Ex vivo and in vivo therapies advance

More large-scale phase-III clinical trials for ex vivo therapies take place, with more therapeutics approved and commercially licensed.32 Patient data shows mid-stage results of CRISPR-based haemophilia and retinitis pigmentosa therapies now in trials.33,34 Early-stage clinical trials of in vivo editing techniques, targeting easily accessible tissues such as the eye35 or the liver, show results. In vivo therapies move to experimental clinics. CRISPR corrects for mitochondrial genetic disease in IVF procedures. Next-generation “one-shot” genome editors in vivo show long-term safety data in clinical trials.36 Duchenne muscular dystrophy trial uses base editing to get into major tissues.37

10-yearhorizon

Safer germline editing blurs boundaries between therapy and prevention

Inhaled and other new delivery methods move into the clinic. Epigenome editing has its first trials, targeting chronic diseases. New non-viral delivery techniques reduce the need for large doses, also reducing cost. Adenosine transversion editors expand the capabilities and applications of base editing.38 Heritable gene editing begins to gain limited acceptance, although not everywhere, as a consequence of successful somatic techniques and preclinical safety data. Base and prime editing enable in vivo therapeutics, bringing costs of therapy down.

25-yearhorizon

Polygenic editing erodes boundaries between therapy and enhancement

In vitro derived gametes can be edited safely before implantation. Many forms of gene editing are mainstream. It becomes possible to engineer protection from radiation, chemical warfare and infectious diseases by altering single genes, enabling military applications as well as casual space travel. We use gene technologies to correct, slow down or even reverse processes linked to premature ageing to increase healthspan. A sleep-shortening gene is the first popular enhancement. Up- and down-regulating some specific genetic elements enhances some aspects of cognition.

The two likeliest candidates are base and prime editing. Base editing is powerful against point mutations, which account for 80 per cent of human genetic diseases.21 It also enables mitochondrial gene editing, which is harder to achieve with CRISPR.22 Prime editing is also more specific and accurate, and new research continues to enhance its efficiency.23 Research is under way to replicate CRISPR successes in sickle-cell disease and beyond with base and prime editing.24,25,26 Prime editing can target multiple genes at the same time.27,28

Modified adeno-associated viruses (AAVs) can deliver gene editors, although the large quantities required can trigger dangerous immune responses. Efforts are under way to re-engineer AAV to be bigger and evade immune response. One alternative is more efficient lentiviral vectors, or viruses engineered to make them preferentially infect specific cell types, for example neural cells or airway cells.29

Non-viral delivery has become an increasingly viable alternative, thanks to rapid progress in the use of lipid nanoparticles and inorganic nanoparticle-based delivery systems.30,31

Next-generation editors and delivery - Anticipation Scores

The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:

  1. The uncertainty related to future science breakthroughs in the field
  2. The transformative effect anticipated breakthroughs may have on research and society
  3. The scope for action in the present in relation to anticipated breakthroughs.

This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.

SubField

Engineered organisms and AI-based tools

AI promises to accelerate drug discovery.39 Synthetic organisms and AI will help advance genome editing for human applications in several crucial ways, including improved ways to deliver the editing payload to the cell and experimental organisms that provide a better proxy for human testing. 40

Future Horizons:

×××

5-yearhorizon

Synthetic biology circuits go in vivo

Extremely rapid progress in machine learning and AI solves many obstacles to engineering proteins and enzymes. AI helps create de novo gene editor. Genome reading and writing allows us to build large genetic circuits composed of many repeated guide RNA sequences that enable us to simultaneously target multiple genes. AI leads to engineered proteins and enzymes.

10-yearhorizon

Chimeras, synthetic viruses and other models become mainstream

Synthetic biology circuits, now in mammalian cell cultures, find applications in vivo and for enhanced control of genome editors for gene therapies. Chimeras generated by injecting human stem cells into animal embryos grow organs for xenotransplantation or grow human-like brain structures to study the effects of gene edits. Improved synthetic viruses and genome editors knock out genes in animal organs to supply the increasing need for human organ donation without the risk of rejection. Engineered cells and tissues serve as novel delivery systems to easily grafted tissues such as bone and skin.

25-yearhorizon

Universal editors emerge

Engineered cells and tissues are grafted into complex tissues like the brain or the endocrine system. With prime and base editing, plus tissues grown outside the body and reimplanted, modification becomes easier and cheaper, rivalling in vivo. Genetically modified viruses, synthetic viruses and large genetic circuits are widely deployed for pre-emptive “gene surgery” on otherwise healthy people, directly linking genetic circuits to genome editors. We see the first demonstration in humans of universal cells carrying gene circuitry.

AI will help to quickly scan whole genomes and then design vectors that can be used more universally. Work is also under way in AI design of entirely new proteins and editors.41 However, human screeners are still needed to identify the small percentage that will work as they are meant to. This situation may improve with access to more training data. Generally, advances here will require more collaboration between mathematicians and biologists.

Furthermore, machine-learning algorithms may help identify the relationships among genes, gene networks and other variables (such as epigenetic factors) involved in disease, as well as the potential consequences of edits to these.42 AI-enabled searches through microbial data obtained from uncultivated samples may reveal more suitable enzymes — helicases, nucleases, transposases or recombinases — that solve the problems of currently available editors.

Recent rapid advances in stem-cell engineering, stem-cell-derived embryo models, organoids (artificial and simplified versions of an organ) and tissue engineering are helping research move towards providing experimental organisms based on human physiology that will help predict the functionalities of genome editors outside the human body and before clinical applications.43,44

Engineered organisms and AI-based tools - Anticipation Scores

The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:

  1. The uncertainty related to future science breakthroughs in the field
  2. The transformative effect anticipated breakthroughs may have on research and society
  3. The scope for action in the present in relation to anticipated breakthroughs.

This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.

SubField

Alternatives to direct gene editing

Existing approaches to gene editing are all-or-nothing: gene sequences are altered, removed or added. However, some diseases manifest through inadequate gene expression that is dialled too far up or down rather than turned on or off. This means that, in some cases, techniques such as editing the epigenome may be a better option.45 Simply adding or removing the chemical tags that adorn DNA, for instance, could dial down or up expression of certain genes or variants without the risk of dangerous mutations. Epigenetic mechanisms include histone modifications and DNA methylation; manipulating the factors that control these can be both tuneable and reversible, and could be especially useful for controlling more than one gene.46 Once considered a dark art, epigenome editing is now rapidly advancing.47

Future Horizons:

×××

5-yearhorizon

Disease spread is monitored through metagenomics

Metagenomics advances make it possible to monitor the emergence (or re-emergence) of viral diseases with the goal of containing their spread. Epigenome editors alter epigenetic state at precise locations within the genome, lowering the chance of immune response, and are fine-tuned for first use on disease genes and tissues, and tested in vivo. New sequencing methods identify epigenetic modifications while preserving the accuracy of genome sequencing. Insights are gained into how interventions like diet and exercise alter gut microbiome.

10-yearhorizon

Epigenome editors are fine-tuned

Metagenomics becomes a standard tool for microbial ecology laboratories, using methods similar to gene fingerprinting to profile microbial communities. Epigenome editing becomes titratable.

25-yearhorizon

Cosmetic gene editing becomes possible

Delivery methods of enzymes and editors — whether gene or epigenome — become straightforward and open to dynamic control. Epigenome editing helps people temporarily mute some genes or express others, making for temporary alterations including military night vision and resistance to radiation, viruses and chemical weapons. Cosmetic mutations, such as temporary eye-colour changes, are popular in body-hacking subcultures. Fundamental alterations to the microbiome make humans capable of digesting cellulose or extracting nutrition from plastic.
Another approach, editing RNA, could open up much more common diseases like chronic pain. Some drugs are already in clinical trials.

Alternatives to direct gene editing - Anticipation Scores

The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:

  1. The uncertainty related to future science breakthroughs in the field
  2. The transformative effect anticipated breakthroughs may have on research and society
  3. The scope for action in the present in relation to anticipated breakthroughs.

This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.

References

Citations

Topic brief

  1. National Cancer Institute. First Cancer TIL Therapy Gets FDA Approval for Advanced Melanoma https://www.cancer.gov/news-events/cancer-currents-blog/2024/fda-amtagvi-til-therapy-melanoma
  2. J. Couzin-Frankel. Cutting-Edge CRISPR Gene Editing Appears Safe in Three Cancer Patients https://www.science.org/content/article/cutting-edge-crispr-gene-editing-appears-safe-three-cancer-patients
  3. R. Stein. CRISPR Gene-Editing May Boost Cancer Immunotherapy () New Study Finds https://www.npr.org/sections/health-shots/2022/12/13/1140384354/crispr-improves-cancer-immunotherapy-car-t-cell
  4. EMA. New gene therapy for rare inherited disorder causing vision loss recommended for approval https://www.ema.europa.eu/en/news/new-gene-therapy-rare-inherited-disorder-causing-vision-loss-recommended-approval
  5. US Food and Drug Administration. FDA Approves First Gene Therapies to Treat Patients with Sickle Cell Disease https://www.fda.gov/news-events/press-announcements/fda-approves-first-gene-therapies-treat-patients-sickle-cell-disease
  6. J. Li et al. Precise large-fragment deletions in mammalian cells and mice generated by dCas9-controlled CRISPR/Cas3 https://doi.org/10.1126/sciadv.adk8052
  7. Vertex Pharmaceuticals Incorporated. A Phase 1/2/3 Study to Evaluate the Safety and Efficacy of a Single Dose of Autologous CRISPR-Cas9 Modified CD34+ Human Hematopoietic Stem and Progenitor Cells (CTX001) in Subjects With Severe Sickle Cell Disease https://clinicaltrials.gov/ct2/show/NCT03745287
  8. T. Hagen. Gene Therapy for Hemophilia Is Becoming a Reality. Who Will Write the Checks to Pay for It? https://www.managedhealthcareexecutive.com/view/gene-therapy-for-hemophilia-is-becoming-a-reality-who-will-write-the-check-to-pay-for-it-
  9. R. Leuty. Task force from Nobel-winner Jennifer Doudna's institute points way to cheaper, more accessible gene therapies https://www.bizjournals.com/bizwomen/news/profiles-strategies/2023/07/uc-berkeley-jennifer-doudna-cell-gene-therapy-igi.html
  10. M. Jibrilla M et al.. Survey of attitude to human genome modification in Nigeria httos://doi.org/10.1007/s12687-023-00689-1

2.2.1 Diagnostics

  1. G. Costain et al.. Genome Sequencing as a Diagnostic Test https://doi.org/10.1503/cmaj.210549
  2. R. Ding et al.. CRISPR/Cas12-Based Ultra-Sensitive and Specific Point-of-Care Detection of HBV https://doi.org/10.3390/ijms22094842
  3. M. Eisenstein. Streamlined workflows for DNA and RNA sequencing are helping clinicians to deliver prompt, targeted care to people in days — or even hours https://www.nature.com/articles/d41586-024-00483-0
  4. National Human Genome Research Institute. The Cost of Sequencing a Human Genome https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost
  5. V. Marx. Method of the year: long-read sequencing https://doi.org/10.1038/s41592-022-01730-w
  6. M. Paneque et al. An European overview of genetic counselling supervision provision https://doi.org/10.1016/j.ejmg.2023.104710
  7. J. Wosen. Stanford Scientist Who Broke Genome Sequencing Record on What Faster Diagnoses Mean for Patients https://www.statnews.com/2023/03/22/euan-ashley-stanford-genome-sequencing/

2.2.2 Next-generation editors and delivery

  1. B. Bekaert et al. Retained chromosomal integrity following CRISPR-Cas9-based mutational correction in human embryos https://doi.org/:10.1016/j.ymthe.2023.06.013
  2. C. A. Tsuchida et al. Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells https://doi.org/10.1016/j.cell.2023.08.041
  3. L. Yang et al. Engineering APOBEC3A deaminase for highly accurate and efficient base editing https://doi.org/10.1038/s41589-024-01595-4
  4. S-I. Cho et al. Engineering TALE-linked deaminases to facilitate precision adenine base editing in mitochondrial DNA https://doi.org/10.1016/j.cell.2023.11.035
  5. S. Mu et al. Enhancing prime editor flexibility with coiled-coil heterodimers https://doi.org/10.1186/s13059-024-03257-z
  6. T. Mayuranathan et al. Potent and uniform fetal hemoglobin induction via base editing https://doi.org/10.1038/s41588-023-01434-7
  7. K. A. Everette et al.. Ex vivo prime editing of patient haematopoietic stem cells rescues sickle-cell disease phenotypes after engraftment in mice https://doi.org/10.1038/s41551-023-01026-0
  8. C. Li et al. In vivo HSC prime editing rescues sickle cell disease in a mouse model https://doi.org/10.1182/blood.2022018252
  9. M. Bulcaen et al. Prime editing functionally corrects cystic fibrosis-causing CFTR mutations in human organoids and airway epithelial cells https://doi.org/10.1016/j.xcrm.2024.101544
  10. R. Liang et al. Prime editing using CRISPR-Cas12a and circular RNAs in human cells https://doi.org/10.1038/s41587-023-02095-x
  11. A. Cooney et al.. Reciprocal mutations of lung-tropic AAV capsids lead to improved transduction properties https://doi.org/10.3389/fgeed.2023.1271813
  12. F. Sinclair et al.. Recent Advances in the Delivery and Applications of Nonviral CRISPR/Cas9 Gene Editing https://doi.org/10.1007/s13346-023-01320-z
  13. Y. Du et al. CRISPR/Cas9 systems, Delivery technologies and biomedical applications https://doi.org:10.1016/j.ajps.2023.100854
  14. L. Chen et al. Adenine transversion editors enable precise, efficient A•T-to-C•G base editing in mammalian cells and embryos https://doi.org/10.1038/s41587-023-01821-9
  15. A. Zamecnik. CRISPR Gene Therapies: Is 2023 a Milestone Year in the Making? https://www.pharmaceutical-technology.com/features/crispr-gene-therapies-is-2023-a-milestone-year-in-the-making/
  16. US Food and Drug Administration. Approval of roctavian to treat haemophilia https://www.fda.gov/vaccines-blood-biologics/roctavian
  17. Y. Ma et al.. Generation of an MESC Model with a Human Hemophilia B Nonsense Mutation via CRISPR/Cas9 Technology https://doi.org/10.1186/s13287-022-03036-2
  18. Mayo Clinic. Potential one-time gene therapy treatment for wet age-related macular degeneration https://www.mayoclinic.org/medical-professionals/ophthalmology/news/potential-one-time-gene-therapy-treatment-for-wet-age-related-macular-degeneration/mac-20551865
  19. M. Naddaf. First trial of ‘base editing’ in humans lowers cholesterol — but raises safety concerns https://www.nature.com/articles/d41586-023-03543-z
  20. E. Olson. Toward the correction of muscular dystrophy by gene editing https://doi.org/10.1073/pnas.2004840117

2.2.3 Engineered organisms and AI-based tools

  1. Genentech. Redefining Drug Discovery with AI https://www.gene.com/stories/redefining-drug-discovery-with-ai
  2. J. Kaiser. Better than CRISPR? Another way to fix gene problems may be safer and more versatile https://www.science.org/content/article/better-crispr-another-way-fix-gene-problems-may-be-safer-and-more-versatile
  3. D. M. Ichikawa et al.. A Universal Deep-Learning Model for Zinc Finger Design Enables Transcription Factor Reprogramming https://doi.org/10.1038/s41587-022-01624-4
  4. K. Mochida et al.. Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets https://doi.org/10.3389/fpls.2018.01770
  5. K. Saha et al.. The NIH Somatic Cell Genome Editing Program https://doi.org/10.1038/s41586-021-03191-1
  6. I. Sample. Scientists Create World’s First ‘Synthetic Embryos’ https://www.theguardian.com/science/2022/aug/03/scientists-create-worlds-first-synthetic-embryos

2.2.4 Alternatives to direct gene editing

  1. J. Kaiser. Better than CRISPR? Another Way to Fix Gene Problems May Be Safer and More Versatile https://www.science.org/content/article/better-crispr-another-way-fix-gene-problems-may-be-safer-and-more-versatile
  2. J.K. Nuñez. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing https://www.sciencedirect.com/science/article/pii/S0092867421003536
  3. J. Qian and S. X. Liu. CRISPR/dCas9-Tet1-Mediated DNA Methylation Editing https://doi.org/10.21769/BioProtoc.4976