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Record W6940220148 · doi:10.7488/era/4123

Regulation, traceability and stakeholder engagement for genome editing technology

2024· other· en· W6940220148 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueERA · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTraceabilitySelection (genetic algorithm)ProductivityAgricultureStakeholderGenome editingProduction (economics)Agricultural biotechnology

Abstract

fetched live from OpenAlex

Over the course of time, improvements based on quantifiable traits have been made to both crops and animals to either increase their productivity or make them more resilient to diseases or pests. For generations, farmers have employed a method of seed selection based on performance, where they carefully chose seeds each planting season to cultivate crops with desirable traits. These traits might encompass improved taste, higher yields, distinct appearances, extended storage life, or resistance to diseases and pests. Starting in the mid-20th century, the practice of deliberate and precise plant breeding has expedited this natural selection process, leading to the enhancement of various characteristics, notably drought tolerance, among others. In farmed animals, selection has emphasised production of milk, meat, eggs and fibre and efficiency of production, as well as appearance. During the 1980s, scientists initiated the use of biotechnology techniques, which involved the direct transfer of genes responsible for specific traits into plants or animals. This process, commonly referred to as genetic modification, allowed for the precise introduction of desired traits into organisms. With the adoption of biotechnology, countries began putting in place regulatory frameworks that governed research using genetically modified (GM) crops and animals, their movement and commercialisation or placing on the market. Studies done on the adoption of GM technology have shown that the regulatory framework adopted by a country played a huge role in whether GM crops and animals were adopted and subsequently contributed towards the agricultural output. For this PhD, the focus was on genome-edited (GEd) organisms, particularly animals, with the overall research question being ‘How will genome editing and the products of the technology be regulated?’. Genome editing encompasses a set of technologies that empower scientists to modify an organism's DNA by adding, removing, or altering genetic material at specific locations within the genome. This precision allows for the targeted and controlled manipulation of an organism's genetic information. An interdisciplinary approach is adopted based on three aspects involved in the future development of genetic technologies - establishment of regulatory frameworks, traceability and public engagement. The first objective aimed at investigating countries’ experience so far in regulating GEd organisms. Ten countries were selected to give a range of geographical locations, approaches to regulation and degree of adoption. They comprised Argentina, Australia, Canada, China, Brazil, EU, Japan, Kenya, United States and Zambia. The results show that the countries that are among the world’s top producers and exporters of agricultural commodities, for example Argentina, Canada, Brazil and the United States, have regulatory frameworks which create an enabling environment for uptake of innovations and are benefiting greatly from the introduction of GEd-based products. GEd applications that have been submitted to regulators in the selected countries have traits that can contribute to sustainable agriculture and the factors listed as crucial for realization of GEd potential for sustainable agricultural development were regulatory predictability/legal certainty, end-user empowerment and global co-operation. The second objective looked at traceability of organisms whose genome was edited using CRISPR-Cas9. A DNA footprint was introduced in the exon 10 region of the prolactin receptor gene in sheep where mutations for the SLICK phenotype are known to occur in cattle. The SLICK phenotype is caused by a mutation that results in shorter hair and lower follicle density in the coat in comparison to wild type animals, which contributes to heat tolerance adaptation in Senepol cattle. The DNA footprint comprised a restriction site for the EcoRI enzyme incorporated in an oligonucleotide intended as a template for homology directed repair. Transfection was done in sheep embryonic fibroblast cells using plasmid and ribonucleoprotein transfection techniques. Single cells were then isolated and screened for the edits of interest. Three techniques were used to screen for the introduced edits: polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and Sanger sequencing. EcoRI PCR and PCR-RFLP can be applied in low infrastructure settings such as universities and public institutions in low and middle-income countries, where sequencing infrastructure is not well established, while Sanger sequencing can be used in areas with established sequencing infrastructures. It was demonstrated that, for GEd organisms, traceability is possible using a DNA footprint to identify where the edit was introduced and to distinguish them from products made using genetic modification or conventional breeding. The third objective sought to identify through surveys the knowledge levels of various genetic technologies; views towards use of GEd technology for various uses; where people obtain science information; who they trust as reliable sources of science and technology information; attitudes towards labelling of GEd products; concerns regarding GEd products and the kind of information that should be included during public engagement forums with various stakeholders. The targeted stakeholders were people in academia and research environments. The aim of this was to establish baseline information for this particular cohort of stakeholders through which regulators, developers and scientists can draw specific insights on how to design public engagement programs. The results obtained showed that for this select group of stakeholders: initially self-analysed knowledge levels for various technologies were low but improved when brief descriptions were given; and they were positive towards use of GEd to reduce crop losses, make crops and livestock more resilient to environmental stress and climate change, and improve productivity. However, their views were that improvement of animals should not encourage farmers to keep them in poor welfare conditions. Further, respondents in both UK and Kenya emphasised the importance of labelling GEd products to facilitate informed decision-making by consumers. Additionally, the results showed that this particular cohort of stakeholders (in universities and research environments) highly trust scientists and teachers rather than journalists, social media influencers or religious leaders as sources of science information. Some of the aspects they had concerns on with respect to GEd comprised: effects of GEd crops and animals on the environment; long-term effects of consumption of GEd products; unexpected effects of GEd; and new allergens from GEd crop and animal products. We argue that although this was a particular sub set of stakeholders, these findings can inform public engagement on products of GEd technology and help provide knowledge on some areas of concern in terms of risk decision-making. Overall, the thesis chapters show that for governance of GEd products and other genetic technologies, aspects of regulation, traceability and stakeholder engagement should be integrated. This is because during drafting of guidelines or regulations, policy makers have to consider how the rules will be enforced as well as how they will communicate to the public and various stakeholders involved. For future governance of GEd plants and animals, having these three components in mind will lead to regulatory frameworks that are fit for purpose and create enabling environments for technology uptake

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.287
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

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Citations0
Published2024
Admission routes1
Has abstractyes

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