Gene-Editing for Production Traits in Forest Trees: Challenges to Integration and Gene Target Identification

Steven H. Strauss*, Gancho T. Slavov, Stephen P. DiFazio

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

5 Dyfyniadau (Scopus)
46 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

Gene-editing methods, particularly CRISPR, provide extraordinary opportunities for scientific insights and applications in the life sciences. However, the prospects for near-term applications to commercial forestry appear limited. Loss-of-function phenotypes that can be imparted by mutation of one or a few conserved genes offer the best opportunities in the near term. For traits with complex inheritance, there is insufficient science to guide gene-editing efforts, and Genome-Wide Association Studies (GWASs), without strong validation, typically cannot provide high-confidence gene identification. Other obstacles include the difficulty of transformation in many important genotypes, difficulties of transient editing or complete editor removal, and complexity of use in breeding programs. Gene edits that cause loss-of-function traits will generally be recessive, and thus not be expressed among outbred progeny, so vegetative propagules (clones) will be required in most cases. There are also important societal constraints, such as strict regulations for field trials in most countries, and market certification systems that do not allow any kinds of recombinant DNA-modified trees, including those produced by gene-editing, in certified production forests. We conclude that gene-editing applications will be extremely limited for the foreseeable future (i.e., at least 10 years). Nevertheless, gene-editing is a very powerful scientific tool that will be widely used by molecular forest scientists and can lead to important applications in the longer term, if research advances are made on key fronts and regulatory and market obstacles greatly attenuated.

Iaith wreiddiolSaesneg
Rhif yr erthygl1887
Nifer y tudalennau13
CyfnodolynForests
Cyfrol13
Rhif cyhoeddi11
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 10 Tach 2022
Cyhoeddwyd yn allanolIe

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