Programmable Domestication: CRISPR, Pan-Genomics and System Level Engineering for Next-Generation Crops

Creative Commons License

Ercişli S.

PLANT BIOTECHNOLOGY JOURNAL, cilt.0, ss.1-26, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 0
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1111/pbi.70749
  • Dergi Adı: PLANT BIOTECHNOLOGY JOURNAL
  • Derginin Tarandığı İndeksler: Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Biological Science Database (ProQuest), Biomedical Reference Collection: Corporate Edition (EBSCO), Scopus, Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest), Science Citation Index Expanded (SCI-EXPANDED), BIOSIS, EMBASE, Environment Index, CAB Abstracts, MEDLINE, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1-26
  • Atatürk Üniversitesi Adresli: Evet

Özet

Global agriculture is increasingly challenged by climate instability, genetic erosion, emerging pathogens and rising food demands,

exposing the limitations of conventional breeding and traditional domestication strategies. Recent advances in CRISPR-based

genome editing, pangenomic, synthetic biology, artificial intelligence (AI)-assisted

breeding and predictive phenomics are

transforming de novo domestication from a slow evolutionary process into a programmable framework for rational crop redesign.

This review synthesises recent advances in programmable de novo domestication and highlights how crop wild relatives

and underutilised germplasm can be harnessed to develop resilient, climate-adaptive

and sustainable crop systems. The integration

of multiplex genome editing, pan-genomic

variation discovery, AI-driven

genomic prediction and predictive breeding enables

precise engineering of key domestication traits governing plant architecture, yield potential, stress resilience and nutritional

quality. Furthermore, we propose a trajectory-based

framework for programmable domestication comprising Adaptive Rescue,

Agronomic Refinement and Novel Chassis Engineering, which illustrates distinct evolutionary pathways, engineering complexity

and crop redesign objectives. We also examine the major system level challenges that constrain programmable domestication,

including cryptic genetic variation, epistasis, gene regulatory network complexity, genotype phenotype predictability, biodiversity

conservation and regulatory considerations. Collectively, programmable domestication represents a transformative shift

from conventional crop improvement towards system-level

engineering of next-generation

crops, providing a strategic foundation

for enhancing global food security, agricultural sustainability and environmental resilience in the face of accelerating

climate change.