Implementation and Methods
1. EDITOR lines: Stable maize B104 lines expressing Cas9 were created as a basis for super-transformations. New lines with different editing efficiencies (from saturation to low-order editing) were generated to expand experimental flexibility.
2. Target selection: Based on literature and in-house data, 59 genes linked to plant growth and drought tolerance were chosen. Guide RNAs (gRNAs) targeting coding regions were designed using the SMAP design bioinformatic tool, ensuring efficiency and minimal off-target effects.
3. SCRIPT constructs and transformation: Five constructs containing 12 gRNAs each were cloned, targeting all 60 genes in total. These were introduced into EDITOR lines using Agrobacterium-mediated transformation to produce T0 material expressing Cas9 and gRNAs.
4. Genotyping-by-sequencing pipeline: Multiplex amplicon sequencing coupled with the SMAP haplotype pipeline allowed precise detection of mutations. Out-of-frame indels were prioritized as likely gene knockouts. Genetic outcomes were categorized into null, hemi, and full knockouts, better reflecting dosage effects compared to classical heterozygous/homozygous distinctions.
5. Crossing schemes: Intra- and inter-SCRIPT crosses, as well as selfings, were performed to combine edits and increase knockout frequencies. Transgenerational editing was observed, generating new edits in successive generations.
6. Phenotyping: More than 6,000 seedlings were screened for leaf size and other growth traits, followed by mature-plant phenotyping to confirm causative edits. Traits such as plant architecture, stem thickness, and yield potential were associated with specific edits.
7. Data analysis: Machine learning and statistical approaches enabled phenotype–genotype association in highly diverse populations where each plant carried unique combinations of edits. This allowed the identification of both single-gene effects and synergistic gene interactions.
Results and Exploitation
The project generated a wealth of edited maize populations and established a comprehensive genotype–phenotype dataset. Clear growth-related phenotypes, such as larger leaves, modified architecture, and improved biomass and seed yield potential, were directly linked to edits in specific genes and gene combinations. These findings validate the power of multiplex gene editing in unraveling complex regulatory networks.
Greenhouse trials confirmed the robustness of many edits, but validation under field conditions is essential. Starting in 2025, field trials will test promising gene-edit combinations across three consecutive years and in hybrid maize backgrounds to ensure relevance under real-world agricultural settings. This step will be crucial for transferring BREEDIT outcomes into practical breeding pipelines.
