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Candidate genes with antagonistic roles in stomatal development are associated with population-wide variation in apple

Jul 2026 · Horticulture Research · Vol 13 · 1 citation · 105 references
Medicine

TL;DR

The variation in stomatal density in a diverse apple population consisting of 269 accessions is investigated to provide a foundation for understanding SD variation at the population scale and opportunities to modulate SD by genomics-assisted breeding strategies.

Abstract

Abstract A sustainable approach to address climate change and increasing water demand in agriculture is breeding for plant functional traits that conserve water and enhance climate resilience. Stomata regulate plant–water relations and are promising targets for crop improvement. Here, we investigate the variation in stomatal density (SD) in a diverse apple population (Malus domestica Borkh.) consisting of 269 accessions. Genome-wide association studies identified robust associations with SD on chromosomes 2, 9, and 10 (classified as SNPs with a P-value higher than adjusted Bonferroni threshold of −log10(P) > 8.78 that were consistently identified across datasets). On chromosome 9, a candidate gene that negatively regulates stomatal development, EPIDERMAL PATTERNING FACTOR 1 (EPF1), was identified inside a genomic region of 241 kb determined by six robust associations. On chromosome 10, a positive regulator candidate gene, EPIDERMAL PATTERNING FACTOR LIKE 9 (STOMAGEN), was identified 1680 kb from the robust association. Identification of positive (STOMAGEN) and negative (EPF1) regulators of SD suggest potential antagonistic roles at the population scale in determining SD. On chromosome 2, a gene co-expression analysis identified a gene cluster containing both EPF1 and STOMAGEN together with a novel candidate gene, CYTOCHROME P450 (CYP77A4), that was located 544 kb from the robust association. The percentage of SD phenotypic variance explained by each robust association was between 7% and 10%. These findings provide a foundation for understanding SD variation at the population scale and opportunities to modulate SD by genomics-assisted breeding strategies.

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