The timing of flowering in fruit trees is tightly regulated by seasonal temperature cues. Warmer winters may hinder chilling requirements, delaying floral induction, while warmer springs may trigger early blooming, increasing frost risk. For cross-pollinated species like olive, mismatches in flowering periods between compatible varieties can reduce pollination success and compromise yields. Previous studies using quantitative trait locus (QTL) mapping and genome-wide association studies (GWAS) have clarified flowering control in apple, peach, and apricot, but olives\u2014iconic to the Mediterranean Basin and highly vulnerable to climate warming\u2014have not been comprehensively examined. Due to these challenges, there is a pressing need to investigate the genetic control of flowering date in olives.<\/p>\n
A team of researchers from Montpellier, Marrakech, and partner institutions published (DOI: 10.1093\/hr\/uhae265)<\/a> their study on September 24, 2024, in Horticulture Research<\/a>. The article explores the genetic determinants of olive flowering time. By analyzing seven years of phenological data together with high-density single nucleotide polymorphism (SNP) markers, the study pinpoints specific loci influencing flowering date and demonstrates the value of genomic prediction approaches for future olive breeding programs.<\/p>\n The researchers assessed 318 genotypes from the Worldwide Olive Germplasm Bank of Marrakech, representing the genetic diversity of eastern, central, and western Mediterranean regions. Using capture sequencing, they identified over 235,000 high-quality SNPs, later refined to ~119,000 for association analyses. Flowering dates recorded over seven years were modeled using best linear unbiased predictors, yielding a broad-sense heritability of 0.84. GWAS revealed three robust loci: on chromosome 1, chromosome 4, and scaffold s04305, explaining 6.2\u20137.1% of trait variance. Candidate genes within these regions included OE9A117378 and OE9A084268, homologs of the XAP5 circadian timekeeper (XCT) gene, and OE9A057547, a signal peptidase complex subunit. Genomic prediction models further supported a polygenic determinism of flowering date. Ridge regression and Reproducing Kernel Hilbert Space approaches significantly outperformed LASSO models, achieving prediction accuracies above 0.63. These results indicate that flowering date is controlled by many small-effect loci, a pattern common in perennial fruit trees, and provide a foundation for molecular breeding aimed at optimizing flowering under climate change.<\/p>\n \u201cOlive cultivation is at the heart of Mediterranean agriculture, yet its reproductive cycle is increasingly threatened by shifting climate conditions,\u201d said Evelyne Costes, senior author of the study. \u201cBy identifying genetic regions and candidate genes controlling flowering date, we are paving the way for breeding strategies that can sustain production under future environments. The integration of genomic prediction tools into olive breeding programs will accelerate the development of cultivars better adapted to warmer winters and earlier springs, safeguarding both farmer livelihoods and global olive oil supply chains.\u201d<\/p>\n The discovery of genetic markers linked to flowering time in olive opens new opportunities for marker-assisted and genomic selection in breeding. By incorporating these loci into predictive models, breeders can design cultivars that synchronize flowering for reliable pollination, withstand climatic fluctuations, and maintain consistent yields. Such advances are crucial for the Mediterranean Basin, where climate change poses direct risks to olive productivity and rural economies. Beyond olives, this research also serves as a model for studying flowering genetics in other perennial fruit crops, strengthening global food security through climate-smart crop improvement.<\/p>\n ###<\/p>\n References<\/p>\n DOI<\/strong><\/p>\n 10.1093\/hr\/uhae265<\/a><\/p>\n Original Source URL<\/strong><\/p>\n https:\/\/doi.org\/10.1093\/hr\/uhae265<\/a><\/p>\n Funding information<\/strong><\/p>\n L.A. was funded by an IOC scholarship (N\u00b0 2021-03- PhD GRANT). This study was funded through Labex AGRO 2011 \u2013 LABX-002, project n\u00b0 2003-001 (under I-Site Muse framework) coordinated by Agropolis Foundation.<\/p>\n