Genome-wide association analysis of flowering date in a collection of cultivated olive tree

Abstract

Flowering date in perennial fruit trees is an important trait for fruit production. Depending on the winter and spring temperatures, flowering of olive may be advanced, delayed, or even suppressed. Deciphering the genetic control of flowering date is thus key to help selecting cultivars better adapted to the current climate context. Here, we investigated the genetic determinism of full flowering date stage in cultivated olive based on capture sequencing data of 318 genotypes from the worldwide olive germplasm bank of Marrakech, Morocco. The genetic structure of this collection was organized in three clusters that were broadly attributed to eastern, central, and western Mediterranean regions, based on the presumed origin of genotypes. Flowering dates, collected over 7 years, were used to estimate the genotypic best linear unbiased predictors, which were then analyzed in a genome-wide association study. Loci with small effects were significantly associated with the studied trait, by either a single- or a multi-locus approach. The three most robust loci were located on chromosomes 01 and 04, and on a scaffold, and explained 7.1%, 6.2%, and 6.5% of the trait variance, respectively. A significantly higher accuracy in the best linear unbiased predictors of flowering date prediction was reported with Ridge- compared to LASSO-based genomic prediction model. Along with genomic association results, this suggests a complex polygenic determinism of flowering date, as seen in many other fruit perennials. These results and the screening of associated regions for candidate genes open perspectives for further studies and breeding programs targeting flowering date.

Acknowledgements

We thank Hélène Vignes, Ronan Rivallan, and Anaïs Fossot for the laboratory help. Analyses were conducted on MESO@LR-Platform at the University of Montpellier with the help of members of the French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform. We also thank Marie Denis and David Cros for their advice in the use of RKHS model. L.A. was funded by an IOC scholarship (N° 2021-03- PhD GRANT). This study was funded through Labex AGRO 2011 - LABX-002, project n° 2003-001 (under I-Site Muse framework) coordinated by Agropolis Foundation.

Author contributions

Research design: B.K. and A.E. Laboratory experiment design: L.Z. and P.M. Laboratory work: L.A., F.B., and P.M. Resources, phenotypic data acquisition, and curation: O.A., A.E., and H.Z. Genotypic data acquisition and curation: L.A. and G.S. Data analysis and interpretation of results: L.A., P.C., G.S., E.C., B.K., and V.S. PhD Supervision: E.C., P.C., G.S., and B.K. Writing: L.A., E.C., and P.C. Review & editing: all authors.

Data availability

Raw sequences data are available in the following database: ClimOliveMed; 2023;GenomiCOM: ClimOliveMed Genomic resources for research on adaptation of olive tree to climate change; European Nucleotide Archive; 2023-04-17; PRJEB61410. Scripts used in this study are available in the GitHub repository: https://github.com/laqbouch/Genetic_determinism_of_cultivated_olive.git.

Conflict of interest statement

The authors declare no competing interests.

Supplementary Data

Supplementary data is available at Horticulture Research online.

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