Almond population genomics and non-additive GWAS reveal new insights into almond dissemination history and candidate genes for nut traits and blooming time

Abstract

Domestication drastically changed crop genomes, fixing alleles of interest and creating different genetic populations. Genome-wide association studies (GWASs) are a powerful tool to detect these alleles of interest (and so QTLs). In this study, we explored the genetic structure as well as additive and non-additive genotype–phenotype associations in a collection of 243 almond accessions. Our genetic structure analysis strongly supported the subdivision of the accessions into five ancestral groups, all formed by accessions with a common origin. One of these groups was formed exclusively by Spanish accessions, while the rest were mainly formed by accessions from China, Italy, France, and the USA. These results agree with archaeological and historical evidence that separate modern almond dissemination into four phases: Asiatic, Mediterranean, Californian, and southern hemisphere. In total, we found 13 independent QTLs for nut weight, crack-out percentage, double kernels percentage, and blooming time. Of the 13 QTLs found, only one had an additive effect. Through candidate gene analysis, we proposed Prudul26A013473 as a candidate gene responsible for the main QTL found in crack-out percentage, Prudul26A012082 and Prudul26A017782 as candidate genes for the QTLs found in double kernels percentage, and Prudul26A000954 as a candidate gene for the QTL found in blooming time. Our study enhances our knowledge of almond dissemination history and will have a great impact on almond breeding.

Acknowledgements

We acknowledge Dr. Vincent Segura for his incisive comments reviewing this paper, substantially improving it. We acknowledge financial support from the grants SEV-2015-0533 and CEX2019-000902-S, PID2019-110599RR-I00, and PID2020-118612RR-I00 (Better Almonds) funded by MCIN/AEI/ 10.13039/501100011033; the Grant RTA2017-00084-00-00 funded by MCIN/AEI/ 10.13039/ 501100011033 and by ‘ESF Investing in your future’; the Grant PCI2019-103670 funded by MCIN/AEI/ 10.13039/501100011033 and co-financed by the European Union; and to the project ANR-18-PRIM-0001 (FREECLIMB) funded by the French National Research Agency. Finally, the grant of F.P.C. PRE2018-086724 funded by MCIN/AEI/ 10.13039/501100011033 and by ‘ESF Investing in your future’. This work has been carried out within the framework of F.P.C.’s PhD in Plant Biology and Biotechnology at the Autonomous University of Barcelona.

Author Contributions

F.P.C.: conceptualization, analysis, and writing the original draft. E.C.: conceptualization, analysis and writing the original draft. N.D.: laboratory tasks and analysis. B.Q.T.: supervision, reviewing and editing. I.B.: supervision, reviewing, editing and project management. P.A.: supervision, reviewing, editing and project management. I.E.: conceptualization, supervision, reviewing, editing, project management and seeking funding. H.D.: conceptualization, supervision, reviewing, editing, project management and seeking funding.

Conflict of Interest

The authors declare that they have no conflict of interest.

Data Availability

All resequences used in this study can be found at NCBI under the following accession numbers: SRR3141040, SRR3141049, SRR3141057, SRR3141065, SRR3141073, SRR3141083, SRR3141098, SRR3141113, SRR3141181, SRR3141192, SRR3141204, SRR3141229, SRR4036105, SRR4045224, SRR4045225, SRR4045227, SRR4045228, SRR4045229.

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