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Orcid Publication

Detalle de: From Phenomics to Genomics: Macro-GWAS of Almond Morphology and Quality

Title From Phenomics to Genomics: Macro-GWAS of Almond Morphology and Quality
Abstract

In plant breeding and genetics, recent advances in high-throughput phenotyping are beginning to meet the growing demand for large-scale, high-quality phenotypic data that emerged after the development of next-generation sequencing technologies. Recent developments in phenomics have been incorporated into almond breeding programs, facilitating the large-scale acquisition of quantitative phenotypes and the dissection of the genetic architecture underlying morphological and quality-related traits. The implementation of a high-throughput phenotyping platform integrating RGB and hyperspectral imaging with genotyping using the 60K almond SNP array enabled the large-scale characterization of almond populations and the identification of 567 robust marker–trait associations across 66 traits. These analyses revealed two major genomic hotspots on chromosomes 2 and 5 associated with morphological and quality-related traits. These regions harbored biologically relevant candidate genes, including genes associated with OVATE family proteins, brassinosteroid signaling, protein ubiquitination, and acyl-CoA metabolism, as well as other regulators of organ growth, cell proliferation, hormone signaling, and seed development. Furthermore, a novel candidate gene encoding a COMT-like O-methyltransferase involved in lignin biosynthesis was identified and proposed to contribute to shell hardness, a major genetically controlled trait in almond. Together, these findings demonstrate the potential of integrating high-throughput phenomics and genomics to dissect complex traits, identify candidate genes, and accelerate genomics-informed breeding in almond.

Apa Reference Mas-Gómez, J., Rubio, M., Duval, H., Dicenta, F. & Martínez-García, P.J. (2026). From Phenomics to Genomics: Macro-GWAS of Almond Morphology and Quality. 10.64898/2026.07.06.736816
Doi 10.64898/2026.07.06.736816
Publication Date 7 Jul 2026
Publication Type Preprint
Researcher Pedro José Martínez García
Ontology Genomics, Population genomics, Development, Quantitative genetics
Research Groups
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