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bioRxiv · 10.1101/2025.09.22.677618

Insights from farming Macrocystis pyrifera offshore: phenotypic analysis, genome-wide association studies, genomic selection

Abstract

Seaweed farming, as a part of aquaculture, offers a sustainable alternative to modern agricultural practices; however, genetic enhancement and breeding programs for most species are underdeveloped. We aimed to advance seaweed domestication by focusing on giant kelp (Macrocystis pyrifera), the fastest-growing haplodiplontic brown alga, which has significant ecological and commercial importance. We analyzed phenotypic data from two offshore experimental farms conducted in 2019 and 2020, which involved hundreds of outplanted genetically diverse sporophytes. We found that outplanting season and farm design had significant effects on giant kelp biomass. Broad-sense heritability estimates showed moderate (0.27-0.50) genetic contributions to two phenotypes, carbon content and total biomass. Genome-wide association studies for these phenotypes resulted in three statistically significant SNPs, located near or within genes involved in carbohydrate metabolism and cytoskeletal functions. In addition, we applied genomic selection models that integrated sporophyte phenotypes and parental gametophyte genotypes. These models utilized reduced sets of GWAS-ranked SNPs obtained by a procedure based on linkage disequilibrium estimations. Model testing yielded cross-validation accuracy values of up to 0.84 and predictive accuracy values of up to 0.40, demonstrating the potential of marker-assisted breeding for phenotype improvement. Our results provide foundational genomic resources and tools for domesticating and breeding M. pyrifera, offering a basis for developing giant kelp varieties with desirable traits.

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Kovalev, M., Arismendi, G. M., Wade, R. M., Molano, G., Miller, R., Reed, D., Alberto, F., Nuzhdin, S.. 2025-09-24. Insights from farming Macrocystis pyrifera offshore: phenotypic analysis, genome-wide association studies, genomic selection. https://doi.org/10.1101/2025.09.22.677618

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