HeredityGenomicsPeer-reviewed journal article
Insights from farming Macrocystis pyrifera offshore: phenotypic analysis, genome-wide association studies, genomic selection
Maxim KovaleviD, Gabriel J. MontecinosiD, Christie E. YorkeiD, Rachael M. WadeiD, Gary Molano, Robert James MilleriD, Daniel Reed, Filipe AlbertoiD, Sergey V. NuzhdiniD
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.
- assay: whole-genome sequencing
- research focus: genome assembly
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 41th percentile
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genotype and farm effects on yield and morphology reveal potential for breeding and site selection for sugar kelp
Sanne Put, Andries A. Temme, … Luisa M. Trindade·bioRxiv·May 13, 2026
- Genome-wide association study of morphometric and metabolic characteristics in the European populations of the sugar kelp Saccharina latissima
Stéphane Mauger, Komlan Avia, … Myriam Valéro·bioRxiv·Apr 28, 2026
- Climate stress priming of juvenile Southern California giant kelp (Macrocystis pyrifera) to thermal extremes
Lauren Leigh Smith, Briana Le, … Halley E. Froehlich·bioRxiv·Jan 6, 2026
- Comparison of the performance of sporophytes derived from narrow and wide genetic crosses between strains of the cultivated kelp Saccharina latissima
Zofia Nehr, Francis Le Madec, … Jeremy Mark Cock·bioRxiv·Oct 18, 2026
- Genomic selection in organisms with biphasic lifecycles: a Saccharina latissima (sugar kelp) case study
Mao Fang Huang, Kelly R. Robbins, … Jean‐Luc Jannink·bioRxiv·Aug 1, 2022
- Simulation of sugar kelp (Saccharina latissima) breeding guided by practices to prioritize accelerated research gains
Mao Fang Huang, Kelly R. Robbins, … Jean‐Luc Jannink·bioRxiv·Jan 21, 2021