Green macroalgal blooms associated with the sea lettuce Ulva increase in intensity and frequency globally. Why some Ulva populations display this enormous growth potential, and other species or strains apparently do not, is currently unknown. It has been hypothesised that a genetic factor could underlie this capacity of bloom formation. Mapping populations enable the association of growth behaviour with underlying genetic regions. For that, efficient genotyping is necessary to characterise species identity and life stage in Ulva. Additionally, a standardised approach for growth quantification is currently lacking in macroalgae. This study demonstrates a workflow for an efficient genotyping pipeline using sex-specific markers for U. compressa/mutabilis. This way, thirty-five gametophytic lines sampled from three distant natural populations of conspecific U. compressa across Europe were successfully identified. Fragmentation-induced gametogenesis yields gametes that can be used in cross-experiments; however, strain-specific adaptations may be needed to raise efficiency. An automated phenotyping system was adapted to allow growth measurement over time in Ulva. The measured growth rates of a maximum of 8.4 % per day are sufficient to detect strain- and treatment-specific responses. The here-described genotyping and phenotyping workflow provides tools for creating and phenotyping mapping populations suitable for large-scale quantitative genetic studies in Ulva.
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