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In situ evaluation of artificial selection and assisted gene flow for the advancement of flowering onset in Lupinus angustifolius L. (Fabaceae)

Sacristan-Bajo, S.; Garcia-Fernandez, A.; Lara-Romero, C.; Poyatos, C.; Rubio Teso, M. L.; Morente-Lopez, J.; Prieto-Benitez, S.; Torres, M. E.; Iriondo, J. M.

2025-07-27 evolutionary biology
10.1101/2025.07.23.666208 bioRxiv
Show abstract

Artificial selection and assisted gene flow represent promising conservation strategies for enhancing species adaptive capacity under accelerating climate change. We tested the application of artificial selection and assisted gene flow by evaluating progeny performance under field conditions, using Lupinus angustifolius L. (Fabaceae) as a model to advance flowering onset. Seeds were collected from four wild populations and two contrasting latitudes in Spain for parallel artificial selection and assisted gene flow three-year experiments. In the artificial selection treatment, we developed two early-flowering selection lines per population over three generations using both selfing and outcrossing. For assisted gene flow, we created F1 hybrids by crossing northern populations with southern pollen donors, then produced F2 and F3 generations through successive self-pollination. Finally, F3 seeds from this process were sown in autumn in a common garden under natural conditions, near the original population sites. Spring 2021 measurements of flowering onset and morphological traits revealed contrasting treatment effects. Artificial selection lines showed no significant phenotypic differentiation from controls across all measured traits, contradicting previous controlled-environment results. Conversely, assisted gene flow lines exhibited significantly earlier flowering and reduced shoot growth relative to controls, consistent with prior findings under controlled conditions. These results show greater efficacy of assisted gene flow over artificial selection for advancing flowering onset under natural conditions.

Published in Annals of Botany (predicted rank #5) · training set

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