Biology

Reducing herbivory in mixed planting by genomic prediction of neighbor effects in the field

Y. Sato, R. Shimizu-inatsugi, et al.

Discover how genetically diverse populations can enhance plant resistance to herbivory! This research, conducted by Yasuhiro Sato, Rie Shimizu-Inatsugi, Kazuya Takeda, Bernhard Schmid, Atsushi J. Nagano, and Kentaro K. Shimizu, identifies key genotype pairs that reduce herbivore damage, demonstrating the impact of biodiversity through innovative genomic prediction techniques.

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Abstract

Genetically diverse populations can increase plant resistance to natural enemies. This study identifies key genotype pairs responsible for associational resistance to herbivory using genome-wide polymorphism data of *Arabidopsis thaliana*. A genome-wide association method named “Neighbor GWAS” and genomic prediction inspired by the Ising model predict that 823 of 19,701 candidate pairs can reduce herbivory. Field experiments with three predicted pairs showed 18–30% herbivore damage reduction in mixed planting, demonstrating the power of genomic prediction for assembling genotype mixtures with positive biodiversity effects.

Publisher

Nature Communications

Published On

Oct 07, 2024

Authors

Yasuhiro Sato, Rie Shimizu-Inatsugi, Kazuya Takeda, Bernhard Schmid, Atsushi J. Nagano, Kentaro K. Shimizu

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