Natural variation in IBF1 confers antimicrobial activity through altered flavonoid accumulation in rice hulls

Abstract Secondary metabolites perform diverse physiological functions, and studies have identified genes and mechanisms underlying their biosynthesis. However, the genetic basis of intraspecific variation in secondary metabolism remains poorly understood, particularly in less-studied tissues such as rice hulls. In this study, we identified variants in the F-box protein IBF1 that underlie genotypic differences in hull color and flavonoid accumulation using positional cloning. While IR64 (straw-white hull) harbors the functional IBF1, DJ123 (pigmented hull) harbors frame-shift mutations that result in the loss of a Kelch domain. Yeast two-hybrid analysis showed that all three Kelch domains of IBF1 are required for interaction with chalcone synthase 1 (CHS1). Accordingly, the DJ123 variant (IBF1DJ123) does not interact with CHS1. This finding was further supported by deep learning-based structural modeling. An IR64-based chromosomal segment substitution line (CSSL) carrying IBF1DJ123 showed increased flavonoid content and reduced expression of CAD, a gene involved in lignin synthesis, compared to IR64. Metabolites in the CSSL suppressed the growth and siderophore generation activity of Pantoea species, which can act as beneficial or pathogenic endophytes. This study highlights the impact of a single gene on diverse metabolite accumulation patterns and suggests that such variation may be exploited for defense against pathogens.

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Publication Details

Journal
Journal of Experimental Botany
Published
2026-09-15
DOI
https://doi.org/10.1093/jxb/erag461
Primary Topic
Plant Gene Expression Analysis
Type
article
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article

Natural variation in IBF1 confers antimicrobial activity through altered flavonoid accumulation in rice hulls

Matthias Wissuwa, Takuma Ishizaki, Nozomu Sakurai, Yoshinori Murata et al.
Journal of Experimental Botany
Plant Gene Expression Analysis
article

Natural variation in IBF1 confers antimicrobial activity through altered flavonoid accumulation in rice hulls

Matthias Wissuwa, Takuma Ishizaki, Nozomu Sakurai, Yoshinori Murata, Hideki Takanashi, Juan Pariasca Tanaka, Yoshiaki Ueda, T. Ogata, Yasunari Fujita, Katsuhiko Kondo, Hiroki Saito
article en

Abstract

Abstract Secondary metabolites perform diverse physiological functions, and studies have identified genes and mechanisms underlying their biosynthesis. However, the genetic basis of intraspecific variation in secondary metabolism remains poorly understood, particularly in less-studied tissues such as rice hulls. In this study, we identified variants in the F-box protein IBF1 that underlie genotypic differences in hull color and flavonoid accumulation using positional cloning. While IR64 (straw-white hull) harbors the functional IBF1, DJ123 (pigmented hull) harbors frame-shift mutations that result in the loss of a Kelch domain. Yeast two-hybrid analysis showed that all three Kelch domains of IBF1 are required for interaction with chalcone synthase 1 (CHS1). Accordingly, the DJ123 variant (IBF1DJ123) does not interact with CHS1. This finding was further supported by deep learning-based structural modeling. An IR64-based chromosomal segment substitution line (CSSL) carrying IBF1DJ123 showed increased flavonoid content and reduced expression of CAD, a gene involved in lignin synthesis, compared to IR64. Metabolites in the CSSL suppressed the growth and siderophore generation activity of Pantoea species, which can act as beneficial or pathogenic endophytes. This study highlights the impact of a single gene on diverse metabolite accumulation patterns and suggests that such variation may be exploited for defense against pathogens.

Journal of Experimental Botany
University of Bonn (DE), University of Tsukuba (JP), Japan International Research Center for Agricultural Sciences (JP), Food Research Institute (JP), Kanagawa Odawara Nursing School (JP), Kazusa DNA Research Institute (JP), The University of Tokyo (JP)
Life below water
Openalex Percentile: Top 18%
Plant Gene Expression Analysis
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