Oral Presentation International Plant Molecular Biology Conference 2024

Environmental robustness of allopolyploid species in natura: field genomic and image analysis using machine learning-based phenotyping method PlantServation (#531)

Kentaro Shimizu 1 2 , Reiko Akiyama 1 , Takao Goto 3 , Toshiaki Tameshige 2 , Jiro Sugisaka 2 , Ken Kuroki 4 , Jianqiang Sun 5 , Junichi Akita 6 , Masaomi Hatakeyama 1 , Hiroshi Kudoh 7 , Tanaka Kenta 8 , Aya Tonouchi 3 , Yuki Shimahara 3 , Jun Sese 9 , Natsumaro Kutsuna 3 , Rie Shimizu-Inatsugi 1 , Atsushi G Nagano 10 11 , Yoko Kamiya 12 , Ryohei Fujita 1 12
  1. Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
  2. Kihara Institute for Biological Research, Yokohama City University, Yokohama, Kanagawa, Japan
  3. Research and Development Division, LPIXEL Inc., Takyo, Japan
  4. Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
  5. Research Center for Agricultural Information Technology, National Agriculture and Food Research Organization, Ibaraki, Japan
  6. Department of Electric and Computer Engineering, Kanazawa University, Kanazawa, Japan
  7. Center for Ecological Research, Kyoto University, Kyoto, Japan
  8. Sugadaira Research Station, Mountain Science Center, University of Tsukuba, Ueda, Japan
  9. Artificial Intelligence Research Center AIST, Tokyo, Japan
  10. Faculty of Agriculture, Ryukoku University, Shiga, Japan
  11. Institute for Advanced Biosciences, Keio University, Yamagata, Japan
  12. Yokohama City University, Yokohama, Japan

More than 50 years ago, Ledyard Stebbins (1971) proposed that polyploid species are generalists that can tolerate a wide range of environmental conditions. However, little has been known about the underlying mechanisms of environmental robustness of polyploid species. Using a model allopolyploid species Arabidopsis kamchatica, we developed bioinformatic tools for genomic analysis, and PlantServaton, a machine learning-based phenotyping method in natura, or in naturally fluctuating environments. To test whether the allotetraploid A. kamchatica inherited and combined the environmental responses of the two diploid progenitor species A. halleri and A. lyrata, we grew these species and A. thaliana for three seasons at two field locations. We analyzed > 4 million images (12 genotypes × 20 replicates × 2 sites × 16–24 images/day × 150 days/year × 3 years). We estimated anthocyanin content as a proxy of stress, and examined environmental and genotypic effects on it. Anthocyanin content was affected by past radiation, coldness and precipitation in the naturally fluctuating conditions, consistent with the previous studies in regulated chamber conditions. Synthetic polyploids combined responses of diploid progenitor species and recapitulated the response of natural polyploid genotypes. These data support the combined environmental responses of polyploid species.

  1. Akiyama R, Goto T, Tameshige T, Sugisaka J, Kuroki K, Sun J, Akita J, Hatakeyama M, Kudoh H, Kenta T, Tonouchi A, Shimahara Y, Sese J, Kutsuna N, Shimizu-Inatsugi R, Shimizu KK. Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation. Nature Communications 2023 Sep 22;14(1):5792. doi: 10.1038/s41467-023-41260-3
  2. Shimizu KK. Robustness and the generalist niche of polyploid species: Genome shock or gradual evolution? Curr Opin Plant Biol. 2022 Oct;69:102292. doi: 10.1016/j.pbi.2022.102292