RRC ID 72629
Author Andi Madihah Manggabarani, Takuyu Hashiguchi, Masatsugu Hashiguchi, Atsushi Hayashi, Masataka Kikuchi, Yusdar Mustamin, Masaru Bamba, Kunihiro Kodama, Takanari Tanabata, Sachiko Isobe, Hidenori Tanaka, Ryo Akashi, Akihiro Nakaya, Shusei Sato
Title Construction of prediction models for growth traits of soybean cultivars based on phenotyping in diverse genotype and environment combinations
Journal DNA Research
Abstract As soybean cultivars are adapted to a relatively narrow range of latitude, the effects of climate changes are estimated to be severe. To address this issue, it is important to improve our understanding of the effects of climate change by applying the simulation model including both genetic and environmental factors with their interactions (G×E). To achieve this goal, we conducted the field experiments for soybean core collections using multiple sowing times in multi-latitudinal fields. Sowing time shifts altered the flowering time (FT) and growth phenotypes, and resulted in increasing the combinations of genotypes and environments. Genome-wide association studies for the obtained phenotypes revealed the effects of field and sowing time to the significance of detected alleles, indicating the presence of G×E. By using accumulated phenotypic and environmental data in 2018 and 2019, we constructed multiple regression models for FT and growth pattern. Applicability of the constructed models was evaluated by the field experiments in 2020 including a novel field, and high correlation between the predicted and measured values was observed, suggesting the robustness of the models. The models presented here would allow us to predict the phenotype of the core collections in a given environment.
Volume 29
Published 2022-6-25
DOI 10.1093/dnares/dsac024
PMID 35916715
PMC PMC9358015
MeSH Alleles Genome-Wide Association Study* Genotype Phenotype Soybeans* / genetics
IF 4.009
Lotus / Glycine Soybean cultivars