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Updated: Jul 15, 2025

High-throughput, Robust and Highly Time-flexible Method for Surface Sterilization of Arabidopsis Seeds
Published on: October 4, 2021
Genetic adaptations in the population history of Arabidopsis thaliana
Hirohisa Kishino1,2, Reiichiro Nakamichi3, Shuichi Kitada4
1Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
Abstract:
A population encounters a variety of environmental stresses, so the full source of its resilience can only be captured by collecting all the signatures of adaptation to the selection of the local environment in its population history. Based on the multiomic data of Arabidopsis thaliana, we constructed a database of phenotypic adaptations (p-adaptations) and gene expression (e-adaptations) adaptations in the population. Through the enrichment analysis of the identified adaptations, we inferred a likely scenario of adaptation that is consistent with the biological evidence from experimental work. We analyzed the dynamics of the allele frequencies at the 23,880 QTLs of 174 traits and 8,618 eQTLs of 1,829 genes with respect to the total SNPs in the genomes and identified 650 p-adaptations and 3,925 e-adaptations [false discovery rate (FDR) = 0.05]. The population underwent large-scale p-adaptations and e-adaptations along 4 lineages. Extremely cold winters and short summers prolonged seed dormancy and expanded the root system architecture. Low temperatures prolonged the growing season, and low light intensity required the increased chloroplast activity. The subtropical and humid environment enhanced phytohormone signaling pathways in response to the biotic and abiotic stresses. Exposure to heavy metals selected alleles for lower heavy metal uptake from soil, lower growth rate, lower resistance to bacteria, and higher expression of photosynthetic genes were selected. The p-adaptations are directly interpretable, while the coadapted gene expressions reflect the physiological requirements for the adaptation. The integration of this information characterizes when and where the population has experienced environmental stress and how the population responded at the molecular level.
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