Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
Research and Development Initiative, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan.
G3 (Bethesda). 2023 Dec 6;13(12). doi: 10.1093/g3journal/jkad218.
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.
一个种群会遇到各种各样的环境压力，因此只有通过收集种群历史中对当地环境选择的所有适应特征的全部特征，才能捕捉到其全部适应能力的来源。基于拟南芥的多组学数据，我们构建了一个表型适应（p-适应）和基因表达（e-适应）适应的数据库。通过对已确定的适应特征进行富集分析，我们推断出一个可能的适应情景，该情景与来自实验工作的生物学证据一致。我们分析了 174 个性状的 23880 个 QTL 和 1829 个基因的 8618 个 eQTL 相对于基因组中总 SNP 的等位基因频率动态，并确定了 650 个 p-适应和 3925 个 e-适应（错误发现率（FDR）= 0.05）。种群沿着 4 条谱系经历了大规模的 p-适应和 e-适应。极冷的冬天和短暂的夏天延长了种子休眠期并扩展了根系结构。低温延长了生长季节，低光照强度需要增加叶绿体活性。亚热带和潮湿的环境增强了植物激素信号通路，以应对生物和非生物胁迫。暴露于重金属选择了从土壤中吸收较低重金属、生长速度较慢、对细菌的抵抗力较低和光合作用基因表达较高的等位基因。p-适应可以直接解释，而共适应的基因表达反映了适应的生理需求。整合这些信息可以描述种群何时何地经历了环境压力，以及种群在分子水平上的反应方式。
