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Dynamic effects of interacting genes underlying rice flowering-time phenotypic plasticity and global adaptation

机译:水稻开花时间表型可塑性互动基因的动态效应及全球适应

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摘要

The phenotypic variation of living organisms is shaped by genetics, environment, and their interaction. Understanding phenotypic plasticity under natural conditions is hindered by the apparently complex environment and the interacting genes and pathways. Herein, we report findings from the dissection of rice flowering-time plasticity in a genetic mapping population grown in natural long-day field environments. Genetic loci harboring four genes originally discovered for their photoperiodic effects (Hd1, Hd2, Hd5, and Hd6) were found to differentially respond to temperature at the early growth stage to jointly determine flowering time. The effects of these plasticity genes were revealed with multiple reaction norms along the temperature gradient. By coupling genomic selection and the environmental index, accurate performance predictions were obtained. Next, we examined the allelic variation in the four flowering-time genes across the diverse accessions from the 3000 Rice Genomes Project and constructed haplotypes at both individual-gene and multigene levels. The geographic distribution of haplotypes revealed their preferential adaptation to different temperature zones. Regions with lower temperatures were dominated by haplotypes sensitive to temperature changes, whereas the equatorial region had a majority of haplotypes that are less responsive to temperature. By integrating knowledge from genomics, gene cloning and functional characterization, and environment quantification, we propose a conceptual model with multiple levels of reaction norms to help bridge the gaps among individual gene discovery, field-level phenotypic plasticity, and genomic diversity and adaptation.
机译:生物体的表型变异是由遗传,环境,和它们的相互作用形。在自然条件下理解表型可塑性是由明显复杂的环境和相互作用的基因和途径受阻。在此,我们在自然长日的现场环境中生长的遗传作图群体汇报水稻开花时间的可塑性的解剖结果。基因位点窝藏四个基因最初发现他们的光周期效应(HD1,HD2,HD5,HD6和)被发现于温度差异响应在早期生长阶段共同决定开花时间。这些可塑性基因的影响,揭示沿着温度梯度多重反应的规范。通过结合基因组选择与环境指数,获得准确的性能预测。接下来,我们检查了对面的3000水稻基因组计划的不同加入和构建单倍型的四处开花时间基因的等位基因变异在个体基因和多基因的水平。单倍型的地理分布透露了自己的优惠适应不同的温度区。用较低的温度区通过单倍型对温度变化敏感为主,而赤道区域有多数那些对温度较不敏感的单倍型。通过从基因组学,基因的克隆和功能特性,以及环境定量整合知识,我们提出用的反应规范多层次的帮助下,概念模型桥之间的个体基因的发现,字段级表型可塑性和基因组多样性和适应的空白。

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