Collaborative Research: Mechanisms of Malleability and Resilience of Flowering Responses to Current and Future Variability in Seasonal Cues in a Geographically-widespread Species

许多对植物生长和繁殖至关重要的环境因素随着季节的变化而变化。植物应对这种挑战的一个基本方法是通过监测日长，这是最可靠地预测日历日期的环境信号。根据这些信息，个体要么继续营养生长，要么开始开花。一年中开花的最佳时间因地点而异。例如，在高纬度和海拔地区，冬天来得早。因此，了解光周期开花反应如何以及为什么被调整以允许物种在广泛的地理范围内茁壮成长是重要的知识，可以为保护生物多样性和在面对不断变化的环境时成功管理作物提供信息。这项工作将通过研究常见的猴花（Mimulus guttatus）在诱导开花所需的关键日长中如何沿着海拔梯度变化来实现这一目标。这种变异的分子变化和生态影响将在实验室和实地进行补充研究。然后，这些综合数据集将允许开发预测模型，以测试人口是否能够适应未来的气候。这些研究人员——与加州大学三所研究所的本科生、美国国家物候学网络和志愿者一起工作——还将开发一项新的公民科学计划，以监测太平洋屋脊小道沿线偏远高山地区重要野花物种的开花情况。尽管人们对光周期在受控条件下调控开花的分子机制了解甚多，但对这些途径在自然季节条件下如何发挥作用，以及对这些途径进行哪些调整可能在未来气候中被证明是有益的，人们知之甚少。初步研究表明，在关键的光周期中，复制的高度变化是通过不同位点的变化来进化的。本研究将利用这一新兴模式植物系统中广泛的基因组工具包来描述这些不同机制的遗传基础和生理后果。具体来说，将建立临界光周期大范围变化的分子基础。通过受控条件下的转录分析和田间试验，研究人员还将测试在关键光周期中实现类似转变的不同基因座组是通过开花基因调控网络中下游表达的等效修改来实现的，还是具有适应每个局部环境的独特作用。前者的发现将表明生理系统具有适应新环境的广泛能力，后者将表明遗传变异可能被证明是适应速度的重要限制。最后，通过对一年生木桐中丰富而在其他模式植物中未被充分探索的多样性形式的研究，本研究将扩展开花时间的生态生理模型，并有助于更准确地预测环境变化对植物生长和种群分布的影响。

Many environmental factors critical for plant growth and reproduction vary in abundance from season to season. A fundamental means by which plant species cope with this challenge is through monitoring day length, the environmental signal that most reliably predicts calendar date. Based on that information, individuals then either continue vegetative growth or initiate flowering. The most favorable time of year for flowering differs by location. For instance, winter arrives earlier at higher latitudes and elevations. Therefore, understanding how and why photoperiodic flowering responses have been adjusted to permit species to thrive across broad geographic ranges is important knowledge that can inform efforts to preserve biodiversity and successfully manage crops in the face of a changing environment. The proposed work will address this goal by studying how populations of the common monkeyflower, Mimulus guttatus, vary along elevation gradients in the critical day length necessary to induce flowering. The molecular changes and ecological impacts of this variation will be investigated with complementary studies in the lab and field. These combined datasets will then permit development of predictive models to test whether populations will be resilient to future climates. The investigators - working with undergraduates at three University of California institutions, the USA National Phenology Network, and volunteers - will also develop a new citizen science initiative to monitor the flowering of important wildflower species in remote alpine locations along the Pacific Crest Trail.Although much is known about the molecular mechanisms by which photoperiod regulates flowering in controlled conditions, far less is understood about how these pathways function in natural seasonal conditions or what adjustments to these pathways may prove beneficial in future climates. Preliminary work in M. guttatus has shown that replicate altitudinal shifts in critical photoperiod evolved through changes at distinct sets of loci. The proposed research will characterize the genetic basis and physiological consequences of these diverse mechanisms by utilizing the extensive genomic toolkit available in this emerging model plant system. Specifically, the molecular basis of range-wide variation in critical photoperiod will be established. Through transcriptional analyses under controlled conditions and through field trials, the investigators will also test whether the distinct sets of loci that achieve similar shifts in critical photoperiod do so via equivalent modifications of downstream expression within the flowering gene regulatory network or have unique effects that are adaptive within each local environment. The former finding would suggest a broad capacity for physiological systems to adjust to novel conditions, and the latter would suggest genetic variation may prove a significant constraint on the pace of adaptation. Finally, through investigating forms of diversity abundant in annual M. guttatus but not well explored in other model plants, the proposed research will extend ecophysiological models of flowering time and foster more accurate forecasts of the impact of environmental variation on plant growth and population distribution.