Genetic characterisation and mathematical modelling of speed-breeding plasticity in barley.

随着人口结构、城市化和苏格兰宣布的气候紧急情况的变化，需要更可持续地利用资源。培育适应气候变化的作物的重要性从未如此突出。已经提出了围绕颠覆性技术部署建立的各种方法（Hickey et al . 2017），以提高育种的速度和精度。其中一项技术是快速育种，旨在加速植物发育，特别是基于延长光照制度的开花时间（Watson et al. 2018）。尽管这个概念在经验上已经很先进了，但人们对基础生物学和昼夜节律时钟和光周期途径的潜在破坏知之甚少。植物育种家经常操纵光照和温度，通过采用单种子下降的方法来缩短一代时间，加快育种周期。这种方法可能为快速繁殖的反应型引入了无意识的选择。SRUC获得的初步数据证实，通过加速育种培育的现代大麦品种与较老的品种和陆地品种在对快速育种制度的反应方面存在遗传差异。这些观察结果提供了实验框架，以确定快速育种的关键遗传决定因素，以及大麦这一重要经济作物中生物钟相关成分和基因组可塑性选择的后果。此外，揭示可塑性遗传学以加快育种速度，为培育气候适应性作物带来了机会。我们建议确定速度繁殖可塑性的关键决定因素。我们将把大麦作为生态适应的典范和苏格兰的重要作物。现代优质大麦种质以及不太可能经历快速循环育种干预无意识选择的旧品种将被筛选为快速育种可塑性。这将通过暴露于快速繁殖环境后恢复正常生长的程度来衡量。我们的初步数据表明，从持续快速发育到恢复正常发育速率的植物反应变化将被检测到。这种可塑性将通过诸如下一代极端体积测序等方法来绘制。此外，将采用系统生物学方法（Chew et al. 2017），进一步深入了解对快速育种的反应。总的来说，我们的目标是将我们对快速育种的理解从经验方法转移到一种预测使能技术，这种技术可以直接应用于对选择对基因组可塑性的影响知之甚少的预育种。该项目将为学生提供现代植物育种、数学和系统生物学方面的跨学科培训。在植物育种和数量遗传学方面的培训将通过我们在SRUC的团队提供，在系统生物学和数学建模方面的培训将通过我们的项目合作伙伴，爱丁堡大学（UoE）的Karen Halliday教授提供，进一步加强学生的培训。watson et al.（2018）快速育种是加快作物研究和育种的有力工具。自然植物4:23-29。Chew et al.（2017）多尺度建模协同植物系统生物学和作物科学。农田作物研究15:77-83。Hickey et al.（2017）基因组预测将动物和植物育种计划统一起来，形成生物发现平台。自然遗传，49(9):1297-1303。

With changes in population demographics, urbanisation and the declared climate emergency in Scotland there is a need to use resources more sustainably. The importance of breeding climate resilient crops has never been greater. Various approaches built around the deployment of disruptive technologies (Hickey et al 2017) have been proposed to increase the pace and precision of breeding. One such technology is speed breeding which is designed to accelerate plant development, particularly flowering time based on extended light regimes (Watson et al. 2018). Although the concept is empirically well advanced the underpinning biology and potential disruption of the circadian clockwork and photoperiod pathways is poorly understood. Plant breeders regularly manipulate light and temperature to reduce generation time and hasten the breeding cycle through the adoption of single seed descent approaches. This approach may have introduced unconscious selection for speed-breeding responsive types. Preliminary data obtained at SRUC have confirmed that there are genetic differences between modern barley varieties developed through accelerated breeding and older varieties and land races in their response to speed breeding regimes. These observations provide the experimental framework to identify the key genetic determinants of speed breeding and the consequences of selection on clock associated components and genomic plasticity in an economically important crop, barley. Furthermore, unravelling the genetics of plasticity to speed breeding brings the opportunity to deliver step changes in the breeding of climate resilient crops.We propose to identify key determinants of speed-breeding plasticity. We will use barley as a model for ecological adaptation and an important crop for Scotland. Modern elite barley germplasm along with older varieties that are less likely to have undergone unconscious selection from rapid cycling breeder interventions will be screened for speed breeding plasticity. This will be measured by extent of reversion to normal growth after exposure to a speed breeding environment. Our preliminary data indicate that variation in plant responses ranging from continued rapid development to reversion to normal rates of developmental will be detected. This plasticity will be mapped by methods such as next generation sequencing of the extreme bulks. Additionally, system biology approaches (Chew et al. 2017) will be deployed to provide further and deeper understanding of the response to speed breeding. Overall, we aim to move our understanding of speed breeding from an empirical approach to a predictive enabling technology that can be directly applied in pre-breeding where little is known about the consequences of selection on genome plasticity. This project will provide interdisciplinary student training in modern plant breeding mathematical and systems biology. Training in plant breeding and quantitative genetics will be provided through our group in SRUC, and training in systems biology and mathematical modelling will be available through our project partner, Prof. Karen Halliday, University of Edinburgh (UoE), further enhancing the training of the student.ReferencesWatson et al. (2018) Speed breeding is a powerful tool to accelerate crop research and breeding. Nature Plants 4: 23-29.Chew et al. (2017) Multi-scale modelling to synergise plant systems biology and crop science. Field Crop Research 15: 77-83.Hickey et al. (2017) Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery. Nature Genetics 49(9): 1297-1303.