Evaluating epigenetic and transcriptomic adaptations to climate change in Brasicca napus (oilseed rape)

该项目的目的是提供热胁迫对英国特定品种甘蓝型油菜产量影响的系统水平的分子和代谢理解。这种系统生物学方法将通过监测DNAm和全球转录组分析以及油菜热胁迫下的代谢分析来实现。该项目的主要目标是：1。研究热胁迫对英国产甘蓝型油菜花前和花后授粉力和种子品质的影响热胁迫下甘蓝型油菜基因组dna位点特异性修饰及潜在基因组印迹的鉴定使用RNA-Seq进行转录组分析，以确定热应激导致的关键差异表达基因。利用obj的发现，通过基因调控网络的发展，整合表观遗传谱和相应的基因表达。研究了表观遗传对传粉肥力和种子品质的影响。开发机器学习模型，预测未来热胁迫对授粉肥力和种子质量的影响。使用决策树模型，甲基化位点和基因表达之间的相关性将被评估。接下来，将站点作为输入馈送到决策树中，以便按照重要性对这些站点进行排序，并最终估计代谢概况和表型性状（即授粉肥力和种子质量）作为输出变量。

The aim of this project is to provide a systems-level molecular and metabolic understanding of the impact of heat stress on yield of B. napus for UK-specific varieties. Such a systems biology approach will be achieved through monitoring DNAm and global transcriptome profiling in tandem with metabolic analysis of oilseed rape as a result of heat stress. The main objectives of the project are:1. Investigating the effect of heat stress on two UK-grown lines on pollination fertility and seed quality at pre- and post-anthesis periods of B. napus.2. Identifying site-specific modification of DNAm and potential genomic imprinting in the B. napus genome susceptible to heat stress3. Performing a transcriptome profiling using RNA-Seq, to identify key differentially expressed genes as a result of heat stress.4. Integrating the epigenetic profiling and the corresponding gene expression through the development of a gene regulatory network using findings from obj.2&3, in order to assess the epigenetic mediation effect on pollination fertility and seed quality measures.5. Developing a machine learning model which will predict the future impact of heat stress on pollination fertility and seed quality. Using the decision tree models, correlation between methylation sites and gene expression will be assessed. Next, sites will be fed to the decision tree as input in order to rank these in order of importance, and ultimately estimate metabolic profiles and phenotypic traits (i.e. pollination fertility and seed quality) as output variables.