RESEARCH-PGR: Discovery and Evaluation of Inbred-specific and Hybrid-specific Regulatory Modules

在农业中，杂种优势被定义为后代产量超过其近交亲本产量的增加。杂种优势是包括玉米在内的许多作物高产的关键组成部分。虽然杂种优势在许多作物中得到了有效利用，但我们对它的作用机制缺乏基本的了解。更好的理解可以提供新的途径，提高杂种优势，并扩大其利益的非杂交作物。这个项目将开发新的方法来发现自交亲本的相互作用基因。了解这些基因的身份将使人们有可能将它们用作预测工具和作物改良的操纵目标。该项目将提供一个模型，用于使用基于预测基因网络的方法来理解和改善作物的复杂性状。对利用生物网络进行作物研究的兴趣正在增长，但获得必要技术能力的机会仍然有限。因此，该项目还将为植物科学家提供免费的技术和分析服务，重点是作物基因组学研究。这些服务将从实验设计咨询到数据解释，确保结果有用，不浪费能力。培训希望成为植物生物网络专家的调查人员将是该项目的最高优先事项。两到三名本科生将提供服务。这些学生将接受化学、生物化学、计算机科学和工程方面的培训，以便他们能够在样品制备、数据生成和网络分析方面为用户提供支持。该项目将为两个玉米自交系（B73，Mo 17）及其杂交种（SX 19）创建无监督的基因调控网络（GRNs）和蛋白激酶网络（PKNs）。GRN模块由转录因子（TF）及其靶基因组成。PKN模块由蛋白激酶及其底物组成。GRN将使用三种不同的TF活性替代物来制备：TF mRNA丰度、TF蛋白丰度和TF蛋白磷酸化水平;网络靶标将通过所有mRNA的水平来测量。PKN将使用激活环的磷酸化作为激酶活性的代表来制备;网络靶标将通过所有蛋白质的蛋白质磷酸化水平来测量。将在26种不同组织上进行所有测量。将使用GENIE 3随机森林算法构建GRN。PKN将使用我们先前描述的相关方法进行。我们将测量自交系和它们的杂种之间模块的保存和分歧。我们将测试是否自交系特定或杂交特定的模块有助于杂种优势。将来自SX 19的具有含有模块调节子的渐渗片段的选择的近等基因系（NIL）与供体亲本测交。F1将与SX 19完全一样，除了含有调节子的区段，其将是纯合的。将SX 19的转录组和蛋白质组与测试交叉的NIL进行比较，将揭示调节剂是否如网络预测的那样作用于其靶点。如果构件对杂种优势的贡献显著，则测交近等基因系的杂种优势将降低。

Hybrid vigor in agriculture is defined as the increase in yield of an offspring over those of its inbred parents. Hybrid vigor is a critical component of the high productivity of many crops, including maize. While hybrid vigor has been efficiently employed in many crops, we lack a basic understanding of how it works. A better understanding could provide novel avenues for the improvement of hybrid vigor, and for extending its benefits to non-hybrid crops. This project will develop new approaches for discovering sets of interacting genes from the inbred parents. Knowing the identity of those genes will make it possible to use them as predictive tools and as targets of manipulation for crop improvement. The project will provide a model for using predictive gene network-based approaches to understand and improve complex traits in crops. Interest in using biological networks for crop research is growing, but access to the necessary technical capabilities remains limited. Therefore, the project will also provide plant scientists with free technical and analytical services with an emphasis on crop genomics-enabled research. These services will range from consultation on experimental design to data interpretation, ensuring that results are useful and capacity is not wasted. Training investigators who wish to become plant biological network experts will be the project's highest priority. Two to three undergraduate students will provide the services. These students will be trained in chemistry, biochemistry, computer science, and engineering so that they can support users in sample preparation, data generation, and network analysis.This project will create unsupervised gene regulatory networks (GRNs) and protein kinase networks (PKNs) for two maize inbreds (B73, Mo17) and their hybrid (SX19). GRN modules are comprised of a transcription factor (TF) and its target genes. PKN modules are comprised of a protein kinase and its substrates. The GRN s will be made using three different proxies for TF activity: TF mRNA abundance, TF protein abundance, and level of TF protein phosphorylation; network targets will be measured by the levels of all mRNAs. The PKN will be made using phosphorylation of the activation-loop as a proxy for kinase activity; network targets will be measured by protein phosphorylation levels of all proteins. All measures will be made on 26 different tissues. GRNs will be constructed using the GENIE3 random forest algorithm. The PKN will be made using our previously described correlative method. We will measure the preservation and divergence of modules between the inbreds and their hybrid. We will test whether inbred-specific or hybrid-specific modules contribute to heterosis. Selected near­ isogenic lines (NILs) derived from SX19 with introgressed segments containing module regulators will be test-crossed to the donor parent. The Fl will be exactly like SX19 except for the segment containing the regulator, which will be homozygous. Comparison of the transcriptome and proteome of SX19 to the test-crossed NIL will reveal whether the regulator is acting on its targets as predicted by the network. If the module contributes significantly to heterosis then hybrid vigor will be reduced in the test-crossed NIL.