玉米株型建成调控网络研究

Ideal plant architecture is the basis of maize high yield production. Plant height, stalk strength and leaf angle, which vary synergistically in general, are the major factors constituting plant architecture in maize. The applicant and participants have fine-mapped and cloned a series of key genes underlying plant architecture (PA), such as DLF1, qPH7, stiff1, HB53, and ABPH. These PA associated key genes function with multigenic effect controlling plant height, and synergistically regulate a certain number of PA sub-traits in a pleiotropic manner. On the basis of previous works, here, we propose to collaborate with all participants tightly, utilize modern molecular biological and genetic techniques, do the machine learning based on the comprehensive multi-omic biological big-data for the identification of regulatory networks of these PA associated key genes. Our proposal is dedicated to demonstrating the molecular mechanism of pleiotrophism, and systematically dissection of the molecular network associated with multigenic effect. Furthermore, we will conduct re-sequencing on an association panel of ~500 diverse inbred lines and maize relative-teosinte, followed by association mapping and evolutionary analysis, to identify favorable alleles for high-yield breeding and the selection sites during maize domestication and selection. Our proposal will not only enhance our understanding of the molecular mechanism of maize plant architecture, decipher the regulatory network during maize plant development, but also potentially provide a substantial number of new functional markers for maize high-yield breeding.

理想株型是玉米高产的基础，而株高、茎杆强度与茎叶夹角是玉米株型的重要构成因子，并表现出一定的协调变异规律。申请人及参与人团队前期分离和克隆了株型关键功能基因DLF1、qPH7、STIFF1、HB53和ABPH等，这些基因表现出明显的“多因一效”的调控关系共同影响株高，同时又各自表现出“一因多效”效应影响多个株型子性状协同变异。本项目拟在此基础上，进一步通过各参与团队的密切合作，利用现代分子生物学与遗传学技术，基于多维组学等生物大数据，进行机器学习挖掘与深度功能验证这些株型关键基因的调控网络，系统阐明这些株型关键基因“一因多效”调控株型各性状协同变异的分子机制，解析其“多因一效”共同调控株高变异的分子网络，进而，通过重测序、关联分析与进化分析，鉴定株型关键基因在玉米驯化与育种中的选择位点，挖掘并聚合优良等位基因，为玉米产量分子育种提供理论指导与基因资源。

玉米产量主要依赖种植密度，而种植密度又决定于株型。玉米株型是一个非常复杂的性状，由株高、叶夹角、叶长等十几个紧密联系又相对独立的性状组成，遗传基础复杂。前期项目克隆了玉米株型关键基因DLF1、qPH7、stiff1、ABPH、HB53等，本项目利用遗传学，分子生物学技术，生物大数据的人工智能挖掘技术，以及群体遗传学等工具，构建了玉米株型关键基因DLF1、qPH7、stiff1、ABPH、HB53的分子调控网络，建立了玉米株型建成关键基因预测的人工智能算法，批量挖掘并克隆了十几个新的玉米株型节点基因并进行了功能验证。本项目初步解析了玉米株型建成关键基因DLF1、qPH7、stiff1、ABPH、HB53的“一因多效”协同调控株型各子性状的分子基础，阐明了玉米株型关键基因DLF1、qPH7、stiff1、ABPH、HB53的“多因一效”地控制玉米株高变异的分子机制。进一步，群体水平的重测序与关联分析鉴定到玉米株型关键基因的广泛序列变异及其调控株型变异的优异等位基因，开发了可以用于玉米株型改良的功能性分子标记。本项目的研究成果为玉米理想株型改良提供了理论基础与基因资源，具有一定的理论与应用价值。在本集成项目的支持下，尽管只有1年的执行期项目组已经在国际主流期刊发表论文9篇，还有多篇高水平研究论文在审中，申请并获批专利2项，另有3个专利正在申请中，培养博士生9名，硕士生3名，其中2021年毕业硕士2名。