现代数字育种技术的研究进展  

Advances in Modern Data-driven Breeding Technologies

作　　者：董春水 才卓 

机构地区：[1]<世界种业>网 [2]<玉米科学>编辑部,长春130033

出　　处：《玉米科学》2013年第1期1-8,共8页Journal of Maize Sciences

基　　金：国家"863"计划"强优势玉米杂交种的创制与应用"(2011AA10A103);国家"973"计划"玉米大豆高产优质品种分子设计和选育基础研究"(2009CB118400)

摘　　要：现代计算机技术促进了作物育种技术的数字化进程。随着作物性状数据采集技术的发展成熟,作物育种过程中产生的数据呈指数增长,促使传统作物育种技术变革。作物育种过程中产生的数据类型十分复杂,数据的存储、分析和利用是作物育种技术的一个组成部分,促成了现代数字育种技术的迅猛发展。通过分析玉米育种过程中涉及到的各类数据,提出概念性的作物育种数据管理系统框架,并阐明各类数据之间的相互关系。完善的育种数据管理系统除核心数据库外,还包括多项数据分析模块,包括系谱树和亲缘分析、分子标记和基因定位、数据采集和性状分解、杂交组合和后代选择、育种策略分析、田间试验设计和统计分析、生长发育系统模拟和基因功能和调控网络等。数据分析模块可以根据作物育种实践的实际需要进行组合,但并非所有模块都是必需的。The modern computer technologies have greatly fostered the modern data-driven crop breeding tech- nology. As data acquisition technologies getting mature, data generated in the crop breeding process grow exponential- ly and explosively. Traditional crop breeding technology has been revolutionized to accommodate the massive data in breeding processes. Because the data types generated in crop breeding processes are extremely complex, storing, ana- lyzing, and effectively utilizing them become increasingly challenging and directly lead to the rapid development of modern data-driven breeding techniques. A conceptual framework of crop breeding data management system was pro- vided based on the thorough analysis of the diverse types of data generated in maize breeding programs, and the rela- tionship were also enucleated. In addition to the core database, a well-designed crop breeding data management sys- tem should include a number of data analysis modules： the genealogical tree and phylogenetic analysis, molecular markers and gene discovery, data acquisition and trait dissection, selection of parents and progenies, breeding strategy, experiment design and statistical analysis, crop modeling, and dynamic gene network modeling. These data processing modules can be integrated together according to the actual needs of the crop breeding practices.

关 键 词：玉米育种 数据库管理 数字育种技术 数据分析 概念框架 

分 类 号：S513.035[农业科学—作物学]