Choi Hong-Kyu
Department of Molecular Genetics, College of Natural Resources and Life Science, Dong-A University, Nakdong-Daero 550-Beongil 37, Saha-Gu, Busan, 49315, Republic of Korea.
Genes Genomics. 2019 Feb;41(2):133-146. doi: 10.1007/s13258-018-0751-8. Epub 2018 Oct 23.
Recent next generation sequencing-driven mass production of genomic data and multi-omics-integrated approaches have significantly contributed to broadening and deepening our knowledge on the molecular system of living organisms. Accordingly, translational genomics (TG) approach can play a pivotal role in creating an informational bridge between model systems and relatively less studied plants. This review focuses mainly on addressing recent advancement in omics-related technologies, a diverse array of bioinformatic resources and potential applications of TG for the crop breeding. To accomplish above objectives, information on omics data production, various DBs and high throughput technologies was collected, integrated, and used to analyze current status and future perspectives towards omics-assisted crop breeding. Various omics data and resources have been organized and integrated into the databases and/or bioinformatic infrastructures, and thereby serve as the ome's information center for cross-genome translation of biological data. Although the size of accumulated omics data and availability of reference genomes are different among plant families, translational approaches have been actively progressing to access particular biological characteristics. When multi-layered omics data are integrated in a synthetic manner, it will allow providing a stereoscopic view of dynamic molecular behavior and interacting networks of genes occurring in plants. Consequently, TG approach will lead us to broader and deeper insights into target traits for the plant breeding. Furthermore, such systems approach will renovate conventional breeding programs and accelerate precision crop breeding in the future.
近年来，由新一代测序驱动的基因组数据大规模生产以及多组学整合方法，极大地拓宽和加深了我们对生物体分子系统的认识。因此，转化基因组学（TG）方法能够在构建模型系统与研究相对较少的植物之间的信息桥梁方面发挥关键作用。本综述主要聚焦于阐述组学相关技术的最新进展、一系列多样的生物信息资源以及TG在作物育种中的潜在应用。为实现上述目标，收集、整合了有关组学数据生产、各种数据库和高通量技术的信息，并用于分析组学辅助作物育种的现状和未来前景。各种组学数据和资源已被整理并整合到数据库和/或生物信息基础设施中，从而成为生物数据跨基因组翻译的组学信息中心。尽管不同植物家族积累的组学数据规模和参考基因组的可用性存在差异，但转化方法一直在积极推进，以探究特定的生物学特性。当以综合方式整合多层组学数据时，将能够提供植物中基因动态分子行为和相互作用网络的立体视图。因此，TG方法将引导我们对植物育种的目标性状有更广泛和深入的了解。此外，这种系统方法将革新传统育种计划，并在未来加速精准作物育种。
