Lee Tak, Kim Hyojin, Lee Insuk
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.
Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.
Curr Opin Plant Biol. 2015 Apr;24:61-70. doi: 10.1016/j.pbi.2015.02.001. Epub 2015 Feb 16.
Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years.
尽管下一代测序(NGS)技术已使许多作物物种的基因组得以解码,但经济上重要的作物性状的大多数潜在遗传成分仍有待确定。网络方法已被证明对参考植物拟南芥的研究有用,基于网络的作物遗传学的成功也将需要作物物种的基因组规模功能网络。在本综述中,我们讨论了如何构建功能网络并阐明作物系统的整体视图。作物基因网络随后可用于基因优先级排序以及基于重测序的全基因组关联研究(GWAS)数据的分析,在未来几年,作物科学领域此类数据的数量将迅速增长。