Zainal-Abidin Rabiatul-Adawiah, Harun Sarahani, Vengatharajuloo Vinothienii, Tamizi Amin-Asyraf, Samsulrizal Nurul Hidayah
Biotechnology and Nanotechnology Research Centre, Malaysian Agricultural Research and Development Institute (MARDI), Serdang 43400, Selangor, Malaysia.
Centre for Bioinformatics Research, Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia.
Plants (Basel). 2022 Jun 21;11(13):1625. doi: 10.3390/plants11131625.
Transcriptomics has significantly grown as a functional genomics tool for understanding the expression of biological systems. The generated transcriptomics data can be utilised to produce a gene co-expression network that is one of the essential downstream omics data analyses. To date, several gene co-expression network databases that store correlation values, expression profiles, gene names and gene descriptions have been developed. Although these resources remain scattered across the Internet, such databases complement each other and support efficient growth in the functional genomics area. This review presents the features and the most recent gene co-expression network databases in crops and summarises the present status of the tools that are widely used for constructing the gene co-expression network. The highlights of gene co-expression network databases and the tools presented here will pave the way for a robust interpretation of biologically relevant information. With this effort, the researcher would be able to explore and utilise gene co-expression network databases for crops improvement.
转录组学作为一种用于理解生物系统表达的功能基因组学工具，已经有了显著发展。生成的转录组学数据可用于构建基因共表达网络，这是重要的下游组学数据分析之一。迄今为止，已经开发了几个存储相关值、表达谱、基因名称和基因描述的基因共表达网络数据库。尽管这些资源分散在互联网上，但此类数据库相互补充，支持功能基因组学领域的高效发展。本文综述了作物中基因共表达网络数据库的特点和最新情况，并总结了广泛用于构建基因共表达网络的工具的现状。这里介绍的基因共表达网络数据库和工具的亮点将为有力解读生物学相关信息铺平道路。通过这项工作，研究人员将能够探索和利用基因共表达网络数据库来改良作物。
