Sandhu Maninder, Sureshkumar V, Prakash Chandra, Dixit Rekha, Solanke Amolkumar U, Sharma Tilak Raj, Mohapatra Trilochan, S V Amitha Mithra
ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India.
Shobhit University, Modipuram, Meerut, 250110, Uttar Pradesh, India.
BMC Bioinformatics. 2017 Sep 30;18(1):432. doi: 10.1186/s12859-017-1846-y.
Genome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice.
RiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. 'Physical position search' is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the 'common genes across varieties' search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search.
The aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201.
全基因组微阵列技术已助力构建了用于水稻功能基因组学研究的强大数据库。然而，此类数据库并不能直接满足育种者的需求。在此，我们试图开发一个网络界面，将来自不同遗传背景的功能基因组学研究信息与DNA标记相结合，以便能将它们直接应用于作物改良。在数据库的当前版本中，我们纳入了干旱和盐胁迫研究，因为这两种是水稻中的主要非生物胁迫。
RiceMetaSys是一个用户友好且免费可用的网络界面，它提供了从多个微阵列数据集中识别出的、跨基因型、作物发育阶段和组织的盐响应基因（SRGs）和干旱响应基因（DRGs）的全面信息。“物理位置搜索”对于那些使用基于QTL的方法剖析对盐和干旱胁迫耐受性的人来说是一个有吸引力的工具，因为它可以提供任何物理区间内的SRGs和DRGs列表。为了识别用于作物改良的可靠候选基因，“品种间共同基因”搜索工具很有用。已实现对基因和水稻基因型的表达谱进行图形化可视化，以方便用户并使比较更具影响力。在SRGs和DRGs中进行简单序列重复（SSR）搜索是精细定位和标记辅助选择的宝贵工具，因为它提供了用于多态性检测的引物。为此还提供了内含子特异性标记的外部链接。在进行基因座和SSR搜索时，已实现无限制的数据批量检索。
该数据库的目的是为用户提供简单直接的搜索选项，以便从数千个SRGs和DRGs中识别出可靠的候选基因，从而便于将表达谱的变异与表型变异联系起来。数据库网址：http://14.139.229.201
