Normalization of quantitative gene expression data with a suitable reference gene is essential for accurate and reliable results. However, the availability and choice of most suitable reference gene(s) showing uniform expression across all the experimental conditions remain a drawback. We have developed a web server, PlantRGS (http://www.nipgr.res.in/PlantRGS), for the identification of most suitable candidate reference gene(s) at the whole-genome level using microarray data for quantitative gene expression studies in plants. Microarray data from more than 11 000 tissue samples for nine plant species have been included in the PlantRGS for meta-analysis. The web server provides a user-friendly graphical user interface-based analysis tool for the identification of most suitable reference genes in the selected plant species under user-defined experimental conditions. Various parameter options and output formats will help users to investigate desired number of most suitable reference genes with wide range of expression levels. Validation of results revealed that novel reference genes identified by the PlantRGS outperforms the traditionally used reference genes in terms of expression stability. We anticipate that the PlantRGS will provide a platform for the identification of most suitable reference gene(s) under given experimental conditions and facilitate quantitative gene expression studies in plants.