Oryza sativa (rice) is an important monocot family member because it serves as model crop for genetic studies in closely related grass species and as staple food source for a major world population. Rice functional genomics research deserves attention because only a certain proportion of the annotated genes have been elucidated and many agronomically important genes are remain unknown. Since the completion of genome, tremendous effort has been made to facilitate functional genomic studies including establishment of germ plasm collection, gene indexed mutants, full length cDNA and development of high throughput techniques. Among these sources, microarray based genome-wide expression studies lead identification of several novel candidates from individual studies and these data are regularly deposited in public platforms such as NCBI GEO. Monitoring of spatiotemporal gene expression from these datasets provide clues on gene function.We have constructed and maintained Rice oligonucleotide array database (ROAD) since 2012 . However, meta-expression analysis utility in ROAD encounter drawbacks in terms of types of available meta-data. Firstly, ROAD primarily function on meta-analysis of anatomical samples and developmental stages from processed microarray experiments. To address these shortcomings, we have developed an updated version of Rice oligonucleotide array database (ROAD 2.0). For researchers interested stress or treatment studies, ROAD 2.0 is enabled with large collection of biotic and abiotic, and hormone treated profiles. In addition, RNA-Seq datasets that span rice anatomical tissues and stress treatments are also integrated.