Globally, the glycophytic plant rice suffers from severe crop losses due to salinity stress every year. With the aggravating climatic changes the scenario is becoming more threatening day by day. Understanding the plant variation in growth and physiological responses towards the stress coupled with in depth gene expression and SNP variation analysis will enable us to better understand the mechanism of salt tolerance at genome level. We began with screening eight rice genotypes hydroponically based on morphological, qualitative and physiological traits. Pokkali ranked the top based on morphological traits like leaf and root elongation rate, plant height and total biomass; qualitative traits like standard evaluation score (Gregorio et. al., 1997) and leaf rolling score and physiological trait like shoot Na+/K+ followed by PSB Rc50 and IR 58 at both moderate and high salt levels. High correlation was observed between these parameters. Principal component analysis identified the traits that contributed most to the overall variability and cluster analysis separated the genotypes into tolerant (Pokkali), moderately tolerant (PSBRC50, IR 58, Banikat and Nipponbare) and susceptible (BRRI dhan 29, O. latifolia and O. rupipogon) groups at both stress levels. We are analysing the gene expression data derived from the whole genome transcriptional profiling using 4/44k Agilent array. The gene expression data will be interrogated by physiological data to predict the candidate genes with their putative functions for salinity tolerance in rice. The identified candidates will then selectively be sequenced using Agilent’s new SureSelect platform to identify the SNP variation across the genotypes.