Sesame is naturally adapted to arid environments but highly susceptible to waterlogging stress. A few hours of waterlogging (lasting over 36 h) are detrimental to the crop growth, yield and survival. To better understand the molecular mechanisms underlying sesame responses to waterlogging and recovery, it is essential to design a high-resolution time-series experiment. In this study, we reported the RNA-seq profiling of two contrasting genotypes under waterlogging and recovery. The plants were grown in pots and subjected to waterlogging treatment at the flowering stage for 36 h and subsequently, 12 h drainage. Root samples were collected in triplicate at 22 time points under waterlogging/drainage treatments and at 10 time points in the control condition. This represents a total of 195 biological samples and the RNA-seq yielded over eight billion reads. Basic data analyses demonstrated a clear separation of transcriptomes from control, waterlogging and drainage treatments. Overall, the generated high-quality and comprehensive RNA-seq resources will undoubtedly advance our understanding of waterlogging/drainage responses in a non-model sensitive crop.