RNA sequencing (RNA-seq)-based whole transcriptome analysis (WTA) using ever-evolving next-generation sequencing technologies has become a primary tool for coding and/or noncoding transcriptome profiling. As WTA requires RNA-seq data for both coding and noncoding RNAs, one key step for obtaining high-quality RNA-seq data is to remove ribosomal RNAs, which can be accomplished by using various commercial kits. Nonetheless, an ideal rRNA removal method should be efficient, user-friendly and cost-effective so it can be adapted for homemade RNA-seq library construction. Here, we developed a novel reverse transcriptase-mediated ribosomal RNA depletion (RTR2D) method. We demonstrated that RTR2D was simple and efficient, and depleted human or mouse rRNAs with high specificity without affecting coding and noncoding transcripts. RNA-seq data analysis indicated that RTR2D yielded highly correlative transcriptome landscape with that of NEBNext rRNA Depletion Kit at both mRNA and lncRNA levels. In a proof-of-principle study, we found that RNA-seq dataset from RTR2D-depleted rRNA samples identified more differentially expressed mRNAs and lncRNAs regulated by Nutlin3A in human osteosarcoma cells than that from NEBNext rRNA Depletion samples, suggesting that RTR2D may have lower off-target depletion of non-rRNA transcripts. Collectively, our results have demonstrated that the RTR2D methodology should be a valuable tool for rRNA depletion.