Enzymes in high-throughput RNA sequencing: Applications and challenges

High-throughput RNA sequencing provides genome-wide information on the dynamics of RNA in each cell and how the dynamics responds to environmental changes. Next-generation sequencing by the Illumina platform currently provides the highest information output as compared to other platforms. A key component of next generation sequencing of each RNA is the successful end-to-end reverse-transcription into a cDNA strand. This can be highly challenging given the propensity of each RNA to adopt ordered structures and to contain post-transcriptional modifications. While many reverse transcriptase (RT) enzymes have been developed over the years to maximize read-through of an RNA, their processivity and efficiency varies, raising the question of how to select the RT for the experiment at hand. Here, we use tRNA as a model for genome-wide sequencing, as tRNA has a stable secondary and tertiary structure and has a high density and wide variety of post-transcriptional modifications, presenting one of the most challenging problems of sequencing RNA. We compare the efficiency of end-to-end cDNA synthesis of tRNA among several recent RT enzymes and provide a general sequencing workflow that is applicable to most of these enzymes.