Abstract

RNA editing is a post-transcriptional modification in which adenosine residues are converted to inosine (adenosine-to-inosine editing). Commonly used methodologies to quantify RNA editing levels involve either direct sequencing or pyrosequencing of individual cDNA clones. The limitations of these methods lead to a small number of clones characterized in comparison to the number of mRNA molecules in the original sample, thereby producing significant sampling errors and potentially erroneous conclusions. We have developed an improved method for quantifying RNA editing patterns that increases sequence analysis to an average of more than 800,000 individual cDNAs per sample, substantially increasing accuracy and sensitivity. Our method is based on the serotonin 2C receptor (5-hydroxytryptamine_2C; 5HT_2C) transcript, an RNA editing substrate in which up to five adenosines are modified. Using a high-throughput multiplexed transcript analysis, we were able to quantify accurately the expression of twenty 5HT_2C isoforms, each representing at least 0.25% of the total 5HT_2C transcripts. Furthermore, this approach allowed the detection of previously unobserved changes in 5HT_2C editing in RNA samples isolated from different inbred mouse strains and dissected brain regions, as well as editing differences in alternatively spliced 5HT_2C variants. This approach provides a novel and efficient strategy for large-scale analyses of RNA editing and may prove to be a valuable tool for uncovering new information regarding editing patterns in specific disease states and in response to pharmacological and physiological perturbation, further elucidating the impact of 5HT_2C RNA editing on central nervous system function.