In this article, we developed and utilized an ultra HTS approach using the Illumina Genome Analyzer II platform to analyze 5-HT2C
RNA editing and provide quantitative estimates of editing site frequencies and transcript/isoform frequencies. We also compared our ultra high-throughput approach to the most commonly used low-throughput approach and show that our high-throughput approach is superior in part because it detects all transcripts, facilitating between-genotype comparisons of even rare transcripts, which is either impossible or prohibitively expensive and laborious by the more common low-throughput approach. We then used our novel approach to assess the effect of endogenous serotonin on RNA editing of the 5-HT2C
receptor by comparing RNA editing frequencies in the hippocampi of Pet-1 wild-type and knockout mice, which have a defective serotonin system due to dysfunctional serotonergic raphe neurons that produce almost no serotonin. Surprisingly, we found that abnormally low levels of brain serotonin had no significant effect on 5-HT2C
receptor RNA editing. We also show that the editing frequencies at each of the five individual editing sites are unchanged and that there is little or no alteration in the frequency of any one of the 32 5-HT2C
transcripts in the absence of a normally functioning central serotonergic system. An examination of the effect on 5-HT2C
editing of 10 different drugs with varying mechanisms of action indicated that their ability to modulate editing could not be predicted in a straightforward manner based on their activity at 5-HT2C
receptors. Notably, our results in untreated mice are consistent with previous studies measuring the proportions of transcripts edited at the five edited sites (21
Prior studies have yielded inconsistent results regarding the effects of various pharmacological manipulations of the serotonergic system on 5-HT2C
RNA editing. As an example, one study reported increases in editing frequencies at the A, B, C and D sites after fluoxetine treatment of BALB/c mice, and no RNA editing changes after fluoxetine treatment in C57BL/6 mice (though there were consistent trends towards a decrease at the A, B, C and D sites). It should be noted that these mice were subjected to a modified forced swim test (FST) on their last 2 days of treatment (51
). Another study in rats reported decreases in A, B and E site editing frequencies after fluoxetine treatment (52
A potential shortcoming of all of these previous studies is the small number of sequences that was sampled, typically 50 or so samples per animal, with three or four animals in each treatment group. Small sample sizes are inevitable due to the labor-intensive nature of methods that rely on sequencing transcripts derived from individual bacterial clones (one clone = one transcript). The small sample sizes make measuring editing at the E site difficult because of the very low frequency of editing at this site (<5%). Not surprisingly, therefore, the most common change reported between treatment groups is at the E site, which is the most difficult to measure accurately. Furthermore, previous studies generally focus only on common transcripts, because rare transcripts are impossible to identify and quantify given the small sample sizes. Other studies rely on primer-extension analysis, which does not allow for the comprehensive assessment of individual transcript frequencies, but merely editing frequencies at each site. Two very recent articles apply next-generation sequencing technology to measuring or discovering RNA editing (53
). Both sequenced only a few hundred to a few thousand 5-HT2C
transcripts—an approach comparable to what can be done with presently established methods. In addition, neither study examined all 32 conceivable transcripts and no comparison was made with a gold standard method to validate the results.
Our novel HTS method has a number of advantages with respect to the previously established methods for quantifying RNA editing. First, HTS is many orders of magnitude less expensive per sequence. Furthermore, the Genome Analyzer II, on which our HTS experiment was performed, is amenable to multiplexing 26 or more samples in each lane of a flow cell, which cuts the cost per experiment by an order of magnitude, making RNA editing analysis by HTS considerably less expensive on a per animal basis than RNA editing analysis by LTS. Second, measuring RNA editing by HTS is less labor-intensive than LTS. For HTS, PCR fragments are simply generated and loaded into the Cluster Station and then the Genome Analyzer II, which sequences individual fragments directly. To generate similar information by LTS, fragments must be first ligated into a vector, the vector transformed into bacteria, the bacteria plated, individual bacterial clones picked and grown, plasmids purified, and finally the inserted fragment sequenced by Sanger sequencing. Third, HTS is advantageous as compared to primer-extension analysis and other similar PCR-based strategies in that data is digital rather than analog, with at least some of the advantages associated with digital information (55
). Fourth, HTS permits the analysis of rare transcripts, which is either impossible or prohibitively expensive and labor intensive by the LTS method. The analysis of rare transcripts is also impossible by analog methods such as primer-extension analysis. We have also compared our results, where possible, to gold standard LTS, thus validating our method and the sequence quality filters we used.
To our knowledge, this study represents the first comprehensive measurement of the frequencies of all 32 possible 5-HT2C
transcripts. Although we detected many rare transcripts, it is not clear to what extent rare transcripts may or may not be important in vivo
. Experiments with mice expressing only the fully edited VGV isoform, however, have indicated that mutant VGV mice exhibit increases in total 5-HT2C
expression as compared to wild-type mice, along with dramatic reductions in fat mass despite hyperphagia (18
). This suggests the possibility that alterations in rare transcript frequencies may have important physiological consequences.
Finally, we would like to note that our data are easily reconcilable with the known mechanisms by which the 5-HT2C
receptor pre-mRNA is edited by ADAR1, which edits the A and B sites, and ADAR2, which edits the C and D sites (16
). Our data suggest that fluoxetine/amitriptyline and SB206553, which have the opposite effects on signaling through the 5-HT2C
receptor but nonetheless all increase editing frequency at the A and B sites in at least one brain region, modulate 5-HT2C
RNA editing by influencing ADAR1 function at the receptor without affecting function of ADAR2. In contrast, lithium appears to affect only the ability of ADAR2 to edit 5-HT2C
pre-mRNA. Furthermore, our data indicate that chronic treatment leads to reciprocal changes in transcripts that are either unedited or fully edited at the A and B or C and D sites, with no change in transcripts edited at only one or the other site. We also show region-specific changes with respect to the handful of drugs which do affect editing (fluoxetine, amitriptyline, SB206553 and lithium) Finally, although we report significant changes in editing after some drug regimens, most of these changes are relatively small in magnitude (typically <10%) and it is unclear if such small changes are physiologically significant.
In summary, we have developed and optimized a novel ultra high-throughput method for measuring RNA editing digitally by adapting newly developed genome-wide sequencing tools. Our method is inexpensive, technically feasible for most laboratories, and provides more comprehensive information regarding 5-HT2C receptor editing than either existing analog methods or digital low-throughput methods. We applied our newly developed ultra high-throughput method to assess whether or not modulating endogenous brain serotonin would alter 5-HT2C RNA editing. We demonstrated through our more powerful measurement method that lowering endogenous brain serotonin levels does not affect 5-HT2C RNA editing in vivo. In contrast, treating mice with chronic fluoxetine, amitriptyline, SB206553 and lithium increased editing at a subset of the sites in one more brain regions, whereas chronic LSD, DOI, MK-212, valproate, clozapine and olanzapine had no effect. Our data suggest that the ability of a drug to alter 5-HT2C RNA editing cannot be predicted from its activity at 5-HT2C receptors. Given its considerable advantages, massively parallel HTS is likely to rapidly become the method of choice for quantifying RNA editing as next-generation sequencing platforms become more widely available.