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Title: RNA Editome in Rhesus Macaque Shaped by Purifying Selection}
Article:
Abstract:
Understanding of the RNA editing process has been broadened considerably by the next generation sequencing technology; however, several issues regarding this regulatory step remain unresolved – the strategies to accurately delineate the editome, the mechanism by which its profile is maintained, and its evolutionary and functional relevance. Here we report an accurate and quantitative profile of the RNA editome for rhesus macaque, a close relative of human. By combining genome and transcriptome sequencing of multiple tissues from the same animal, we identified 31, 250 editing sites, of which 99. 8% are A-to-G transitions. We verified 96. 6% of editing sites in coding regions and 97. 5% of randomly selected sites in non-coding regions, as well as the corresponding levels of editing by multiple independent means, demonstrating the feasibility of our experimental paradigm. Several lines of evidence supported the notion that the adenosine deamination is associated with the macaque editome – A-to-G editing sites were flanked by sequences with the attributes of ADAR substrates, and both the sequence context and the expression profile of ADARs are relevant factors in determining the quantitative variance of RNA editing across different sites and tissue types. In support of the functional relevance of some of these editing sites, substitution valley of decreased divergence was detected around the editing site, suggesting the evolutionary constraint in maintaining some of these editing substrates with their double-stranded structure. These findings thus complement the “continuous probing” model that postulates tinkering-based origination of a small proportion of functional editing sites. In conclusion, the macaque editome reported here highlights RNA editing as a widespread functional regulation in primate evolution, and provides an informative framework for further understanding RNA editing in human.
Introduction:
Since its discovery in 1986[1], an increasing number of genes have been found to be subject to RNA editing, a co-transcriptional process that alters hereditary information by introducing differences between RNA and its corresponding DNA sequence[2]. The investigation of such regulation accelerated dramatically after the development of next generation sequencing( NGS) technology, which facilitates the genome-wide determination of DNA and RNA sequences at relatively low cost[3]–[5]. Several early NGS-based editome studies in human[4]–[7] have challenged the traditional view of human genetics, since RNA editing might be a source of variations inaccessible to previous genetic studies. Although the identification of RNA-editing sites by discerning sequence discrepancies between RNA and DNA derived from the same specimen seems to be a straightforward approach, it is error-prone when the RNA/DNA sequences are compiled by short reads generated from NGS technology[5]. As is being extensively discussed[5],[8]–[12], widespread RNA-editing sites detected in a recent study might be largely a result of technical errors. It thus remains technically challenging to accurately identify human editing sites using NGS data[5],[8]–[12]. In addition, given the difficulties of obtaining specimens of different tissues from the same human individual as well as accurately quantifying the levels of editing using merely NGS data, the mechanisms by which the editome is maintained and regulated remain unclear. Recent studies with contrasting findings are thus in line with the notion that RNA editome may be governed by complex regulation, despite the fact that a large proportion of non-canonical editing types were identified due to technical errors[5]. First, large cross-tissue variations of the RNA editome were detected[4], while the tissue-biased RNA editome could not be directly explained by the expression and activity of known enzymes catalyzing adenosine deamination[13],[14]. Second, genome-wide editome analysis in human also suggested large intra-population variations[3],[7], whereas one study on candidate genes demonstrated otherwise[15]. Third, as only sporadic functional RNA-editing sites have been reported, it remains controversial whether the editing events detected by NGS represent functional regulation rather than neutral signals[16]. The “continuous probing” model postulated that most of the editing sites are neutral with low editing levels, acting as a selection pool for a few functional editing sites[17], further challenged the functional significance of those widespread RNA-editing sites detected by NGS. Overall, NGS technology has helped open the Pandora's box of the editome and so has raised more questions than it answers. Key issues, including experimental and computational strategies to accurately identify the editome, the mechanism by which its profile is maintained, and its functional significance, are presently not well addressed[18]. Cross-species comparisons with our close evolutionary relatives would provide a framework to clarify these issues. Therefore, we set out to study the editome in rhesus macaque, with the aim of complementing several recent reports on human editome[4]–[7]. The macaque editome we report here provides an important evolutionary context to understand RNA-editing regulation in human, emphasizing RNA editing as a form of widespread functional regulation shaped by purifying selection.
Discussion:
Despite extensive efforts and discussion, accurate definition of the human editome by using NGS data alone remains technically challenging[5],[8]–[12]. The widespread human editing sites detected in a recent study might have been largely a result of technical artifacts, such as systematic sequencing errors and flaws in the subsequent computational analyses[5],[8]–[12]. Other studies introduced more stringent pipelines to control for high false-positive rate, such as by sequencing only target regions with putative RNA-editing sites[4], by removing RNA-editing sites on repetitive genomic regions[3], or by rejecting sites corresponding to genomic polymorphisms[12]. These approaches have significantly improved the accuracy of RNA editing site calling, but additional barriers still exist for unbiased and definite identification of editome on the genome-wide scale[18]. Particularly for species with poor genome annotations and error-prone gene structures such as the rhesus macaque[19],[22], successful editome detection is hampered by difficulties in accurately mapping RNA-Seq reads and discerning discrepancies. In this study, beyond the filters established previously to remove potentially erroneous editing sites with i) low read coverage[6],[7], ii) poor base-calling quality or multiple types of variation[6],[7], iii) strand-biased cDNA read distributions[7], and iv) location in repeat genomic regions[3],[7],[12], we installed additional experimental designs and analytical measures with advantage in eliminating false-positives in our pipeline. First, all NGS assays were performed in macaque tissues derived from the same animal, which effectively excluded individual differences in the genome and transcriptome( Materials and Methods). Second, strand-specific RNA-Seq technique significantly controlled for potentially ambiguous calls due to the widespread cis-natural anti-sense expression[18],[38]( Figure 2A). Third, long paired-end reads were generated in our deep sequencing analysis, ensuring accurate mapping with sufficient sequencing depth on >18, 000 mRNAs[39] and 96. 9% of macaque genomic regions. Fourth, a more stringent read mapping strategy was applied to facilitate the definition of uniquely-mapped reads( Materials and Methods), which efficiently diminished false mapping due to processed pseudogenes[3]. In addition, considering the error-prone gene structure annotations for rhesus macaque[19],[20], we further introduced inclusion criteria to remove editing sites located in previously mis-annotated macaque transcripts. Taken together, as we demonstrated above, these efforts ensured the identification of an accurate and quantitative catalog of RNA-editing sites. However, the stringent criteria we used to control for the false-positives would cause some false-negatives in RNA-editing detection, although the calling sensitivity in coding region was proved to be good( Figures 1 & 2). To evaluate the degrees of false-negatives of our stringent computational pipelines, we applied the identical pipeline and inclusion criteria on human poly( A)-positive RNA-Seq data reported previously to identify human editing sites[7],[21]. Compared with the original poly( A)-positive RNA-Seq study reporting 84, 750 human editing sites( see Supplementary Table 1 in Reference[7],[21]), 20, 065 editing sites were identified by our pipeline, with A-to-G transitions accounted for 94. 3% of the identified editing sites. Considering the total sequencing depth of this human study is much lower than that of our study in rhesus macaque, we slightly modified our inclusion criteria for RNA-editing sites by decreasing from five to two the minimum RNA-Seq reads required to support the variant form( while keeping all other parameters used in sequence alignment and single-nucleotide variation calling), and consequently identified 80, 375 editing sites, a number comparable with the original report in human( 84, 750 sites; Materials and Methods)[21]. It is obvious that more macaque editing sites would be expected, especially when increasing the sequencing depth of the transcriptome. However, with the experimental efforts in minimizing the effects of computational detection sensitivity in our study, such as the significantly elevated transcriptome sequencing depth in rhesus macaque to increase the detection power of variants, and the strand-specific, long paired-end reads designed to increase the proportions of uniquely-mapped reads( Materials and Methods), it is likely that some non-technical factors, e. g., the inherent difference in genetic makeup for the inverted Alu pairs, may also contribute to this human-macaque difference[4],[7],[40],[41]. Viewed together, although our rigorous experimental and computational paradigm would cause some false-negatives, it would be a necessary compensation for an accurate and quantitative catalog of RNA-editing sites in rhesus macaque, considering the poor genome annotations and error-prone gene structures in rhesus macaque[19],[20],[22]. Importantly, the catalog represents a representative account of RNA-editing sites across rhesus macaque genome for further interrogation of the global attributes of the RNA editome. Aside from the technical issues, the present work on the macaque RNA editome provided novel insights into several aspects of the RNA editing process. First, large-scale sequencing on a broad range of tissue samples from the same or different animals allowed for a comparative editome analysis. We subsequently deduced from such a study that, while there is large degree of variance between sites and tissues( Figure 3A), the intra-population variability of editing levels is significantly lower than that across tissues, suggesting a regulatory commonality of RNA editing within populations similar to other fundamental gene regulation mechanisms[26],[27]( Figures 3B, C, D, S7 & S8). Second, the global attributes of editing were further verified and quantified to show that the occurrence of RNA editing is correlated with the flanking sequence signatures, as well as the levels of ADARs expression( Figure 4). The macaque editome is thus partially associated with ADARs-mediated enzymatic reactions, and the cis- and trans-directed mechanisms associate with ADARs, such as the chemical affinity of ADAR binding sites and ADARs concentration, are thus likely to be relevant with the regulation of the macaque editome. While hereditary information is modified by RNA editing, evidence for functional significance of this process is largely lacking thus far[17]. Although functional RNA-editing sites have been sporadically reported, they may represent only isolated cases rather than a general mode of regulation. In this study, with an accurate and informative editome defined across multiple tissues and animals, we found some intra-population conservation of the macaque editome, as well as some parallels of the editome across multiple primate species( Figures 3, 4 & 5). However, our findings also suggest that the editome is partially associated with ADARs-mediated enzymatic reactions. It is thus possible that sites showing high affinity to ADARs in one macaque animal would also have high affinity to ADARs in other macaque animals, or in humans and chimpanzees, considering the relatively lower sequence divergences among these closely related primate species. To this end, we tested whether the cross-species similarities in RNA editome were maintained by purifying selection due to the functional implications of these regulations, or simply due to such a passive mechanism. Interestingly, in support of the functional relevance of some of these editing sites, substitution valley of decreased divergence was detected around the editing site( Figure 5), suggesting the evolutionary necessity of retaining some of these editing substrates with their double-stranded structure. Taken together, the findings on the population-wide and evolutionary conservation of the macaque editome, as well as the contribution of purifying selection to editome shaping, lend support to the functional significance of this co-transcriptional regulation as a whole. Interestingly, when investigating the dampened divergence rate for editing sites across different genomic regions, stronger selective constraint was detected on coding regions, while sites in other regions also showed some degrees of weaker evolutionary constraints( Figure 5A & B). This analysis implies that, in contrast to the sites in coding regions, a smaller proportion of functional RNA editing sites exist in non-coding genomic regions( Figure 5A & B). The varied proportions of functional editing sites across different genomic regions thus support the “continuous probing” model postulating that most of the editing sites are neutral with low editing levels, acting as a selection pool for a few functional editing sites[17]. However, our findings also suggest that the RNA editing levels are partially associated with the chemical affinity of ADAR binding sites, as well as ADAR concentration. Thus, the editing levels are not necessarily low even for those potentially neutral editing sites( Figure S12), a notion that complements the “continuous probing” model by illustrating a clearer process for the tinkering-based origination of functional RNA editing sites[17],[37].
RNA editing is a co-transcriptional process that introduces differences between RNA and its corresponding DNA sequence . Currently , the next generation sequencing have allowed study of the editome in a comprehensive and efficient manner . However , fundamental issues involving accurate mapping of the editome as well as its regulation and functional outcome remain unresolved . To further unveil the underlying mechanisms from the evolutionary perspective , we report here the editome profile in rhesus macaque , one of our closest evolutionary relatives . We identified a list of 31 , 250 RNA-editing sites and deciphered an accurate and informative editome across multiple tissues and animals . We found that the adenosine deamination is associated with the macaque editome , in that both the sequence context and the expression profile of ADARs are relevant factors in determining the quantitative variance of RNA editing across different sites and tissue types . Importantly , some of these RNA-editing events represent functional regulation , rather than neutral signals , as suggested by substitution valley of decreased divergence detected around the editing sites , an indication of selective constraint in maintaining some of these editing substrates with their double-stranded structure . The macaque editome thus provides an informative evolutionary context for an in-depth understanding of RNA editing regulation .