MBE Advance Access originally published online on June 24, 2007
Molecular Biology and Evolution 2007 24(9):1971-1981; doi:10.1093/molbev/msm125
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Research Articles |
Computational Analysis of RNA Editing Sites in Plant Mitochondrial Genomes Reveals Similar Information Content and a Sporadic Distribution of Editing Sites
,1,1
* Department of Developmental and Cell Biology, University of California, Irvine
Department of Information and Computer Science, University of California, Irvine
E-mail: rmmullig{at}uci.edu.
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Abstract |
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A computational analysis of RNA editing sites was performed on protein-coding sequences of plant mitochondrial genomes from Arabidopsis thaliana, Beta vulgaris, Brassica napus, and Oryza sativa. The distribution of nucleotides around edited and unedited cytidines was compared in 41 nucleotide segments and included 1481 edited cytidines and 21,390 unedited cytidines in the 4 genomes. The distribution of nucleotides was examined in 1, 2, and 3 nucleotide windows by comparison of nucleotide frequency ratios and relative entropy. The relative entropy analyses indicate that information is encoded in the nucleotide sequences in the 5 prime flank (–18 to –14, –13 to –10, –6 to –4, –2/–1) and the immediate 3 prime flanking nucleotide (+1), and these regions may be important in editing site recognition. The relative entropy was large when 2 or 3 nucleotide windows were analyzed, suggesting that several contiguous nucleotides may be involved in editing site recognition. RNA editing sites were frequently preceded by 2 pyrimidines or AU and followed by a guanidine (HYCG) in the monocot and dicot mitochondrial genomes, and rarely preceded by 2 purines. Analysis of chloroplast editing sites from a dicot, Nicotiana tabacum, and a monocot, Zea mays, revealed a similar distribution of nucleotides around editing sites (HYCA). The similarity of this motif around editing sites in monocots and dicots in both mitochondria and chloroplasts suggests that a mechanistic basis for this motif exists that is common in these different organelle and phylogenetic systems. The preferred sequence distribution around RNA editing sites may have an important impact on the acquisition of editing sites in evolution because the immediate sequence context of a cytidine residue may render a cytidine editable or uneditable, and consequently determine whether a T to C mutation at a specific position may be corrected by RNA editing. The distribution of editing sites in many protein-coding sequences is shown to be non-random with editing sites clustered in groups separated by regions with no editing sites. The sporadic distribution of editing sites could result from a mechanism of editing site loss by gene conversion utilizing edited sequence information, possibly through an edited cDNA intermediate.
Key Words: RNA editing • relative entropy • gene conversion • copy correction • non-random distribution • evolution of editing • editing site recognition • retroconversion • gene transfer
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Introduction |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionSupplemental InformationAcknowledgementsReferences |
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RNA editing is a post-transcriptional process that changes the nucleotide sequence of RNAs. C-to-U editing occurs in the organelles of vascular plants and changes the coding information in mRNAs. In higher plants, specific cytidine residues are converted to uridine residues in chloroplast and in mitochondrial transcripts, and this process frequently re-specifies the codon to direct the incorporation of a non-synonymous amino acid residue (Covello and Gray 1989
; Gualberto et al. 1989; Hiesel et al. 1989). The amino acid specified by the edited codon is typically the evolutionarily conserved amino acid at that position, and the unedited codon would code for a radical amino acid substitution.
Several higher plant chloroplast genomes have been sequenced and analysed for editing, and generally have about 30 C-to-U editing sites (Maier et al. 1995; Sugiura 1995; Schmitz-Linneweber et al. 2002; Kugita et al. 2003a; Kugita et al. 2003b; Tillich et al. 2005). The complete Arabidopsis thaliana, Brassica napus, Beta vulgaris and Oryza sativa mitochondrial genomes have been sequenced and analysed for RNA editing, and these genomes encode 441, 427, 357, and 491 C-to-U editing sites, respectively (Giege and Brennicke 1999; Kubo et al. 2000; Notsu et al. 2002; Handa 2003; Mower 2005). Thus, the number of nucleotide changes directed by RNA editing is much greater in mitochondria than in chloroplasts, although the editing process is generally thought to be similar in these organelles (Maier et al. 1996; Mulligan 2004).
The plant organellar editing complexes must specifically recognize 
30 editing sites in chloroplasts and about 400 editing sites in plant mitochondria. Analysis of 3 editing sites in transgenic tobacco chloroplasts by 5' and 3' deletion led to the broad conclusion that recognition elements exist largely in the 5' flanking region with some sequence requirements in the 3' region (Chaudhuri et al. 1995; Bock et al. 1996; Chaudhuri and Maliga 1996; Bock et al. 1997; Reed and Hanson 1997; Hermann and Bock 1999; Reed et al. 2001; Chateigner-Boutin and Hanson 2002, 2003). A detailed analysis of the petB and psbE editing site in Nicotiana tabucum chloroplasts has identified the –20 to +10 region as important for editing site conversion (Miyamoto et al. 2002), and mutations at nucleotides –11 to –1, +2 to +4, and +8/9 were deleterious to in vitro editing of psbE RNAs (Hayes and Hanson 2007). RNA editing site recognition in chloroplasts appears to occur through trans-acting factors that recognize several editing sites with similar cis elements (Chateigner-Boutin and Hanson 2002, 2003). The groups of editing sites are referred to as editing site clusters and share common sequence motifs that are frequently composed of 3 or 4 nucleotides. Recently, the pentatricopeptide proteins have been recognized as a large class of organellar RNA binding proteins that are required for RNA editing and other RNA processing reactions (Kotera et al. 2005; Schmitz-Linneweber et al. 2006).
Computational analysis of sequences around editing sites has been performed by examination of the distribution of single nucleotides in close proximity to RNA editing sites in plant mitochondrial genomes, and were compared to a small subset of unedited cytidines (Giege and Brennicke 1999; Cummings and Myers 2004). An analysis of the Arabidopsis mitochondrial genome compared nucleotide frequencies from –17 to +7 in sequences around all known edited cytidines and 30 randomly selected unedited cytidines. This study reported a high incidence of pyrimidines in position –2 and –1, a low incidence of guanines at position –1, and other unexpected nucleotide frequencies at –5 and –17 (Giege and Brennicke 1999). A second computational analysis of plant mitochondrial editing sites analyzed editing sites from the Oryza, Arabidopsis, and Brassica mitochondrial genomes and compared them with a subset of randomly selected non-edited cytidines with the same codon position frequencies (Cummings and Myers 2004). This study detected the pyrimidine bias that exists at position –1, and reported a correlation of the free energy of folding of the 41 nucleotide RNA segments centered on an edited or unedited cytidine.
In this study we present a comprehensive analysis of edited and unedited cytidines in the protein-coding sequences of 4 mitochondrial genomes. In order to evaluate possible higher order distribution of nucleotides, our analyses have included analysis of the distribution of single, di- and tri-nucleotides around edited and unedited cytidines in the Arabidopsis, Beta, Brassica and Oryza mitochondrial genomes. The relative entropy of the nucleotide sequences flanking edited and unedited cytidines are very similar in these genomes, suggesting that the same regions are utilized in editing site recognition in mitochondria of moncots and dicots. Analysis of information content suggests that several groups of 2 or 3 contiguous nucleotides may be utilized in editing site recognition. Comparison of the RNA sequences immediately adjacent to chloroplast and mitochondrial editing sites to unedited cytidines suggests that a similar sequence of YYCR are enriched around editing sites in both organelle systems in monocots and dicots, and the immediate sequence context of a cytidine residue may be critical factor in whether a cytidine is editable. In addition, the distribution of editing sites within individual coding sequences was analyzed and editing sites are frequently non-randomly distributed. Evolutionary mechanisms that may result in a sporadic distribution of RNA editing sites are discussed.
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Materials and Methods |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionSupplemental InformationAcknowledgementsReferences |
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DNA Sequence Data
A comprehensive analysis of RNA editing sites in mitochondrial genomes has been reported for the A. thaliana, B. vulgaris, B. napus, and O. sativa (Giege and Brennicke 1999
; Kubo et al. 2000; Notsu et al. 2002; Handa 2003; Mower and Palmer 2006). DNA sequences and editing site locations were obtained from Genbank accession numbers NC001284, AP006444
[GenBank]
, BA000009
[GenBank]
with DQ381444
[GenBank]
-DQ381465
[GenBank]
, and BA000029
[GenBank]
, respectively. Genbank genome entries were converted into a series of FASTA-formatted text for all known protein-coding sequences, and were annotated with edited cytidines represented as an upper case C. Thus, editing sites are represented as the unedited nucleotide and are considered to be cytidines in these analyses. These files are available in the supplemental information. Protein coding sequences were limited to entries that were larger than 100 nucleotides, and included only protein coding sequences, with no intron or untranslated regions. In addition, small ORFs, uncharacterized ORFs, and small exons were eliminated from the database.
Computational Analyses
Computer programs were written and compiled with Dr Java (version 1.4). The nucleotide distribution around all edited and all unedited cytidines in the database was analyzed in a sliding window of one, 2, or 3 nucleotides. We scanned each FASTA entry in the genome file for an edited C or an unedited c, and every time a cytidine was encountered, a sequence was written to an array of edited or unedited sequences. Thus, the sequences flanking all edited or unedited cytidines in the database are aligned in a matrix. The size of the region to be analyzed was specified as an input to the program, and was typically the 20 or 50 nucleotides flanking a cytidine (e.g. a 41 or 101-nucleotide sequence was written to the matrix). Cytidines that were encountered in a FASTA entry that had less than the specified region in either the 5' or 3' direction were ignored; thus the first and last 20 (or 50) nucleotides of the coding sequences were eliminated from analysis.
The arrays represent the alignment of all RNA sequence surrounding edited or unedited cytidines, and were analyzed for the distribution of nucleotide sequences by scanning one, 2, or 3 nucleotide windows and calculating the number of times each sequence was encountered in a specific position relative to a cytidine. As an example of the output, table 1 shows the distribution of dinucleotides around Arabidopsis mitochondrial editing sites and unedited cytidines in the –2/–1 window. The frequency that each dinucleotide is encountered adjacent to an edited or unedited cytidine (P, Q) is the number of times that a dinucleotide is observed divided by the total number of edited or unedited cytidines. The ratio of the frequencies that each dinucleotide is around an edited and unedited cytidine is defined as the selectivity ratio (P/Q). Thus, a sequence with a selectivity ratio of 1 has the same relative frequency around edited and unedited cytidines, while a sequence with a selectivity ratio greater than 1 is more frequently present around an editing site. Relative entropy was calculated as the Kullback-Leibler distance by the equation d = 
Pk log (Pk/Qk) over k terms (k = 4n) for the distribution of nucleotides in 1, 2, or 3 nucleotide windows.
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Random Editing Site Assignment
We used random editing site assignment to compare the results of the mitochondrial database with a random distribution of editing sites. The random editing site assignment program scanned each FASTA formatted entry in the database and determined the number and codon position of each of the editing sites. The program then randomly selected a cytidine in the same codon position to be assigned as an editing site. Thus, the random editing site assignment program maintained the number and codon position of editing sites in a coding sequence. Statistics such as mean, standard deviation, variance, and confidence intervals were determined from 1000 genome files with randomly assigned editing sites.
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Nucleotide Distribution Around Edited and Unedited Cytidines
The distribution of nucleotides around edited and unedited cytidines was analyzed by calculation of relative entropy to determine where information content existed within these sequences (fig. 1). Figure 1 shows the relative entropy of edited and unedited cytidines for Arabidopsis and Oryza mitochondrial coding sequences. The analysis was performed by analysis of nucleotides in the 40 or 100 nucleotides flanking edited and unedited cytidines. The 5% confidence interval for the relative entropy of each mitochondrial genome was determined by 1000 iterations of random assignment of RNA editing sites and calculation of the mean and standard deviation of the relative entropy values. The Beta vulgaris and Brassica napus mitochondrial genomes were also analyzed, but are provided in the supplemental material to improve figure clarity.
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Figure 1 shows the relative entropy for the analysis of a 1 nucleotide window over the entire 101 nucleotide segment. The relative entropy is extremely high in the immediate vicinity of the editing site (nucleotides –2, –1, +1) and several peaks are observed that exceed the 5% confidence interval in the –20 to +8 nucleotide region. Figure 1B shows an expanded view of the –20 to +8 nucleotide region, and the relative entropies of the Arabidopsis and Oryza mitochondrial genomes are very similar in this region. The relative entropy of the 2 nucleotides immediately upstream of an editing site is very large suggesting great importance of these nucleotides in editing site recognition. In addition, the coincidence and magnitude of peaks in the relative entropy profiles are very similar, suggesting similar regions are involved in editing site recognition. Thus, the information content is very similar around RNA editing sites in the dicot (Arabidopsis) and the monocot (Oryza) genomes. These taxa are thought to have diverged about 150 MY ago (Chaw et al. 2004
), and these results suggest that similar editing site recognition mechanisms are utilized in these mitochondrial systems. Analysis of the relative entropy around editing sites in 2 and 3 nucleotide windows resulted in some important differences. For example, nucleotide position –5 shows a peak in relative entropy over the adjacent nucleotides when analyzed as a single nucleotide (fig. 1B). Uridines are enriched at the –5 position and the selectivity ratio is very high (fig. 2); however, the selectivity ratio of C at position 5 is not remarkable, nor is the entropy or distribution of mononucleotides at –6 or –4 positions. When dinucleotides are analyzed, the entropy analysis shows a broad peak that includes dincleotides at –6/–5 and –5/–4 (fig. 1C), and CU and CC are enriched at –6/–5 and UA and CG are enriched at the –5/–4 position (fig. 2). Finally, when trinucleotides are analyzed, a large peak in the entropy profile is evident at trinucleotide –6/–5/–4 (fig. 1D), and CUA and CCG are enriched at these positions (fig. 2). The trinucleotide CCG has a greater selectivity ratio than CUA that includes the highly enriched U at position –5. Thus, analysis of multiple adjacent nucleotides reveals that combinations of nucleotides are enriched around the RNA editing sites that are not evident when single nucleotides are analyzed. These results suggest that multiple contiguous nucleotides are recognized by the editing apparatus, and that distinct combinations of nucleotides in regions with high relative entropy may exist in the cis element of RNA editing sites.
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Similar changes in the relative entropy profile are evident in the –12 to –10 region and the –18 to –15 region. In summary, the relative entropy of nucleotide sequences around RNA editing sites suggests that the greatest information is present immediately upstream of editing sites (–2/–1), and additional information is present in the –18 to –14, –13 to –10, –6 to –4, –2/–1, and +1/+2, regions.
The distribution of nucleotides is similar around plant mitochondrial and chloroplast editing sites. Table 1 shows the distribution of dinucleotides in the –2/–1 window around plant mitochondrial editing sites. Panel A shows the number of times each dinucleotide occupies the –2/–1 window upstream of an edited or an unedited cytidine. P and Q, the frequencies that a dinucleotide is upstream of an edited or unedited cytidine is calculated as the number of times that a specific dinucleotide is present divided by the total number of edited or unedited cytidines. The ratio of these frequencies (P/Q) is the selectivity ratio that expresses the relative frequency of a specific dinucleotide around an edited or unedited cytidine.
The selectivity ratios for editing sites in the Arabidopsis, Beta, and Oryza genomes are compared in columns 6, 7, and 8, respectively (table 1). The selectivity ratios are very similar for editing sites in the 3 genomes with about half of the dinucleotides rarely observed upstream of an editing site (UA, UG, CA, GG, CG, AA, GA, AG). These dinucleotides have very low selectivity ratios, and include all 8 dinucleotides with a purine in the –1 position. The dinucleotides with consistently high selectivity ratios (UU, CU, UC, AU) are pyrimidine-pyrimidine or AU combinations.
Figure 3 compares the selectivity ratios for Arabidopsis with the Beta or Oryza editing sites in the –2/–1 and +1/+2 windows (fig. 3A and B, respectively). Each point represents the selectivity ratios for one of the 16 dinucleotides. About half of the dinucleotides exhibit low selectivity ratios in all 3 species, and as a result are clustered near the origin. In addition, dinucleotides with high selectivity ratios in Arabidopsis generally have high selectivity ratios in Beta and Oryza, and linear regression of the selectivity ratios shows lines with slopes of nearly one and intercepts very close to zero. The coefficient of determination (r2) between Arabidopsis and Oryza selectivity ratios is 0.90 and indicates a very strong degree of correlation.
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Figure 3B compares the selectivity ratios for Arabidopsis with the Beta or Oryza editing sites in the +1/+2 window. The selectivity ratios also exhibit a strong correlation in the +1/+2 window with a coefficient of determination of 0.68 between Arabidopsis and Oryza editing sites. In contrast to the –2/–1 window, none of the selectivity ratios are very small indicating that dinucleotides downstream to the editing site are not discriminated against as highly as in the upstream position. The dinucleotides with high selectivity ratios in the +1/+2 position are GG and GU.
The distribution of nucleotides around RNA editing sites in chloroplasts is very similar to plant mitochondria. Table 1B and figure 4 show selectivity ratios for the distribution of dinucleotides in the –2/–1 window for Arabidopsis mitochondria compared to editing sites in tobacco and maize chloroplast genomes. Eight of the dinucleotides are clustered near the origin and are rarely observed upstream of editing sites in mitochondria or in chloroplasts (AG, GA, AA, CG, GG, CA, UG, UA), and several dinucleotides are frequently detected upstream of editing sites (UU, AU, CC) in both organelles. Regression analysis of these values gives a coefficient of determination (r2) of 0.65 between the Arabidopsis mitochondrial and tobacco chloroplast and 0.73 between the Arabidopsis mitochondria and Zea chloroplast editing sites, and indicates a moderate to strong correlation. The similarity of nucleotide distribution around editing sites in dicots and monocots and in both chloroplast and mitochondria suggests that common features are necessary for editing site conversion in these diverse taxa and organelle systems.
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Effect of Codon Position of an Editing Site
The distribution of editing sites in plant mitochondrial genomes is typically about 35%:55%:10% in the first, second and third positions of the codon (Giege and Brennicke); thus the second codon position is over represented and the third codon position is under represented in edited cytidines, and the sequence context of editing sites may be influenced by codon position.
In order to directly assess the effect of codon position, relative entropy was separately analyzed in a one nucleotide window for editing sites in the first, second, or third position, and compared to unedited cytidines from the same codon position (fig. 5). If entropy values were strongly influenced by codon position, then the peaks and troughs in the entropy profile would be expected to be displaced by one nucleotide. However, the entropy profile in the 5' flanking region is quite similar, especially for the first and second positions that exhibit peaks at –1, –5, and –8/–9, and intervening troughs. In the –10 to –20 region, many peaks coincide with a few differences; however, a strong single nucleotide displacement of the profile is not evident. The analysis of a small number of editing sites from the third codon position resulted in much larger fluctuations in the entropy values, but showed similar trends. This analysis suggests that although there is some influence of editing site position in the entropy value, information is similarly embedded in the 5' flanking region of editing sites irrespective of position in the codon.
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Some codon position effects are evident, especially in the nucleotides immediately downstream of an editing site. In both the Oryza and Arabidopsis genomes, the downstream region exhibited a peak at the +1 nucleotide for editing sites in the second position, and at the +2 nucleotide for editing sites in the first position. This position represents the first downstream wobble position, and synonymous mutations may allow optimization of the editing site for efficient editing, and would result in increased entropy at these positions.
Editing Sites are Sporadically Distributed in Some Genes
Some coding sequences exhibited an unusual distribution of editing sites that appeared to be clustered in groups and separated by gaps that lacked editing sites. In order to systematically examine the distribution of RNA editing sites within individual coding sequences, the interval between editing sites was calculated for all coding sequences greater than 500 nucleotides that included at least 3 editing sites.
The variance of the intervals between editing sites for an individual coding sequence was determined as a measurement of the distribution of editing site intervals relative to the mean interval size, and was compared to the variances of 1000 randomly assigned coding sequences. Table 2 shows p values for the analysis of coding sequences in the 3 genomes, and 31%, 45%, and 35% of the coding sequences analyzed from each genome exhibited a non-random distribution of editing sites with p values less than 0.05. A random distribution of editing sites would be expected to yield a p value of 0.05 for only 5% of the coding sequences, and would be expected only once for each of the 20 coding sequences analyzed from each genome. These results demonstrate that an unexpectedly large fraction of plant mitochondrial coding sequences exhibit a non-random distribution of editing sites. Figure 6 graphically shows the distribution of editing sites for several coding sequences with small p values.
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionSupplemental InformationAcknowledgementsReferences |
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Editing Site Sequence Context
Analysis of the information content around RNA editing sites in plant mitochondrial transcripts suggests that groups of nucleotides in specific regions are important in editing site recognition (fig. 7). The relative entropy immediately upstream and downstream of an editing site is large and suggests that these regions are critical for editing site recognition. Based on these results, it would appear that the simple motif "HYCGK" represents a sequence that is likely to be edited in plant mitochondria. These observations extend earlier studies based on single nucleotide analyses that concluded that editing sites are frequently preceded by pyrimidines and rarely preceded by a guanine (Maier et al. 1996
; Giege and Brennicke 1999; Cummings and Myers 2004).
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The distribution of nucleotides in the immediate 5' flanking region of editing sites in monocot and dicot mitochondria was shown to be remarkably similar (table 1A) and the selectivity ratios exhibit a strong correlation between monocots and dicots (fig. 3A). The distribution of dinucleotides in the –2/–1 window in chloroplasts editing sites of a dicot (Nicotiana tabacum) and a monocot (Zea mays) is very similar to the distribution of dinucleotides observed in plant mitochondria (table 1B, fig. 4). Thus, a similar distribution of nucleotides immediately upstream of RNA editing sites in monocots and dicots and in both mitochondria and chloroplasts suggests that similar molecular systems are involved and that a preferred editing site sequence context is shared among these organisms and organelles. However, some differences are noted between the mitochondrial and chloroplast systems: in chloroplast editing sites, the dinucleotide CU is not prevalent in the –2/–1 window and the +1 nucleotide is more typically an A. These may represent differences that distinguish the editing machinery in these 2 systems.
Monocots and dicots diverged 150 MY ago (Chaw et al. 2004), and chloroplast trans-acting specificity factors are proposed to change rapidly in evolution (Schmitz-Linneweber et al. 2001). In principle, a trans-acting RNA binding factor would be expected to be able recognize virtually any sequence. Thus, the similarity of editing site context that is maintained across diverse taxa and different organelles may reflect common features in the mechanisms of editing. The sequence similarity around RNA editing sites as well as the strong selection for and against nucleotides immediately adjacent to editing sites in these disparate systems suggests that some cytidines may exist in an "editable" context while other cytidines may exist in an "uneditable" context. Thus, the immediate sequence context of a nucleotide may have an important impact on whether a T to C mutation could be edited and has important consequences on how RNA editing sites are acquired in evolution (Covello and Gray 1993).
Analysis of relative entropy suggests that information around RNA editing sites exists in the –18 to 14, –13 to –10, –6 to –4, –2 to –1, and +1 to +2 regions. These regions would be expected to be recognized by the editing machinery, and figure 7 shows the combinations of nucleotides most frequently observed in these positions based on selectivity ratios. Analysis of the relative entropy in larger nucleotide windows exhibited large increases over the relative entropy of randomly assigned editing sites, and several contiguous nucleotides may be important in editing site recognition rather than an individual nucleotides at specific positions. These results are consistent with the editing site cluster model that proposes that groups of editing sites are recognized by the same trans-acting factor (Chateigner-Boutin and Hanson 2002).
The groups of trinucleotides indicated in the –18 to –14 region overlap, and suggest that a larger series of nucleotides may be important in editing site recognition. For example, YUC, UCC, and CCU are frequently encountered at positions –18/–16, –17/–15, and –16/–14, respectively (fig. 7). The pentanucleotide YUCCU is present at nucleotide –18 to –14 in eleven editing sites of the 376 rice editing sites analyzed, suggesting that this may represent a portion of an editing site recognition sequence. Other 4 and 5 nucleotide combinations were noted in the Arabidopsis genome such as YUACA (–18/–14) that may be important editing site recognition motifs.
Editing Site Recognition
RNA editing site recognition and conversion has been analyzed with an in vitro editing system and by electroporation of intact mitochondria. Deletion of 5' and 3' sequences suggests that nucleotide sequences from –20 to +10 are required for editing site conversion (Takenaka et al. 2004; Neuwirt et al. 2005). These studies examined an atp9 editing site and showed that 5 pentanucleotide nucleotide regions between –25 and –1 were highly important to critical in editing site conversion, while sequences in the –35 to –25 and +1 and greater were much less important. In addition, the +1 nucleotide and was shown to be extremely important for editing site conversion, as well as nucleotide deletions or insertions at –2. These results suggest that spacing between cis-elements may be important and is a conclusion supported by the entropy analyses in this study.
The cis-acting sequences of the 2 editing sites in wheat cox2 are proposed to be present within –16 to +6 nucleotides of the editing site (Farre et al. 2001; Choury et al. 2004). Single nucleotide mutagenesis within the 23 nucleotide region of editing site C77 of the cox2 transcript demonstrated that residues at –11, –10, –9, –6, –2, and –1 were critical for effective editing site conversion, while editing site C259 showed a similar trend with critical residues at –12, –11, +1, +3, and +4. These positions correspond well with regions identified as potentially important in editing site recognition in this study. While the analysis of individual editing sites provides detailed information about an individual editing site, this study has analyzed all editing sites of entire genomes, and provides statistical information about the features of a "typical" editing site.
Editing Sites Distribution
A statistical analysis of the intervals between RNA editing sites demonstrated that coding sequences frequently include groups of editing sites that are separated by gaps with no editing sites. The mechanism of editing site acquisition is proposed to involve T to C mutation in the genome that can be corrected by C-to-U editing (Covello and Gray 1993; Schmitz-Linneweber et al. 2001; Schmitz-Linneweber et al. 2002; Tillich et al. 2005). Conversely, the simplest mechanism of editing site loss would be a C to T mutation at an edited C, such that the edited cytidine was lost from the genome. These mechanisms are predicted to occur randomly within a gene; however, the distribution of editing sites is frequently non-random with large gaps between clustered RNA editing sites.
The molecular process that results in the sporadic distribution of editing sites in these genes is open for speculation. The distribution of editing sites in the matR coding sequence has been previously noted to correspond to regions that encode the reverse transcriptase and maturase domains of this protein (Thomson et al. 1994; Begu et al. 1998), and the distribution of editing sites could be related to maintenance of these functions. Alternatively, the targeting of one region of a transcript by the editing apparatus might facilitate editing of additional T to C mutations in that region, and consequently the acquisition of editing sties might tend to occur in groups.
Figure 8 illustrates a possible mechanism for the generation of the sporadic distribution of editing sites. Loss of RNA editing sites from relatively large regions of a coding sequence could occur through retroconversion that would remove adjacent editing sites by replacement with the edited sequence information. This process would presumably require conversion of edited mRNA to cDNA through reverse transcription, and there is limited evidence for reverse transcriptase activity in plant mitochondria (Wahleithner et al. 1990; Begu et al. 1998; Farre and Araya 1999). Recombination or gene conversion could integrate the edited information into the genome, and this process is thought to happen readily in plant mitochondria (Knoop 2004).
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A number of individual examples of loss of editing sites within a plant mitochondrial transcripts have provided examples that may have occurred through retroconversion. Editing in cox3 and rps13 transcripts was completely or nearly eliminated in the Iridaceae and Amarylliadaceae, yet these transcripts include numerous editing sites in related dicots (Lopez et al. 2007
). A similar example involved the loss of editing sties from cox1 in several gymnosperm taxa, yet cox1 is heavily edited with 25 to 34 editing sites in related species (Lu et al. 1998). 2 compelling examples involve the loss of introns and the adjacent editing sites in the Caryophylales and the Asterales. The nad4 gene lost an intron in the Caryophylaceae, and editing sites were eliminated near the newly created exon-exon boundary (Itchoda et al. 2002), while nad4 transcripts in Lactuca lost 2 introns as well as the RNA editing sites in that region of the gene (Geiss et al. 1994). The simultaneous loss of both introns and the adjacent editing sites strongly suggests that the process involved recombination with a spliced and edited intermediate.
Numerous examples of gene transfer from the mitochondrial to the nuclear genome demonstrate that the nuclear forms of these transferred genes have lost mitochondrial introns and editing sites (Nugent and Palmer 1991; Kadowaki et al. 1996). Mitochondrial gene transfer to the nucleus would require RNA-mediated transfer through a cDNA intermediate, or wholesale loss of editing sites and introns in the mitochondrial genome prior to DNA-mediated gene transfer (Henze and Martin 2001). Thus, RNA editing represents an obstacle to gene transfer to the nucleus, and may contribute to the retention of genes in plant mitochondrial genomes. Loss of editing sites in the mitochondrial genome would facilitate DNA-mediated gene transfer to the nucleus (Henze and Martin 2001). Both DNA-mediated and RNA-mediated gene transfer would be facilitated by mechanisms related to retroconversion, either by removal of editing sites to facilitate DNA-mediate gene transfer, or as a mechanism to produce a cDNA for integration in the nuclear genome.
While individual examples of editing site and intron loss suggest that retroconversion has occurred in specific taxonomic groups, the statistical analysis of the distribution of editing sites in mitochondrial genomes demonstrates that numerous genes exhibit a sporadic distribution of editing sites. Taken together, these observations suggest that loss of editing sites has occurred periodically and may have important consequences in the evolution of plant mitochondrial genomes.
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Supplemental Information |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionSupplemental InformationAcknowledgementsReferences |
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Text files of DNA sequence information for the coding sequences of the Arabidopsis, Beta, and Oryza mitochondrial genomes are provided at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/). The files are in fasta format and edited cytidines are represented as an upper case C. Figure 1E–H shows relative entropy analyses for editing sites in the Brassica and Beta genomes. A detailed table of trinucleotides and selectivity ratios around RNA editing sites is provided as a supplement to figure 7.
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Acknowledgements |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionSupplemental InformationAcknowledgementsReferences |
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The authors are grateful to Dr. Brandon Gaut for assistance with statistical analyses, experimental design, and thoughtful discussion. Kenneth L. C. Chang and Chia Ching Chou each contributed equally to this work. Ms. Nam Nguyen provided excellent technical assistance.
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Footnotes |
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1 These 2 authors contributed equally to the manuscript
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References |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionSupplemental InformationAcknowledgementsReferences |
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