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Plant Cell. Mar 2008; 20(3): 543–551.
PMCID: PMC2329928

Promoter-Proximal Introns in Arabidopsis thaliana Are Enriched in Dispersed Signals that Elevate Gene Expression[W][OA]

Abstract

Introns that elevate mRNA accumulation have been found in a wide range of eukaryotes. However, not all introns affect gene expression, and direct testing is currently the only way to identify stimulatory introns. Our genome-wide analysis in Arabidopsis thaliana revealed that promoter-proximal introns as a group are compositionally distinct from distal introns and that the degree to which an individual intron matches the promoter-proximal intron profile is a strong predictor of its ability to increase expression. We found that the sequences responsible for elevating expression are dispersed throughout an enhancing intron, as is a candidate motif that is overrepresented in first introns and whose occurrence in tested introns is proportional to its effect on expression. The signals responsible for intron-mediated enhancement are apparently conserved between Arabidopsis and rice (Oryza sativa) despite the large evolutionary distance separating these plants.

INTRODUCTION

The positive effect of introns on gene expression, which has been termed intron-mediated enhancement (IME) (Mascarenhas et al., 1990), is often eclipsed by the better known roles of promoters, enhancers, silencers, and chromatin modifications in controlling transcription. However, IME has been observed in a wide range of eukaryotes, including vertebrates, invertebrates, fungi, and plants (Buchman and Berg, 1988; Palmiter et al., 1991; Okkema et al., 1993; Koziel et al., 1996; Simpson and Filipowicz, 1996; Duncker et al., 1997; Lugones et al., 1999; Ho et al., 2001; Xu and Gong, 2003; Juneau et al., 2006), suggesting that it reflects a fundamental feature of gene expression. In many cases, introns have a larger influence than do promoters in determining the level and pattern of expression (Virts and Raschke, 2001; Wang et al., 2002; Jeong et al., 2006).

The mechanism of IME is largely unknown. Some efficiently spliced introns boost expression more than 10-fold, while others have little or no effect, arguing against generic mechanisms related to splicing that would apply to all introns equally. Introns enhance gene expression by increasing the steady state amount of mature mRNA in the cell (Callis et al., 1987; Dean et al., 1989; Rethmeier et al., 1997; Rose and Last, 1997; Nott et al., 2003), apparently without significantly changing mRNA stability (Rethmeier et al., 1997; Nott et al., 2003). Although modest effects of introns on transcription have been noted (Rose and Last, 1997; Fong and Zhou, 2001; Furger et al., 2002), these are insufficient to entirely explain the increase in mRNA accumulation. IME is therefore not simply due to traditional transcriptional enhancers embedded in introns, although examples of these are known. The distinction from enhancer elements is underscored by the need for introns to be within transcribed sequences and in their natural orientation to increase expression and that an enhancing intron must be within ~1 kb of the transcription start to have an effect (Rose, 2004). Taken together, these observations suggest a model where signals present in introns render the transcription machinery more processive, increasing the likelihood that full-length polyadenylated mRNAs will be formed and accumulate. In the absence of these signals, the polymerase may tend to dissociate and produce short, truncated transcripts that are rapidly degraded.

The different enhancing ability of introns suggests that some contain more stimulatory signals than do others, yet prior attempts to identify the responsible sequences by deletion analysis have largely failed to identify any specific elements necessary for IME (Clancy et al., 1994; Rose and Beliakoff, 2000). For example, removing 883 nucleotides from the 1028-nucleotide first intron of the maize (Zea mays) Sh1 gene has a negligible effect on its enhancing ability (Clancy and Hannah, 2002), and all sequences in Arabidopsis thaliana TRP1 intron 1 can be individually deleted without reducing the stimulation it mediates (Rose and Beliakoff, 2000). The sequences responsible for increasing expression are therefore likely to be redundant and dispersed throughout enhancing introns.

Here, we report an experimental and computational analysis of the intron sequences responsible for elevating expression. In addition to confirming the distributed nature of enhancing sequences, we found that the signals responsible for boosting expression are most abundant in introns near the start of transcription and that the compositional differences between promoter-proximal and later introns can be used to predict the ability of an intron to stimulate expression.

RESULTS

The Distribution of Stimulatory Sequences

To determine if IME signals are dispersed and redundant, we created a series of hybrid introns (Figure 1) containing fragments of an enhancing intron (UBQ10 intron 1) within a context of an otherwise nonenhancing intron (COR15a intron 2). Each was inserted at the same location in the TRP1:β-glucuronidase (GUS) reporter gene used previously to compare the UBQ10 and COR15a introns (Rose, 2002), and steady state expression levels were determined in homozygous single-copy transgenic Arabidopsis. Each of the first three quarters of the UBQ10 intron was individually sufficient for increasing mRNA accumulation (Figure 1B; see Supplemental Table 1 online). Even though the sequences at the 3′ end of the intron appear to be less active than those at the 5′ end, they are also further from the start of transcription in the hybrid introns, a variable known to diminish the stimulating effects of the UBQ10 intron (Rose, 2004). Still, the ability to boost expression is clearly dispersed throughout at least the first 238 nucleotides of the 304-nucleotide UBQ10 intron, and the enhancing effect of the entire intron is roughly the sum of the stimulation mediated by each part. This finding has significant implications for the mechanism of IME, which must be very different from more familiar regulatory elements, such as promoters, enhancers, mRNA secondary structures, or small RNAs, which depend on discrete or localized sequences.

Figure 1.
Enhancing Signals Are Distributed throughout UBQ10 Intron 1.

Computational Analysis of Introns

To better understand the mechanism of IME, we undertook a bioinformatics approach with two related goals: (1) to build a discriminator that would be able to predict the enhancing ability of an untested intron and (2) to identify sequence motifs responsible for IME. We expected that introns near the start of transcription would be particularly enriched in IME signals because most enhancing introns are first introns (Tables 1 and and2)2) and because of the ~1 kb positional requirement. Since introns from the middle or 3′ end of genes have not been observed to greatly affect expression, we expected these distal introns to have few IME signals. To determine if compositional properties in promoter-proximal and distal introns were correlated with IME, we built a word-based discriminator called the IMEter. The IMEter reports a log-odds score based on the frequencies of all possible words (nucleotide sequences of a given length): a positive score indicates the input sequence is similar to proximal introns, and a negative score indicates similarity to distal introns.

Table 1.
Qualitative Analysis of Expression in Arabidopsis
Table 2.
Qualitative Analysis of Expression in Rice

The IMEter was trained on a set of introns whose positions are known relative to their transcription start sites. We collected all introns in the Arabidopsis genome whose parent gene was represented by full-length cDNAs and formed an IMEter training set with half of these genes. Variable parameters for the training protocol include word size and the threshold positions of proximal and distal introns. For example, a particular parameter set may define a word size of 4, proximal introns as those appearing <200 bp from the transcription start, and distal introns as those appearing >800 bp from the start site. To evaluate a particular parameter set, we ran the IMEter on six experimentally tested introns (Rose, 2002) and plotted the IMEter scores against the observed level of mRNA accumulation (Figure 2A, closed symbols). These six introns represent the largest available data set in any species for which the absence of variables other than the intron, and the use of homozygous single-copy lines, permitted quantitative comparison of expression levels with minimal variation. We found that several values for word size and intron location result in accurate predictions for the enhancing ability of these six introns (see Supplemental Figure 1 online). Using the optimal parameters of word size 5, and proximal and distal introns split at 400 bp from the transcription start site, a regression line had an R2 value of 0.90.

Figure 2.
IMEter Scores in Arabidopsis and Rice Introns.

The high correlation between IMEter score and experimentally observed enhancement suggests that the IMEter can be used to predict the ability of introns to stimulate expression. To test this, we chose six previously uncharacterized Arabidopsis introns that have a range of IMEter scores but are similar in GC composition and length and are all found within 500 bp of the start of single-intron genes. The expression levels mediated by all six introns in single-copy TRP1:GUS fusions correlate with their IMEter scores (Figure 2A, open symbols), giving an R2 value of 0.89 for the entire set of experimentally tested introns.

Arabidopsis Introns

At least 21 Arabidopsis introns have been found by others to enhance expression. Quantitative comparisons between them usually cannot be made due to differences in the promoter used, the intron location, or the methods of transformation and measuring expression. Despite this limitation, these introns can be used to evaluate the IMEter because they are known to enhance expression. The IMEter assigns a positive score to all but one of these introns (Table 1), and the exception (from the eEF-1β gene) may affect expression by a mechanism unrelated to IME because it elevates expression when inserted upstream of the promoter in reverse orientation (Gidekel et al., 1996). Furthermore, 18 of the remaining 20 introns give a score of 20 or higher, even though <4.8% of the Arabidopsis introns analyzed generate scores that high. By contrast, three of the six introns shown not to affect expression have negative scores, and just one has a score over 10. Thus, the IMEter recognizes virtually all known enhancing introns from Arabidopsis and would have predicted their stimulating ability.

To analyze genome-wide properties of IMEter scores, we ran the IMEter on the testing set, which comprised the half of the Arabidopsis genome not used for training. On average, IMEter scores for introns are slightly negative. Approximately 2% of introns have scores >50, and <1% have scores of 80 or more. Average IMEter scores decline steadily with distance from the start of the gene, becoming negative at ~500 bp and leveling off ~1200 bp from the 5′ end (Figure 2C). This pattern is in striking agreement with the enhancement caused by a single intron as it is moved down a gene, which declines with distance until it is lost entirely between 550 and 1100 bp from the start of transcription (Rose, 2004). This pattern clearly indicates that introns near the start of a gene are compositionally distinct from later introns. IMEter scores of proximal introns are not uniformly high, however, but rather form a distribution centered just above 0, consistent with the inability of many first introns to elevate expression (Figure 2D).

Motifs Associated with Enhancement

To identify the sequences most responsible for the high IMEter scores of enhancing introns, and thus candidates for involvement in the mechanism of IME, we searched for sequence motifs among the 100 highest scoring introns with NestedMICA (Down and Hubbard, 2005). Several motifs were found (see Supplemental Figure 2 online), and the one whose abundance in the 12 tested introns best correlates with its ability to elevate TRP1:GUS expression is shown in Figure 3A. This motif appears numerous times and is dispersed throughout enhancing introns but is nearly absent from nonenhancing introns. The overlap between the motif and IMEter score density suggests that the IMEter is detecting the motif (Figure 3B), although the IMEter may be detecting other signals as well. The IMEter scores of the UBQ10-COR15a hybrid introns (Figure 1B) are proportional to their effect on expression (R2 = 0.93), indicating that the sequences recognized by the IMEter and those responsible for enhancement colocalize at this level of resolution.

Figure 3.
Motifs in Enhancing Introns.

Rice Introns

Some dicot introns can elevate expression in a monocot (Vain et al., 2004), suggesting that IME signals are conserved across species. To test this, we evaluated the 12 Arabidopsis introns with measured effects on TRP1:GUS expression using an IMEter that had been trained with rice (Oryza sativa) introns. The rice IMEter scores of these Arabidopsis introns generally correlate with their ability to stimulate expression (R2 = 0.74), indicating that these distantly related plants share some signals in common (Figure 2B). Even though IME has been observed in Caenorhabditis elegans and Drosophila melanogaster, an IMEter trained with introns from these species had no predictive value for Arabidopsis introns (R2 = 0.32 and 0.1, respectively), suggesting that either IME signals are not universally conserved or that general compositional differences interfere with their discovery.

Although we do not have quantitative expression values for rice introns, and therefore cannot use regression to correlate IMEter scores with expression levels, we trained the IMEter in rice and analyzed the 13 rice introns and three maize introns whose enhancing ability has been reported in the literature (Table 2). Thirteen of the enhancing introns had positive IMEter scores, nine of which were well over 100, while an intron known to have no effect on expression gave a negative score. An examination of all rice introns shows that only 2% of introns have scores of 100 or more (see Supplemental Figure 3A online). As in Arabidopsis, we find that promoter-proximal introns in rice have higher IMEter scores than distal introns (see Supplemental Figure 3B online). Since the IMEter apparently identifies enhancing introns in rice, we looked for motifs in the 100 highest scoring introns with NestedMICA just as we had done for Arabidopsis (see Supplemental Figure 4 online). The most common motif we found is very similar to the core of the Arabidopsis motif (Figure 3C).

DISCUSSION

Here, we show that signals concentrated in and dispersed throughout promoter-proximal introns are responsible for IME and identify a motif that comprises part of the IME signal. The IMEter algorithm we developed provides a measure of the abundance of promoter-proximal signals in any intron, which strongly predicts the ability of that intron to stimulate gene expression.

Although the correlation between the enhancing ability of introns and their IMEter scores is very high, it is not absolute. One potential explanation for discrepancies between IMEter scores and our quantitative expression data is that the distribution of enhancing sequences within an intron could influence its ability to elevate expression. For example, stimulatory sequences near the 5′ end of an intron might have the greatest impact on enhancement, while those closer to the 3′ end could influence overall IMEter score but have much less effect on expression. Thus, the two hybrid introns with UBQ10 sequences at the 5′ end had comparable effects on mRNA accumulation (Figure 1), even though the one with more COR15a sequence had a lower IMEter score. The contribution made to the total IMEter score by each part of an intron can be visualized by scanning the sequence in a sliding window (see Figure 3B), providing a high-resolution method to locate the regions that may be involved in the mechanism of enhancement. The IMEter will be refined to improve accuracy as more is learned about the sequences that boost expression.

The variables that preclude quantitative comparisons of the introns in Tables 1 and and22 are the least for different introns reported in the same publication, allowing a limited evaluation of the IMEter with these introns. In the only work to compare different introns at one location in the same reporter gene, the first intron from the rice tua1 gene was found to stimulate expression to a much higher degree than does the second or third intron from that gene (Jeon et al., 2000), consistent with their IMEter scores (Table 2). Similarly, both the enhancing ability and IMEter score of the first intron of the Arabidopsis SUVH3 gene are higher than those of the second intron (Table 1), although the second intron had the disadvantage of being further from the promoter because the introns were tested in their natural locations (Casas-Mollano et al., 2006). In most experiments, the promoters used were from the same gene as the intron being tested. The potential for gene-specific interactions between promoters and introns makes this approach quite reasonable but complicates even intrastudy comparisons of different introns. With this caveat, introns whose effects on expression are comparable to their IMEter scores include those from the histone H3, Cox5c, PRF, UBQ, and tua genes (Tables 1 and and2).2). The largest discrepancy between IMEter score and stimulation is the very low-scoring rice RPBF intron, which has a larger effect than the high-scoring GAMyb intron (Washio and Morikawa, 2006). Determining whether the RPBF intron increases expression by IME or an unrelated mechanism, such as an enhancer element, alternative promoter, or some other positive regulatory element located within the intron, will require further experimentation.

Monocot and dicot introns differ in several ways. For example, the GC content of introns is 32% in Arabidopsis and 39% in rice, and the average length of introns in rice is more than twice that in Arabidopsis. In addition, monocots are better able to splice introns from other species or introns containing stem-loop structures than are dicots (Keith and Chua, 1986; Goodall and Filipowicz, 1991), indicating that some aspects of intron recognition and splicing have diverged in these two groups. Despite these differences, the intron sequences that mediate enhancement must be sufficiently conserved for a rice-trained IMEter to generate scores for Arabidopsis introns that correlate with their ability to elevate expression in Arabidopsis. The decline in average IMEter scores with distance from the start of transcription (Figure 2C; see Supplemental Figure 3B online) and the inability of enhancing introns to affect expression from the 3′ UTR in both Arabidopsis and rice (Snowden et al., 1996; Rose, 2004) are further evidence that the mechanism of IME is conserved in these plants.

Why should enhancing signals be most common in proximal introns? Transcripts that originate from spurious promoters in the body of a gene are potentially dangerous because they could encode partial proteins with dominant-negative effects, and those from intergenic regions could result in antisense transcripts that could silence genes. A close association of promoters with signals that increase processivity would help to ensure that the majority of stable RNAs from a particular locus correspond to complete mRNAs. The C-terminal domain of the largest subunit of RNA polymerase II is a likely candidate for regulation by introns because the C-terminal domain is known to bind to splicing factors and also to regulate the activity of the transcription machinery (Meinhart et al., 2005). Other mechanisms are also possible, and even those in which intron sequences operate at the DNA or chromatin level have not been ruled out. While the available biochemical data do not support intron-specific differences in transcript initiation (Dean et al., 1989; Rose and Last, 1997), splicing efficiency (Rose, 2002), or RNA stability (Rethmeier et al., 1997), future technological improvements may reveal effects missed in earlier studies. The exon junction complex proteins deposited on mRNA during splicing promote nuclear export in Xenopus (Zhou et al., 2000) and increase association of the mRNA with polysomes in mammals (Wiegand et al., 2003; Nott et al., 2004). Similar mechanisms may operate in plants, as the increase in mRNA accumulation does not fully account for the boost in enzyme activity caused by introns in Arabidopsis (Rose, 2004).

It is unclear why some genes contain enhancing introns and some do not. Although highly expressed genes tend to have more enhancing signals than do poorly expressed ones, many abundantly expressed genes have introns with low IMEter scores. Perhaps there are several mechanisms to ensure complete transcription, and the IMEter is detecting only one kind. Alternatively, IME-like signals may be present in the 5′ UTR or coding sequences of these genes, bypassing the need for enhancing introns. Experiments to test these possibilities are underway.

The success of many biotechnology ventures depends on optimizing the expression of a transgene from another species. To elevate expression, the transgene should be engineered to contain an intron from the host species to avoid cross-species problems in intron recognition and splicing. The IMEter will be beneficial for finding host introns with a desired degree of enhancement or for identifying IME motifs whose abundance in an intron can be modified. These motifs will also form the basis for the biochemical isolation of factors involved in the mechanism of IME.

METHODS

Hybrid Introns

To introduce BamHI sites into the UBQ10 and COR15a introns, the regions of the intron 5′ and 3′ to the target site were amplified in separate PCR reactions using primers (see Supplemental Figure 5 online) containing the desired change. The PCR products were cloned and subsequently ligated together using the BamHI site, and the entire intron was verified by sequencing. The BglII or BclI sites were introduced by the same strategy into introns in which the BamHI site had been created. Hybrids between the modified UBQ10 and COR15a introns were made by conventional cloning using BamHI, BclI, and BglII, all of which generate the same cohesive end.

Expression Analysis

Introns were inserted as a PstI restriction fragment between exons 1 and 2 of a translational fusion between the Arabidopsis thaliana TRP1 gene and the Escherichia coli uidA gene (GUS) as described previously (Rose, 2002). Following Agrobacterium tumefaciens–mediated transformation of the constructs into Arabidopsis (ecotype Columbia) by floral dip (Clough and Bent, 1998), lines containing a single copy of the transgene were identified by individually placing 100 T2 seeds derived from each of 36 T1 plants on agar medium containing 50 μg mL−1 kanamycin. Lines that segregated kanamycin resistance and sensitivity in a 3:1 ratio were subjected to three gel blots in which genomic DNA was digested with BamHI, PstI, or BglII. Homozygous lines in which all three enzymes indicated a single-copy insert were identified as those whose T3 progeny were 100% kanamycin resistant. All of the single-copy lines obtained (between one and seven for each construct) were used in expression studies. Plants were grown in Sunshine Mix #1 (Sun Gro Horticulture) at 20°C and 60% humidity under continuous light. Total RNA was isolated from leaves of homozygous 3-week-old T3 plants using the RNeasy Plant mini kit (Qiagen). Steady state mRNA levels were determined in at least two biological replicates by hybridizing gel blots of total RNA with 32P-labeled GUS and TRP1 probes (Rose, 2004). Because the TRP1 probe includes only exons 4 through 9, it hybridizes to endogenous but not TRP1:GUS transcripts. The filters were scanned with a STORM 860 PhosphorImager and analyzed using ImageQuant 5.2 software (Molecular Dynamics). After correcting for differences in loading using the endogenous TRP1 mRNA signal, the fold enhancement by an intron was calculated as the amount of TRP1:GUS mRNA relative to that in an intronless TRP1:GUS control line. Because the variation in expression between different lines containing the same construct on a single blot was less than the variation of a single line in replicate blots (see Supplemental Table 1 online), all data points for a construct (n ≥ 7) were given equal weight in determining mean expression and standard deviations. The mRNA quantification was verified using GUS enzyme assays as detailed in Supplemental Table 2 online. Intron splicing efficiency was determined by reverse transcription using random hexamers, followed by PCR with primers that flank the intron as described (Rose, 2002).

Genome Data

The Arabidopsis genome sequence and annotation (TAIR7) were downloaded from The Institute for Genomic Research (TIGR; http://www.tigr.org/) and processed to ensure all the genes were complete, nonredundant, and of high quality. Since intron position was an important factor, and introns may occur in UTRs, genes were required to contain both 5′ and 3′ UTRs. To remove redundancy, only one isoform of any gene was kept, and any genes that were highly similar to other genes (>95% identical over 400 nucleotides) were removed. The decision of which isoform or gene to keep was based on order of precedence in the data file. Genes with unusually short coding sequences (<50 amino acids), short introns (<60 bp), or long introns (>1000 bp) were removed to ensure that all the genes were of high quality. The final set comprised 14,220 genes (53% of known genes) and 80,784 introns. The set was split randomly in half to create training and testing sets. Accession numbers of the genes in each set are listed in Supplemental Data Set 1 online.

The Oryza sativa genome and annotation (release 5) were also downloaded from TIGR. The processing procedure was similar to that used for Arabidopsis with one additional step. We found that some of the introns had abnormally high GC compositions and were possibly erroneous. Therefore, genes containing introns with >50% GC were removed. The final set consisted of 11,857 genes and 61,753 introns that were divided into training and test sets as listed in Supplemental Data Set 1 online. The Caenorhabditis elegans and Drosophila melanogaster genes were obtained from a previous collection (Korf, 2004).

The IMEter Algorithm

For each possible subsequence of length K in a test intron (except the conserved sequences at the 5′ and 3′ ends), its observed frequency in the group of promoter-proximal introns is divided by its expected occurrence in sequence with the average nucleotide composition of all the introns in a genome. The logarithms of the observed/expected ratios are summed, and the process is repeated using the observed frequencies in distal introns. The difference between these sums is the IMEter score, which will be positive for introns that resemble promoter-proximal introns. This can be expressed as follows:

equation M1

where S is IMEter score, i is the position in the sequence, L is the length of the intron, K is the word size, wi is a word of length K starting at position i, D is the length of the splice donor site consensus (usually 5), A is the length of the splice acceptor site consensus (usually 10), P is the frequency distribution of words of size K in promoter-proximal introns, and Q is the frequency distribution of words of size K in distal introns. The IMEter program is implemented in Perl with command line options for the various parameters. The IMEter is available for public use at http://korflab.ucdavis.edu/cgi-bin/web-imeter.pl, and the software is available from the authors on request.

Accession Numbers

The six introns chosen for testing on the basis of their IMEter scores are from the genes At1g05810, At1g62170, At1g69930, At3g04150, At3g21970, and At5g61930. The introns previously tested (Rose, 2002) are from UBQ10 (At4g05230), ATPK1 (At3g08730), TCH3 (At2g41100), COR15a (At2g425400), and TRP1 (formerly known as PAT1: At5g17990). Accession numbers of the genes used to train and test the IMEter in Arabidopsis and rice are in Supplemental Data Set 1 online. Additional accession numbers can be found in Table 1.

Supplemental Data

The following materials are available in the online version of this article.

  • Supplemental Figure 1. Optimizing IMEter Settings.
  • Supplemental Figure 2. Motifs in High-Scoring Arabidopsis Introns.
  • Supplemental Figure 3. IMEter Scores in Rice Introns.
  • Supplemental Figure 4. Motifs in High-Scoring Rice Introns.
  • Supplemental Figure 5. Strategy for Introducing Restriction Sites.
  • Supplemental Table 1. Expression Data.
  • Supplemental Table 2. Verification of mRNA Quantification.
  • Supplemental Data Set 1. Genes Used to Train and Test the IMEter in Arabidopsis and Rice.

Supplementary Material

[Supplemental Data]

Acknowledgments

This research was supported by USDA Grant 2006-35301-17072 to A.B.R. and by National Institutes of Health Grant K22-HG-0064 to I.K. We thank Kim Blahnik and Artem Zykovich for early contributions and Keith Bradnam and Lesilee Rose for comments on the manuscript.

Notes

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantcell.org) is: Alan B. Rose (ude.sivadcu@esorba).

[W]Online version contains Web-only data.

[OA]Open access articles can be viewed online without a subscription.

www.plantcell.org/cgi/doi/10.1105/tpc.107.057190

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