Expression proteomics of UPF1 knockdown in HeLa cells reveals autoregulation of hnRNP A2/B1 mediated by alternative splicing resulting in nonsense-mediated mRNA decay
© McGlincy et al; licensee BioMed Central Ltd. 2010
Received: 2 June 2010
Accepted: 14 October 2010
Published: 14 October 2010
In addition to acting as an RNA quality control pathway, nonsense-mediated mRNA decay (NMD) plays roles in regulating normal gene expression. In particular, the extent to which alternative splicing is coupled to NMD and the roles of NMD in regulating uORF containing transcripts have been a matter of debate.
In order to achieve a greater understanding of NMD regulated gene expression we used 2D-DiGE proteomics technology to examine the changes in protein expression induced in HeLa cells by UPF1 knockdown. QPCR based validation of the corresponding mRNAs, in response to both UPF1 knockdown and cycloheximide treatment, identified 17 bona fide NMD targets. Most of these were associated with bioinformatically predicted NMD activating features, predominantly upstream open reading frames (uORFs). Strikingly, however, the majority of transcripts up-regulated by UPF1 knockdown were either insensitive to, or even down-regulated by, cycloheximide treatment. Furthermore, the mRNA abundance of several down-regulated proteins failed to change upon UPF1 knockdown, indicating that UPF1's role in regulating mRNA and protein abundance is more complex than previously appreciated. Among the bona fide NMD targets, we identified a highly conserved AS-NMD event within the 3' UTR of the HNRNPA2B1 gene. Overexpression of GFP tagged hnRNP A2 resulted in a decrease in endogenous hnRNP A2 and B1 mRNA with a concurrent increase in the NMD sensitive isoforms.
Despite the large number of changes in protein expression upon UPF1 knockdown, a relatively small fraction of them can be directly attributed to the action of NMD on the corresponding mRNA. From amongst these we have identified a conserved AS-NMD event within HNRNPA2B1 that appears to mediate autoregulation of HNRNPA2B1 expression levels.
Nonsense-mediated mRNA decay (NMD) is one of a number of RNA surveillance pathways that help to ensure the fidelity of gene expression by degrading mRNAs that lack the proper arrangement of translational signals (reviewed in [1–4]). As the name suggests, NMD is responsible for recognizing and degrading mRNAs that contain premature termination codons (PTCs). In mammals, a termination codon is generally defined as premature by its spatial relationship to exon-exon junctions. The presence of one or more junctions at a distance of > 50-55 nucleotides downstream of the termination codon marks the mRNA for destruction [2, 4]. The biochemical basis of this effect is an interaction between the exon junction complex (EJC), a large multi-protein complex that is deposited on the mRNA as a result of splicing, and the complex formed at the stop codon by the terminating ribosome during the first round of translation [1, 2, 4]. This interaction is mediated by the essential NMD factors UPF1, UPF2 and UPF3 (UP-Frameshift suppressor, from their original identification in Saccharomyces cerevisiae). Furthermore, in a number of metazoans, the phosphorylation state of UPF1 is regulated by the factors SMG1 and SMG5-7 (Supressor with Morphological defects on the Genitalia, from their originally identification in Caenorhabditis elegans), which is required for NMD to take place . Until recently the position of any downstream EJCs was thought to be the primary determinant of a PTC in mammals. Recent studies, however, have shown that the distance from the PTC to various cues within the 3' UTR (particularly the cytoplasmic poly-A binding protein PABP) can also play an important role in defining termination events as aberrant [3, 8–13]. This is in a similar fashion to those organisms, such as S. cerevisiae, C. elegans and Drosophila melanogaster, where the EJC is absent or plays no role in NMD, and is thought to reflect a primordial mechanism of PTC recognition upon which, in mammals, the EJC has been superimposed [3, 4, 13].
Apart from its role in dealing with unintended errors in gene expression, NMD has a well documented role in regulating the abundance of many physiological transcripts in all model organism examined to date [14–21]. Moreover, many NMD factors are now known to have additional functions extending beyond NMD (reviewed in ). The difference between species in those genes regulated by NMD is thought to be the cause of the differing phenotypes of animals in which Upf1 has been removed [16, 19, 22]. Amongst these, Mus musculus lacking Upf1 are embryonic lethal , indicating that Upf1, and presumably NMD, plays an important role in mammalian physiology and development. NMD-regulated transcripts can be divided into two broad categories. First those mRNAs that "normally" possess a PTC. These include transcripts that contain upstream open reading frames (uORF) within their 5' UTR, or in which a PTC is introduced as the result of a regulated alternative splicing event (AS-NMD), including those transcripts with an intron more than 50-55 nt into the 3'UTR such that the coding sequence (CDS) termination codon appears premature [15, 16, 24–26]. Secondly, those mRNAs where NMD is co-opted as a decay mechanism through the interaction of UPF1 with a protein that recognizes a specific set of mRNAs. Two examples are staufen-1 (STAU1) mediated decay (SMD) and the decay of certain replication-dependent histone mRNAs at the end of S-phase of the mammalian cell cycle [27–29]. In both cases a protein recognizes a specific cis-element within the 3' UTR and also interacts with UPF1 [27–29]. mRNA degradation is then triggered in a fashion that is dependent on UPF1 and active translation, but independent of the other UPF proteins [27–29].
Previous large-scale investigations into the role of UPF1/NMD in regulating physiological gene expression in metazoans have focused on changes in mRNA abundance [15, 20, 21, 29–34]. In this study we have sought to deepen our understanding of the role of UPF1 in regulating physiological gene expression by examining the changes in protein expression in response to siRNA mediated depletion of UPF1 in HeLa cells, using the expression proteomics technique 2D difference gel electrophoresis (2D-DiGE). We observed a large number of alterations in protein levels; both increases and decreases. By analyzing the levels of the corresponding mRNAs after treatment with either siRNAs against UPF1 or the translation inhibitor cycloheximide we were able to identify a small group of bona fide NMD targets; indicating that UPF1's role in regulated gene expression may be more limited than previously thought. However, the majority of these bona fide NMD targets contained recognizable NMD-activating features, such as splicing dependent PTCs, introns in the 3'UTR and uORFs. From among these we identified a highly conserved AS-NMD event with the 3' UTR of the HNRNPA2B1 gene, which appears to be involved in the autoregulation of HNRNPA2B1 mRNA levels.
mRNA stabilized as a result of the inhibition of NMD is translated to yield protein
To further examine the differing response of pGFPint to the knockdown of different NMD factors, the levels of the NMD sensitive isoforms of SC35 (SFRS2) were examined by QPCR (1.6 and 1.7 kb , Figure 1D, right. Schematics of events in Figure 1E). Interestingly, the pattern of changes in the SC35 isoforms mirrored that of pGFPint mRNA: UPF1 knockdown provoked the largest fold change followed by SMG1 and then UPF2. Given the high degree of knockdown achieved for all the factors examined, it appears that NMD of pGFPint and SC35 1.6 and 1.7 kb mRNA is differentially sensitive to the knockdown of UPF1, UPF2 or SMG1. This phenomenon has been described previously and is thought to reflect distinct branches of the NMD pathway with differential requirements for UPF2 . Since the inception of this work two further reports of similar NMD reporter systems support our conclusion that mRNAs stabilized as a result of NMD inhibition are active substrates for translation [38, 39]. Indeed, this idea is also borne out by published data from more physiological circumstances [40–42].
A multi-gel 2D-DiGE study of UPF1 knockdown in HeLa cells reveals numerous changes in protein expression
To identify global changes in protein expression in response to UPF1 knockdown we performed a multi-gel 2D-DiGE study of HeLa cells in which UPF1 had been depleted by RNA interference (RNAi). Samples were harvested 48 h after the second siRNA hit on the basis that this provided sufficient time to observe the primary consequences of UPF1 knockdown, while minimizing any secondary indirect effects. The basic principle of 2D-DiGE is that protein extracts from two different biological situations (in this case HeLa cells treated with a control or targeted siRNA) are differentially labelled with fluorescent dyes before being mixed and fractionated by 2D gel electrophoresis [43, 44]. The fluorescent image of the gel is then examined to identify protein spots where one fluorescent dye predominates indicating the change in expression of one or more of the constituent proteins between the two biological situations [43, 44]. The protein spot is then excised from the gel and its composition determined by mass spectrometry [43, 44].
The 2D-DiGE multi-gel study resulted in identification of a large number of both upward and downward changes in protein expression (p < 0.01, Student's t-test, two tails). As expected, many but not all changes were common to both siRNAs (Figure 2C). Of the 3081 spots detected in the analysis, 47 spots increased in expression in response to Upf1_A treatment while 194 spots increased in expression in response to Upf1_B treatment. Of the upward changes, 35 were common to both siRNAs. Furthermore, Upf1_A treatment resulted in 97 spots decreasing in abundance while 297 spots decreased in abundance in response to Upf1_B treatment. Of the downward changes, 80 were common to both siRNAs.
Multivariate statistical analysis provides an alternative method to Student's t-test for identifying patterns in large multivariate datasets such as that generated by the 2D-DiGE multi-gel study . Abundance data from all spots (3081) for all samples was subject to principle component analysis (PCA) to examine how the experimental samples clustered on the basis of all spot changes. The scores scatter plot for the first two principal components revealed a separation between C2 and the two UPF1 knockdown conditions along PC1 (Figure 2D). Interestingly, there is no apparent separation between Upf1_A and Upf1_B treated samples. This was also the case when other PCs were examined (data not shown). This suggests that despite the appearance that some spots change with one siRNA but not the other, most spots undergo correlated changes in response to both siRNAs, although one change or the other may not achieve significance in the univariate sense.
In order to identify which proteins were responsible for the observed increases in expression, and hence are candidate UPF1 targets, 85 of the protein spots that had increased in expression were excised for identification by mass spectrometry (Additional file 1 1). Spots were picked first from those that had changed significantly in response to both Upf1_A and Upf1_B. Then, on the basis of the PCA, others were picked that had changed significantly in response to either siRNA, starting with those that had narrowly escaped significance with the second siRNA. 17 down-regulated spots were also picked, from those that had decreased significantly in response to both siRNAs (Additional file 1). Of the 85 up-regulated spots, 58 yielded sufficient material to allow protein identification, whereas of the 17 down-regulated spots, 13 yielded sufficient material. For each spot, potential protein constituents were identified from liquid chromatography-tandem mass spectrometry of trypic peptides produced by in-gel digestion, using the MASCOT search engine . As a result, 128 unique proteins were identified from up-regulated spots and 21 from down-regulated spots. Some proteins were identified in more than one spot, including 6 that were found in both up- and down-regulated spots. This could be due to post-translational modification of the proteins, or the existence of isoforms that are different in size or pI, but are indistinguishable by their tryptic peptide pattern. Information on the identified proteins and peptide sequences, along with the change observed for each spot is detailed in Additional file 2.
Validation of NMD targeted mRNAs
In order to determine which of the identified proteins represented bona fide NMD targets, two rounds of QPCR validation were employed. In the first round we tested whether levels of the mRNAs corresponding to the identified proteins were affected by UPF1 knockdown mediated by Upf1_A siRNA. Since NMD and the other UPF1-dependent mRNA decay pathways (SMD and histone mRNA decay) are dependent on active translation [27, 28, 48], we next measured changes in mRNA levels following treatment of cells with the translation inhibitor cycloheximide. For each gene of interest QPCR primers were designed to mRNA regions not known to undergo alternative splicing, and eight replicate samples were used in order to achieve the same statistical power as the 2D-DiGE multi-gel study [49, 50]. Only genes that showed statistically significant increases (p < 0.05, Student's t-test, one-tail) in response to both treatments were deemed to be genuine targets of NMD/UPF1-dependent mRNA decay.
The 47 validated UPF1 target genes from up-regulated spots were then subjected to the second round of validation by cycloheximide treatment. Of the 47 UPF1 targets, 17 (34%) increased in expression, as expected of authentic NMD targets (IMMT, GOLGA4, IDI2, TH1L, PLG, KIAA1529, CCT8, TUBA8, SFRS7, MAGEA1, CDC6, SERPINB1, NAPA, HNRNPA2B1, VAPB, RAB1A, RAB35). Of the remainder, one (CANX) failed to give an intelligible signal, 10 (21%) showed no significant change in expression, while 19 (40%) actually decreased in expression. The 30 genes that did not increase in expression in response to cycloheximide treatment may represent secondary effects of UPF1 knockdown or targets of UPF1 in processes other than NMD.
With reference to the original 2D DiGE analysis, of the 58 upregulated spots that yielded protein identifications, 34 (59%) contained at least one protein whose corresponding mRNA was validated as being upregulated by knockdown of UPF1, and in 26 cases (45%) the upregulated mRNA corresponded to the major protein component of the spot, as indicated by MASCOT scores (see Additional file 2). Of the 34 spots, 18 (i.e. 31% of the total) contained proteins that were also upregulated by cycloheximide treatment. In five cases (CCT8, SERPINB1, NAPA, HNRNPA2B1, RAB1A) the doubly validated NMD target corresponded to the major protein constituent of the protein spot, as judged by MASCOT scores, and so provides a clear explanation for the observed upregulation. A number of the other NMD targets were among the more abundant components of the spots in which they were identified (e.g. IMMT, VAPB, TUBA8, RAB35). In the remaining cases (e.g. GOLGA4, IDI2, TH1L, PLG, SFRS7, MAGEA1, CDC6, KIAA1529), the doubly validated NMD targets represented relatively minor constituents of their resident spots. In four of these cases the spot also contained a more abundant validated UPF1 target that was not cycloheximide upregulated.
The remaining 24 spots (41% of the total) contained no protein whose mRNA was upregulated by UPF1 knockdown. This suggests that relatively few of the changes in protein expression upon UPF1 knockdown can be attributed directly to UPF1's role in mRNA decay. This result is in broad agreement with the more extensively validated studies of UPF1's role in physiological gene expression [20, 21, 34, 51]. (discussed below)
Identification of NMD activating features
We next sought to identify possible NMD activating features within the doubly validated genes. To this end, maximum transcript alignments  of corresponding Unigene clusters  were generated using SPA  and examined for instances of: i) introns more than 50 nt downstream of the termination codon of the largest ORF within a transcript, as an indication of AS-NMD. ii) The presence of ORFs upstream of the largest ORF within a maximum transcript, as an indication of the presence of uORFs within the 5' UTR. Potential NMD sensitive maximum transcripts were then scored according to the number of peptides identified by mass spectrometry that were present within the protein sequence encoded by the largest ORF of the maximum transcript. Only transcripts encoding all of the identified peptides were considered as being potentially responsible for the observed upregulation of protein spots. For some genes, this step eliminated many potential NMD substrates. For example, the SFRS7 gene encodes the SR splicing regulatory protein 9G8, which has a well characterized AS-NMD event involving a "poison" cassette exon . In this study however, the 9G8 peptides identified by mass spectrometry are not encoded by the alternatively spliced PTC-containing isoform. In contrast, many of the SFRS7 maximum transcripts contain one or two additional short uORFs upstream of the main protein coding ORF.
Of the 17 doubly validated genes, we found evidence of at least one NMD feature in 12 cases. Notably, all five doubly validated genes that constituted the major components of their resident spots (CCT8, SERPINB1, NAPA, HNRNPA2B1, RAB1A) had at least one NMD feature that was consistent with the peptide data. The most common features, found in 11 cases, were uORFs. In addition, there were three genes (TH1L, NAPA and HNRNPA2B1) with one or more alternative splicing events at a sufficient distance downstream of the main ORF to activate NMD.
AS-NMD events in TH1L and NAPA
AS-NMD mediated autoregulation of HNRNPA2B1
The role of UPF1-dependent mRNA decay in regulating physiological gene expression
We have demonstrated that the knockdown of UPF1 in HeLa cells results in a large number of changes in protein expression but that only a minority of these can be attributed to UPF1's characterized roles in NMD and other translation dependent mRNA decay pathways. This result is in broad agreement with the more extensively validated studies of UPF1's role in physiological gene expression [20, 21, 34, 51], suggesting that NMD plays a more restricted role in regulating gene expression than previously claimed [67, 68]. For example, in order to measure the efficiency of NMD in cell lines expressing different amounts of RNPS1, Viegas and colleagues sought to identify genuine NMD target genes from genes identified by microarray as upregulated upon UPF1 knockdown . They examined both the abundance of the fully processed mRNA and pre-mRNA, finding that in the majority of cases (14/16) both were upregulated. This indicates that the increase in mRNA levels was likely to be a transcriptional effect rather than due to the direct action of NMD .
The majority of the 17 confirmed NMD targets (defined as UPF1 and translation-dependent) have not been previously identified by microarray studies of UPF1 dependent gene expression in mammals [15, 29–32, 51, 69], indicating the complementarity of proteomic and transcriptomic analyses. However, given the bias of 2D-DiGE towards higher abundance proteins, it may be that this mechanism is more pertinent for genes with lower absolute expression levels. Recent findings have indicated that the distance between the stop codon and poly(A) tail can also be an important determinant of NMD (reviewed in ). However, we were unable to find an over-representation of greater 3' UTR lengths within our set of doubly validated genes (data not shown). We believe that it is relevant that all of the identified NMD activating features within the 17 doubly validated NMD targets were either uORFs or introns positioned in the 3'UTR or towards the 3' end of the transcript. As a result the detected proteins would all represent regular full-length isoforms, and would be expected to be stable. The protein products produced from other stabilized AS-NMD substrate mRNAs might be inherently unstable due to their truncated nature. This would argue against the functional roles often proposed for these products [70, 71]. In support of this, we observed that the potential truncated PTB isoform, encoded by the AS-NMD targeted mRNA in which exon 11 is skipped , is not detectably expressed from cDNA expression vectors (in which there is no NMD activating feature) unless proteasome activity is inhibited by the proteasomal inhibitor MG132 (NJM and CWJS, unpublished observation). This suggests that the inherent instability of some protein products might preclude their identification as NMD targets by proteomic approaches. Nevertheless, a pilot DiGE experiment did not reveal a noticeable increase in upregulated spots when UPF1 knockdown was analyzed under conditions of proteasome inhibition by MG-132 (NJM and CWJS, unpublished observation), suggesting that our current investigation has not suffered substantially from this potentially confounding effect.
In addition to identifying genuine NMD targets, our validation strategy also highlighted a number of other interesting groups. First, those proteins whose mRNA was not up-regulated by UPF1 knockdown may represent targets of nonsense mediated translational repression (NMTR), wherein PTC containing mRNAs apparently escape NMD but do not produce detectable levels of protein [72, 73]. Secondly, those genes that were upregulated by UPF1 knockdown but not upregulated by cycloheximide treatment. An interesting feature of these 19 unusual UPF1 targets is an enrichment of heat shock proteins of the hsp90, hsp70 and hsp60 classes (HSP90AA1, HSP90AB1, HSPA1A, HSPD1, AHSA1). In S. cerevisiae a specialized mRNA decay pathway, termed initiation dependent decay, operates under conditions where translation initiation is down-regulated but not abolished [74, 75]. Of particular interest, initiation dependent decay targets a variety of heat shock proteins, including hsp70 and 90, and is dependent upon UPF1 and UPF2. While our experiments were not carried out under conditions where translation initiation is expected to be impaired, they suggest that initiation dependent decay may be relevant to mammalian systems. However, this observation could also be the result of a shared transcriptional activator of these heat-shock proteins being NMD sensitive, but generally translationally down-regulated by cyclohexamide. Thirdly, analysis of the spots that were down-regulated upon UPF1 knockdown indicate yet another potentialiy interesting group of UPF1 targets. None of the mRNAs corresponding to the protein constituents of these spots were down-regulated by UPF1 knockdown; indeed some were actually upregulated. This suggests that UPF1 may play a role in the synthesis or degradation of these proteins. Given UPF1's known roles, it seems more likely that it acts at the translational level and that for these proteins UPF1 has a positive influence on their translation.
uORFs as NMD features
The most prevalent NMD activating feature predicted for the doubly validated NMD targets was the presence of uORFs. Indeed, two of our confirmed cases that can be explained by uORFs have previously been identified as AS-NMD targets. SFRS7 (also known as 9G8) is already a well-characterised example of AS-NMD [55, 62, 76], our finding that some isoforms may also possess a uORF indicate that SFRS7's post-transcriptional regulation may be more complex than previously appreciated, as recently described for SFRS1 (SF2/ASF) . Furthermore, a CCT8 alternative isoform was reported to be sensitive to the translation inhibitor emetine by AS-sensitive microarray .
A priori it might be expected that all uORF containing mRNAs would be NMD sensitive. The termination codon of the uORF(s) would be premature with regard to the exon-exon junctions within the CDS, and would likely be at great distance from signals in the 3' UTR determining proper translation termination. This, however, does not appear to be the case as uORFs often mediate translational repression of the protein coding ORF without an accompanying decrease in mRNA abundance [26, 77]. Moreover, inhibition of NMD in C. elegans results in the upregulation of only some transcripts bearing uORFs . So what characteristics make a uORF baring transcript NMD sensitive? uORF length has been shown to be important; short open reading frames or those that have been translated more quickly favour translation reinitiation downstream [11, 78, 79], possibly by the remaining association of translation inititiation factors with the ribosome [80, 81]. Reinitiation then inhibits NMD [11, 78, 79]. So NMD sensitive uORFs might be expected to be longer than average, or composed of sequence that results in slow translation. Ramani et al. (2009) found a weak correlation between the Kozak consensus at the start codon of the protein coding ORF and the extent to which the uORF containing transcript was up-regulated in NMD deficient C. elegans. Calvo and colleagues examined the effect of various uORF characteristics on reduction in protein expression. They found that uORF containing 5' UTRs, when examined in a heterologous system, generally exerted a greater effect on protein abundance (average 58% decrease) than mRNA abundance (average 5% decrease). Similar trends were observed in published datasets they examined. The decreasing protein expression correlated with stronger context at the uAUG, a greater cap-uORF distance (both in the case of a single uORF) and, to a lesser extent, an increasing number of uORFs. In the case of a single uORF, uORF length and uORF-CDS distance did not correlate with the extent of protein repression. The absolute amplitude of changes in mRNA abundance are similar to those observed for our predicted uORF carrying genes. Unfortunately the relationship of these variables with decreasing mRNA abundance, which we might presume to be due to NMD, was not examined .
We have been unable to find any characteristics that distinguish the uORFs in our doubly validated NMD targets from others (data not shown). However, uORF mediated regulation is often complex, involving not only the uORFs themselves but also interactions with other conserved sequences and trans-acting factors [26, 83, 84]. Indeed, the relatively small fold changes in mRNA level observed during validation indicate that in each case only a proportion of the mRNA is NMD-sensitive, suggesting that some sort of probabilistic event is responsible. Thus, it is not clear that identification of a uORF is currently a powerful predictor of NMD sensitivity. A larger dataset and broader scope of analysis may prove more fruitful in finding some association between specific uORF characteristics, or groups thereof, and NMD-sensitivity.
Autoregulation of HNRNPA2B1 via AS-NMD
We have identified a highly conserved example of autoregulatory AS-NMD within the HNRNPA2B1 gene. The hnRNP family of proteins plays many roles in RNA metabolism [85, 86]. HNRNPA2B1 itself has been shown to regulate both alternative splicing  and mRNA stability . Our data is consistent with HNRNPA2B1 activating splicing within it's own UTR to produce NMD sensitive forms that account for the decrease in total gene expression: over-expression of the HNRNPA2 isoform resulted in down-regulation of A2 and B1 isoform expression and the up-regulation of one of the NMD-sensitive exon junctions within the 3' UTR (Figure 6). For simplicity we measured two UTR exon-exon junctions that would always be expected to be NMD (in)sensitive, but the splicing patterns involved are almost certainly more complex.
While hnRNP A/B proteins were initially characterised as splicing repressors [86, 89, 90], it has recently been shown that intronic binding of hnRNP A1/A2 proteins can activate splicing, particularly of elongated introns [87, 91]. This is thought to proceed by homophilic interactions between A2/A1 proteins bound at separate sites (or indeed heterophilic interactions between A1/A2 proteins and hnRNP F/H proteins) causing the looping out of portions of intron, which in turn results in promoting the splicing of said intron [87, 92]. We have not examined whether HNRNPA2B1 directly binds to its own UTR, but motifs thought to represent bindings sites for HNRNPA1 and HNRNPA2B1 (taken from ) are clearly present in the HNRNPA2B1 3' UTR introns we identified (Additional file 3). This also raises the possibility that HNRNPA1 may also regulate these splicing events. Indeed increased expression of HNRNPA1 has been observed to correlate with decreased HNRNPA2/B1 in some cancer cell lines .
AS-NMD within hnRNP and SR protein genes has been shown to mediate quantitative regulation by repressing protein expression at inappropriate times [63, 94–96] or providing homeostatic regulation of protein levels through autoregulatory negative feedback [32, 36, 58, 60–66]. Our data is consistent with the later case. However, these two modes of regulation are not mutually exclusive, and it will be interesting to see whether biological circumstances can be identified where this AS-NMD event is used to repress expression of HNRNPA2B1. Indeed, up-regulation of HNRNPA2B1 levels has pathological associations. Increased HNRNPA2 expression has also been observed in pancreas and breast cancer [97, 98], and in the foetal brain of Down's syndrome patients . Underscoring the functional relevance of these increases, increased expression of HNRNPA2B1 and PTBP1 has been shown to be responsible for the predominance of the PKM2 isoform that is the hallmark of many types of cancer, promoting the aerobic glycolysis that is important for cell growth [100, 101]. Furthermore, HNRNPA2 was recently shown to be responsible for splicing events that promote invasive migration of cancer cells in three-dimensional matrices 
Despite the large number of changes in protein expression upon UPF1 knockdown, our two-stage validation shows that a relatively small fraction of them can be directly attributed to the action of NMD on the corresponding mRNA. This indicates that the role of NMD in directly regulating gene expression may be less prominent than previously suggested. The majority of the doubly-validated mRNAs contain computationally predicted uORFs, confirming this feature as an indicator of NMD sensitivity. We have also identified three examples of AS-NMD, including a highly conserved AS-NMD event that appears to mediate autoregulation of HNRNPA2B1 expression levels. This extends the observation that many RNA binding proteins auto-regulate their own expression through highly conserved elements. Consideration of this autoregulation will be important when examining biological situations, such as several types of cancer, where HNRNPA2B1 levels are deregulated.
Construction of pEGFPint: an efficient artificial intron with associated exonic sequence was amplified from plasmid pY7  using primers PY7INTF (TCTCAGCAAAGCGGCCGCTGCTGCGGGC) and PY7INTR2 (CTCTAGAGTCCAATTGCCTGCAGGCA) and pfu high fidelity polymerase. The pY7 intron is based on a β-globin intron while the exons are exons 2 and 3 from α-tropomyosin . The resulting PCR product was cloned into pGEM T-easy (Invitrogen) and its identity confirmed by sequencing with T7 and SP6 primers. pEGFP-N1 (Promega) contains unique NotI and MfeI sites between the GFP stop codon and the SV40 polyA signals. The insert was liberated from pGEM T-easy by sequential digestion of the NotI and MfeI sites within PY7INTF and PY7INTR2 respectively and ligated with the corresponding fragment of pEGFP-N1. Cloning of FLAG-hnRNPA2: hnRNPA2 sequence was amplified from HeLa cell cDNA using primers hnRNPA2_F TACAGAATTCATGGAGAGAGAAAAGGAAC and hnRNPA2B1_R TCAGGTCGACGTATCGGCTCCTCCCACC. PCR was performed using 1.25 U Stratagene Native Pfu DNA Polymerase, 200 uM dNTPs and 400 uM primers. Cycling parameters: 95°C 2 min, [95°C 30 sec, 48°C 30 sec, 72°C 2 min]35, 72°C 5 min. The resulting PCR product was digested with EcoRI and SalI and ligated into pCI-NLS-FLAG , which allows expression of hnRNPA2 protein with N-terminal Flag tag and NLS, and 13 amino acid C-terminal tag. This cloning was confirmed by sequencing with T7 primer.
Cell culture and transfections
HeLa cells were cultured under standard conditions in DMEM medium with glutamax (Invitrogen) and 10% fetal bovine serum. HeLa cells stably expressing pGFPint were generated by lipofectAMINE (Invitrogen) transfection of approximately 6 μg of pGFPint linearised at the Apa LI site. Transformant cell lines were then selected through growth in medium supplemented with 1 mg/mL G418 (Sigma) and isolated through ring cloning. Cell lines were then constantly maintained in growth medium containing G418 with the exception of when they were being used in an experiment. siRNA transfection of HeLa cells was performed using lipofectAMINE 2000 (Invitrogen) according to the "two-hit" protocol previously described . The 19-mer sense target sequence and associated details of each siRNA are: control C2, 5'-GGUCCGGCUCCCCCAAAUG-3', 120 pmol/transfection or pGFPint experiments, 2.5 pmol/transfection 2D-DiGE expreiments ; Upf1_A, 5'-GAUGCAGUUCCGCUCCAUU-3', 120 pmol/transfection or pGFPint experiments, 2.5 pmol/transfection 2D-DiGE expreiments ; Upf1_B, 5'-GCUCCUACCUGGUGCAGUA-3', 2.5 pmol/transfection; Upf2, 5'-GGCUUUUGUCCCAGCCAUC-3', 120 pmol/transfection; SMG1_A, 5'-GUGAAGAUGUUCCCUAUGA-3', 120 pmol/transfection, Dharmacon siGENOME duplex D-005033-01-0050. Unless otherwise noted siRNA were designed and purchased from Dharmacon Inc. Samples were harvested for analysis 48 hours after the second transfection. In each case prior analysis had confirmed a high degree of knockdown at this time-point. This timepoint also represented a suitable trade-off between the need to allow sufficient accumulation of proteomic alterations directly resulting from UPF1 knockdown, while minimizing secondary effects. Such secondary effects might include false positives, which could arise if primary targets included, for example, transcription or translation factors, as well as false negatives due to compensatory mechanisms. Inhibition of NMD by cycloheximide was achieved by dosing HeLa cells to a final concentration of 10 ug/mL, or with an equivalent volume of DMSO, for 8 hours, as described .
Analysis of protein expression by western blot
Extracts of total protein were obtained from tissue culture cells using RIPA buffer or ASB14 buffer. The concentration of these extracts was determined by Bradford assay . Protein extracts were separated on 15% SDS-PAGE gels, transferred to PVDF membrane and then detected by a standard immunoblotting procedure followed by enhanced chemiluminescence detection. Primary antibodies used: rabbit anti-UPF1 , goat anti-UPF2 (Santa Cruz Biotechnology inc.), rabbit anti-GFP (Molecular Probes), rabbit anti-actin (Sigma), rabbit anti-ERK1 (invitrogen) Primary antibodies were detected by donkey anti-rabbit and donkey anti-goat antibodies conjugated to horseradish peroxidase.
Analysis of mRNA expression by RT-PCR and QPCR
Total cellular RNA was harvested using TRI reagent (Sigma) according to the manufacturers instructions. 1 μg total RNA was treated with DNase I (Ambion) before oligo-dT reverse transcription using 200 U Superscript II (Invitrogen). PCR for the AS-NMD event within U2AF35 was performed on 1/20th of the RT reaction using the primers U2AF35_F: 5'-GCACAATAAACCGACGTTTAGCCAG-3', and U2AF35_R: 5'-TGGATCGGCTGTCCATTAAACCAAC-3' for 30 cycles with an annealing temperature of 59°C. AS-NMD events within the TH1L gene were examined using primers: Hs.517148_1_F 5'-GGGAGGAGGTGGATGACTTC-3' and Hs.517148_1_R 5'-GGTCAGCTTGGAAAGGAGTT-3' (intron retention, Figure 4B) for 38 cycles at 60°C annealing; Hs.517148_2_F 5'-ACTGCTGGACAGGATGGTTC-3' and Hs.517148_2_R 5'-TACCTGCGATGCTGTCATTC-3' for 40 cycles at 60°C annealing (alternative 5' splice site, Figure 4C). Electronic images of gels were captured using a MultiDoc-It Imaging System (UVP) and band intensities were analysed using the associated Doc-It(r) LS Image Analysis Software (UVP). Quantitative PCR (QPCR) was performed on a Rotor-GeneTM 6000 (QIAGEN) using a SYBR green master mix (Applied Biosystems). QPCR data was analysed using the comparative concentration module of the Rotor-Gene software, which is based on the second derivative maximum method described by Tichopad et al.. Signal for the gene of interest (GOI) was normalized to GAPDH or HPRT levels then fold change in mRNA levels was calculated relative to the control sample. Gene specific QPCR primers were generally obtained from Primerbank  or designed using Primer3 plus , for sequences see Additional file 4. For each primer pair the formation of a single product was confirmed by melt curve analysis .
Proteomics 2D-DiGE multi-gel study
Proteomics work was performed at the Cambridge Centre for Proteomics, Cambridge Systems Biology Centre, University of Cambridge. Extracts of total protein for analysis by 2D-DiGE were obtained from tissue culture cells using ASB14 lysis buffer and their concentrations quantified by DC Bradford protein assay (Biorad). For each sample 100 μg total protein was used for analysis. Protein separation was performed using a pI range of pH3-10 (non-linear strip) and a 12.5% SDS-PAGE gel. CyDye labeling, 2D protein separation, gel imaging, and analysis were performed as described previously using systems and software primarily obtained from GE healthcare [46, 49, 63, 111]. PCA was performed using the software package SIMCA (Umetrics). Spots present in < 75% of the experimental samples (1061) were excluded, leaving 2021 for analysis. The first eight principal components (PCs) describing the data were calculated and the first two, PC1 and PC2, identified as significant. PC1 and PC2 result in a model with R2 = 0.55 (goodness of fit) and Q2 = 0.34 (goodness of prediction). Protein spots were excised both manually from gels stained with colloidal Coomassie, and automatically from fluorescently labelled gels using a CyProt-Picker robotics system (GE Healthcare). The protein constituents of the spots were then identified by LC-MS/MS sequencing of the tryptic peptides produced by in-gel digestion of the spots with trypsin. MS/MS fragmentation data were used to search the NCBI primary sequence database using MASCOT search engine .
Computational prediction of AS-NMD was performed using a computational pipeline based on that described previously [112, 113]. To begin with the Unigene cluster(s)  corresponding to each gene of interest was aligned to the genome sequence using SPA . The resulting clusters of alignments were then processed by PASA . PASA acts to subsume equivalent alignments to form a number of maximal transcript assemblies (termed maximum transcripts) that represent alternative mRNA isoforms consistent with the data from the alignment cluster. For each maximum transcript the largest ORF was defined and tested to determine whether the stop codon lay greater than 50 nucleotides upstream of an exon-exon junction. If this was the case for one or more of the maximum transcripts corresponding to a particular gene, then the gene was designated as possessing AS-NMD.
uORF prediction was performed on all the RefSeq transcripts and Ensembl annotated 5' UTRs corresponding to the genes of interest. In the case of the Refseq transcripts the largest ORF was defined and then the region directly upstream of this taken to be the 5' UTR. Then, for both sets of UTRs, ORFs beginning with ATG were sought for in the forward three reading frames.
Finally, potential NMD sensitive maximum transcripts were then scored according to the number of peptides identified by mass spectrometry that were present within the protein sequence encoded by the largest ORF of the maximum transcript. Only transcripts encoding all of the identified peptides were considered as being potentially responsible for the observed upregulation of protein spots.
1 μg of DNAase I treated total RNA from HeLa cells having undergone UPF1 knockdown was subject to reverse transcription by superscript II (Invitrogen) using an oligo-dT primer with the 5' adaptor sequence: 5'-GGACGCGTAAGCTTGTCGAC-3'. PCR was then performed using a primer with the adaptor sequence and primers within both the terminal coding exon of hnRNPA2/B1 (A2B15'1: TTTGGTGGTAGCAGGAACAT, A2B15'2: TGGAGGAAACTATGGTCCAG) and within predicted portions of the 3' UTR (A2B15'3: TTGGTTCCTTCAGTGGTGTT, A2B15'4: TGCTGCCACAAAGACTGTAA). Sequences from these reactions were cloned into pGEM T-easy (Invitrogen) and sequenced.
Sorting of cells by flow cytometry
2 × 105 HeLa cells/well of a 6 well plate were co-transfected with 1 μg pCI-NLS-FLAG hnRNPA2 (or the empty pCI-NLS-FLAG vector) and an equivalent molar amount of pEGFP-N1 (927.94 ng) using Lipofectamine 2000 (Invitrogen). 48 hours later cells were harvested for flow cytometry by trypsination. Cells from four wells were pooled for each replicate and resuspended in 1 mL DMEM + 2% FCS. For each replicate 1 × 106 GFP positive cells were collected using a MoFlo high-speed cell sorter (Beckman Coulter). GFP flourescence was detected using a 530/30 filter and live/dead cells discriminated with To-Pro-3 staining, detected using a 670/30 filter. Cells were gated based on forward and side scatter to eliminate debris and then doublet discrimination was carried out to ensure only single cells were sorted (Additional file 5).
We would like to thank members of the Cambridge Centre for Proteomics for their invaluable help and advice in the execution of this study. We thank P. Berninger for his help with programming in Perl, J. Mendell for the kind gift of antibodies against UPF1. Work in CWJS' laboratory is funded by the Wellcome Trust (077877) and in part by the EC grant EURASNET-LSHG-CT-2005-518238. Collaboration with MZ's group was also supported by EURASNET. NJM was supported by a studentship from the MRC. LYT was supported by a studentship from the Cambridge Australia Trust.
- Shyu AB, Wilkinson MF, van Hoof A: Messenger RNA regulation: to translate or to degrade. Embo J. 2008, 27 (3): 471-481. 10.1038/sj.emboj.7601977.PubMed CentralPubMedGoogle Scholar
- Isken O, Maquat LE: The multiple lives of NMD factors: balancing roles in gene and genome regulation. Nat Rev Genet. 2008Google Scholar
- Brogna S, Wen J: Nonsense-mediated mRNA decay (NMD) mechanisms. Nat Struct Mol Biol. 2009, 16 (2): 107-113. 10.1038/nsmb.1550.PubMedGoogle Scholar
- Nicholson P, Yepiskoposyan H, Metze S, Zamudio Orozco R, Kleinschmidt N, Muhlemann O: Nonsense-mediated mRNA decay in human cells: mechanistic insights, functions beyond quality control and the double-life of NMD factors. Cell Mol Life Sci. 2010, 67 (5): 677-700. 10.1007/s00018-009-0177-1.PubMedGoogle Scholar
- Culbertson MR, Underbrink KM, Fink GR: Frameshift suppression Saccharomyces cerevisiae. II. Genetic properties of group II suppressors. Genetics. 1980, 95 (4): 833-853.PubMed CentralPubMedGoogle Scholar
- Hodgkin J, Papp A, Pulak R, Ambros V, Anderson P: A new kind of informational suppression in the nematode Caenorhabditis elegans. Genetics. 1989, 123 (2): 301-313.PubMed CentralPubMedGoogle Scholar
- Yamashita A, Kashima I, Ohno S: The role of SMG-1 in nonsense-mediated mRNA decay. Biochim Biophys Acta. 2005, 1754 (1-2): 305-315.PubMedGoogle Scholar
- Behm-Ansmant I, Gatfield D, Rehwinkel J, Hilgers V, Izaurralde E: A conserved role for cytoplasmic poly(A)-binding protein 1 (PABPC1) in nonsense-mediated mRNA decay. Embo J. 2007, 26 (6): 1591-1601. 10.1038/sj.emboj.7601588.PubMed CentralPubMedGoogle Scholar
- Ivanov PV, Gehring NH, Kunz JB, Hentze MW, Kulozik AE: Interactions between UPF1, eRFs, PABP and the exon junction complex suggest an integrated model for mammalian NMD pathways. Embo J. 2008, 27 (5): 736-747. 10.1038/emboj.2008.17.PubMed CentralPubMedGoogle Scholar
- Eberle AB, Stalder L, Mathys H, Orozco RZ, Muhlemann O: Posttranscriptional gene regulation by spatial rearrangement of the 3' untranslated region. PLoS Biol. 2008, 6 (4): e92-10.1371/journal.pbio.0060092.PubMed CentralPubMedGoogle Scholar
- Silva AL, Ribeiro P, Inacio A, Liebhaber SA, Romao L: Proximity of the poly(A)-binding protein to a premature termination codon inhibits mammalian nonsense-mediated mRNA decay. Rna. 2008, 14 (3): 563-576. 10.1261/rna.815108.PubMed CentralPubMedGoogle Scholar
- Singh G, Rebbapragada I, Lykke-Andersen J: A competition between stimulators and antagonists of Upf complex recruitment governs human nonsense-mediated mRNA decay. PLoS Biol. 2008, 6 (4): e111-10.1371/journal.pbio.0060111.PubMed CentralPubMedGoogle Scholar
- Rebbapragada I, Lykke-Andersen J: Execution of nonsense-mediated mRNA decay: what defines a substrate?. Curr Opin Cell Biol. 2009, 21 (3): 394-402. 10.1016/j.ceb.2009.02.007.PubMedGoogle Scholar
- Morrison M, Harris KS, Roth MB: smg mutants affect the expression of alternatively spliced SR protein mRNAs in Caenorhabditis elegans. Proc Natl Acad Sci USA. 1997, 94 (18): 9782-9785. 10.1073/pnas.94.18.9782.PubMed CentralPubMedGoogle Scholar
- Mendell JT, Sharifi NA, Meyers JL, Martinez-Murillo F, Dietz HC: Nonsense surveillance regulates expression of diverse classes of mammalian transcripts and mutes genomic noise. Nat Genet. 2004, 36 (10): 1073-1078. 10.1038/ng1429.PubMedGoogle Scholar
- Neu-Yilik G, Gehring NH, Hentze MW, Kulozik AE: Nonsense-mediated mRNA decay: from vacuum cleaner to Swiss army knife. Genome Biol. 2004, 5 (4): 218-10.1186/gb-2004-5-4-218.PubMed CentralPubMedGoogle Scholar
- Rehwinkel J, Letunic I, Raes J, Bork P, Izaurralde E: Nonsense-mediated mRNA decay factors act in concert to regulate common mRNA targets. Rna. 2005, 11 (10): 1530-1544. 10.1261/rna.2160905.PubMed CentralPubMedGoogle Scholar
- Guan Q, Zheng W, Tang S, Liu X, Zinkel RA, Tsui KW, Yandell BS, Culbertson MR: Impact of nonsense-mediated mRNA decay on the global expression profile of budding yeast. PLoS Genet. 2006, 2 (11): e203-10.1371/journal.pgen.0020203.PubMed CentralPubMedGoogle Scholar
- Rehwinkel J, Raes J, Izaurralde E: Nonsense-mediated mRNA decay: Target genes and functional diversification of effectors. Trends Biochem Sci. 2006, 31 (11): 639-646. 10.1016/j.tibs.2006.09.005.PubMedGoogle Scholar
- Hansen KD, Lareau LF, Blanchette M, Green RE, Meng Q, Rehwinkel J, Gallusser FL, Izaurralde E, Rio DC, Dudoit S: Genome-wide identification of alternative splice forms down-regulated by nonsense-mediated mRNA decay in Drosophila. PLoS Genet. 2009, 5 (6): e1000525-10.1371/journal.pgen.1000525.PubMed CentralPubMedGoogle Scholar
- Ramani AK, Nelson AC, Kapranov P, Bell I, Gingeras TR, Fraser AG: High resolution transcriptome maps for wild-type and nonsense-mediated decay-defective Caenorhabditis elegans. Genome Biol. 2009, 10 (9): R101-10.1186/gb-2009-10-9-r101.PubMed CentralPubMedGoogle Scholar
- Wittkopp N, Huntzinger E, Weiler C, Sauliere J, Schmidt S, Sonawane M, Izaurralde E: Nonsense-mediated mRNA decay effectors are essential for zebrafish embryonic development and survival. Mol Cell Biol. 2009, 29 (13): 3517-3528. 10.1128/MCB.00177-09.PubMed CentralPubMedGoogle Scholar
- Medghalchi SM, Frischmeyer PA, Mendell JT, Kelly AG, Lawler AM, Dietz HC: Rent1, a trans-effector of nonsense-mediated mRNA decay, is essential for mammalian embryonic viability. Hum Mol Genet. 2001, 10 (2): 99-105. 10.1093/hmg/10.2.99.PubMedGoogle Scholar
- Mignone F, Gissi C, Liuni S, Pesole G: Untranslated regions of mRNAs. Genome Biol. 2002, 3 (3): REVIEWS0004-10.1186/gb-2002-3-3-reviews0004.PubMed CentralPubMedGoogle Scholar
- Soergel DAW, Lareau LF, Brenner SE: Regulation of gene expression by the coupling of alternative splicing and nonsense-mediated mRNA decay. Nonsense-mediated mRNA decay. Edited by: Maquat LE. 2006, Landes BioscienceGoogle Scholar
- Sachs MS, Geballe AP: Downstream control of upstream open reading frames. Genes Dev. 2006, 20 (8): 915-921. 10.1101/gad.1427006.PubMedGoogle Scholar
- Kaygun H, Marzluff WF: Regulated degradation of replication-dependent histone mRNAs requires both ATR and Upf1. Nat Struct Mol Biol. 2005, 12 (9): 794-800. 10.1038/nsmb972.PubMedGoogle Scholar
- Kim YK, Furic L, Desgroseillers L, Maquat LE: Mammalian Staufen1 recruits Upf1 to specific mRNA 3'UTRs so as to elicit mRNA decay. Cell. 2005, 120 (2): 195-208. 10.1016/j.cell.2004.11.050.PubMedGoogle Scholar
- Kim YK, Furic L, Parisien M, Major F, Desgroseillers L, Maquat LE: Staufen1 regulates diverse classes of mammalian transcripts. Embo J. 2007, 26 (11): 2670-2681. 10.1038/sj.emboj.7601712.PubMed CentralPubMedGoogle Scholar
- Pan Q, Saltzman AL, Kim YK, Misquitta C, Shai O, Maquat LE, Frey BJ, Blencowe BJ: Quantitative microarray profiling provides evidence against widespread coupling of alternative splicing with nonsense-mediated mRNA decay to control gene expression. Genes Dev. 2006, 20 (2): 153-158. 10.1101/gad.1382806.PubMed CentralPubMedGoogle Scholar
- Wittmann J, Hol EM, Jack HM: hUPF2 silencing identifies physiologic substrates of mammalian nonsense-mediated mRNA decay. Mol Cell Biol. 2006, 26 (4): 1272-1287. 10.1128/MCB.26.4.1272-1287.2006.PubMed CentralPubMedGoogle Scholar
- Ni JZ, Grate L, Donohue JP, Preston C, Nobida N, O'Brien G, Shiue L, Clark TA, Blume JE, Ares M: Ultraconserved elements are associated with homeostatic control of splicing regulators by alternative splicing and nonsense-mediated decay. Genes Dev. 2007, 21 (6): 708-718. 10.1101/gad.1525507.PubMed CentralPubMedGoogle Scholar
- Saltzman AL, Kim YK, Pan Q, Fagnani MM, Maquat LE, Blencowe BJ: Regulation of multiple core spliceosomal proteins by alternative splicing-coupled nonsense-mediated mRNA decay. Mol Cell Biol. 2008Google Scholar
- Barberan-Soler S, Lambert NJ, Zahler AM: Global analysis of alternative splicing uncovers developmental regulation of nonsense-mediated decay in C. elegans. Rna. 2009, 15 (9): 1652-1660. 10.1261/rna.1711109.PubMed CentralPubMedGoogle Scholar
- Scadden ADJ, Smith CW: Interactions between the terminal bases of mammalian introns are retained in inosine-containing pre-mRNAs. Embo J. 1995, 14 (13): 3236-3246.PubMed CentralPubMedGoogle Scholar
- Sureau A, Gattoni R, Dooghe Y, Stevenin J, Soret J: SC35 autoregulates its expression by promoting splicing events that destabilize its mRNAs. Embo J. 2001, 20 (7): 1785-1796. 10.1093/emboj/20.7.1785.PubMed CentralPubMedGoogle Scholar
- Gehring NH, Kunz JB, Neu-Yilik G, Breit S, Viegas MH, Hentze MW, Kulozik AE: Exon-junction complex components specify distinct routes of nonsense-mediated mRNA decay with differential cofactor requirements. Mol Cell. 2005, 20 (1): 65-75. 10.1016/j.molcel.2005.08.012.PubMedGoogle Scholar
- Paillusson A, Hirschi N, Vallan C, Azzalin CM, Muhlemann O: A GFP-based reporter system to monitor nonsense-mediated mRNA decay. Nucleic Acids Res. 2005, 33 (6): e54-10.1093/nar/gni052.PubMed CentralPubMedGoogle Scholar
- Boelz S, Neu-Yilik G, Gehring NH, Hentze MW, Kulozik AE: A chemiluminescence-based reporter system to monitor nonsense-mediated mRNA decay. Biochem Biophys Res Commun. 2006, 349 (1): 186-191. 10.1016/j.bbrc.2006.08.017.PubMedGoogle Scholar
- Dreumont N, Maresca A, Boisclair-Lachance JF, Bergeron A, Tanguay RM: A minor alternative transcript of the fumarylacetoacetate hydrolase gene produces a protein despite being likely subjected to nonsense-mediated mRNA decay. BMC Mol Biol. 2005, 6 (1): 1-10.1186/1471-2199-6-1.PubMed CentralPubMedGoogle Scholar
- Holbrook JA, Neu-Yilik G, Hentze MW, Kulozik AE: Nonsense-mediated decay approaches the clinic. Nat Genet. 2004, 36 (8): 801-808. 10.1038/ng1403.PubMedGoogle Scholar
- Brumbaugh KM, Otterness DM, Geisen C, Oliveira V, Brognard J, Li X, Lejeune F, Tibbetts RS, Maquat LE, Abraham RT: The mRNA surveillance protein hSMG-1 functions in genotoxic stress response pathways in mammalian cells. Mol Cell. 2004, 14 (5): 585-598. 10.1016/j.molcel.2004.05.005.PubMedGoogle Scholar
- Alban A, David SO, Bjorkesten L, Andersson C, Sloge E, Lewis S, Currie I: A novel experimental design for comparative two-dimensional gel analysis: two-dimensional difference gel electrophoresis incorporating a pooled internal standard. Proteomics. 2003, 3 (1): 36-44. 10.1002/pmic.200390006.PubMedGoogle Scholar
- Vanden Bergh G, Arckens L: Fluorescent two-dimensional difference gel electrophoresis unveils the potential of gel-based proteomics. Curr Opin Biotechnol. 2004, 15 (1): 38-43. 10.1016/j.copbio.2003.12.001.Google Scholar
- Pacheco TR, Gomes AQ, Barbosa-Morais NL, Benes V, Ansorge W, Wollerton M, Smith CW, Valcarcel J, Carmo-Fonseca M: Diversity of vertebrate splicing factor U2AF35: identification of alternatively spliced U2AF1 mRNAS. J Biol Chem. 2004, 279 (26): 27039-27049. 10.1074/jbc.M402136200.PubMedGoogle Scholar
- Karp NA, Griffin JL, Lilley KS: Application of partial least squares discriminant analysis to two-dimensional difference gel studies in expression proteomics. Proteomics. 2005, 5 (1): 81-90. 10.1002/pmic.200400881.PubMedGoogle Scholar
- Perkins DN, Pappin DJ, Creasy DM, Cottrell JS: Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis. 1999, 20 (18): 3551-3567. 10.1002/(SICI)1522-2683(19991201)20:18<3551::AID-ELPS3551>3.0.CO;2-2.PubMedGoogle Scholar
- Chang YF, Imam JS, Wilkinson MF: The nonsense-mediated decay RNA surveillance pathway. Annu Rev Biochem. 2007, 76: 51-74. 10.1146/annurev.biochem.76.050106.093909.PubMedGoogle Scholar
- Karp NA, Lilley KS: Maximising sensitivity for detecting changes in protein expression: experimental design using minimal CyDyes. Proteomics. 2005, 5 (12): 3105-3115. 10.1002/pmic.200500083.PubMedGoogle Scholar
- Lenth RV: Java Applets for Power and Sample Size. 2006Google Scholar
- Viegas MH, Gehring NH, Breit S, Hentze MW, Kulozik AE: The abundance of RNPS1, a protein component of the exon junction complex, can determine the variability in efficiency of the Nonsense Mediated Decay pathway. Nucleic Acids Res. 2007Google Scholar
- Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK, Hannick LI, Maiti R, Ronning CM, Rusch DB, Town CD: Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 2003, 31 (19): 5654-5666. 10.1093/nar/gkg770.PubMed CentralPubMedGoogle Scholar
- Pontius JU, Wagner L, Schuler GD: UniGene: a unified view of the transcriptome. The NCBI Handbook. 2003, Bethesda (MD): National Center for Biotechnology InformationGoogle Scholar
- van Nimwegen E, Paul N, Sheridan R, Zavolan M: SPA: a probabilistic algorithm for spliced alignment. PLoS Genet. 2006, 2 (4): e24-10.1371/journal.pgen.0020024.PubMed CentralPubMedGoogle Scholar
- Lareau LF, Inada M, Green RE, Wengrod JC, Brenner SE: Unproductive splicing of SR genes associated with highly conserved and ultraconserved DNA elements. Nature. 2007, 446 (7138): 926-929. 10.1038/nature05676.PubMedGoogle Scholar
- Kent WJ: BLAT--the BLAST-like alignment tool. Genome Res. 2002, 12 (4): 656-664.PubMed CentralPubMedGoogle Scholar
- Kuersten S, Goodwin EB: The power of the 3' UTR: translational control and development. Nat Rev Genet. 2003, 4 (8): 626-637. 10.1038/nrg1125.PubMedGoogle Scholar
- Wollerton MC, Gooding C, Wagner EJ, Garcia-Blanco MA, Smith CW: Autoregulation of polypyrimidine tract binding protein by alternative splicing leading to nonsense-mediated decay. Mol Cell. 2004, 13 (1): 91-100. 10.1016/S1097-2765(03)00502-1.PubMedGoogle Scholar
- Bejerano G, Pheasant M, Makunin I, Stephen S, Kent WJ, Mattick JS, Haussler D: Ultraconserved elements in the human genome. Science. 2004, 304 (5675): 1321-1325. 10.1126/science.1098119.PubMedGoogle Scholar
- Rossbach O, Hung LH, Schreiner S, Grishina I, Heiner M, Hui J, Bindereif A: Auto- and cross-regulation of the hnRNP L proteins by alternative splicing. Mol Cell Biol. 2009, 29 (6): 1442-1451. 10.1128/MCB.01689-08.PubMed CentralPubMedGoogle Scholar
- Heintzen C, Nater M, Apel K, Staiger D: AtGRP7, a nuclear RNA-binding protein as a component of a circadian-regulated negative feedback loop in Arabidopsis thaliana. Proc Natl Acad Sci USA. 1997, 94 (16): 8515-8520. 10.1073/pnas.94.16.8515.PubMed CentralPubMedGoogle Scholar
- Lejeune F, Cavaloc Y, Stevenin J: Alternative splicing of intron 3 of the serine/arginine-rich protein 9G8 gene. Identification of flanking exonic splicing enhancers and involvement of 9G8 as a trans-acting factor. J Biol Chem. 2001, 276 (11): 7850-7858. 10.1074/jbc.M009510200.PubMedGoogle Scholar
- Spellman R, Llorian M, Smith CW: Crossregulation and functional redundancy between the splicing regulator PTB and its paralogs nPTB and ROD1. Mol Cell. 2007, 27 (3): 420-434. 10.1016/j.molcel.2007.06.016.PubMed CentralPubMedGoogle Scholar
- Staiger D, Zecca L, Wieczorek Kirk DA, Apel K, Eckstein L: The circadian clock regulated RNA-binding protein AtGRP7 autoregulates its expression by influencing alternative splicing of its own pre-mRNA. Plant J. 2003, 33 (2): 361-371. 10.1046/j.1365-313X.2003.01629.x.PubMedGoogle Scholar
- Stoilov P, Daoud R, Nayler O, Stamm S: Human tra2-beta1 autoregulates its protein concentration by influencing alternative splicing of its pre-mRNA. Hum Mol Genet. 2004, 13 (5): 509-524. 10.1093/hmg/ddh051.PubMedGoogle Scholar
- Sun S, Zhang Z, Sinha R, Karni R, Krainer AR: SF2/ASF autoregulation involves multiple layers of post-transcriptional and translational control. Nat Struct Mol Biol. 2010Google Scholar
- Green RE, Lewis BP, Hillman RT, Blanchette M, Lareau LF, Garnett AT, Rio DC, Brenner SE: Widespread predicted nonsense-mediated mRNA decay of alternatively-spliced transcripts of human normal and disease genes. Bioinformatics. 2003, 19 (1): i118-121. 10.1093/bioinformatics/btg1015.PubMedGoogle Scholar
- Hillman RT, Green RE, Brenner SE: An unappreciated role for RNA surveillance. Genome Biol. 2004, 5 (2): R8-10.1186/gb-2004-5-2-r8.PubMed CentralPubMedGoogle Scholar
- Chan WK, Huang L, Gudikote JP, Chang YF, Imam JS, MacLean JA, Wilkinson MF: An alternative branch of the nonsense-mediated decay pathway. Embo J. 2007, 26 (7): 1820-1830. 10.1038/sj.emboj.7601628.PubMed CentralPubMedGoogle Scholar
- Donnadieu E, Jouvin MH, Rana S, Moffatt MF, Mockford EH, Cookson WO, Kinet JP: Competing functions encoded in the allergy-associated F(c)epsilonRIbeta gene. Immunity. 2003, 18 (5): 665-674. 10.1016/S1074-7613(03)00115-8.PubMedGoogle Scholar
- Kumar S, Lopez AJ: Negative feedback regulation among SR splicing factors encoded by Rbp1 and Rbp1-like in Drosophila. Embo J. 2005, 24 (14): 2646-2655. 10.1038/sj.emboj.7600723.PubMed CentralPubMedGoogle Scholar
- Lee HC, Oh N, Cho H, Choe J, Kim YK: Nonsense-mediated translational repression involves exon junction complex downstream of premature translation termination codon. FEBS Lett. 2010, 584 (4): 795-800. 10.1016/j.febslet.2010.01.003.PubMedGoogle Scholar
- You KT, Li LS, Kim NG, Kang HJ, Koh KH, Chwae YJ, Kim KM, Kim YK, Park SM, Jang SK: Selective translational repression of truncated proteins from frameshift mutation-derived mRNAs in tumors. PLoS Biol. 2007, 5 (5): e109-10.1371/journal.pbio.0050109.PubMed CentralPubMedGoogle Scholar
- Barnes CA: Upf1 and Upf2 proteins mediate normal yeast mRNA degradation when translation initiation is limited. Nucleic Acids Res. 1998, 26 (10): 2433-2441. 10.1093/nar/26.10.2433.PubMed CentralPubMedGoogle Scholar
- Heikkinen HL, Llewellyn SA, Barnes CA: Initiation-mediated mRNA decay in yeast affects heat-shock mRNAs, and works through decapping and 5'-to-3' hydrolysis. Nucleic Acids Res. 2003, 31 (14): 4006-4016. 10.1093/nar/gkg474.PubMed CentralPubMedGoogle Scholar
- Popielarz M, Cavaloc Y, Mattei MG, Gattoni R, Stevenin J: The gene encoding human splicing factor 9G8. Structure, chromosomal localization, and expression of alternatively processed transcripts. J Biol Chem. 1995, 270 (30): 17830-17835. 10.1074/jbc.270.30.17830.PubMedGoogle Scholar
- Stockklausner C, Breit S, Neu-Yilik G, Echner N, Hentze MW, Kulozik AE, Gehring NH: The uORF-containing thrombopoietin mRNA escapes nonsense-mediated decay (NMD). Nucleic Acids Res. 2006, 34 (8): 2355-2363. 10.1093/nar/gkl277.PubMed CentralPubMedGoogle Scholar
- Silva AL, Pereira FJ, Morgado A, Kong J, Martins R, Faustino P, Liebhaber SA, Romao L: The canonical UPF1-dependent nonsense-mediated mRNA decay is inhibited in transcripts carrying a short open reading frame independent of sequence context. Rna. 2006, 12 (12): 2160-2170. 10.1261/rna.201406.PubMed CentralPubMedGoogle Scholar
- Zhang J, Maquat LE: Evidence that translation reinitiation abrogates nonsense-mediated mRNA decay in mammalian cells. Embo J. 1997, 16 (4): 826-833. 10.1093/emboj/16.4.826.PubMed CentralPubMedGoogle Scholar
- Poyry TA, Kaminski A, Jackson RJ: What determines whether mammalian ribosomes resume scanning after translation of a short upstream open reading frame?. Genes Dev. 2004, 18 (1): 62-75. 10.1101/gad.276504.PubMed CentralPubMedGoogle Scholar
- Roy B, Vaughn JN, Kim BH, Zhou F, Gilchrist MA, Von Arnim AG: The h subunit of eIF3 promotes reinitiation competence during translation of mRNAs harboring upstream open reading frames. Rna. 2010, 16 (4): 748-761. 10.1261/rna.2056010.PubMed CentralPubMedGoogle Scholar
- Calvo SE, Pagliarini DJ, Mootha VK: Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans. Proc Natl Acad Sci USA. 2009, 106 (18): 7507-7512. 10.1073/pnas.0810916106.PubMed CentralPubMedGoogle Scholar
- Morris DR, Geballe AP: Upstream open reading frames as regulators of mRNA translation. Mol Cell Biol. 2000, 20 (23): 8635-8642. 10.1128/MCB.20.23.8635-8642.2000.PubMed CentralPubMedGoogle Scholar
- Ruiz-Echevarria MJ, Peltz SW: The RNA binding protein Pub1 modulates the stability of transcripts containing upstream open reading frames. Cell. 2000, 101 (7): 741-751. 10.1016/S0092-8674(00)80886-7.PubMedGoogle Scholar
- Krecic AM, Swanson MS: hnRNP complexes: composition, structure, and function. Curr Opin Cell Biol. 1999, 11 (3): 363-371. 10.1016/S0955-0674(99)80051-9.PubMedGoogle Scholar
- Matlin AJ, Clark F, Smith CW: Understanding alternative splicing: towards a cellular code. Nat Rev Mol Cell Biol. 2005, 6 (5): 386-398. 10.1038/nrm1645.PubMedGoogle Scholar
- Martinez-Contreras R, Fisette J-F, ois Nasim F-uH, Madden R, Cordeau M, lanie Chabot B: Intronic Binding Sites for hnRNP A/B and hnRNP F/H Proteins Stimulate Pre-mRNA Splicing. PLoS Biology. 2006, 4 (2): e21-10.1371/journal.pbio.0040021.PubMed CentralPubMedGoogle Scholar
- Fahling M, Mrowka R, Steege A, Martinka P, Persson PB, Thiele BJ: Heterogeneous nuclear ribonucleoprotein-A2/B1 modulate collagen prolyl 4-hydroxylase, alpha (I) mRNA stability. J Biol Chem. 2006, 281 (14): 9279-9286. 10.1074/jbc.M510925200.PubMedGoogle Scholar
- Black DL: Mechanisms of alternative pre-messenger RNA splicing. Annu Rev Biochem. 2003, 72: 291-336. 10.1146/annurev.biochem.72.121801.161720.PubMedGoogle Scholar
- Goina E, Skoko N, Pagani F: Binding of DAZAP1 and hnRNPA1/A2 to an exonic splicing silencer in a natural BRCA1 exon 18 mutant. Mol Cell Biol. 2008, 28 (11): 3850-3860. 10.1128/MCB.02253-07.PubMed CentralPubMedGoogle Scholar
- Venables JP, Koh CS, Froehlich U, Lapointe E, Couture S, Inkel L, Bramard A, Paquet ER, Watier V, Durand M: Multiple and specific mRNA processing targets for the major human hnRNP proteins. Mol Cell Biol. 2008, 28 (19): 6033-6043. 10.1128/MCB.00726-08.PubMed CentralPubMedGoogle Scholar
- Fisette JF, Toutant J, Dugre-Brisson S, Desgroseillers L, Chabot B: hnRNP A1 and hnRNP H can collaborate to modulate 5' splice site selection. Rna. 2010, 16 (1): 228-238. 10.1261/rna.1890310.PubMed CentralPubMedGoogle Scholar
- Patry C, Bouchard L, Labrecque P, Gendron D, Lemieux B, Toutant J, Lapointe E, Wellinger R, Chabot B: Small interfering RNA-mediated reduction in heterogeneous nuclear ribonucleoparticule A1/A2 proteins induces apoptosis in human cancer cells but not in normal mortal cell lines. Cancer Res. 2003, 63 (22): 7679-7688.PubMedGoogle Scholar
- Boutz PL, Stoilov P, Li Q, Lin CH, Chawla G, Ostrow K, Shiue L, Ares M, Black DL: A post-transcriptional regulatory switch in polypyrimidine tract-binding proteins reprograms alternative splicing in developing neurons. Genes Dev. 2007, 21 (13): 1636-1652. 10.1101/gad.1558107.PubMed CentralPubMedGoogle Scholar
- Makeyev EV, Zhang J, Carrasco MA, Maniatis T: The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing. Mol Cell. 2007, 27 (3): 435-448. 10.1016/j.molcel.2007.07.015.PubMed CentralPubMedGoogle Scholar
- McGlincy NJ, Smith CW: Alternative splicing resulting in nonsense-mediated mRNA decay: what is the meaning of nonsense?. Trends Biochem Sci. 2008Google Scholar
- Yan-Sanders Y, Hammons GJ, Lyn-Cook BD: Increased expression of heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNP) in pancreatic tissue from smokers and pancreatic tumor cells. Cancer Lett. 2002, 183 (2): 215-220. 10.1016/S0304-3835(02)00168-4.PubMedGoogle Scholar
- Zhou J, Allred DC, Avis I, Martinez A, Vos MD, Smith L, Treston AM, Mulshine JL: Differential expression of the early lung cancer detection marker, heterogeneous nuclear ribonucleoprotein-A2/B1 (hnRNP-A2/B1) in normal breast and neoplastic breast cancer. Breast Cancer Res Treat. 2001, 66 (3): 217-224. 10.1023/A:1010631915831.PubMedGoogle Scholar
- Kim SH, Dierssen M, Ferreres JC, Fountoulakis M, Lubec G: Increased protein levels of heterogeneous nuclear ribonucleoprotein A2/B1 in fetal Down syndrome brains. J Neural Transm Suppl. 2001, 273-280. 61
- Clower CV, Chatterjee D, Wang Z, Cantley LC, Vander Heiden MG, Krainer AR: The alternative splicing repressors hnRNP A1/A2 and PTB influence pyruvate kinase isoform expression and cell metabolism. Proc Natl Acad Sci USA. 2010, 107 (5): 1894-1899. 10.1073/pnas.0914845107.PubMed CentralPubMedGoogle Scholar
- David CJ, Chen M, Assanah M, Canoll P, Manley JL: HnRNP proteins controlled by c-Myc deregulate pyruvate kinase mRNA splicing in cancer. Nature. 2010, 463 (7279): 364-368. 10.1038/nature08697.PubMed CentralPubMedGoogle Scholar
- Moran-Jones K, Grindlay J, Jones M, Smith R, Norman JC: hnRNP A2 regulates alternative mRNA splicing of TP53INP2 to control invasive cell migration. Cancer Res. 2009, 69 (24): 9219-9227. 10.1158/0008-5472.CAN-09-1852.PubMedGoogle Scholar
- Gromak N, Rideau A, Southby J, Scadden AD, Gooding C, Huttelmaier S, Singer RH, Smith CW: The PTB interacting protein raver1 regulates alpha-tropomyosin alternative splicing. Embo J. 2003, 22 (23): 6356-6364. 10.1093/emboj/cdg609.PubMed CentralPubMedGoogle Scholar
- Wagner EJ, Garcia-Blanco MA: RNAi-mediated PTB depletion leads to enhanced exon definition. Mol Cell. 2002, 10 (4): 943-949. 10.1016/S1097-2765(02)00645-7.PubMedGoogle Scholar
- Mendell JT, ap Rhys CM, Dietz HC: Separable roles for rent1/hUpf1 in altered splicing and decay of nonsense transcripts. Science. 2002, 298 (5592): 419-422. 10.1126/science.1074428.PubMedGoogle Scholar
- Bradford MM: A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem. 1976, 72: 248-254. 10.1016/0003-2697(76)90527-3.PubMedGoogle Scholar
- Tichopad A, Dilger M, Schwarz G, Pfaffl MW: Standardized determination of real-time PCR efficiency from a single reaction set-up. Nucleic Acids Res. 2003, 31 (20): e122-10.1093/nar/gng122.PubMed CentralPubMedGoogle Scholar
- Wang X, Seed B: A PCR primer bank for quantitative gene expression analysis. Nucleic Acids Res. 2003, 31 (24): e154-10.1093/nar/gng154.PubMed CentralPubMedGoogle Scholar
- Rozen S, Skaletsky HJ: Primer3 on the WWW for general users and for biologist programmers. Bioinformatics Methods and Protocols: Methods in Molecular Biology. Edited by: Krawetz S, Misener S. 2000, Totowa, NJ: Humana Press, 365-386.Google Scholar
- Ririe KM, Rasmussen RP, Wittwer CT: Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem. 1997, 245 (2): 154-160. 10.1006/abio.1996.9916.PubMedGoogle Scholar
- Karp NA, Kreil DP, Lilley KS: Determining a significant change in protein expression with DeCyder during a pair-wise comparison using two-dimensional difference gel electrophoresis. Proteomics. 2004, 4 (5): 1421-1432. 10.1002/pmic.200300681.PubMedGoogle Scholar
- Zavolan M, Kondo S, Schonbach C, Adachi J, Hume DA, Hayashizaki Y, Gaasterland T: Impact of alternative initiation, splicing, and termination on the diversity of the mRNA transcripts encoded by the mouse transcriptome. Genome Res. 2003, 13 (6B): 1290-1300. 10.1101/gr.1017303.PubMed CentralPubMedGoogle Scholar
- Zavolan M, van Nimwegen E, Gaasterland T: Splice variation in mouse full-length cDNAs identified by mapping to the mouse genome. Genome Res. 2002, 12 (9): 1377-1385. 10.1101/gr.191702.PubMed CentralPubMedGoogle Scholar
- Karolchik D, Baertsch R, Diekhans M, Furey TS, Hinrichs A, Lu YT, Roskin KM, Schwartz M, Sugnet CW, Thomas DJ: The UCSC Genome Browser Database. Nucleic Acids Res. 2003, 31 (1): 51-54. 10.1093/nar/gkg129.PubMed CentralPubMedGoogle Scholar
- Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, Clawson H, Spieth J, Hillier LW, Richards S: Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005, 15 (8): 1034-1050. 10.1101/gr.3715005.PubMed CentralPubMedGoogle Scholar
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