UBC Faculty Research and Publications

Discovery of novel alternatively spliced C. elegans transcripts by computational analysis of SAGE data Ruzanov, Peter; Jones, Steven J; Riddle, Donald L Nov 30, 2007

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata


52383-12864_2007_Article_1160.pdf [ 631.13kB ]
JSON: 52383-1.0167788.json
JSON-LD: 52383-1.0167788-ld.json
RDF/XML (Pretty): 52383-1.0167788-rdf.xml
RDF/JSON: 52383-1.0167788-rdf.json
Turtle: 52383-1.0167788-turtle.txt
N-Triples: 52383-1.0167788-rdf-ntriples.txt
Original Record: 52383-1.0167788-source.json
Full Text

Full Text

ralssBioMed CentBMC GenomicsOpen AcceResearch articleDiscovery of novel alternatively spliced C. elegans transcripts by computational analysis of SAGE dataPeter Ruzanov1, Steven J Jones2 and Donald L Riddle*1Address: 1Michael Smith Laboratories University of British Columbia, Vancouver BC V6T 1Z4, Canada and 2Genome Sciences Centre, BC Cancer Research Centre, Vancouver, BC V5Z 4S6, CanadaEmail: Peter Ruzanov - pruzanov@bcgsc.ca; Steven J Jones - sjones@bcgsc.ca; Donald L Riddle* - driddle@msl.ubc.ca* Corresponding author    AbstractBackground: Alternative RNA splicing allows cells to produce multiple protein isoforms from onegene. These isoforms may have specialized functions, and may be tissue- or stage-specific. Our aimwas to use computational analysis of SAGE and genomic data to predict alternatively splicedtranscripts expressed in C. elegans.Results: We predicted novel alternatively spliced variants and confirmed five of eighteencandidates selected for experimental validation by RT-PCR tests and DNA sequencing.Conclusion: We show that SAGE data can be efficiently used to discover alternative mRNAisoforms, including those with skipped exons or retained introns. Our results also imply that C.elegans may produce a larger number of alternatively spliced transcripts than initially estimated.BackgroundIn eukaryotes, alternative splicing creates a diversity ofproteins with a limited number of genes. Producing vari-ants of the same protein may be beneficial for tissue spe-cialization at different developmental stages, or whensubject to changing physiological conditions. Regulationof alternative splicing also provides an additional layer ofcontrol over gene expression. The importance of alterna-tive splicing has been shown in multiple studies of devel-opment and cancer [1-3]. Identification of new alternativesplice variants may provide additional knowledge aboutgene regulation and function. Such information is essen-tial for developing treatments for diseases associated withsplicing abnormalities, for instance, by using inhibitors ofthe aberrant transcript expression [4].common in complex, multicellular organisms. This biasmay be caused by the difficulties in developing such amechanism by fast-growing unicellular organisms, as pro-duction of splice variants, although helpful in achievingprotein diversity, also poses a risk of generating aberrantprotein products [5].Splicing studies identified different varieties of transcriptrearrangements together with several key proteinsinvolved in this process [6]. The most prevalent form ofalternative splicing is exon skipping (cassette exons), com-prising about 40% of all splicing events conservedbetween humans and mice [7]. Comparative studies ofexon skipping in mice and humans also indicate the pres-ence of selective pressure for retaining 'functional splicevariants', in which exon skipping does not shift the openPublished: 30 November 2007BMC Genomics 2007, 8:447 doi:10.1186/1471-2164-8-447Received: 30 March 2007Accepted: 30 November 2007This article is available from: http://www.biomedcentral.com/1471-2164/8/447© 2007 Ruzanov et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 8(page number not for citation purposes)Although non-coding sequences (introns) are present inthe genomes of all eukaryotes, alternative splicing is morereading frame (ORF) for the encoded protein [8]. In C. ele-gans, 77% of cassette exon splice variants retain the origi-BMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/447nal ORFs according to the data available in release WS130of public Wormbase database [9].C. elegans is a well-studied model organism with a fullysequenced genome, and its alternative splicing has beenthoroughly investigated using computational analysis ofEST (Expressed Sequence Tags) sequences [10]. The resultsof this analysis are available through Wormbase. Compar-ison of ESTs with genomic sequence revealed 1782 geneswith alternatively spliced transcripts (Wormbase releaseWS130), which accounts for about 9% of all C. elegansgenes. By comparison, it is estimated that 40–80% of allhuman genes may be alternatively spliced [11,12].We used data from serial analysis of gene expression(SAGE) for computational prediction of novel alternativeexon skipping and intron retention events to discover pre-viously unidentified splice variants in C. elegans. Unlikemicroarrays, SAGE provides information for previouslyunknown polyadenylated mRNA. We analyzed the datafrom six C. elegans SAGE libraries using a set of customPerl scripts. For computational predictions we used C. ele-gans DNA sequence information from Wormbase releaseWS130. Applying strict selection criteria, we chose theeighteen most probable predictions of novel alternativesplicing events for validation experiments with RT-PCR.Three of the eight predicted exon skipping and two of tenintron retention cases were confirmed in these experi-ments, demonstrating that computational predictionsbased on genomic and SAGE data are useful for discoveryof novel alternative splice variants. This study is aimed attesting the possibility of predicting alternative splice usingcomputational analysis of SAGE data and genomesequence. To our knowledge, this is the first such study inC. elegans.ResultsComputational prediction of novel alternative splicing eventsWe used Wormbase release WS130 as the source of infor-mation about the intron/exon structure of C. elegans genesand their DNA sequences. Sequences for each of the pre-dicted 22,249 transcripts were composed using gff filesdownloaded from Wormbase and custom Perl scripts. Wegenerated virtual splicing events for all genes with intronsin the database. For the exon skipping simulation, one ormore exons were excluded from the final transcript foreach gene that had at least 3 exons. The sequences of vir-tual splicing junctions were then checked for potentialSAGE tags (Fig. 1) by scanning 13 bp sequences of eachupstream and downstream exon forming the virtual splicejunction. The SAGE protocol [13] generated 14 bp tags fortranscripts starting with a CATG sequence (NlaIII diges-least one virtual SAGE tag for 6157 C. elegans transcripts(28% of C. elegans transcriptome).For the intron retention analysis, we used the introns andtheir flanking 13 bp sequences for extraction of virtualSAGE tags (Fig. 1), the presence of which in the expressiondata set would indicate possible intron retention events.In the latter analysis we retrieved 67,709 tag sequences for14,213 genes (64% of C. elegans transcriptome).We used the virtual transcriptome of C. elegans [14] to fil-ter the initial list of predicted SAGE tags. All the tags pre-viously unambiguously mapped to transcripts wereremoved from the initial list to avoid an overlap. We alsoanalyzed whether the predicted splicing events shifted theORFs of the analyzed transcripts. Also, we limited ourexon skipping candidate list to the variants with undis-turbed ORFs, aiming to narrow it to the most interestingfunctional splice variants. Finally, the SAGE data wereexamined to determine which tags, corresponding to thepredicted splicing events, were actually expressed in sixSAGE libraries used for this analysis.Forty-one unique virtual SAGE tags derived during theanalysis of exon skipping were present in at least one ofthe six SAGE libraries. We chose eight candidate variantsfor subsequent validation, giving priority to the predictedsplice variants with the highest SAGE tag counts and a sin-gle dropped exon (Table 1).Analysis of the transcripts annotated in the release WS130of Wormbase with intron retention (Additional file 1)showed that the majority of virtual retained introns hadlength of 40–60 bp and more than 80% of them havelength less than 125 bp. Based on this information, wechose to eliminate tags extracted from introns longer than125 bp. For each of the remaining 4361 virtual SAGE tagswe analyzed its position in the corresponding transcript.Although most of the SAGE tags would be expected tocome from the first position (closest to the 3' end),incomplete digestion of the cDNA during library prepara-tion may produce tags positioned further from the 3' end.According to this logic, we chose to keep only virtualSAGE tags with ordinal positions first through third.Forty-one of the 648 tags fulfilling all criteria were presentin the SAGE libraries analyzed. We selected ten candidateswith the highest tag counts for experimental validation(Table 2). A flowchart illustrating the filtering process isalso provided in Additional file 2.RT-PCR validationWe conducted RT-PCR experiments to test our predic-tions. In the validation experiments for exon skippingPage 2 of 8(page number not for citation purposes)tion site), so not every virtual junction is expected to pro-duce a SAGE tag. Nevertheless, it was possible to derive atcandidates, one of the primers overlapped the predictedsplice junction (Fig. 1), so a PCR product was expected toBMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/447Page 3 of 8(page number not for citation purposes)Schematic illustration of computational prediction and experimental validation of splice variantsFigure 1Schematic illustration of computational prediction and experimental validation of splice variants. We used vir-tual splicing events to extract all potential SAGE tags spanning the predicted splice junctions as shown. Introns and flanking 13 bp sequences were used for extraction of SAGE tags identifying cases of intron retention. For exon skipping validation, one of the primers spanned the predicted splice junction, so that hybridization with the template mRNA was possible only if the pre-dicted transcript was present in the mRNA pool. Detection of an RT-PCR product with a larger size than expected for a nor-mally spliced isoform confirmed intron retention events.VERIFICATION13 bp sequencesTAG EXTRACTIONexon skipping intron retentionCATG AAGGTTCGAACATG AAGGTTCGTTCATG AAGGTTCGGCCATG TGTTTCGACCCATG TGCAGGTCCACATG TGATAGGGTC1 31 41 2CATGGGTAA AAATGPredicted dropPrimer APrimer BPredicted retentionPrimer APrimer BBMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/447appear only if there was a detectable expression of a tran-script with the predicted exon rearrangement. In RT-PCRexperiments we analyzed the same total RNA samples,which were used for generation of the SAGE libraries. Wedetected the product of expected size (400 – 600 bp) forthe four of eight selected candidates (Fig. 2). All but oneof the amplified cDNA fragments had the predictedsequence, confirming the predicted alternative splicingevents for C52E4.6a (cyl-1, cyclin L), T05B4.1 (ionicchannel protein, also confirmed in a separate RT-PCRTable 2: Expression data for intron retention candidatesGene/Tag Intron Intron length F-1 F-6 DF1 DF-6 DF10 N2-1 DAUB0041.3TACGATTTCA 2 48 1 2 1 2 0 1 2C08B6.13AGGATACAAT 1 81 4 6 1 1 1 1 0C14C6.5CGGTTATTGC 3 69 27 7 31 1 73 10 3C24G6.3TGAAATAATA 12 51 0 0 1 5 0 0 2D1054.10ATCGGTGTGT 2 91 0 0 4 0 3 0 0F07C6.2TAATGAATTT 2 56 1 1 1 2 0 1 2R09E10.3TCAATAAATA 8 82 9 0 0 0 0 0 0T23G7.5TTTTATATAA 4 47 2 3 3 0 1 8 1W01A8.3AAAACAATAA 5 70 8 1 0 0 0 0 0Y116A8C.30TATTGGAATC 3 97 0 0 1 0 0 0 3SAGE data for ten tags selected for validation of intron retention by RT-PCR. The Intron column indicates which intron was predicted to be retained and the Intron Length column shows the length of that intron in nucleotides. The other columns show the normalized tag counts in the Table 1: Expression data for exon skipping candidatesGene/Tag Junction Exon length F-1 F-6 DF1 DF-6 DF10 N2-1C33G3.4TGAAAGAAAA 5..7 255 3 0 0 1 1 3C52E4.6aATAAAAATAG 6..8 723 0 0 0 0 1 0F27D4.4AGAATGAAAA 4..6 102 3 0 0 0 1 0T01G5.1TATTCATTCT 4..6 219 2 3 2 0 1 5T05B4.1GGTTTATAAA 3..5 66 0 2 2 0 0 1T14G10.1CCAGAAATGG 4..6 264 3 13 6 1 12 22W04G5.9GAACTGAATG 10..12 123 3 4 0 1 2 1Y49F6B.8CTAAAATGAT 1..3 399 0 1 0 0 0 0SAGE data for eight tags selected for validation of predicted exon skipping by RT-PCR. Junction column shows the exons that form the predicted splice junction, and the other columns show the normalized tag counts in the SAGE libraries made from the RNA preparations used in validation experiments: F-1, 6: fer-15 at days 1 and 6 of adulthood; DF-1, 6, 10: daf-2; fer-15 at days 1, 6 and 10 of adulthood; N2-1: N2 at day 1 of adulthood. Tags in all libraries were normalized to 100,000 total tags.Page 4 of 8(page number not for citation purposes)SAGE libraries made from the RNA preparations used in validation experiments: F-1, 6: fer-15 at days 1 and 6 of adulthood; DF-1, 6, 10: daf-2; fer-15 at days 1, 6 and 10 of adulthood; N2-1: N2 at day 1 of adulthood; DAU: young dauer larvae. Tags in all libraries were normalized to 100,000 total tags.BMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/447experiment with a different primer design) and W04G5.9(predicted N-glycanase).In validation experiments for intron retention candidates(Fig. 1), we performed RT-PCR using primers complemen-tary to the flanking exons. The positive candidates weredetected by the appearance of a longer PCR product. Weobtained positive results for five of ten candidates:C08B6.13 (srxa-19, Serpentine Receptor class XA),C14C6.5 (Secreted surface protein), F07C6.2 (predictedprotein), R09E10.3 (Long-chain acyl-CoA synthetase) andW01A8.3 (cuticulin). To assess the possibility that ourRNA samples contained immature transcripts, we per-formed additional RT-PCR experiments for each of fivepre-selected candidates using one of the gene-specificprimers in combination with oligo(dT) primer in at leastthree trials, expecting a PCR product only from a polyade-nylated transcript. We observed a PCR product of the pre-dicted size (confirmed by DNA sequencing) for twocandidates – C14C6.5 and F07C6.2. In both cases, theintron retention is corroborated by aligned ESTs (Worm-base web site [9], WS170, February 10, 2007). However,the latter observation may also indicate that Wormbasemodels for these two genes are incorrect and need to berevised, especially that in both cases there are no ESTalignments with exons following the corresponding (pre-that these three candidates resulted from contaminationwith immature nuclear polyA(-) RNA.We analyzed the integrity of the functional domains of thesplice variants for both C14C6.5 and F07C6.2. The openreading frame of the C14C6.5 variant is promptly termi-nated after short intron-encoded peptide sequence GYCK,generating an isoform 14 amino acids shorter than theoriginal 181-amino-acid protein. As we determined byanalysis with PROSITE [15], C14C6.5 native protein con-tains putative Casein kinase II phosphorylation and N-myristoylation sites, which are also both present in thevariant retaining the third intron. In the case of F07C6.2,retention of its second intron leads to the loss of 51 aminoacids, including a putative phosphorylation site for tyro-sine kinase. The open reading frame of this variant stopsinside the retained intron after a single valine codon.However, two putative sites for Casein kinase II phospho-rylation, an N-myristoylation site and phosphorylationsites for cAMP- and cGMP-dependent protein kinases(PKA and PKB) remain intact in the 115-amino acidF07C6.2 splice variant.DiscussionBy simulating virtual splicing in silico we were able to pre-dict novel alternatively spliced transcripts for previouslyValidation RT-PCR experimentsFigure 2Validation RT-PCR experiments. Left panel: the results of RT-PCR experiments for eight selected exon skipping candi-dates are shown. Lanes 1–8 correspond to the genes C33G3.4, C52E4.6a, F27D4.4, T01G5.1, T05B4.1, T14G10.1, W04G5.9 and Y49F6B.8. PCR products of the expected sizes (400 – 600 bp) were observed for four genes. *DNA sequencing did not confirm one of the candidates (C33G3.4, lane 1 on the left panel). Right panel: the results of the intron retention analysis. The positions of the PCR product for normally spliced isoforms (empty arrows) and isoforms with intron retention (black arrows) are shown. Lanes 1–10 correspond to the genes B0041.3, C08B6.13, C14C6.5, C24G6.3, D1054.10, F07C6.2, R09E10.3, T23G7.5, W01A8.3 and Y116A8C.30. * Additional RT-PCR experiments with oligo(dT) primer followed by DNA sequencing disproved three candidates (C08B6.13, R09E10.3 and W01A8.3).Page 5 of 8(page number not for citation purposes)dicted as retained) introns. We did not see any PCR prod-uct for the other three genes, leaving open the possibilityannotated genes. Hence, this method can produce newinformation even in the case of a well-studied organism.BMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/447We analyzed two types of alternative splicing (exon skip-ping and intron retention) using strict filtering criteria. Asimilar approach to other types of alternative splicing inC. elegans would likely reveal additional splice variants.This approach is also applicable to other organisms, suchas the mouse [16], for which adequate gene annotationsand SAGE data are available. Although we cannot readilyestimate how many additional alternatively spliced vari-ants C. elegans may have, we have shown that SAGE datacan be efficiently used for discovery of novel transcriptisoforms.SAGE allowed us to examine the transcript levels for a fewthousand genes (typically, 4000–7000 per library) in oneexperiment. This approach may significantly expand ourability to study alternative splicing and improve ourunderstanding of its mechanism. Alternatively splicedtranscripts in C. elegans have been characterized using ESTdata [10], indicating that about 10% of C. elegans genesare alternatively spliced. As the authors comment, thisnumber may be an underestimate.It is interesting that both of our confirmed candidateswith intron retention also had ESTs aligned with retainedintrons, supporting the presence of these transcripts in themRNA population. However, if taken alone the EST datamay not provide sufficient evidence of intron retention. Infact, two other candidates, D1054.10 and R09E10.3,although both having ESTs aligned with predictedretained introns, were not confirmed by our RT-PCR tests.Microarray analyses of exon skipping events have used oli-gonucleotide probes designed to overlap the annotated orpredicted splice junctions [17,18], but their use as a dis-covery tool is limited because the design of the oligonu-cleotide probes requires sequence data for the splicevariants being tested. The task of analyzing all possiblerearrangements for every annotated mRNA is beyond thecapacity of all modern arrays, and prediction of all splic-ing events resulting in a new RNA sequence is nearlyimpossible.Recently, Kuo et al. [16] used SAGE data to analyze themouse genome for novel splicing sites in annotated genes.These authors hypothesized that tags neither mapped toknown transcripts nor to the genome might span novelsplice junctions. They developed an algorithm(SAGE2Splice) for mapping SAGE tags to potential splicejunctions. These authors focused on predicting novelsplicing sites in the genome rather than discovery of alter-native splicing events, which was the goal of our study.In contrast to microarrays, the SAGE protocol does notevery polyadenylated mRNA in the cell. Both the SAGEprotocol and the RT-PCR validation experiments sampledthe polyA(+) mRNA population. Although the results ofour validation experiments showed that confirmed candi-dates belong to the pool of poly A(+) mRNA, we do notknow if those transcripts are functional. Demonstration oftheir ability to produce active proteins would requireadditional work, e.g. analysis of polysome-bound fractionof cytoplasmic mRNA. Nevertheless, the computationalpredictions based on SAGE data can provide the initialguidelines for identification of novel alternative splicevariants. Numerous C. elegans SAGE data sets are currentlyavailable via online public databases such as GEO[19,20]. Mining these data using our approach shouldimprove our understanding of alternative splicing mecha-nisms.ConclusionOur results demonstrate a practical application of SAGEdata analysis for discovery of alternative mRNA isoforms.SAGE allows sampling of the whole mRNA populationincluding uncharacterized transcripts, which would bemissed in analysis with alternative large-scale methodssuch as microarray. Our results also imply that C. eleganshas a larger number of alternative mRNA isoforms thaninitially predicted.MethodsComputational resources and data setsWe used C. elegans SAGE data generated for variousprojects at the Michael Smith Genome Science Center, BCCancer Agency [14,21-24]. We also used the publiclyavailable release WS130 of Wormbase [9]. Data were ana-lyzed using scripts written in Perl 5.6. Tag to gene map-ping data were generated using an in-house developed setof scripts as described by McKay, et al. (2003). All SAGElibraries were analyzed and filtered for erroneous data(duplicate ditags, single base mismatches etc.) accordingto standards developed at the Michael Smith Genome Sci-ences Centre [25]. Sequence reads were processed, andtheir quality was assessed by use of Phred [26,27]. TheSAGE data used in this study are available for browsingonline via Multisage tool [28].RT-PCRWe analyzed the same total RNA samples that were origi-nally used for generation of the analyzed SAGE libraries.These libraries were originally constructed to comparegene expression profiles in long-lived daf-2 mutant adultswith adults that had a normal life span [21]. We usedseven RNA samples: fer-15 (b26ts) at days 1 and 6 of adult-hood, fer-15; daf-2(m41) at days 1, 6 and 10 of adulthood,N2 at day 1 of adulthood and two-day-old N2 dauer lar-Page 6 of 8(page number not for citation purposes)require pre-existing information about analyzed tran-scripts. In principle, experimental data are obtained forvae [22,23,29]. The fer-15 (temperature-sensitive spermdeficient) mutation is present in both the daf-2(+) andBMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/447daf-2(-) strains to prevent contamination of aging adultpopulations with progeny.The following gene-specific primers were used in tests forexon skipping candidates: T14G10.1F: GACTGGAAGGT-GTTACAAGA, T14G10.1R: TGTATCTCCATTTCTGGCAT;W04G5.9F: ATGCTGAAGACAACAACTTC, W04G5.9R:CAGCATTCAGTTCCATGATC; T01G5.1F: GTGCTCTTCT-TCGAAATGAT, T01G5.1R: TCCACCAGTGTCCTCGAATC;F27D4.4F: GGGACTCGGACAAATTGAAT, F27D4.4R:TCTCATGTTTTCCAGATTTG; C52E4.6aF: TTGTGA-TAAGTGGTTGATGA, C52E4.6aR: ATTTTTATCATGTT-GTTTCGTA; Y49F6B.8F: CATGCTAAAATGATTCCCAA,Y49F6B.8R: CGTATGAATCATAGTTCGAA; T05B4.1F:CATGGGTTTATAAATTCCCA, T05B4.1R: GAAGTGTAAG-CACTACACCA; alternative primers for T05B4.1:T05B4.1mF: GAATGGACAGACCAACGCTT; T05B4.1mR:GTCACTTTCCATTCGCCATT; C33G3.4F: TAGATTTGCT-CATGTGAAAG C33G3.4R: AGCCACCTTCTTTGCAATCT.For RT-PCR validation tests of intron retention events, thefollowing primers were used: B0041.3F: ACCAC-CGTCGTCGTCA, B0041.3R: AACAAGGCGCTGGGAG;C08B6.13F: AGCCAAGAAGCAGGAGAT, C08B6.13R:GATATTGACATATGCCACTCATT; C14C6.5F: GTGACT-GCCCAGGAATGA, C14C6.5R: AGTAATGCGGAAAAAT-TCTGAA; C24G6.3F: GATCCTCAATTGTTCCACCA,C24G6.3R: GTATCGTCCGTTCTGGCA; D1054.10F:AGGGCCAACAATTCCATT, D1054.10R: TACGCAATT-GCTGTGTGC; F07C6.2F: TGAGCGGCAATTAAGGAA,F07C6.2R: TCTCCAAACGAAAGCGAA; R09E10.3F:AAAAGCAACTGGCGTCAA, R09E10.3R: CGTTGTCCCA-GATCCAGA; T23G7.5F: AAGACGGAATGGGCAGAT,T23G7.5R: TCGAAATTGTGGAATCGG; W01A8.3F:GGAATGTACACCGGCTGA, W01A8.3R: GGAGAAG-GAGCAAGGAGC; Y116A8C.30F: GGCGTCACTTCCAG-GTC, Y116A8C.31R: TCCGGAGCCCAACAG. We alsoused a custom oligo(dT) primer with a short adapterGACTCGAGTCGACATCGATTTTTTTTTTTTTTTTT. AllPCR products of predicted size were analyzed by DNAsequencing, which confirmed the predicted splicingevents.Authors' contributionsPR SJJ and DLR developed the main ideas and methodol-ogy; PR did the computational analysis and RT-PCRexperiments; SJJ and DLR provided feedback and coordi-nation of the project. SJMJ, DLR and PR read andapproved the final manuscript.Additional materialAcknowledgementsThis work was supported by grant AG12689 from the US National Insti-tutes of Health to Donald L. Riddle. Steven M. Jones is a scholar of the Michael Smith Foundation for Health Research. We also thank Dr. Donald G. Moerman for valuable discussion and providing his support with valida-tion of alternative splice candidates using RT-PCR.References1. Brinkman BMN: Splice variants as cancer biomarkers.  ClinicalBiochemistry 2004, 37(7):584-594.2. Venables JP: Aberrant and alternative splicing in cancer.  CancerResearch 2004, 64(21):7647-7654.3. Walker WH DFJ Habener JF.: RNA processing and the controlof spermatogenesis.  Front Horm Res 1999, 25:34-58.4. Iczkowski KA, Omara-Opyene AL, Shah GV: The predominantCD44 splice variant in prostate cancer binds fibronectin, andcalcitonin stimulates its expression.  Anticancer Res 2006,26(4B):2863-2872.5. Ast G: How did alternative splicing evolve?  Nat Rev Genet 2004,5(10):773-782.6. Black DL: Mechanisms of alternative pre-messenger RNAsplicing.  Annual Revew Biochemistry 2003, 72:291-336.7. Sugnet CW, Kent WJ, Ares M Jr, Haussler D: Transcriptome andgenome conservation of alternative splicing events inhumans and mice.  Pac Symp Biocomput 2004:66-77.8. Sorek R, Shamir R, Ast G: How prevalent is functional alterna-tive splicing in the human genome?  Trends in Genetics 2004,20(2):68-71.9. Wormbase   [http://www.wormbase.org]10. Kent WJ, Zahler AM: The intronerator: exploring introns andalternative splicing in Caenorabditis elegans.  Nucleic Acids Res2000, 28:91-93.11. Mironov AA, Fickett JW, Gelfand MS: Frequent alternative splic-ing of human genes.  Genome Research 1999, 9(12):1288-1293.12. Modrek B, Lee C: A genomic view of alternative splicing.  NatureGenetics 2002, 30(1):13-19.13. Velculescu VE, Zhang L, Vogelstein B, Kinzler KW: Serial analysisof gene expression.  Science 1995, 270(5235):484-487.14. McKay SJ, Johnsen R, Khattra J, Asano J, Baillie DL, Chan S, Dube N,Fang L, Goszczynski B, Ha E, Halfnight E, Hollebakken R, Huang P,Hung K, Jensen V, Jones SJ, Kai H, Li D, Mah A, Marra M, McGhee J,Newbury R, Pouzyrev A, Riddle DL, Sonnhammer E, Tian H, Tu D,Tyson JR, Vatcher G, Warner A, Wong K, Zhao Z, Moerman DG:Additional file 1Supplementary Figure 1 presented as a PDF file. It shows the statistics for splice variants of exon skipping and introns retention types annotated in Wormbase release 130. Use Adobe Acrobat Reader to open it.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-447-S1.pdf]Additional file 2Supplementary Figure 2 presented as a PDF file. It is the diagram of our analysis, which also shows the numbers of SAGE tags remaining after each filtering step. Use Adobe Acrobat Reader to open it.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-8-447-S2.pdf]Page 7 of 8(page number not for citation purposes)Gene expression profiling of cells, tissues, and developmen-tal stages of the nematode C. elegans.  Cold Spring Harb SympQuant Biol 2003, 68:159-169.Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central BMC Genomics 2007, 8:447 http://www.biomedcentral.com/1471-2164/8/44715. Hulo N, Bairoch A, Bulliard V, Cerutti L, De Castro E, Langendijk-Genevaux PS, Pagni M, Sigrist CJA: The PROSITE database.Nucleic Acids Res 2006, 34:D227-D230.16. Kuo BY, Chen Y, Bohacec S, Johansson , Wasserman WW, SimpsonEM: SAGE2Splice: Unmapped SAGE Tags Reveal NovelSplice Junctions.  PLoS Computational Biology 2006, 2(4):276-287.17. Johnson JM, Castle J, Garrett-Engele P, Kan Z, Loerch PM, ArmourCD, Santos R, Schadt EE, Stoughton R, Shoemaker DD: Genome-Wide Survey of Human Alternative Pre-mRNA Splicing withExon Junction Microarrays.  Science 2003, 302(5653):2141-2144.18. Pan Q, Shai O, Misquitta C, Zhang W, Saltzman AL, Mohammad N,Babak T, Siu H, Hughes TR, Morris QD: Revealing Global Regula-tory Features of Mammalian Alternative Splicing Using aQuantitative Microarray Platform.  Molecular Cell 2004,16(6):929-941.19. Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C,Kim IF, Soboleva A, Tomashevsky M, Edgar R: NCBI GEO: miningtens of millions of expression profiles--database and toolsupdate.  Nucl Acids Res 2007, 35(suppl_1):D760-765.20. Edgar R, Domrachev M, Lash AE: Gene Expression Omnibus:NCBI gene expression and hybridization array data reposi-tory.  Nucl Acids Res 2002, 30(1):207-210.21. Halaschek-Wiener J, Khattra JS, McKay S, Pouzyrev A, Stott JM, YangGS, Holt RA, Jones SJM, Marra MA, Brooks-Wilson AR, Riddle DL:Analysis of long-lived C. elegans daf-2 mutants using serialanalysis of gene expression.  Genome Res 2005, 15(5):603-615.22. Holt SJ, Riddle DL: SAGE surveys C. elegans carbohydratemetabolism: evidence for an anaerobic shift in the long-liveddauer larva.  Mech Ageing Dev 2003, 124(7):779-800.23. Jones SJ, Riddle DL, Pouzyrev AT, Velculescu VE, Hillier L, Eddy SR,Stricklin SL, Baillie DL, Waterston R, Marra MA: Changes in geneexpression associated with developmental arrest and lon-gevity in Caenorhabditis elegans.  Genome Res 2001,11(8):1346-1352.24. Pleasance ED, Marra MA, Jones SJ: Assessment of SAGE in tran-script identification.  Genome Res 2003, 13(6A):1203-1215.25. Khattra J, Delaney AD, Zhao Y, Siddiqui A, Asano J, McDonald H, Pan-doh P, Dhalla N, Prabhu AL, Ma K, Lee S, Ally A, Tam A, Sa D, RogersS, Charest D, Stott J, Zuyderduyn S, Varhol R, Eaves C, Jones S, HoltR, Hirst M, Hoodless PA, Marra MA: Large-scale production ofSAGE libraries from microdissected tissues, flow-sortedcells, and cell lines.  Genome Res 2007, 17(1):108-116.26. Ewing B, Green P: Base-calling of automated sequencer tracesusing phred. II. Error probabilities.  Genome Res 1998,8(3):186-194.27. Ewing B, Hillier L, Wendl MC, Green P: Base-calling of automatedsequencer traces using phred. I. Accuracy assessment.Genome Res 1998, 8(3):175-185.28. Multisage browser  :- [http://tock.bcgsc.ca/cgi-bin/sage140].29. Ruzanov P, Riddle DL, Marra MA, McKay SJ, Jones SM: Genes thatmay modulate longevity in C. elegans in both dauer larvaeand long-lived daf-2 adults.  Experimental Gerontology 2007,42(8):825-839.yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralPage 8 of 8(page number not for citation purposes)


Citation Scheme:


Citations by CSL (citeproc-js)

Usage Statistics



Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            async >
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:


Related Items