Skip Navigation

This Article
Right arrow Abstract Freely available
Right arrow Print PDF (307K) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Commercial Re-use Guidelines
for Open Access NAR Content
Google Scholar
Right arrow Articles by Romani, A.
Right arrow Articles by Alberti, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Romani, A.
Right arrow Articles by Alberti, S.
Related Collections
Right arrow RNA characterisation and manipulation
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Nucleic Acids Research, 2003, Vol. 31, No. 4 e17
© 2003 Oxford University Press

Detection and analysis of spliced chimeric mRNAs in sequence databanks

Antonello Romani, Emanuela Guerra1, Marco Trerotola1 and Saverio Alberti*,1

Department of Experimental Medicine, Section of Molecular Pathology and Immunology, University of Parma, Italy and 1 Laboratory of Experimental Oncology, Department of Cell Biology and Oncology, Institute Mario Negri - Consorzio Mario Negri Sud, 66030 Santa Maria Imbaro (Chieti), Italy

*To whom correspondence should be addressed. Tel: +39 0872 570 293; Fax: +39 0872 570 412; Email: alberti{at}negrisud.it

Received September 1, 2002; Revised November 13, 2002; Accepted December 17, 2002


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
We have developed a databank screening procedure, the In Silico Trans-splicing Retrieval System (ISTReS), to identify heterologous, spliced mRNAs with potential origin from chromosomal translocations, mRNA trans-splicing and multi-locus transcription. A parsing algorithm to screen cDNA versus genome Blast outputs was implemented. Key filtering criteria were Blast scores of >=300, match lengths of >=95% of the query sequences, junction of the two partners at exon–exon borders and concordant ‘sense/sense’ reading orientation. ISTReS was validated by the successful identification of bona fide chromosomal translocation-derived fusion transcripts in the HGI and RefSeq databanks. The performance of ISTReS was verified against recently identified chimeric antisense transcripts, where it revealed essentially no independent proof of antisense transcription and absence of exon–exon borders at the chimeric join, consistent with an artefactual origin. Analysis of the UNIGENE database revealed 21 742 chimeric sequences overall that correspond to ~1% of the database transcripts. Novel FOP-Rho GAP and methionyl tRNA synthetase-advillin chimeric mRNAs with the canonical features of heterologous-genes spliced-transcripts were identified among 246 chimeras from the RefSeq databank. This suggests a frequency of canonically-spliced chimeras of ~1% of all the hybrid sequences in current databanks. These findings demonstrate the efficiency of ISTReS and the overall feasibility of sequence/structure-based strategies to search for chimeric mRNAs candidate to derive from the splicing of heterologous transcripts.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
Chromosomal translocations are frequently detected in hematologic and solid malignancies, where they can play a causative role or induce a cell growth selective advantage (1). At the molecular level, they act through deregulation of gene expression or through the generation of fusion oncogenes. Examples of the former are translocations where a gene lands near enhancer elements, e.g. within immunoglobulin or T-cell receptor genes, or that disrupt the promoter region of c-myc (2). However, chromosomal translocations in tumour cells much more frequently generate hybrid, oncogenic coding sequences (1). Often, the corresponding hybrid proteins are signaling molecules and/or transcription factors that are deranged from their normal regulatory circuits or acquire novel functional properties. Disruption of regulatory pathways appears, thus, as a major and widespread consequence of the generation of chimeric mRNAs encoding hybrid oncogenic proteins.

Hybrids between heterologous mRNAs are also generated by mRNA trans-splicing. The latter was first detected in vitro (3,4), but was subsequently shown to occur in vivo in several lower and higher eukaryotes (5), including mammals (6–10). Major biological functions of the trans-splicing of a common spliced leader in trypanosomatids and nematodes are the processing of polycistronic transcription units and the regulation of the translation efficiency and stability of the resulting mRNAs (11). On the other hand, the trans-splicing between heterologous transcripts in mammalian cells increases protein diversity through the joining of segments/domains originating from different genes (5). Recent findings indicate that each of the two mRNA moieties also carries specific regulatory signals that dictate the physical location of the mRNA and regulate its stability (12).

Long transcription across neighbouring genes that normally act as independent transcription units, has been demonstrated in several cases (13–16). Similarly to the cases above, this results in hybrid, multi-locus transcripts, which often increase the diversity of the exon complement of the participating genes (13–16).

Chimeric transcripts in ‘antisense’ orientation have also been recently identified in the RefSeq and EMBL databanks (17). The origin and role of these transcripts are not known (17). However, natural, single-gene antisense mRNAs (18) are of frequent occurrence in mammals, including man (17,19), and may play a novel role in the regulation of gene expression. Thus, a similar regulatory role was suggested for the hybrid antisense mRNA.

Hence, diverse classes of hybrid mRNAs appear to play important functional roles in normal and transformed cells (1). A whole-genome exploration for hybrid sequences is, thus, of interest, as it may identify novel members of these hybrid mRNA classes, and reveal common structure/sequence characteristics. However, the construction of cDNA libraries frequently presents with cDNA fusion artifacts, linked to incorrect ligation or abnormal reverse-transcription (20,21). Thus, rigorous retrieval and analysis strategies are required to distinguish between mRNA chimeras of potential physiological origin and artifacts. In this work, we have developed the In Silico Trans-splicing Retrieval System (ISTReS) to extract ‘spliced’ chimeric mRNA from sequence databanks. Our findings demonstrate the overall feasibility of this sequence/structure-based strategy and the efficiency of the ISTReS procedure.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
ISTReS strategy
Chimeric sequences from non-contiguous loci are generated through at least three different molecular mechanisms, i.e. chromosomal translocations (22), mRNA trans-splicing (5) and transcription of long mRNA across neighbouring loci (13–16). In these cases the two heterologous mRNAs are typically joined together by splicing at conventional donor-acceptor exon-bordering sites (see below). RNA–RNA recombination has also been demonstrated, and was shown not to follow the rules of conventional splicing (23–25). However, the in vivo frequency of this phenomenon is extremely low (24) and is largely limited to viral RNA sequences (25). As a consequence, a general strategy was devised to identify hybrid mRNAs that are joined together following the sequence-structure rules of canonical mRNA splicing (26,27) (Fig. 1).



View larger version (30K):
[in this window]
[in a new window]
  		Figure 1. Schematic representation of the ISTReS analysis and retrieval strategy.

 
As shown in Figure 1A, whole cDNA sequence databanks (RefSeq, HGI, 31. jul. 2001 release, and subsets of theirs) were mapped onto the human genome by Blast analysis. Sequence databanks and analysis programs were downloaded to and utilised in two Digital Personal Workstations with Alpha 500 Mhz processors (780 and 255 Mb RAM, respectively) and a Digital AlphaStation 255 (128 Mb RAM).

Blast outputs were parsed for sequences that mapped to different loci (Fig. 1B). A parsing algorithm written in Perl was implemented to this purpose. Filtering criteria validated during the screening were: a Blast score >=300, a Blast match length of >=95% of the query sequence, a minimal Blast match length of 200 nt [lower lengths were permitted in the analysis of the chimeric antisense sequence datasets (17)], identity between the cDNA and genomic sequences of >=97%. A gap of <=10 nt between the two matches of the chimeric sequences was permitted. These criteria were devised to search with high-sensitivity and an acceptable stringency. For example, reasonable numbers of sequencing errors were tolerated, while good matches of short length were still highlighted.

As shown in Figure 1C, the identified chimeras were excluded from further analysis if they: (i) comprised more than two segments, as they were likely to derive from the random co-ligation of unrelated cDNA fragments; (ii) could not be located on the human genome map, as this did not permit verification of their origin from distinct loci; (iii) contained introns, as these were likely to derive from genomic DNA or, less frequently, from nuclear mRNA; (iv) had no independent evidence of ‘sense’ transcription, i.e. no other independent mRNA or EST sequences corresponding to either of the fusion partners could be identified; these sequences were likely to correspond to intergenic/non-transcribed regions of genomic DNA (see below for the antisense chimeras); (v) the fusion join corresponded to poly-linker sequences or enzyme sites utilized in the construction of the library; the chimeras contained vector (vi), mitochondrial (vii) or Escherichia coli (viii) sequences.

Figure 1D shows that the selected mRNA chimeras were further analysed for junction of the two partners at exon–exon borders and for concordant ‘sense/sense’ (or ‘antisense/antisense’) reading orientation. The reading orientation of the mRNA partners of the chimeric sequences was determined by comparison with independent transcripts in the non-redundant GenBank/EMBL sequence collection. EST sequences were not utilised for this purpose, because of their unreliable orientation, due to automated sequencing and non-curated deposit in databanks.

In the case of non-characterised transcripts additional evidence was contributed by a structural analysis of the corresponding transcription units at the genomic level [promoter sequences (28), transcription start sites (29), mRNA cleavage/poly-A addition signals (30) and untranslated regions (31)].

Online sequence analysis sites
Sequences were matched against the non-redundant and human_EST datasets using Blastn (http://www.ncbi.nlm.nih. gov/BLAST/) (32). Query sequences were mapped onto the human genome using Megablast (http://www.ncbi.nlm.nih. gov/genome/seq/HsBlast.html) (0.01 level expectation and default filtration). Sim4 (http://pbil.univ-lyon1.fr/sim4.html) (33) was used to define the exon–intron borders of the chimera partners.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
mRNA chimeras from two different genes most commonly arise from chromosomal translocations (22), mRNA trans-splicing (5) or transcription across neighbouring loci (13–16). As hybrid mRNA sequences play important roles in cell transformation or in regulatory pathways in normal cells (1), a whole-genome exploration, through the analysis of sequence databanks, may offer novel means to reveal other members of these classes and shared structure/sequence characteristics. Most chromosomal translocations identified in cancer cells occur in intronic regions (22,34), likely because of the longer overall length of introns and of the selective pressure for a functional protein, advantageous for cancer cell growth. The two partners in the chimera (as processed from nuclear mRNA precursors) are subsequently joined at exon–exon borders (22). Trans-spliced transcripts originate from the joining of independently transcribed mRNAs (5). This post-translational processing follows the rules of, and is performed by, the canonical cis-splicing apparatus, resulting in the joining of heterologous mRNAs at canonical exon–exon borders (3–5). Long, multi-locus transcription has been observed in several instances (13–16). The processing of the resulting long, immature mRNAs results in the joining of coding regions at exon–exon sites (13–16). Thus, joining at exon-bordering sites is a common feature of all of the above classes of heterologous mRNA chimeras.

On the other hand, cDNA construction artifacts (end-to-end joining or recombination) and the rare products of RNA–RNA recombination in vivo (24) are unlikely to join by chance at exact exon–exon borders. Moreover, while the trans-splicing of heterologous, independently transcribed mRNAs is expected to join ‘sense/sense’ sequences, cDNA/cDNA recombination or fusion would be expected to randomly generate ‘sense/antisense’ sequences in one-half of the cases. Random cDNA artifacts would also be expected to arise in proportion to the abundance of the corresponding mRNA. Hence, frequent transcripts, e.g. for ribosomal proteins, elongation factors, cytoskeletal proteins, globins (in hematopoietic cells) (30), are expected to be frequent among artefactually generated chimeric mRNA.

The concepts above were incorporated in the ISTReS screening strategy and algorithm (Fig. 1). The goal of ISTReS is to identify mRNA chimeras, whether from chromosomal translocations, mRNA trans-splicing or multi-locus transcription, within human transcript datasets. The criteria detailed in Material and Methods were implemented in the proof-of-principle searches presented here. Blast scores of >=300 were used as a cut-off in the analysis of whole sequence databanks. In combination with the sequence identity criteria this also allowed to select for good sequence matches of short length. This cut-off value was relaxed (>=80) for the analysis of the chimeric antisense transcript dataset, as this contained even shorter sequence segments (17).

We verified the capability of ISTReS to detect actual chimeric sequences in the curated databanks Human Gene Index (HGI, TIGR) (http://www.tigr.org/tdb/hgi/) and RefSeq (http://www.ncbi.nlm.nih.gov/LocusLink/refseq.html) (the latter search was kindly supported by the RefSeq curation staff). These searches were performed by Blast comparison of the HGI Tentative Human Consensus (THC) sequences and of the RefSeq candidates versus the human genome. Blast outputs were subsequently parsed for sequences that mapped to two different map locations.

Eighteen fusion sequences corresponding to ten experimentally verified translocated oncogenes, i.e. MLL-hCDCrel, ETV6-NTRK3, AML1-EVI1, AML1-MTG8, Rho GEF-PKA AP (LBC), AML1-EAP, SURF-RET, EWS-CHOP, PML-RAR{alpha}, COL1A1-PDGFB, were identified (Table 1), validating our search procedure. These searches also revealed a much larger number of chimeric sequences that did not meet the structural requirements expected from ‘physiological’ fusion events. mRNA chimeras that failed the criteria outlined in Figure 1 are listed in Tables 2 and 3. A comprehensive analysis of the Unigene database revealed 21 742 chimeric sequences, i.e. ~1% of the total number of transcripts analysed (35). Notably, several frequent mRNAs, e.g. for ribosomal proteins, were rather frequent among chimeric sequences, arguing in favour of a stocastic, artefactual nature. Of interest, intra-chromosomal hybrid sequences were 7.3% of all the RefSeq chimeras (Table 4) and 6.9% of the antisense chimeras (see below). As the fraction of the genome belonging to each separate chromosome ranges from 8.5% for chromosome 1 to 1.6% for the Y chromosome (mean: 4.8%) (36), our results appear close to what would be expected on stocastic grounds only, further supporting the random nature of most of the observed events.


View this table:
[in this window]
[in a new window]
  		Table 1. Fusion oncogenes retrieved from ISTReS searches
 

View this table:
[in this window]
[in a new window]
  		Table 2. Artefactual chimeric sequences identified by ISTReS in the HGI databank
 

View this table:
[in this window]
[in a new window]
  		Table 3. Artefactual chimeric sequences identified by ISTReS in the RefSeq databank
 

View this table:
[in this window]
[in a new window]
  		Table 4. Chromosomal map location of the chimeric sequences identified by ISTReS in the RefSeq databank
 
Rather interestingly, however, ISTReS screenings also identified two novel chimeric mRNAs that demonstrated the canonical features of trans-spliced mRNAs (or long intergenic transcripts), FOP-Rho GAP and methionyl tRNA synthetase-advillin. As these mRNAs were selected-out from 246 RefSeq chimeras (Fig. 2), these findings suggest a 1% frequency of canonically-spliced candidates among the hybrid sequences detected in current databanks.




View larger version (110K):
[in this window]
[in a new window]
  		Figure 2. (A) Structure, sequence and translation product of the FOP-Rho GAP chimeric mRNA (Accession number: AF314817) (Table 4). The 5' partner is FOP (translocated to the FGFR1 oncogene partner), whereas the 3' partner is T-cell activation Rho GTPase activating protein (GAP). The junction between the two partners is at exon–exon borders (exon II for FOP and exon IX for Rho GAP). The large distance between the two loci (6q27 versus 6q25) suggests a trans-splicing origin. However, as transcription is directed toward the centromere in both transcription units, this is formally consistent also with long, intergenic transcription. (Top) DNA sequence of the first 780 bases of the chimeric mRNA; (bottom) sequence of the encoded chimeric protein. DNA bases and aminoacids surrounding the splice site are boxed. (B) Structure, sequence and translation product of the methionyl tRNA synthetase-advillin chimeric mRNA (Accession number: BC004134) (Table 4). The 5' partner is the methionyl tRNA synthetase, whereas the 3' partner is advillin. The junction between the two partners is at exon–exon borders, (exon X for methionyl tRNA synthetase and exon II for advillin). The chromosomal position of methionyl tRNA synthetase is at 12q13.2, whereas that of advillin is at 12q13.1, and might be compatible with intergenic transcription. (Top) DNA sequence flanking the junction of the chimeric mRNA; (bottom) sequence of the encoded chimeric protein. DNA bases and aminoacids surrounding the splice site are boxed.

 
Recent findings have indicated that antisense mRNAs are of frequent occurrence in human cells (17,19). Previous experimental evidence had demonstrated the existence of natural antisense mRNA in eukaryotic cells (18). However, their frequent occurrence in the human transcriptome was unexpected, raising the possibility that they may play a novel role in the regulation of gene expression (17,19). The identified antisense chimeras were analysed with the ISTReS procedure. Thirty-one ‘antisense’ chimeric sequences passed the screening criteria for trivial cDNA artefacts (Fig. 1A–C; Tables 5 and 6). Unexpectedly, though, independent evidence for antisense transcription proved almost nil (2 of 24 148 total hits), and in none of the latter cases were exon–exon borders detected at the chimeric join. Abundant mRNAs (for ribosomal proteins, globins, translation elongation factors, MHC invariant chain, ß2-microglobulin etc.) were frequently present in the antisense chimeras, and hybrid sequences with ribosomal RNA (RNA polymerase I transcripts) (AF159295, AF095784) were also identified. Moreover, transcription initiation and cleavage/poly-adenylation sites were frequently present at the fusion joins for both ‘sense’ and ‘antisense’ mRNA segments (17) (Table 5). As ‘transcription initiation’ and ‘cleavage/poly-adenylation’ refer to the sense strand and do not have structural correlates for the ‘antisense’ strand, this and the analyses above strongly suggested an artifactual origin of the antisense hybrid sequences.


View this table:
[in this window]
[in a new window]
  		Table 5. Structural features of the antisense chimeric sequences in the RefSeq databank
 

View this table:
[in this window]
[in a new window]
  		Table 6. Chromosomal map location of the antisense chimeric sequences in the RefSeq databank
 
In summary, we have developed the ISTReS algorithm and screening procedure to identify spliced, heterologous mRNAs in sequence databanks. Our findings demonstrate the efficiency of ISTReS. They also support the overall feasibility of sequence/structure-based strategies to select for chimeric mRNAs candidate to derive from the splicing of heterologous transcripts.


   ACKNOWLEDGEMENTS
 
We thank Bo Yuan, David Wheeler and Monica Romiti for help with sequence retrieval and databank analysis. This work was performed with the support of the Italian Association for Cancer Research (AIRC, Italy). The financial support of Telethon - Italy (Grant no. GGP02353) is also gratefully acknowledged.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 

  1. Mitelman,F. (2000) Recurrent chromosome aberrations in cancer. Mutat. Res., 462, 247–253.[CrossRef][ISI][Medline]

  2. Croce,C.M., Erikson,J., ar-Rushdi,A., Aden,D. and Nishikura,K. (1984) Translocated c-myc oncogene of Burkitt lymphoma is transcribed in plasma cells and repressed in lymphoblastoid cells. Proc. Natl Acad. Sci. USA, 81, 3170–3174.[Abstract/Free Full Text]

  3. Solnick,D. (1985) Trans splicing of mRNA precursors. Cell, 42, 157–164.[CrossRef][ISI][Medline]

  4. Konarska,M.M., Padgett,R.A. and Sharp,P.A. (1985) Trans splicing of mRNA precursors in vitro. Cell, 42, 165–171.[CrossRef][ISI][Medline]

  5. Bonen,L. (1993) Trans-splicing of pre-mRNA in plants, animals and protists. FASEB J., 7, 40–46.[Abstract]

  6. Bruzik,J.P. and Maniatis,T. (1992) Spliced leader RNAs from lower eukaryotes are trans-spliced in mammalian cells. Nature, 360, 692–695.[CrossRef][Medline]

  7. Bruzik,J.P. and Maniatis,T. (1995) Enhancer-dependent interaction between 5' and 3' splice sites in trans. Proc. Natl Acad. Sci. USA, 92, 7056–7059.[Abstract/Free Full Text]

  8. Puttaraju,M., Jamison,S.F., Mansfield,S.G., Garcia-Blanco,M.A. and Mitchell,L.G. (1999) Spliceosome-mediated RNA trans-splicing as a tool for gene therapy. Nat. Biotechnol., 17, 246–252.[CrossRef][ISI][Medline]

  9. Li,B.L., Li,X.L., Duan,Z.J., Lee,O., Lin,S., Ma,Z.M., Chang,C.C., Yang,X.Y., Park,J.P., Mohandas,T.K. et al. (1999) Human acyl-CoA:cholesterol acyltransferase-1 (ACAT-1) gene organization and evidence that the 4.3-kilobase ACAT-1 mRNA is produced from two different chromosomes. J. Biol. Chem., 274, 11060–11071.[Abstract/Free Full Text]

  10. Caudevilla,C., Serra,D., Miliar,A., Codony,C., Asins,G., Bach,M. and Hegardt,F.G. (1998) Natural trans-splicing in carnitine octanoyltransferase pre-mRNAs in rat liver. Proc. Natl Acad. Sci. USA, 95, 12185–12190.[Abstract/Free Full Text]

  11. Nilsen,T.W. (1993) Trans-splicing of nematode premessenger RNA. Annu. Rev. Microbiol., 47, 413–440.[CrossRef][ISI][Medline]

  12. Hyde,M., Block-Alper,L., Felix,J., Webster,P. and Meyer,D.I. (2002) Induction of secretory pathway components in yeast is associated with increased stability of their mRNA. J. Cell Biol., 156, 993–1001.[Abstract/Free Full Text]

  13. Magrangeas,F., Pitiot,G., Dubois,S., Bragado-Nilsson,E., Cherel,M., Jobert,S., Lebeau,B., Boisteau,O., Lethe,B., Mallet,J. et al. (1998) Cotranscription and intergenic splicing of human galactose-1-phosphate uridylyltransferase and interleukin-11 receptor alpha-chain genes generate a fusion mRNA in normal cells. Implication for the production of multidomain proteins during evolution. J. Biol. Chem., 273, 16005–16010.[Abstract/Free Full Text]

  14. Communi,D., Suarez-Huerta,N., Dussossoy,D., Savi,P. and Boeynaems,J.-M. (2001) Cotranscription and intergenic splicing of human P2Y11 and SSF1 genes. J. Biol. Chem., 276, 16561–16566.[Abstract/Free Full Text]

  15. Moore,R.C., Lee,I.Y., Silverman,G.L., Harrison,P.M., Strome,R., Heinrich,C., Karunaratne,A., Pasternak,S.H., Chishti,M.A., Liang,Y. et al. (1999) Ataxia in prion protein (PrP)-deficient mice is associated with upregulation of the novel PrP-like protein doppel. J. Mol. Biol., 292, 797–817.[CrossRef][ISI][Medline]

  16. Finta,C. and Zaphiropoulos,P.G. (2000) The human cytochrome P450 3A locus. Gene evolution by capture of downstream exons. Gene, 260, 13–23.[CrossRef][ISI][Medline]

  17. Lehner,B., Williams,G., Campbell,R.D. and Sanderson,C.M. (2002) Antisense transcripts in the human genome. Trends Genet., 18, 63–65.[CrossRef][ISI][Medline]

  18. Vanhee-Brossollet,C. and Vaquero,C. (1998) Do natural antisense transcripts make sense in eukaryotes? Gene, 211, 1–9.[CrossRef][ISI][Medline]

  19. Fahey,M.E., Moore,T.F. and Higgins,D.G. (2002) Overlapping antisense transcription in the human genome. Comp. Funct. Genom., 3, 244–253.[CrossRef]

  20. Brakenhoff,R.H., Schoenmakers,J.G. and Lubsen,N.H. (1991) Chimeric cDNA clones: a novel PCR artifact. Nucleic Acids Res., 19, 1949.

  21. Chang,J. and Taylor,J. (2002) In vivo RNA-directed transcription, with template switching, by a mammalian RNA polymerase. EMBO J., 21, 157–164.[CrossRef][ISI][Medline]

  22. Rabbitts,T.H. (1994) Chromosomal translocations in human cancer. Nature, 372, 143–149.[CrossRef][Medline]

  23. Chetverin,A.B., Chetverina,H.V., Demidenko,A.A. and Ugarov,V.I. (1997) Nonhomologous RNA recombination in a cell-free system: evidence for a transesterification mechanism guided by secondary structure. Cell, 88, 503–513.[CrossRef][ISI][Medline]

  24. Chetverina,H.V., Demidenko,A.A., Ugarov,V.I. and Chetverin,A.B. (1999) Spontaneous rearrangements in RNA sequences. FEBS Lett., 450, 89–94.[CrossRef][ISI][Medline]

  25. Gmyl,A.P., Belousov,E.V., Maslova,S.V., Khitrina,E.V., Chetverin,A.B. and Agol,V.I. (1999) Nonreplicative RNA recombination in poliovirus. J. Virol., 73, 8958–8965.[Abstract/Free Full Text]

  26. Burset,M., Seledtsov,I.A. and Solovyev,V.V. (2000) Analysis of canonical and non-canonical splice sites in mammalian genomes. Nucleic Acids Res., 28, 4364–4375.[Abstract/Free Full Text]

  27. Aebi,M., Hornig,H., Padgett,R.A., Reiser,J. and Weissmann,C. (1986) Sequence requirements for splicing of higher eukaryotic nuclear pre- mRNA. Cell, 47, 555–565.[CrossRef][ISI][Medline]

  28. Berman,B.P., Nibu,Y., Pfeiffer,B.D., Tomancak,P., Celniker,S.E., Levine,M., Rubin,G.M. and Eisen,M.B. (2002) Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome. Proc. Natl Acad. Sci. USA, 99, 757–762.[Abstract/Free Full Text]

  29. Kristiansen,T.Z. and Pandey,A. (2002) A database of transcriptional start sites. Trends Biochem. Sci., 27, 174.

  30. Lewin,B. (2000) Genes VII. 8th Edn. Wiley, New York.

  31. Pesole,G., Liuni,S., Grillo,G., Licciulli,F., Mignone,F., Gissi,C. and Saccone,C. (2002) UTRdb and UTRsite: specialized databases of sequences and functional elements of 5' and 3' untranslated regions of eukaryotic mRNAs. Update 2002. Nucleic Acids Res., 30, 335–340.[Abstract/Free Full Text]

  32. Altschul,S.F., Gish,W., Miller,W., Myers,E.W. and Lipman,D.J. (1990) Basic local alignment search tool. J. Mol. Biol., 215, 403–410.[CrossRef][ISI][Medline]

  33. Florea,L., Hartzell,G., Zhang,Z., Rubin,G.M. and Miller,W. (1998) A computer program for aligning a cDNA sequence with a genomic DNA sequence. Genome Res., 8, 967–974.[Abstract/Free Full Text]

  34. Zhang,Y., Strissel,P., Strick,R., Chen,J., Nucifora,G., Le Beau,M.M., Larson,R.A. and Rowley,J.D. (2002) Genomic DNA breakpoints in AML1/RUNX1 and ETO cluster with topoisomerase II DNA cleavage and DNase I hypersensitive sites in t(8;21) leukemia. Proc. Natl Acad. Sci. USA, 99, 3070–3075.[Abstract/Free Full Text]

  35. Zhuo,D., Zhao,W.D., Wright,F.A., Yang,H.Y., Wang,J.P., Sears,R., Baer,T., Kwon,D.H., Gordon,D., Gibbs,S. et al. (2001) Assembly, annotation and integration of UNIGENE clusters into the human genome draft. Genome Res., 11, 904–918.[Abstract/Free Full Text]

  36. Lander,E.S., Linton,L.M., Birren,B., Nusbaum,C., Zody,M.C., Baldwin,J., Devon,K., Dewar,K., Doyle,M., FitzHugh,W. et al. (2001) Initial sequencing and analysis of the human genome. Nature, 409, 860–921.[CrossRef][Medline]


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
X. Shao, V. Shepelev, and A. Fedorov
Bioinformatic analysis of exon repetition, exon scrambling and trans-splicing in humans
Bioinformatics, March 15, 2006; 22(6): 692 - 698.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
N. Kim, P. Kim, S. Nam, S. Shin, and S. Lee
ChimerDB--a knowledgebase for fusion sequences
Nucleic Acids Res., January 1, 2006; 34(suppl_1): D21 - D24.
[Abstract] [Full Text] [PDF]

Home page
 Proc. Natl. Acad. Sci. USAHome page
Y. Hahn, T. K. Bera, K. Gehlhaus, I. R. Kirsch, I. H. Pastan, and B. Lee
Finding fusion genes resulting from chromosome rearrangement by analyzing the expressed sequence databases
PNAS, September 7, 2004; 101(36): 13257 - 13261.
[Abstract] [Full Text] [PDF]

Home page
 RNAHome page
A. P. GMYL, S. A. KORSHENKO, E. V. BELOUSOV, E. V. KHITRINA, and V. I. AGOL
Nonreplicative homologous RNA recombination: Promiscuous joining of RNA pieces?
RNA, October 1, 2003; 9(10): 1221 - 1231.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Print PDF (307K) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Commercial Re-use Guidelines
for Open Access NAR Content
Google Scholar
Right arrow Articles by Romani, A.
Right arrow Articles by Alberti, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Romani, A.
Right arrow Articles by Alberti, S.
Related Collections
Right arrow RNA characterisation and manipulation
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?