Prediction and quality assessment of transposon insertion display data
2004; Future Science Ltd; Volume: 36; Issue: 2 Linguagem: Inglês
10.2144/04362bm04
ISSN1940-9818
AutoresQuang Hien Le, Thomas E. Bureau,
Tópico(s)Advanced biosensing and bioanalysis techniques
ResumoBioTechniquesVol. 36, No. 2 BenchmarksOpen AccessPrediction and quality assessment of transposon insertion display dataQuang Hien Le & Thomas BureauQuang Hien Le*Address correspondence to: Quang Hien Le, Laboratoire de Biologie Cellulaire, INRA Centre de Versailles, 78026 Versailles, France. e-mail: E-mail Address: hien.le@versailles.inra.frMcGill University, Montréal, Québec, Canada & Thomas BureauMcGill University, Montréal, Québec, CanadaPublished Online:6 Jun 2018https://doi.org/10.2144/04362BM04AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Transposons are mobile sequences commonly found in prokaryotic and eukaryotic genomes. Their dispersal, repetitiveness, and the fact that their mobilization is a source of polymorphism make them choice candidates for use as molecular markers in mapping technologies. In recent years, variations of a technique inspired by amplified fragment length polymorphisms (AFLPs) (1) that take advantage of transposons have emerged as valuable tools for molecular analyses (2–7). These transposon-based mapping techniques, referred to as transposon insertion display (TID) after the first published report (2), have been applied to plants as well as to animals for population analysis (8,9), detection of transposition events (10),gene tagging (2), and the recovery of integration sites (3).The common basis of all TID techniques is an adaptor-mediated multiplex PCR amplification of genomic restriction fragments that contain a transposon marker sequence, along with the variable length of the DNA sequences flanking the insertion sites (Figure 1). However, to avoid the amplification of restriction fragments that do not contain transposon marker sequences (i.e., nonspecific), different adaptor designs have been adopted (Figure 1, A and B) (2–11).Figure 1. Transposon insertion display (TID) strategies.Transposon (black), genomic (white), and adaptor sequences (gray and hatched boxes) are represented. Genomic DNA is digested with restriction endonucleases (REases), yielding transposon fragments with varying lengths of adjacent sequence. Adaptors are ligated, and a preselective PCR amplifies transposon termini with flanking DNA sequences using primers directed against the adaptor (ap1) and transposon family (ep1). A selective amplification using nested or more specific primers enrich for transposon-specific products (optional in some protocols) (10). (A) The vectorette (11) is a specially designed double-stranded adaptor that is not completely complementary in sequence (represented by a bulge). Elongation from ap1 can only occur after firststrand synthesis from ep1, selecting for transposon-specific products. (B) TID strategy using different restriction enzymes (REase1 and REase2) and adaptors (gray-shaded and hatched boxes), each specific to either the transposon side or the flanking side. In this manner, amplification can be initiated from different adaptor-specific primers. Biotinylation of the transposon-specific adaptor can also serve as an enrichment step prior to the selective PCR (6). (C) Radioactive or fluorescently labeled primers (indicated by asterisks) allow for detection after size fractionation using polyacrylamide gel electrophoresis (PAGE), and predictTID uses ep2 sequence to calculate the size of the expected fragments. PredictTID serves to optimize experimental design, allows polymorphic bands to be distinguished from artifacts and, in experiments, can provide support for the observed data.TID protocols also differ in the type of transposon chosen as a marker. However, transposon abundance, diversity, and distribution vary greatly between organisms. For example, transposon content can range from 3% in the yeast genome to over 60% in maize, and mammalian genomes primarily contain long and short interspersed nuclear elements, whereas the maize genome is mostly populated by long terminal repeat retrotransposons (12). This high variability can complicate the choice of an appropriate marker since clarity and resolution depend on the copy number of the transposon type used. Furthermore, the accuracy of TID is dependent on the design and PCR conditions of a transposon-specific primer. Transposons are characterized by structural features that may be problematic for PCR [e.g., terminal and subterminal repeats, secondary structures, A and T richness, or poly(A)/(T) tails]. Thus, the ability to predict the banding pattern generated by a specific primer in a specific genome would be useful for optimizing PCR conditions and for assessing the reliability and quality of the observed data.A large data set of genomic sequence is currently available, including the complete sequence for eukaryotic model organisms such as Arabidopsis, Caenorhabditis elegans, Drosophila, mosquito, rice, and human (http://www.ncbi.nlm.nih.gov:80/PMGifs/Genomes/euk_g.html ). In addition, many other genomes are currently in the process of being sequenced. Available sequence information has been exploited in applications to calculate the expected sizes of PCR and AFLP products (http://www.in-silico.com/ and http://elanor.sci.muni.cz/cgi-bin/vpcr2.cgi; unpublished data) (13,14), but these are site-specific or do not deal with the amplification of transposon-specific fragments. In this report, we describe a method to predict the TID banding pattern of a given primer from the available genomic sequence information.We compared the observed against the predicted TID profile of a family of terminal inverted repeat (TIR) transposons called cac1. These elements were first identified from Arabidopsis, and the location of the four members (CAC1, CAC2, CAC3, and CAC4) within the completely sequenced genome is known (Table 1) (15). Exploiting conserved regions near the cac1 TIRs, preselective [(cac1-1; 5′-(T/C)TTTCGTAATGCTATGGTTGAAACACCTAAC-3′) and selective (cac1-2; 5′-CATACAATTCTGACGCTATC-3′)] primers for TID were designed by visual examination. The nucleotide sequences were retrieved from GenBank® (http://ncbi.nlm.nih.gov/Entrez/) and aligned using the PileUp function from the GCG® suite of programs (version 10; Accelrys, Burlington, MA, USA).Table 1. cac1 Elements in ArabidopsisaWe wrote a Perl (version 5.6.0) script, predictTID, to calculate the sizes of bands expected from TID. PredictTID first uses the cac1-2 selective primer sequence as a query in a Basic Local Alignment Search Tool (BLAST®) search (version 2.2.3; ftp://ftp.ncbi.nih.gov/blast/) (16) against the Arabidopsis genome sequence (downloaded from The Institute for Genome Research; ftp://ftp.tigr.org/pub/data/a_thaliana). BLASTN parameters are set to default values, and the repeat filter is set to false. The BLAST search result is then parsed, and high scoring pairs (HSP) (16) that contain more mismatches than allowed by a userdefined variable (threshold limit) are discarded. We observed no differences in the predicted results when 0%–20% mismatches with the primer sequence were allowed. Genomic sequence (1000 bp) flanking the regions of similarity are retrieved and examined for the first BfaI restriction pattern found upstream or downstream, depending on whether the BLAST subject was in the same or in reverse orientation, respectively, relative to the BLAST query on HSP.The expected sizes reported by predictTID were then compared with the banding pattern of Arabidopsis thaliana (Columbia) cac1 elements using a vectorette-mediated TID strategy (2,11) with primers cac1-1 and cac1-2 (Figure 2). Genomic DNA was extracted from one or two rosette leaves of A. thaliana (Columbia-0) using a DNeasy® Plant Mini Kit (Qiagen, Mississauga, ON, Canada), following the manufacturer's instructions. TID as described by Korswagen et al. (2) was modified for the DNA 4200 fluorescence system (Li-Cor, Lincoln, NE, USA ) (8). Approximately 100 ng of genomic DNA were digested with 2.5 U BfaI (New England Biolabs, Beverly, MA, USA) and ligated to 15 pmol adaptor cassettes (5′-TAGCAAGGAGAGGACGCTGTCTGTCGAAGGTAAGGAACGGACGAGAGAAGGGAGA-3′and 5′-TCTTCCCTTCTCGAATCGTAACCGTTCGTACGAGAATCGCTGTCTCTCCTTGC-3′) with T4 DNA ligase (Invitrogen, Burlington, ON, Canada). The ligation product was diluted 4-fold before a preselective amplification using cac1-1 and ap1 (5′-CGAATCGTAACCGTTCGTACGAGAATCGCT-3′). Preselective amplification products were diluted 100-fold and reamplified using cac1-2 and ap2 (5′-GTACGAGAATCGCTGTCCTC-3′), the latter being labeled with a IRDye™ 700 fluorescent dye (Li-Cor). We used the AmpliTaq® PCR system (Perkin-Elmer, Boston, MA, USA) in a PTC-225 DNA Engine Tetrad® Thermal Cycler (MJ Research, Waltham, MA, USA) for both amplifications, which consisted of 94°C for 10 min; 20 cycles of 94°C for 1 min, 50°, 55°, 60°, or 65°C for 1 min, and 72°C for 1 min; and 72°C for 10 min. Six microliters of loading dye (95% formamide, 10 mM EDTA, 0.1% bromophenol blue) were then added to the final amplification products, which were separated by size and visualized on a 5.5% denaturing polyacrylamide gel (BioShop, Burlington, ON, Canada). Fluorescently labeled DNA (50–700 bp) (50-700 sizing standard; Li-Cor) served as molecular weight markers.Figure 2. A transposon insertion display (TID) using cac1-1 and cac1-2 primers.Annealing temperatures for preselective (top, horizontal) and selective (bottom, vertical) PCRs are indicated above each lane. Lane (M), 50–700 bp DNA molecular weight marker. The sizes of the bands observed on the gel are in agreement with the sizes calculated by predict TID (indicated on the right) and correspond to the CAC1, CAC2, CAC3, and CAC4 elements listed in Table 1.Combinations of preselective and selective annealing temperatures between 50°–65°C, with 5°C increments,were tested. Four bands were expected from predictTID, and these could be reliably matched on TID. Annealing temperatures between 55°–60°C yield bands that are in best agreement with sizes calculated from predictTID. The estimated annealing temperatures for the selective amplification primers are between 50.3°–58.0°C (17). As a control, we manually retrieved and visually examined the sequences flanking CAC1, CAC2, CAC3, and CAC4 elements to confirm the sizes of fragments calculated using predictTID. Fragment sizes for the four cac1 members that were determined by manual examination are indicated in Table 1 and Figure 2. An unpredicted band (approximately 850 bp) could be seen but was no longer observed when higher annealing temperatures were used for the preselective amplification, which suggests that this may be a misannealing product.Although not observed in this study, there are potential limitations to the reliability of predictTID. First, the maximum length of sequences flanking an insertion that is examined by predictTID was set to 1000 bp because, in practice, longer fragments cannot be reliably resolved by TID. Here we used BfaI, and analysis of the restriction pattern of the complete Arabidopsis genome indicated that the majority (89.2%) of BfaI fragments generated were shorter than 1000 bp.Second, the initial step of pattern matching the primer sequence is handled by the BLASTN program (16) and may not exactly reflect PCR annealing conditions in terms of mismatches and gaps. The fact that predictTID gives the same weight to mismatches on the 5′ and 3′ ends of the primer sequence may be a source of difference.Third, the applicability of our program is of course dependent on the amount of available sequence information. Even with completely sequenced genomes, there are gaps, especially within the repetitive sequence-laden centromeric and telomeric regions. Sequencing projects also focus on a specific genotype, and in other lines or strains, sequence polymorphisms may be a source of error. Nevertheless, as long as a large quantity of genome sequence information is available, predictTID can be useful to assess the validity of TID-generated bands.Despite these potential limitations, we have shown that available sequence information can be used to test the reliability of primers in TID experiments. In a number of model organisms and for a wide range of transposon families, TID techniques are being adopted for a variety of applications. In these systems, predictTID can provide theoretical support for observed data, thereby facilitating the optimization of PCR conditions and the determination of the quality of designed primers. In addition, and based on the principle used by predictTID, two programs, predictAFLP and predictRAPD, are also available for calculating the sizes of bands expected from AFLP and other PCR-based mapping techniques. All programs are freely available by request and are also accessible online (http://bailly.biol.mcgill.ca/predictTID.html).AcknowledgmentsWe thank Dr. M.-A. Grandbastien, Dr. S.M. Tam, Nikoleta Juretic, and Fabienne Saadé for critical comments on our manuscript. We are grateful to Newton Agrawal for providing computer-programming advice. This work was funded by a National Science and Engineering Research Council (NSERC) grant to T.B. and a McGill Major Fellowship to Q.-H.L.References1. Vos, P., R. Hogers, M. Bleeker, M. Reijans, T. van de Lee, M. Hornes, A. Frijters, J. Pot, et al.. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23:4407–4414.Crossref, Medline, CAS, Google Scholar2. Korswagen, H.C., R.M. Durbin, M.T. Smits, and R.H.A. Plasterk. 1996. Transposon Tc1-derived, sequence-tagged sites in Caenorhabditis elegans as markers for gene mapping. Proc. Natl. Acad. Sci. USA 93:14680–14685.Crossref, Medline, CAS, Google Scholar3. Kohli, A., J. Xiong, R. Greco, P. Christou, and A. Pereira. 2001. Tagged Transcriptome Display (TTD) in indica rice using Ac transposition. Mol. Genet. Genomics 266:1–11.Crossref, Medline, CAS, Google Scholar4. Yephremov, A. and H. Saedler. 2000. Technical advance: display and isolation of transposon-flanking sequences starting from genomic DNA or RNA. Plant J. 21:495–505.Crossref, Medline, CAS, Google Scholar5. Waugh, R., K. McLean, A.J. Flavell, S.R. Pearce, A. Kumar, B.B. "Thomas, and W. Powell. 1997. Genetic distribution of BARE-1-like retrotransposable elements in the barley genome revealed by sequence-specific amplification polymorphisms (S-SAP). Mol. Gen. Genet. 253:687–694.Crossref, Medline, CAS, Google Scholar6. Van den Broeck, D., T. Maes, M. Sauer, J. Zethof, P. De Keukeleire, M. D'hauw, M. Van Montagu, and T. Gerats. 1998. Transposon Display identifies individual transposable elements in high copy number lines. Plant J. 13:121–129.Medline, CAS, Google Scholar7. Ayyadevara, S., J.J. Thaden, and R.J. Shmookler Reis. 2000. Anchor polymerase chain reaction display: a high-throughput method to resolve, score, and isolate dimorphic genetic markers based on interspersed repetitive DNA elements. Anal. Biochem. 284:19–28.Crossref, Medline, CAS, Google Scholar8. Wright, S.I., Q.H. Le, D.J. Schoen, and T.E. Bureau. 2001. Population dynamics of an Ac-like transposable element in self-and cross-pollinating Arabidopsis. Genetics 158:1279–1288.Crossref, Medline, CAS, Google Scholar9. Ellis, T.H., S.J. Poyser, M.R. Knox, A.V. Vershinin, and M.J. Ambrose. 1998. Polymorphism of insertion sites of Ty1-copia class retrotransposons and its use for linkage and diversity analysis in pea. Mol. Gen. Genet. 260:9–19.Medline, CAS, Google Scholar10. Melayah, D., E. Bonnivard, B. Chalhoub, C. Audeon, and M.-A. Grandbastien. 2001. The mobility of the tobacco Tnt1 retrotransposon correlates with its transcriptional activation by fungal factors. Plant J. 28:159–168.Crossref, Medline, CAS, Google Scholar11. Arnold, C. and I.J. Hodgson. 1991. Vectorette PCR: a novel approach to genomic walking. PCR Methods Appl. 1:39–42.Crossref, Medline, CAS, Google Scholar12. Kidwell, M.G. 2002. Transposable elements and the evolution of genome size in eukaryotes. Genetica 115:49–63.Crossref, Medline, CAS, Google Scholar13. Schuler, G.D. 1997. Sequence mapping by electronic PCR. Genome Res. 7:541–550.Crossref, Medline, CAS, Google Scholar14. Rombauts, S., Y. Van De Peer, and P. Rouzé. 2003. AFLPinSilico, simulating AFLP fingerprints. Bioinformatics 19:776–777.Crossref, Medline, CAS, Google Scholar15. Miura, A., S. Yonebayashi, K. Watanabe, T. Toyama, H. Shimada, and T. Kakutani. 2001. Mobilization of transposons by a mutation abolishing full DNA methylation in Arabidopsis. Nature 411:212–214.Crossref, Medline, CAS, Google Scholar16. Altschul, S.F., T.L. Madden, A.A. Schaffer, J. Zhang, Z. Zhang, W. Miller, and D.J. Lipman. 1997. Gapped BLAST and PSIBLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389–3402.Crossref, Medline, CAS, Google Scholar17. Breslauer, K.J., R. Frank, H. Blocker, and L.A. Marky. 1986. Predicting DNA duplex stability from the base sequence. Proc. Natl. Acad. Sci. USA 83:3746–3750.Crossref, Medline, CAS, Google ScholarFiguresReferencesRelatedDetailsCited ByDetection of mPing mobilization in transgenic rice plants12 November 2019 | Genes & Genomics, Vol. 42, No. 1Carrot Molecular Genetics and Mapping9 May 2019Accumulation of transposable elements in selfing populations of Arabidopsis lyrata supports the ectopic recombination model of transposon evolution14 May 2018 | New Phytologist, Vol. 219, No. 2Marker utility of transposable elements for plant genetics, breeding, and ecology: a review6 December 2014 | Genes & Genomics, Vol. 37, No. 2The allotetraploid Arabidopsis thaliana–Arabidopsis lyrata subsp. petraea as an alternative model system for the study of polyploidy in plants16 January 2009 | Molecular Genetics and Genomics, Vol. 281, No. 4Demography and weak selection drive patterns of transposable element diversity in natural populations of Arabidopsis lyrata16 September 2008 | Proceedings of the National Academy of Sciences, Vol. 105, No. 37DcMaster transposon display markers as a tool for diversity evaluation of carrot breeding materials and for hybrid seed purity testingJournal of Applied Genetics, Vol. 49, No. 1Transposon display for active DNA transposons in riceGenes & Genetic Systems, Vol. 82, No. 2Tuareg, a novel miniature-inverted repeat family of pearl millet (Pennisetum glaucum) related to the PIF superfamily of maizeGenetica, Vol. 128, No. 1-3 Vol. 36, No. 2 Follow us on social media for the latest updates Metrics Downloaded 261 times History Received 22 August 2003 Accepted 19 November 2003 Published online 6 June 2018 Published in print February 2004 Information© 2004 Author(s)AcknowledgmentsWe thank Dr. M.-A. Grandbastien, Dr. S.M. Tam, Nikoleta Juretic, and Fabienne Saadé for critical comments on our manuscript. We are grateful to Newton Agrawal for providing computer-programming advice. This work was funded by a National Science and Engineering Research Council (NSERC) grant to T.B. and a McGill Major Fellowship to Q.-H.L.PDF download
Referência(s)