Bioinformatics Advance Access originally published online on August 27, 2004
Bioinformatics 2005 21(3):278-281; doi:10.1093/bioinformatics/bth500
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Bioinformatics vol. 21 issue 3 © Oxford University Press 2005; all rights reserved.
Recombination Analysis Tool (RAT): a program for the high-throughput detection of recombination
1 Department of Food Safety Science, Institute of Food Research Norwich Research Park, Colney Lane, Norwich NR4 7HA, UK
2 Computational Biology Group, John Innes Centre Norwich Research Park, Colney Lane, Norwich NR4 7HA, UK
*To whom correspondence should be add addressed.
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Abstract |
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 TOP Abstract INTRODUCTIONSystems and MethodsIMPLEMENTATIONRESULTSDISCUSSIONREFERENCES |
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Motivation: Recombination can be a prevailing drive in shaping genome evolution. RAT (Recombination Analysis Tool) is a Java-based tool for investigating recombination events in any number of aligned sequences (protein or DNA) of any length (short viral sequences to full genomes). It is an uncomplicated and intuitive application and allows the user to view only the regions of sequence alignments they are interested in.
Results: RAT was applied to viral sequences. Its utility was demonstrated through the detection of a known recombinant of HIV and a detailed analysis of Noroviruses, the most common cause of viral gastroenteritis in humans.
Availability: RAT, along with a user's guide, is freely available from http://jic-bioinfo.bbsrc.ac.uk/bioinformatics-research/staff/graham_etherington/RAT.htm
Contact: Graham.Etherington{at}bbsrc.ac.uk
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INTRODUCTION |
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TOPAbstractINTRODUCTIONSystems and MethodsIMPLEMENTATIONRESULTSDISCUSSIONREFERENCES |
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Recombination is the process whereby two separate molecules of DNA or RNA exchange regions of their genome. The exchange is often in homologous regions of the genome and occurs in both single-stranded and double-stranded DNA and RNA molecules. Thus, recombination is a major mechanism driving evolutionary change. There is a continuing need to define, as accurately as possible, sequences where recombination events may have occurred.
There are five generally recognized methods of detecting recombination in DNA sequences: similarity methods (using the tendency of neighbouring nucleotides to be more compatible than sites farther apart), distance methods (using the estimation of genetic distances between sequences), phylogenetic methods (identifying incongruous tree topologies from different parts of a sequence or genome), compatibility methods (testing for partition phylogenetic incongruence and do not require the phylogeny of the sequences to be known) and substitution distribution (examines the sequences for a significant grouping of substitutions) (Posada et al., 2002). There are also various applications available for examining recombination. SIMPLOT (Lole et al., 1999) PHYPRO (Weiller, 1998) RDP (Martin and Rybicki, 2000) and TOPALi (Milne et al., 2004) look for changes in patterns of genetic diversity. LARD (Holmes et al., 1999) PLATO (Grassly and Holmes, 1997) and BOOTSCAN (Salminen et al., 1995) look for incongruent phylogenetic trees. RETICULATE (Jakobsen and Easteal, 1996) calculates compatibility matrices. PIST (Worobey, 2001) looks for excessive convergent evolution.
However, many current applications have important limitations, e.g. they are not cross-platform tools, are not intuitive to use, do not accept multiple sequence alignments, do not search automatically, use complex, time-consuming algorithms, do not have a user interface, require the sequences to be in a particular format, cannot identify small areas of recombination or do not accept protein sequences. In this paper, we introduce a new program and demonstrate its utility by reference to recombination in viral sequences.
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Systems and Methods |
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TOPAbstractINTRODUCTIONSystems and MethodsIMPLEMENTATIONRESULTSDISCUSSIONREFERENCES |
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A full and detailed explanation of how to use RAT and also the algorithms used may be found on the download page, given in the abstract above.
The Recombination Analysis Tool (RAT) is a cross-platform, Java-based application intended for high-throughput, recombination analysis of both DNA and protein multiple sequence alignments, in any one of seven different file formats. It uses the distance-based method of recombination detection. All of RAT's operations are carried out through the main RAT GUI, and all output can be saved as data files (.txt, .xls, .csv), or as .jpg files in the case of graphical outputs. RAT is intuitive and easy to use, and only requires a minimum of input from the user. All the parameters have default values, all of which may be changed by the user. The user may use RAT to examine sequences individually using the Single-sequence viewer, or may use the Auto Search option that searches for recombination given a user-defined search criterion.
Single-sequence viewer
If a recombinant sequence (the ‘Test Sequence’) is already known or suspected, it may be chosen from a drop-down list of all the sequences in the alignment and then the Sequence Viewer launched to view the similarity of all other sequences to the Test Sequence.
Auto Search
The Auto Search option can be used to search through every sequence for possible recombination events. There are three parameters involved; lower threshold (the genetic distance that a sequence must be under to qualify as a suspect recombinant), upper threshold (the genetic distance that a sequence must jump to/from when compared to the lower threshold) and the number of contributing sequences (the maximum number of sequences allowable to contribute to a recombinant).
The resulting output from RAT Auto Search is a JTextArea report. If RAT finds an area of sequence that matches the input parameters, it prints out a report on the sequence, allowing the user to view the sequence involved in the Sequence Viewer (but with only the contributing sequences checked and displayed).
Testing and verification
Using KAL 153 (accession number AF193276), a known recombinant HIV-1 strain from the region of the former Soviet Union (Liitsola et al., 2000) a multiple sequence alignment of 27 similar HIV-1 strains was obtained by means of a BLAST search (Altschul et al., 1990). First, the recombinant sequence, KAL 153, was examined in the Single-sequence viewer. It was evident that KAL 153 was a recombinant sequence between strains 97BL006 (AF193275) and UKR1216 (AF193278). 97BL006 started off with <80% similarity to KAL153 and then rose sharply to almost 95% similarity. Conversely, UKR1216 started off more than 99% similar to KAL153, but then dropped to 80% similarity at the same point.
In order to test the recombination search feature of RAT, the alignment was searched for sequences that started at <82% similarity and then jumped to >92% similarity. The resulting Auto Search report for the 27 HIV sequences showed six ‘hits’ that involved two or more contributing sequences. Upon visual inspection, two of the six hits showed clear signs of recombination (i.e. two or more sequences showing recombination crossover points). Of the two, one was the known recombinant KAL 153 (Fig. 1), with the known contributing sequences to the recombination event also being successfully identified (97BL006 and UKR1216). The second sequence showing clear evidence of recombination was isolated as 98BY10443 (AF414006), also from the former Soviet Union. The contributing sequences for this strain were the same as for KAL 153, so 98BY10443 was presumed to be a close relative of KAL 153. The remaining four ‘hits’ did not show a clear crossover point and so were presumed to be due to random sequence heterogeneity although further statistical analysis may be worthwhile.
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IMPLEMENTATION |
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TOPAbstractINTRODUCTIONSystems and MethodsIMPLEMENTATIONRESULTSDISCUSSIONREFERENCES |
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All full-length Norovirus genomes, along with other long stretches of Norovirus genomic DNA, were obtained from GenBank, aligned using ClustalW (Thompson et al., 1994) and edited to remove gaps. The Auto Search option on RAT was used to examine recombination.
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RESULTS |
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TOPAbstractINTRODUCTIONSystems and MethodsIMPLEMENTATIONRESULTSDISCUSSIONREFERENCES |
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Recombinant Noroviruses and their contributing sequences were identified as follows (work that found similar results is referenced): Arg320 (AF190817) between Mexico virus (U22498) and Lordsdale virus (X86557) (Jiang et al., 1999) Norovirus Mc37 (AY237415) between Saitama U1 (AB039775) or Gifu'96 (AB045603) in the ORF1 region and an unknown virus in the ORF2 region (Hansman et al., 2004) WUG1 (AB081723) between Southampton virus (L07418) and Norovirus BS5 (AF093797) (Katayama et al., 2002) Norovirus MD 145–12 (AY032605) between Saitama U1 (AB039775) or Gifu'96 (AB045603) in the ORF1 region and an unknown virus in the ORF2 region, Gifu'96 between Lordsdale virus and Hawaii virus (U07611) and Snow Mountain virus (AY134748) between Lordsdale virus and Melksham virus (X81879). The latter three recombinants have not been reported before.
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DISCUSSION |
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TOPAbstractINTRODUCTIONSystems and MethodsIMPLEMENTATIONRESULTSDISCUSSIONREFERENCES |
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Our results demonstrate the utility of RAT in finding viral recombinants and indicate that large-scale recombination occurs in the Noroviruses. We also show a ‘hot spot’ for recombination between the end of ORF 1 (nonstructural polyprotein) and the start of ORF 2 (capsid protein).
When compared to other programs available, RAT is a much easier and intuitive tool to use and allows the examination of large amounts of data with the minimum amount of user intervention. The lack of complex algorithms allows users to speedily obtain a clear insight into the history of recombination by automatically searching through sequence data. RAT is especially useful as an initial, fast, exploratory tool to form the basis for a more detailed analysis. We anticipate that RAT will be equally useful in revealing recombination events in higher organisms as well as in viruses. When analyzing data, it is possible that RAT will throw up false-positives, but these can be quickly dispelled by visual inspection. When positive results are found, further work may be needed to find statistical support for recombination, and to this end, future versions of RAT including statistical tools are planned.
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Acknowledgments |
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This work was supported by a grant from the Biotechnology and Biological Sciences Research Council.
Received on May 28, 2004; revised on August 3, 2004; accepted on August 18, 2004
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REFERENCES |
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Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J. (1990) Basic local alignment search tool. J. Mol. Biol., 215, 403–10[CrossRef][ISI][Medline].
Grassly, N.C. and Holmes, E.C. (1997) A likelihood method for the detection of selection and recombination using nucleotide sequences. Mol. Biol. Evol., 14, 239–247[Abstract].
Hansman, G.S., Katayama, K., Maneekarn, N., Peerakome, S., Khamrin, P., Tonusin, S., Okitsu, S., Nishio, O., Takeda, N., Ushijima, H. (2004) Genetic diversity of norovirus and sapovirus in hospitalized infants with sporadic cases of acute gastroenteritis in Chiang Mai, Thailand. J. Clin. Microbiol., 42, 1305–1307
Holmes, E.C., Worobey, M., Rambaut, A. (1999) Phylogenetic evidence for recombination din dengue virus. Mol. Biol. Evol., 16, 405–409[Abstract].
Jakobsen, I.B. and Easteal, S. (1996) A program for calculating and displaying compatibility matrices as an aid in determining reticulate evolution ini molecular sequences. Comput. Appl. Biosci., 12, 291–295
Jiang, X., Espul, C., Zhong, W.M., Cuello, H., Matson, D.O. (1999) Characterization of a novel human calicivirus that may be a naturally occurring recombinant. Arch. Virol., 144, 2377–2387[CrossRef][ISI][Medline].
Katayama, K., Shirato-Horikoshi, H., Kojima, S., Kageyama, T., Oka, T., Hoshino, F., Fukushi, S., Shinohara, M., Uchida, K., Suzuki, Y., Gojobori, T., Takeda, N. (2002) Phylogenetic analysis of the complete genome of 18 Norwalk-like viruses. Virology, 299, 225–239[CrossRef][ISI][Medline].
Liitsola, K., Holm, K., Bobkov, A., Pokrovsky, V., Smolskaya, T., Leinikki, P., Osmanov, S., Salminen, M. (2000) An AB recombinant and its parental HIV type 1 strains in the area of the former Soviet Union: low requirements for sequence identity in recombination. UNAIDS Virus Isolation Network. AIDS Res. Hum. Retroviruses, 16, 1047–1053[CrossRef][ISI][Medline].
Lole, S., Bollinger, R.C., Paranjape, R.S., Gadkari, D., Kulkarni, S.S., Novak, N.G., Ingersoll, R., Sheppard, H.W., Ray, S.C. (1999) Full-length human immunodeficiencey virus Type 1 genomes from subtype C-infected seroconverters in India, with evidence of intersubtype recombination. J. Virol., 73, 152–160
Martin, D. and Rybicki, E. (2000) RDP: detection of recombination amongst aligned sequences. Bioinformatics, 16, 562–563
Milne, I., Wright, F., Rowe, G., Marshall, D.F., Husmeier, D., McGuire, G. (2004) TOPALi: a software for identification of recombinant sequences within DNA multiple alignments. Bioinformatics, 20, 1806–1807
Posada, D., Crandall, K.A., Holmes, E.C. (2002) Recombination in evolutionary genomics. Annu. Rev. Genet., 36, 75–97[CrossRef][ISI][Medline].
Salminen, M.O., Carr, J.K., Burke, D.S., McCutchan, F.E. (1995) Identification of breakpoints in intergenotypic recombinants of HIV type 1 by bootscanning. AIDS Res. Hum. Retroviruses, 11, 1423–1425[ISI][Medline].
Thompson, J.D., Higgins, D.G., Gibson, T.J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res., 22, 4673–4680
Weiller, G.F. (1998) Phylogenetic profiles: a graphical method for detecting genetic recombinations in homologous sequences. Mol. Biol. Evol., 15, 326–335[Abstract].
Worobey, M. (2001) A novel approach to detecting and measuring recombination: new insights into evolution in viruses, bacteria, and mitochondria. Mol. Biol. Evol., 18, 1425–1434
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