Abstract
Determining the evolutionary history of a sampled sequence can become quite complex when multiple recombination events are part of its past. With at least five new recombination detection methods published in the last year, the growing list of over 40 methods suggests that this field is generating a lot of interest. In previous studies comparing recombination detection methods, the evaluation procedures did not measure how many recombinant sequences, breakpoints and donors were correctly identified. In this paper we will present the algorithm RecIdentify that scans a phylogenetic network and uses its edge lengths and topology to identify the parental/donor sequences and breakpoint positions for each query sequence. RecIdentify findings can be used to evaluate the output of recombination detection programs. RecIdentify may also assist in understanding how network size and complexity may shape recombination signals in a set of DNA sequences. The results may prove useful in the phylogenetic study of serially-sampled viral data with recombination events.
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References
Fan, J., Robertson, D.: Links to recombinant sequence analysis/detection programs (2006), http://bioinf.man.ac.uk/recombination/programs.shtml
Posada, D., Crandall, K.: The effect of recombination on the accuracy of phylogeny reconstruction. Journal of Molecular Evolution 54, 396–402 (2002)
Schierup, M., Hein, J.: Consequences of recombination on traditional phylogenetic analysis. Genetics 156, 879–891 (2000)
Worobey, M.: A novel approach to detecting and measuring recombination: new insights into evolution in viruses, bacteria, and mitochondria. Molecular Biology and Evolution 18, 1425–1434 (2001)
Posada, D., Crandall, K.A.: Evaluation of methods for detecting recombination from DNA sequences: computer simulations. Proc. Natl. Acad. Sci. USA 98(24), 13757–13762 (2001)
Wiuf, C., Christensen, T., Hein, J.: A simulation study of the reliability of recombination detection methods. Molecular Biology and Evolution 18, 1929–1939 (2001)
Martin, D.P., et al.: A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints. AIDS Research and Human Retroviruses 21, 98–102 (2005)
Lole, K.S., et al.: Full-length human immunodeficiency virus type 1 genomes from subtype C-infected seroconverters in India, with evidence of intersubtype recombination. Journal of Virology 73(1), 152–160 (1999)
Strimmer, K., et al.: A novel exploratory method for visual recombination detection. Genome Biology 4(5) (2003)
Martin, D.P., Williamson, C., Posada, D.: RDP2: recombination detection and analysis from sequence alignments. Bioinformatics 21(2), 260–262 (2005)
Tsaousis, A.D., et al.: Widespread recombination in published animal mtDNA sequences. Molecular Biology and Evolution 22(4), 925–933 (2005)
Buendia, P., Narasimhan, G.: Serial NetEvolve: A flexible utility for generating serially-sampled sequences along a tree or recombinant network. Bioinformatics 22(18), 2313–2314 (2006)
Salminen, M., et al.: Identification of recombination breakpoints in HIV-1 by bootscanning. AIDS Research and Human Retroviruses 11, 1423–1425 (1995)
Siepel, A., Korber, B.: Scanning the Database for Recombinant HIV-1 Genomes. In: Human Retroviruses and AIDS Compendium Part III, pp. 35–60 (1995)
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Buendia, P., Narasimhan, G. (2007). Searching for Recombinant Donors in a Phylogenetic Network of Serial Samples. In: Măndoiu, I., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2007. Lecture Notes in Computer Science(), vol 4463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72031-7_10
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DOI: https://doi.org/10.1007/978-3-540-72031-7_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72030-0
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