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Subsequence-Based Indices for Genome Sequence Analysis

Authors Giovanni Buzzega , Alessio Conte , Veronica Guerrini , Giulia Punzi , Giovanna Rosone , Lorenzo Tattini

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Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
  • Theory of computation → Data structures design and analysis
Keywords
  • String Indices
  • Burrows-Wheeler Transform
  • Maximal Common Subsequences
  • Sequence Analysis
  • Phylogeny

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Abstract

Compact indices are a fundamental tool in string analysis, even more so in bioinformatics, where genomic sequences can reach billions in length. This paper presents some recent results in which Roberto Grossi has been involved, showing how some of these indices do more than just efficiently represent data, but rather are able to bring out salient information within it, which can be exploited for their downstream analysis. Specifically, we first review a recently-introduced method [Guerrini et al., 2023] that employs the Burrows-Wheeler Transform to build reasonably accurate phylogenetic trees in an assembly-free scenario. We then describe a recent practical tool [Buzzega et al., 2025] for indexing Maximal Common Subsequences between strings, which can enable analysis of genomic sequence similarity. Experimentally, we show that the results produced by the one index are consistent with the expectations about the results of the other index.

Cite As Get BibTex

Giovanni Buzzega, Alessio Conte, Veronica Guerrini, Giulia Punzi, Giovanna Rosone, and Lorenzo Tattini. Subsequence-Based Indices for Genome Sequence Analysis. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 20:1-20:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.Grossi.20

Author Details

Giovanni Buzzega
  • Department of Computer Science, University of Pisa, Italy
Alessio Conte
  • Department of Computer Science, University of Pisa, Italy
Veronica Guerrini
  • Department of Computer Science, University of Pisa, Italy
Giulia Punzi
  • Department of Computer Science, University of Pisa, Italy
Giovanna Rosone
  • Department of Computer Science, University of Pisa, Italy
Lorenzo Tattini
  • EURECOM, Biot, France
  • CNRS UMR 7284, INSERM U 1081, Université Côte d'Azur, Nice, France

Funding

  • Buzzega, Giovanni: Partially supported by MUR PRIN 2022 project EXPAND: scalable algorithms for EXPloratory Analyses of heterogeneous and dynamic Networked Data (#2022TS4Y3N), and received funding from the European Union’s Horizon 2020 Research and Innovation Staff Exchange programme under the Marie Skłodowska-Curie grant agreement No. 872539.
  • Conte, Alessio: Partially supported by MUR PRIN 2022 project EXPAND: scalable algorithms for EXPloratory Analyses of heterogeneous and dynamic Networked Data (#2022TS4Y3N).
  • Guerrini, Veronica: Supported by the Next Generation EU PNRR MUR M4 C2 Inv 1.5 project ECS00000017 Tuscany Health Ecosystem Spoke 6 CUP B63C2200068007 and I53C22000780001.
  • Punzi, Giulia: Supported by the Italian Ministry of Research, under the complementary actions to the NRRP "Fit4MedRob - Fit for Medical Robotics" Grant (#PNC0000007), and received funding from the European Union’s Horizon 2020 Research and Innovation Staff Exchange programme under the Marie Skłodowska-Curie grant agreement No. 872539.
  • Rosone, Giovanna: Partially supported by the Next Generation EU PNRR MUR M4 C2 Inv 1.5 project ECS00000017 Tuscany Health Ecosystem Spoke 6 CUP B63C2200068007 and I53C22000780001, and by project “Hub multidisciplinare e interregionale di ricerca e sperimentazione clinica per il contrasto alle pandemie e all’antibioticoresistenza (PAN-HUB)” funded by the Italian Ministry of Health (POS 2014–2020, project ID: T4-AN-07, CUP: I53C22001300001).

Supplementary Materials

References

  1. Amir Abboud, Arturs Backurs, and Virginia Vassilevska Williams. Tight hardness results for LCS and other sequence similarity measures. In Venkatesan Guruswami, editor, IEEE 56th Annual Symposium on Foundations of Computer Science, FOCS 2015, Berkeley, CA, USA, 17-20 October, 2015, pages 59-78. IEEE, IEEE Computer Society, 2015. URL: https://doi.org/10.1109/FOCS.2015.14.
  2. M. I. Abouelhoda, S. Kurtz, and E. Ohlebusch. Replacing suffix trees with enhanced suffix arrays. Journal of Discrete Algorithms, 2(1):53-86, 2004. URL: https://doi.org/10.1016/S1570-8667(03)00065-0.
  3. Rakesh Agrawal and Ramakrishnan Srikant. Mining sequential patterns. In Proceedings of the eleventh international conference on data engineering, pages 3-14. IEEE, 1995. URL: https://doi.org/10.1109/ICDE.1995.380415.
  4. H.-J. Bandelt and A. W. M. Dress. A canonical decomposition theory for metrics on a finite set. Advances in mathematics, 92(1):47-105, 1992. Google Scholar
  5. H.-J. Bandelt and A. W. M. Dress. Split decomposition: A new and useful approach to phylogenetic analysis of distance data. Molecular Phylogenetics and Evolution, 1(3):242-252, 1992. URL: https://doi.org/10.1016/1055-7903(92)90021-8.
  6. H.-J. Bandelt, K. T. Huber, J. H. Koolen, V. Moulton, and A. Spillner. Basic Phylogenetic Combinatorics. Cambridge University Press, 2012. URL: http://www.cambridge.org/de/knowledge/isbn/item6439332/.
  7. M.J. Bauer, A.J. Cox, and G. Rosone. Lightweight algorithms for constructing and inverting the BWT of string collections. Theor. Comput. Sci., 483(0):134-148, 2013. URL: https://doi.org/10.1016/j.tcs.2012.02.002.
  8. Lasse Bergroth, Harri Hakonen, and Timo Raita. A survey of longest common subsequence algorithms. In Proceedings Seventh International Symposium on String Processing and Information Retrieval. SPIRE 2000, pages 39-48. IEEE, 2000. URL: https://doi.org/10.1109/SPIRE.2000.878178.
  9. Karl Bringmann and Marvin Künnemann. Quadratic conditional lower bounds for string problems and dynamic time warping. In Proceedings of the 56th Annual IEEE Symposium on Foundations of Computer Science (FOCS), pages 79-97. IEEE, 2015. URL: https://doi.org/10.1109/FOCS.2015.15.
  10. Laurent Bulteau, Mark Jones, Rolf Niedermeier, and Till Tantau. An FPT-algorithm for longest common subsequence parameterized by the maximum number of deletions. In Hideo Bannai and Jan Holub, editors, 33rd Annual Symposium on Combinatorial Pattern Matching, CPM 2022, June 27-29, 2022, Prague, Czech Republic, volume 223 of LIPIcs, pages 6:1-6:11. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. URL: https://doi.org/10.4230/LIPIcs.CPM.2022.6.
  11. M. Burrows and D.J. Wheeler. A Block Sorting data Compression Algorithm. Technical report, DIGITAL System Research Center, 1994. Google Scholar
  12. Giovanni Buzzega, Alessio Conte, Roberto Grossi, and Giulia Punzi. Mcdag: Indexing maximal common subsequences in practice. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024), pages 21-1. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024. Google Scholar
  13. Giovanni Buzzega, Alessio Conte, Roberto Grossi, and Giulia Punzi. McDag: indexing maximal common subsequences for k strings. Algorithms for Molecular Biology, 20(1):6, 2025. URL: https://doi.org/10.1186/s13015-025-00271-z.
  14. Giovanni Buzzega, Alessio Conte, Yasuaki Kobayashi, Kazuhiro Kurita, and Giulia Punzi. The complexity of maximal common subsequence enumeration. Proc. ACM Manag. Data, to appear, 2025. Google Scholar
  15. Davide Cenzato, Zsuzsanna Lipták, Nadia Pisanti, Giovanna Rosone, and Marinella Sciortino. BWT for string collections. Accepted to Festschrift’s honoree Giovanni Manzini, 2025. URL: https://arxiv.org/abs/2506.01092.
  16. Alessio Conte, Roberto Grossi, Giulia Punzi, and Takeaki Uno. Polynomial-delay enumeration of maximal common subsequences. In Nieves R. Brisaboa and Simon J. Puglisi, editors, String Processing and Information Retrieval, pages 189-202, Cham, 2019. Springer International Publishing. URL: https://doi.org/10.1007/978-3-030-32686-9_14.
  17. Alessio Conte, Roberto Grossi, Giulia Punzi, and Takeaki Uno. Enumeration of maximal common subsequences between two strings. Algorithmica, 84(3):757-783, 2022. URL: https://doi.org/10.1007/s00453-021-00898-5.
  18. Alessio Conte, Roberto Grossi, Giulia Punzi, and Takeaki Uno. A compact DAG for storing and searching maximal common subsequences. In Satoru Iwata and Naonori Kakimura, editors, 34th International Symposium on Algorithms and Computation, ISAAC 2023, December 3-6, 2023, Kyoto, Japan, volume 283 of LIPIcs, pages 21:1-21:15. Schloss-Dagstuhl-Leibniz Zentrum für Informatik, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. URL: https://doi.org/10.4230/LIPIcs.ISAAC.2023.21.
  19. Maxime Crochemore, Borivoj Melichar, and Zdenek Tronícek. Directed acyclic subsequence graph - overview. J. Discrete Algorithms, 1(3-4):255-280, 2003. URL: https://doi.org/10.1016/S1570-8667(03)00029-7.
  20. Maxime Crochemore and Zdeněk Troníček. Directed acyclic subsequence graph for multiple texts. Rapport IGM, pages 99-13, 1999. Google Scholar
  21. L. Egidi, F. A. Louza, G. Manzini, and G. P. Telles. External memory BWT and LCP computation for sequence collections with applications. Algorithms for Molecular Biology, 14(1):6:1-6:15, 2019. URL: https://doi.org/10.1186/s13015-019-0140-0.
  22. Campbell Fraser, Robert W. Irving, and Martin Middendorf. Maximal common subsequences and minimal common supersequences. Inf. Comput., 124(2):145-153, 1996. URL: https://doi.org/10.1006/inco.1996.0011.
  23. Stephen K. Gire, Augustine Goba, Kristian G. Andersen, Rachel S. G. Sealfon, Daniel J. Park, Lansana Kanneh, Simbirie Jalloh, Mambu Momoh, Mohamed Fullah, Gytis Dudas, Shirlee Wohl, Lina M. Moses, Nathan L. Yozwiak, Sarah Winnicki, Christian B. Matranga, Christine M. Malboeuf, James Qu, Adrianne D. Gladden, Stephen F. Schaffner, Xiao Yang, Pan-Pan Jiang, Mahan Nekoui, Andres Colubri, Moinya Ruth Coomber, Mbalu Fonnie, Alex Moigboi, Michael Gbakie, Fatima K. Kamara, Veronica Tucker, Edwin Konuwa, Sidiki Saffa, Josephine Sellu, Abdul Azziz Jalloh, Alice Kovoma, James Koninga, Ibrahim Mustapha, Kandeh Kargbo, Momoh Foday, Mohamed Yillah, Franklyn Kanneh, Willie Robert, James L. B. Massally, Sinéad B. Chapman, James Bochicchio, Cheryl Murphy, Chad Nusbaum, Sarah Young, Bruce W. Birren, Donald S. Grant, John S. Scheiffelin, Eric S. Lander, Christian Happi, Sahr M. Gevao, Andreas Gnirke, Andrew Rambaut, Robert F. Garry, S. Humarr Khan, and Pardis C. Sabeti. Genomic surveillance elucidates ebola virus origin and transmission during the 2014 outbreak. Science, 345(6202):1369-1372, 2014. URL: https://doi.org/10.1126/science.1259657.
  24. Ronald I. Greenberg. Bounds on the number of longest common subsequences. CoRR, cs.DM/0301030, 2003. URL: https://arxiv.org/abs/cs/0301030.
  25. Veronica Guerrini, Alessio Conte, Roberto Grossi, Gianni Liti, Giovanna Rosone, and Lorenzo Tattini. phyBWT: Alignment-Free Phylogeny via eBWT Positional Clustering. In Christina Boucher and Sven Rahmann, editors, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022), volume 242 of LIPIcs, pages 23:1-23:19, Dagstuhl, Germany, 2022. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/LIPIcs.WABI.2022.23.
  26. Veronica Guerrini, Alessio Conte, Roberto Grossi, Gianni Liti, Giovanna Rosone, and Lorenzo Tattini. phyBWT2: phylogeny reconstruction via eBWT positional clustering. Algorithms Mol. Biol., 18(1):11, 2023. URL: https://doi.org/10.1186/S13015-023-00232-4.
  27. Miyuji Hirota and Yoshifumi Sakai. Efficient algorithms for enumerating maximal common subsequences of two strings. CoRR, abs/2307.10552, 2023. URL: https://doi.org/10.48550/arXiv.2307.10552.
  28. Miyuji Hirota and Yoshifumi Sakai. A fast algorithm for finding a maximal common subsequence of multiple strings. IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 106(9):1191-1194, 2023. URL: https://doi.org/10.1587/transfun.2022dml0002.
  29. D. H. Huson and D. Bryant. Application of Phylogenetic Networks in Evolutionary Studies. Molecular Biology and Evolution, 23(2):254-267, October 2005. Google Scholar
  30. Michelle Kendall and Caroline Colijn. Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution. Molecular Biology and Evolution, 33(10):2735-2743, 2016. URL: https://doi.org/10.1093/molbev/msw124.
  31. Thomas Leitner, Bette Korber, Marcus Daniels, Charles Calef, and Brian Foley. HIV-1 Subtype and Circulating Recombinant Form (CRF) Reference Sequences, 2005. URL: https://www.hiv.lanl.gov/content/sequence/HIV/REVIEWS/LEITNER2005/leitner.html.
  32. Heng Li and Richard Durbin. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics, 26(5):589-595, 2010. URL: https://doi.org/10.1093/bioinformatics/btp698.
  33. David Maier. The complexity of some problems on subsequences and supersequences. Journal of the ACM (JACM), 25(2):322-336, 1978. URL: https://doi.org/10.1145/322063.322075.
  34. Udi Manber and Gene Myers. Suffix arrays: A new method for on-line string searches. In ACM-SIAM SODA, pages 319-327, 1990. URL: http://dl.acm.org/citation.cfm?id=320176.320218.
  35. S. Mantaci, A. Restivo, G. Rosone, and M. Sciortino. An extension of the Burrows-Wheeler Transform. Theoret. Comput. Sci., 387(3):298-312, 2007. URL: https://doi.org/10.1016/J.TCS.2007.07.014.
  36. Mike Paterson and Vlado Dančík. Longest common subsequences. In International symposium on mathematical foundations of computer science, pages 127-142. Springer, 1994. Google Scholar
  37. N. Prezza, N. Pisanti, M. Sciortino, and G. Rosone. Variable-order reference-free variant discovery with the Burrows-Wheeler transform. BMC Bioinformatics, 21, 2020. URL: https://doi.org/10.1186/s12859-020-03586-3.
  38. Dominique Revuz. Minimisation of acyclic deterministic automata in linear time. Theoretical Computer Science, 92(1):181-189, 1992. URL: https://doi.org/10.1016/0304-3975(92)90142-3.
  39. Yoshifumi Sakai. Maximal Common Subsequence Algorithms. In Gonzalo Navarro, David Sankoff, and Binhai Zhu, editors, 29th Annual Symposium on Combinatorial Pattern Matching (CPM 2018), volume 105 of Leibniz International Proceedings in Informatics (LIPIcs), pages 1:1-1:10, Dagstuhl, Germany, 2018. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/LIPIcs.CPM.2018.1.
  40. Yoshifumi Sakai. Maximal common subsequence algorithms. Theor. Comput. Sci., 793:132-139, 2019. URL: https://doi.org/10.1016/j.tcs.2019.06.020.
  41. Temple F Smith, Michael S Waterman, et al. Identification of common molecular subsequences. Journal of molecular biology, 147(1):195-197, 1981. Google Scholar
  42. Zdenek Tronícek. Common subsequence automaton. In Jean-Marc Champarnaud and Denis Maurel, editors, Implementation and Application of Automata, 7th International Conference, CIAA 2002, Tours, France, July 3-5, 2002, Revised Papers, volume 2608 of Lecture Notes in Computer Science, pages 270-275. Springer, Springer, 2002. URL: https://doi.org/10.1007/3-540-44977-9_28.
  43. Tandy Warnow. Computational Phylogenetics: An Introduction to Designing Methods for Phylogeny Estimation. Cambridge University Press, 2017. Google Scholar
  44. R. Wittler. Alignment- and Reference-Free Phylogenomics with Colored de Bruijn Graphs. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019), volume 143, pages 2:1-2:14, Dagstuhl, Germany, 2019. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/LIPIcs.WABI.2019.2.
  45. Xiaomeng Wu, Zhipeng Cai, Xiu-Feng Wan, Tin Hoang, Randy Goebel, and Guohui Lin. Nucleotide composition string selection in HIV-1 subtyping using whole genomes. Bioinformatics, 23(14):1744-1752, May 2007. URL: https://doi.org/10.1093/bioinformatics/btm248.
  46. Andrzej Zielezinski, Hani Z Girgis, Guillaume Bernard, Chris-Andre Leimeister, Kujin Tang, Thomas Dencker, Anna Katharina Lau, Sophie Röhling, Jae Jin Choi, Michael S Waterman, Matteo Comin, Sung-Hou Kim, Susana Vinga, Jonas S Almeida, Cheong Xin Chan, Benjamin T James, Fengzhu Sun, Burkhard Morgenstern, and Wojciech M Karlowski. Benchmarking of alignment-free sequence comparison methods. Genome Biology, 20:144, 2019. URL: https://doi.org/10.1186/s13059-019-1755-7.
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