Abstract
The improvements in DNA sequence technologies have increased the volume and speed at which genomic data is acquired. Nevertheless, due to the difficulties for completely assembling a genome, many genomes are left in a draft state, in which each chromosome is represented by a set of sequences with partial information on their relative order. Recently, some approaches have been proposed to compare genomes by comparing extracted paths from de Bruijn graphs and comparing such paths. The idea of using data from de Bruijn graphs is interesting because such graphs are built by many practical genome assemblers. In this article we introduce gcBB, a method for comparing genomes represented as succinct de Bruijn graphs directly, without resorting to sequence alignments, by means of the entropy and expectation measures based on the Burrows-Wheeler Similarity Distribution (BWSD). We have compared phylogenies of genomes obtained by other methods to those obtained with gcBB, achieving promising results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Boc, A., Diallo, A.B., Makarenkov, V.: T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks. Nucleic Acids Res. 40(W1), W573–W579 (2012)
Bowe, A., Onodera, T., Sadakane, K., Shibuya, T.: Succinct de Bruijn graphs. In: Raphael, B., Tang, J. (eds.) WABI 2012. LNCS, vol. 7534, pp. 225–235. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33122-0_18
Burrows, M., Wheeler, D.J.: A block-sorting lossless data compression algorithm. Technical report. 124, Systems Research Center (1994)
De Bruijn, N.G.: A combinatorial problem. In: Proceedings of the Koninklijke Nederlandse Academie van Wetenschappen, vol. 49, pp. 758–764 (1946)
Egidi, L., Louza, F.A., Manzini, G., Telles, G.P.: External memory BWT and LCP computation for sequence collections with applications. Algorithms Mol. Biol. 14(1), 1–15 (2019)
Hahn, M.W., Han, M.V., Han, S.G.: Gene family evolution across 12 drosophila genomes. PLoS Genet. 3(11), e197 (2007)
Kolmogorov, M., et al.: metaFlye: scalable long-read metagenome assembly using repeat graphs. Nat. Methods 17(11), 1103–1110 (2020)
Langmead, B., Salzberg, S.L.: Fast gapped-read alignment with Bowtie 2. Nat. Methods 9(4), 357 (2012)
Li, H., Durbin, R.: Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14), 1754–1760 (2009)
Lyman, C.A., et al.: Whole genome phylogenetic tree reconstruction using colored de Bruijn graphs. In: 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE), pp. 260–265. IEEE (2017)
Manber, U., Myers, G.: Suffix arrays: a new method for on-line string searches. SIAM J. Comput. 22(5), 935–948 (1993)
Mantaci, S., Restivo, A., Rosone, G., Sciortino, M.: An extension of the Burrows-Wheeler transform. Theor. Comput. Sci. 387(3), 298–312 (2007)
Mantaci, S., Restivo, A., Sciortino, M.: Distance measures for biological sequences: some recent approaches. Int. J. Approximate Reasoning 47(1), 109–124 (2008)
Navarro, G.: Compact Data Structures: A Practical Approach. Cambridge University Press, Cambridge (2016)
Polevikov, E., Kolmogorov, M.: Synteny paths for assembly graphs comparison. In: 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2019)
Rice, E.S., Green, R.E.: New approaches for genome assembly and scaffolding. Ann. Rev. Animal Biosci. 7(1), 17–40 (2019)
Rizzi, R., et al.: Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era. Quant. Biol. 7(4), 278–292 (2019)
Robinson, D.F., Foulds, L.R.: Comparison of phylogenetic trees. Math. Biosci. 53(1–2), 131–147 (1981)
Saitou, N., Nei, M.: The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4(4), 406–425 (1987)
Simpson, J.T., Durbin, R.: Efficient de novo assembly of large genomes using compressed data structures. Genome Res. 22(3), 549–556 (2012)
Thurmond, J., et al.: FlyBase 2.0: the next generation. Nucleic Acids Res. 47(D1), D759–D765 (2018)
Yang, L., Zhang, X., Wang, T.: The Burrows-Wheeler similarity distribution between biological sequences based on Burrows-Wheeler transform. J. Theor. Biol. 262(4), 742–749 (2010)
Acknowledgements
The authors thank Prof. Marinella Sciortino for helpful discussions and thank Prof. Nalvo Almeida for granting access to the computer used in the experiments.
Funding
L.P.R. acknowledges that this study was financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazil, Financing Code 001. F.A.L. acknowledges the financial support from CNPq (grant number 406418/2021-7) and FAPEMIG (grant number APQ-01217-22). G.P.T. acknowledges the financial support of Brazilian agencies CNPq and CAPES.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ramos, L.P., Louza, F.A., Telles, G.P. (2022). Genome Comparison on Succinct Colored de Bruijn Graphs. In: Arroyuelo, D., Poblete, B. (eds) String Processing and Information Retrieval. SPIRE 2022. Lecture Notes in Computer Science, vol 13617. Springer, Cham. https://doi.org/10.1007/978-3-031-20643-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-031-20643-6_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-20642-9
Online ISBN: 978-3-031-20643-6
eBook Packages: Computer ScienceComputer Science (R0)