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UniAligner: a parameter-free framework for fast sequence alignment

Nature Methods volume 20, pages 1346–1354 (2023)Cite this article

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Abstract

Even though the recent advances in ‘complete genomics’ revealed the previously inaccessible genomic regions, analysis of variations in centromeres and other extra-long tandem repeats (ETRs) faces an algorithmic challenge since there are currently no tools for accurate sequence comparison of ETRs. Counterintuitively, the classical alignment approaches, such as the Smith–Waterman algorithm, fail to construct biologically adequate alignments of ETRs. We present UniAligner—the parameter-free sequence alignment algorithm with sequence-dependent alignment scoring that automatically changes for any pair of compared sequences. UniAligner prioritizes matches of rare substrings that are more likely to be relevant to the evolutionary relationship between two sequences. We apply UniAligner to estimate the mutation rates in human centromeres, and quantify the extremely high rate of large duplications and deletions in centromeres. This high rate suggests that centromeres may represent some of the most rapidly evolving regions of the human genome with respect to their structural organization.

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Fig. 1: Aligning four-unit extra-long tandem repeats S = CCCAACCAACAAACCC and T = CCCAACAAACCAACCC using UniAligner.
Fig. 2: The architecture of the centromere on chromosome X.
Fig. 3: The highest-scoring alignment paths between centromeres cenX1 and cenX2 and strings Template-3 and Template-8 constructed by the standard alignment algorithm and by UniAligner.
Fig. 4: Dot plots DotPlotk,MaxCount(Template-3, Template-8) and DotPlotk,MaxCount(cenX1, cenX2) for various values of parameters k and MaxCount.
Fig. 5: Various dot plots for cenX1 and cenX2.
Fig. 6: The histogram of lengths of insertion-runs and deletion-runs in the rare-alignment of cenX1 and cenX2 and distribution of HOR indels in this alignment along the entire length of cenX1.

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Data availability

We used the T2T assembly v2.0 of the CHM13 genome (available from https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/analysis_set/chm13v2.0.fa.gz); heavy immunoglobulin locus of human (IGHDH; NC_000014.9: 105,865,737–105,964,717) and of orangutan (NC_036917.1: 87,805,787–87,899,312); HG002 v0.7 assembly (publicly available at https://github.com/marbl/hg002). The test launch command on a small test dataset is available in the ‘Makefile’. Alignment of cenX1 and cenX2 generated by UniAligner is located at Zenodo69.

Code availability

The codebase of UniAligner is available at https://github.com/seryrzu/tandem_aligner.

The source code of version 0.1 that was used in this study is available at Zenodo69.

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Acknowledgements

We are indebted to K. Miga and M. Cechova for providing early pedigree centromere assemblies. We are grateful to I. Alexadrov, A. Bankevich, A.V. Bzikadze, R. Chikhi, T. Dvorkina, E. Eichler, G. Logsdon, O. Kunyavskaya and C. Wu for helpful discussions and suggestions. A.V.B. and P.A.P. were supported by the National Science Foundation EAGER award 2032783.

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Authors and Affiliations

  1. Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA

    Andrey V. Bzikadze

  2. Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA

    Pavel A. Pevzner

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Contributions

A.V.B. conducted the experiments and wrote the code for UniAligner. P.A.P. supervised the research. All authors worked on the development of the UniAligner algorithm and wrote and edited the manuscript.

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Correspondence to Pavel A. Pevzner.

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Nature Methods thanks Jue Ruan, Chengzhi Liang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Lei Tang and Lin Tang, in collaboration with the Nature Methods team.

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Bzikadze, A.V., Pevzner, P.A. UniAligner: a parameter-free framework for fast sequence alignment. Nat Methods 20, 1346–1354 (2023). https://doi.org/10.1038/s41592-023-01970-4

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