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Constructing Founder Sets Under Allelic and Non-Allelic Homologous Recombination

Authors Konstantinn Bonnet, Tobias Marschall , Daniel Doerr¹

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ACM Subject Classification
  • Applied computing → Bioinformatics
Keywords
  • founder set reconstruction
  • variation graph
  • pangenomics
  • NAHR
  • homologous recombination

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Abstract

Homologous recombination between the maternal and paternal copies of a chromosome is a key mechanism for human inheritance and shapes population genetic properties of our species. However, a similar mechanism can also act between different copies of the same sequence, then called non-allelic homologous recombination (NAHR). This process can result in genomic rearrangements - including deletion, duplication, and inversion - and is underlying many genomic disorders. Despite its importance for genome evolution and disease, there is a lack of computational models to study genomic loci prone to NAHR.
In this work, we propose such a computational model, providing a unified framework for both (allelic) homologous recombination and NAHR. Our model represents a set of genomes as a graph, where human haplotypes correspond to walks through this graph. We formulate two founder set problems under our recombination model, provide flow-based algorithms for their solution, and demonstrate scalability to problem instances arising in practice.

Cite As Get BibTex

Konstantinn Bonnet, Tobias Marschall, and Daniel Doerr¹. Constructing Founder Sets Under Allelic and Non-Allelic Homologous Recombination. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 6:1-6:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.WABI.2022.6

Author Details

Konstantinn Bonnet
  • Institute for Medical Biometry and Bioinformatics, Heinrich Heine University, Düsseldorf, Germany
Tobias Marschall
  • Institute for Medical Biometry and Bioinformatics, Heinrich Heine University, Düsseldorf, Germany
Daniel Doerr¹
  • Institute for Medical Biometry and Bioinformatics, Heinrich Heine University, Düsseldorf, Germany

Funding

This work was supported in part by the National Institutes of Health grant 1U01HG010973 to T.M., by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 956229, and by the BMBF-funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) (031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D, 031A538A).

Acknowledgements

The authors kindly thank Feyza Yilmaz for providing the haplotype data of the 1p36.13 locus.

Supplementary Materials

References

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