A Maximum Parsimony Principle for Multichromosomal Complex Genome Rearrangements

Authors Pijus Simonaitis , Benjamin J. Raphael

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Pijus Simonaitis
  • Department of Computer Science, Princeton University, Princeton, NJ, USA
Benjamin J. Raphael
  • Department of Computer Science, Princeton University, Princeton, NJ, USA

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Pijus Simonaitis and Benjamin J. Raphael. A Maximum Parsimony Principle for Multichromosomal Complex Genome Rearrangements. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 21:1-21:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


Motivation. Complex genome rearrangements, such as chromothripsis and chromoplexy, are common in cancer and have also been reported in individuals with various developmental and neurological disorders. These mutations are proposed to involve simultaneous breakage of the genome at many loci and rejoining of these breaks that produce highly rearranged genomes. Since genome sequencing measures only the novel adjacencies present at the time of sequencing, determining whether a collection of novel adjacencies resulted from a complex rearrangement is a complicated and ill-posed problem. Current heuristics for this problem often result in the inference of complex rearrangements that affect many chromosomes. Results. We introduce a model for complex rearrangements that builds upon the methods developed for analyzing simple genome rearrangements such as inversions and translocations. While nearly all of these existing methods use a maximum parsimony assumption of minimizing the number of rearrangements, we propose an alternative maximum parsimony principle based on minimizing the number of chromosomes involved in a rearrangement scenario. We show that our model leads to inference of more plausible sequences of rearrangements that better explain a complex congenital rearrangement in a human genome and chromothripsis events in 22 cancer genomes.

Subject Classification

ACM Subject Classification
  • Applied computing → Bioinformatics
  • Genome rearrangements
  • maximum parsimony
  • cancer evolution
  • chromothripsis
  • structural variation
  • affected chromosomes


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