Models and algorithms for genome rearrangement with positional constraints

Abstract : Background Traditionally, the merit of a rearrangement scenario between two gene orders has been measured based on a parsimony criteria alone; two scenarios with the same number of rearrangements are considered equally good. In this paper, we acknowledge that each rearrangement has a certain likelihood of occurring based on biological constraints, e.g. physical proximity of the DNA segments implicated or repetitive sequences. Results We propose optimization problems with the objective of maximizing overall likelihood, by weighting the rearrangements. We study a binary weight function suitable to the representation of sets of genome positions that are most likely to have swapped adjacencies. We give a polynomial-time algorithm for the problem of finding a minimum weight double cut and join scenario among all minimum length scenarios. In the process we solve an optimization problem on colored noncrossing partitions, which is a generalization of the Maximum Independent Set problem on circle graphs. Conclusions We introduce a model for weighting genome rearrangements and show that under simple yet reasonable conditions, a fundamental distance can be computed in polynomial time. This is achieved by solving a generalization of the Maximum Independent Set problem on circle graphs. Several variants of the problem are also mentioned.
Document type :
Journal articles
Complete list of metadatas

https://hal-lirmm.ccsd.cnrs.fr/lirmm-01348502
Contributor : Isabelle Gouat <>
Submitted on : Monday, July 25, 2016 - 6:54:40 AM
Last modification on : Tuesday, November 19, 2019 - 12:55:14 PM

Links full text

Identifiers

Collections

Citation

Krister Swenson, Pijus Simonaitis, Mathieu Blanchette. Models and algorithms for genome rearrangement with positional constraints. Algorithms for Molecular Biology, BioMed Central, 2016, 11 (1), ⟨10.1186/s13015-016-0065-9⟩. ⟨lirmm-01348502⟩

Share

Metrics

Record views

348