Mapping ancestral genomes with massive gene loss: a matrix sandwich problem.

Haris Gavranović 1 Cedric Chauve 2 Jérôme Salse 3 Eric Tannier 4, 5, *
* Corresponding author
4 BEAGLE - Artificial Evolution and Computational Biology
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information, Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : MOTIVATION: Ancestral genomes provide a better way to understand the structural evolution of genomes than the simple comparison of extant genomes. Most ancestral genome reconstruction methods rely on universal markers, that is, homologous families of DNA segments present in exactly one exemplar in every considered species. Complex histories of genes or other markers, undergoing duplications and losses, are rarely taken into account. It follows that some ancestors are inaccessible by these methods, such as the proto-monocotyledon whose evolution involved massive gene loss following a whole genome duplication. RESULTS: We propose a mapping approach based on the combinatorial notion of 'sandwich consecutive ones matrix', which explicitly takes gene losses into account. We introduce combinatorial optimization problems related to this concept, and propose a heuristic solver and a lower bound on the optimal solution. We use these results to propose a configuration for the proto-chromosomes of the monocot ancestor, and study the accuracy of this configuration. We also use our method to reconstruct the ancestral boreoeutherian genomes, which illustrates that the framework we propose is not specific to plant paleogenomics but is adapted to reconstruct any ancestral genome from extant genomes with heterogeneous marker content. AVAILABILITY: Upon request to the authors. CONTACT: haris.gavranovic@gmail.com; eric.tannier@inria.fr.
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Haris Gavranović, Cedric Chauve, Jérôme Salse, Eric Tannier. Mapping ancestral genomes with massive gene loss: a matrix sandwich problem.. Bioinformatics, Oxford University Press (OUP), 2011, 27 (13), pp.i257-65. ⟨10.1093/bioinformatics/btr224⟩. ⟨hal-00680540⟩

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