On the ability to reconstruct ancestral genomes from Mycobacterium genus

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Abstract

Technical signs of progress during the last decades has led to a situation in which the accumulation of genome sequence data is increasingly fast and cheap. The huge amount of molecular data available nowadays can help addressing new and essential questions in Evolution. However, reconstructing evolution of DNA sequences requires models, algorithms, statistical and computational methods of ever increasing complexity. Since most dramatic genomic changes are caused by genome rearrangements (gene duplications, gain/loss events), it becomes crucial to understand their mechanisms and reconstruct ancestors of the given genomes. This problem is known to be NP-complete even in the “simplest” case of three genomes. Heuristic algorithms are usually executed to provide approximations of the exact solution. We state that, even if the ancestral reconstruction problem is NP-hard in theory, its exact resolution is feasible in various situations, encompassing organelles and some bacteria. Such accurate reconstruction, which identifies too some highly homoplasic mutations whose ancestral status is undecidable, will be initiated in this work-in-progress, to reconstruct ancestral genomes of two Mycobacterium pathogenetic bacterias. By mixing automatic reconstruction of obvious situations with human interventions on signaled problematic cases, we will indicate that it should be possible to achieve a concrete, complete, and really accurate reconstruction of lineages of the Mycobacterium tuberculosis complex. Thus, it is possible to investigate how these genomes have evolved from their last common ancestors.

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Guyeux, C., Al-Nuaimi, B., AlKindy, B., Couchot, J. F., & Salomon, M. (2017). On the ability to reconstruct ancestral genomes from Mycobacterium genus. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10208 LNCS, pp. 642–658). Springer Verlag. https://doi.org/10.1007/978-3-319-56148-6_57

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