Reconciliation with Segmental Duplication, Transfer, Loss and Gain

Yoann Anselmetti, Mattéo Delabre, Nadia El-Mabrouk

Abstract: We generalize the reconciliation approach, used for inferring the evolution of a single gene family given a species tree, to groups of co-localized genes, also called syntenies. More precisely, given a set \({\mathcal X}\) of syntenies in a set \(\varSigma \) of genomes, a tree T for \({\mathcal X}\) and a tree S for \(\varSigma \), the problem is to find a most parsimonious history for \({\mathcal X}\) with respect to a given evolutionary model. We extend a previous model involving segmental duplications and losses, to also include segmental horizontal gene transfers (HGTs) and gene gains. We present a polynomial-time dynamic programming algorithm to solve the problem. We apply it to CRISPR-associated (Cas) gene syntenies. These genes are part of CRISPR-Cas systems, one of its members (CRISPR-Cas9) well-known as currently the most reliable and accurate molecular scissor technology for genome editing. The inferred evolutionary scenario is a plausible explanation of the diversification of this system into its different types. An implementation of the algorithm presented in this paper is available at: https://github.com/UdeM-LBIT/superrec2/releases/tag/rcg2022.