@article {Menet2022.07.01.498457, author = {Hugo Menet and Alexia Nguyen Trung and Vincent Daubin and Eric Tannier}, title = {Host-symbiont-gene phylogenetic reconciliation}, elocation-id = {2022.07.01.498457}, year = {2022}, doi = {10.1101/2022.07.01.498457}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Motivation Biological systems are made of entities organized at different scales (e.g. macro-organisms, symbionts, genes{\textellipsis}) which evolve in interaction. These interactions range from independence or conflict to cooperation and coevolution, which results in them having a common history. The evolution of such systems is approached by phylogenetic reconciliation, which describes the coevolution of two different levels, genes and species, or hosts and symbionts for example. The limit to two levels hides the multi-level inter-dependencies that characterize complex systems.Results We present a probabilistic model of evolution of three nested levels of organization which can account for the coevolution of hosts, symbionts and their genes. This model allows gene transfer as well as host switch, gene duplication as well as symbiont diversification inside a host, gene or symbiont loss. It handles the possibility of ghost lineages as well as temporary free-living symbionts.Given three phylogenetic trees, we devise a Monte Carlo algorithm which samples evolutionary scenarios of symbionts and genes according to an approximation of their likelihood in the model. We evaluate the capacity of our method on simulated data, notably its capacity to infer horizontal gene transfers, and its ability to detect host-symbiont co-evolution by comparing host/symbiont/gene and symbiont/gene models based on their estimated likelihoods. Then we show in a aphid enterobacter system that some reliable transfers detected by our method, are invisible to classic 2-level reconciliation. We finally evaluate different hypotheses on human population histories in the light of their coevolving Helicobacter pylori symbionts, reconciled together with their genes.Availability Implementation is available on GitHub https://github.com/hmenet/TALE. Data are available on Zenodo https://doi.org/10.5281/zenodo.6782794.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2022/07/03/2022.07.01.498457}, eprint = {https://www.biorxiv.org/content/early/2022/07/03/2022.07.01.498457.full.pdf}, journal = {bioRxiv} }