High resolution refinement of Large Scale Genomic Rearrangements using repetitions: A case study

DNA repetitions play a quite important role in the evolution of species. However, they are usually discarded in computational genomic rearrangement (GR) studies such as synteny blocks identification or borders refinement. Repetitions are excluded from analysis because they are harder to detect, increase the computational complexity and what is more important, avoiding repetitions simplifies the model. The functionality at each extreme fits the biological models. The method is based on transitions in the difference between the alignment of the two blocks involved in the LSGR and the consensus alignment of the repetitions in between. Then, a Finite State Machine is designed to detect these transitions. To illustrate the procedure, we present a study on two strains of Mycoplasma hyorhinis: SK76 and HUB-1. In this study, repetitions are used for high-resolution refinement of borders. Both, computational and biological evaluation of results is discussed, obtaining consistent evidences on the enhancements produced by our methodology. In conclusion, functional annotations support our method for the LSGR border refinement and might help to understand the evolutionary model of species. In a recent work we proposed a method to refine borders of large-scale genomic rearrangement (LSGR) including repetitions (Arjona-Medina J.A. and Trelles O. 2016). Now, a high-resolution analysis of the borders (i.e. at nucleotide level) is presented in this work. To perform this study we incorporate functional annotations in the borders of LSGR to learn on the specific characteristics of such borders, and decide whether the functionality at each extreme fits the biological models. The method is based on transitions in the difference between the alignment of the two blocks involved in the LSGR and the consensus alignment of the repetitions in between. Then, a Finite State Machine is designed to detect these transitions. To illustrate the procedure, we present a study on two strains of Mycoplasma hyorhinis: SK76 and HUB-1. In this study, repetitions are used for high-resolution refinement of borders. Both, computational and biological evaluation of results is discussed, obtaining consistent evidences on the enhancements produced by our methodology. In conclusion, functional annotations support our method for the LSGR border refinement and might help to understand the evolutionary model of species.