Inferring phylogenetic networks from gene order data.
Existing algorithms allow us to infer phylogenetic networks from sequences (DNA, protein or binary), sets of trees, and distance matrices, but there are no methods to build them using the gene order data as an input. Here we describe several methods to build split networks from the gene order data, perform simulation studies, and use our methods for analyzing and interpreting different real gene order datasets. All proposed methods are based on intermediate data, which can be generated from genome structures under study and used as an input for network construction algorithms. Three intermediates are used: set of jackknife trees, distance matrix, and binary encoding. According to simulations and case studies, the best intermediates are jackknife trees and distance matrix (when used with Neighbor-Net algorithm). Binary encoding can also be useful, but only when the methods mentioned above cannot be used.
Limnological Institute of the Siberian Branch of the Russian Academy of Sciences, 3 Ulan-Batorskaya Street, Irkutsk 664033, Russia.
Alexey Anatolievich
AA
Morozov
Yuri Pavlovich
YP
Galachyants
Yelena Valentinovna
YV
Likhoshway
D000465:Algorithms; D029422:Campanulaceae / Q000145:classification / Q000235:genetics; D003198:Computer Simulation; D030541:Databases, Genetic; D017377:Diatoms / Q000145:classification / Q000235:genetics; D023061:Gene Order; D010802:Phylogeny