Reversing Gene Erosion – Reconstructing Ancestral Bacterial Genomes from Gene-Content and Order Data

Abstract

In the last few years, it has become routine to use gene-order data to reconstruct phylogenies, both in terms of edge distances (parsimonious sequences of operations that transform one end point of the edge into the other) and in terms of genomes at internal nodes, on small, duplication-free genomes. Current gene-order methods break down, though, when the genomes contain more than a few hundred genes, possess high copy numbers of duplicated genes, or create edge lengths in the tree of over one hundred operations. We have constructed a series of heuristics that allow us to overcome these obstacles and reconstruct edges distances and genomes at internal nodes for groups of larger, more complex genomes. We present results from the analysis of a group of thirteen modern γ-proteobacteria, as well as from simulated datasets.

IEEE/ACM Transactions on Computational Biology and Bioinformatics

“…Then, it suffices to deal with linear vertices whose parent is linear in the same way than for a definite tree. 3, 2, 1, 13, 15, 14, 16, 8, 9, 10, 11, 12 (1), (13,15,14,16,8,9,10,11,12,5,6,7), (13,15,14,16), (13), (15,14), (14), (16), (8,9,10,11,12), (11), (5, 6, 7).…”

“…Otherwise K \ K (resp. K \ K) would Comparing the rat and mouse X chromosomes with a subset of their common intervals (intervals (13,14,15), (14,15,16), (13,14,15,16), (10,11), (9,10,11), (10,11,12), (8,9,10,11) and (9,10,11,12) were removed from the set of common intervals). The length of a parsimonious perfect scenario with respect to F * .…”

A Framework for Orthology Assignment from Gene Rearrangement Data

“…(In absence of this constraint, of course, the most parsimonious edit sequence is almost always that which deletes the entire genome G 1 as a single operation, then insert the entire genome G 2 , an absurd scenario.) Once that identification has been made, the algorithms of ElMabrouk [9] and of our group [8,12,17,18] can complete the work of finding one ore more parsimonious edit sequences.…”

“…While these assumptions allow one to work with organellar genomes [2-7, 11, 18], they are too restrictive when comparing nuclear genomes [8], where the main challenge is how to deal with gene families, specifically, how to identify orthologs. While searching for orthologies is a common task in computational biology, it is usually done using sequence data.…”

Linear Programming for Phylogenetic Reconstruction Based on Gene Rearrangements

“…Handling genomes with unequal gene content (i.e., involving duplications, insertions, and deletions of genes) remains largely unsolved, although some progress has been made in computing pairwise distances in such cases [9,10,25,28]. Handling large genomes within GRAPPA is very expensive, because the median computation takes time exponential in the size of the genomes; this problem prevents its application to organismal genomes with thousands of genes.…”