ReEVOLVER
1.0
A tool to detect functional lineage-specific genes by
evolutionary simulations
The ReEVOLVER 1.0 software implements an
approach that can be used to support the functionality of recent duplicate
genes using evolutionary simulations. By repeatedly simulating the evolution of
a putative gene under neutrality, our method estimates the probability that its
open reading frame has been selectively preserved during its evolutionary
history and is therefore likely to be functional. In parallel, our method tests
whether the accumulation of nonsynonymous substitutions is consistent with
neutrality or selective constraint. The method is described in Dupanloup and
Kaessmann (submitted).
Linux, Mac (OS X 10.4), and Windows versions of the
ReEVOLVER 1.0 software are available.
ReEVOLVER 1.0 requires 3 input files.
- a file containing the
sequences of the putative gene and an outgroup sequence (example)
- a treefile in
parenthesis format (example)
- a treefile in
parenthesis format with a label for each branch [(1) time in MYA (2)
number of observed stop codons (3) number of frameshifts indels] (example)
ReEVOLVER 1.0 requires:
- the name of the input
files
- the mutation and indel
rates per site per million years
- the mutation rate per
site per million years at CpG sites
- the number of
simulations you wish to perform
- the softwares used to
reconstruct the ancestral sequence at the time of the 1st speciation event
(this reconstruction can be done using a maximum parsimony or a maximum
likelihood approach (see Dupanloup and Kaessmann (submitted));
the dnapars program of the PHYLIP
package (Felsenstein 1996) and the codeml program of PAML (Yang
1997) are used respectively;
these programs are provided in the archive files containing the ReEVOLVER
software (see below)
ReEVOLVER 1.0 runs with the parsimony approach
(for the reconstruction of ancestral sequences):

Click on the figure to get a pdf with a detailed
description of the run !
ReEVOLVER 1.0 runs with the maximum likelihood
approach (for the reconstruction of ancestral sequences):

Click on the figure to get a pdf file with a
detailed description of the run !
ReEVOLVER 1.0 creates 4 output files.
- a logfile containing all
information for each round of the simulations such as the inferred
ancestral sequence, the number of observed substitutions along the
different lineages of the species phylogeny, details about the simulations
procedure
- the number of
deleterious mutations (stop codons and indels) for each replicate
- the number of
nonsynonymous and synonymous substitutions per replicate run,
- the test probabilities,
Pdis and PNaNs (including associated information).
- Dupanloup, I.,
Kaessmann, H. (2006) Evolutionary simulations to detect functional
lineage-specific genes. Bioinformatics Jun 9; [Epub ahead of print].
- Felsenstein, J. 1996.
Inferring phylogenies from protein sequences by parsimony, distance, and
likelihood methods. Methods Enzymol 266: 418-427.
- Marques, A.C.,
Dupanloup, I., Vinckenbosch, N., Reymond, A., Kaessmann, H. (2005)
Emergence of Young Human Genes after a Burst of Retroposition in Primates.
Plos Biology 3 (11).
- Yang, Z. 1997. PAML: a
program package for phylogenetic analysis by maximum likelihood. Comput
Appl Biosci 13: 555-556.
- LINUX version (you will get a file (a
tar archive compressed using gunzip) that contains all the files necessary
for ReEVOLVER to run properly as well as examples; in this archive, the
ReEVOLVER software is called Reevolver1.0_linux.out)
- Mac version (you will get a file (an
archive compressed with winzip) that contains all the files necessary for
ReEVOLVER to run properly as well as examples; in this archive, the
ReEVOLVER software is called Reevolver1.0_mac.exe)
- WINDOWS version (you will get a file
(an archive compressed with winzip) that contains all the files necessary
for ReEVOLVER to run properly as well as examples; in this archive, the
ReEVOLVER software is called Reevolver1.0_windows.exe)
Correspondence: Isabelle Dupanloup (1,2) and
Henrik Kaessmann (1)
(1) Center for Integrative Genomics, University of Lausanne, Génopode, CH-1015
Lausanne, Switzerland
(2) Computational and Molecular Population Genetics Lab, Zoological Institute,
University of Bern, 3012 Bern, Switzerland
E-mail: Isabelle.Dupanloup@zoo.unibe.ch
and Henrik.Kaessmann@unil.ch