Published October 28, 2021 | Version 1. Basic software / Core model
Software documentation Open

Software related to the paper entitled "Development and selective grain make plasticity 'take the lead' in adaptive evolution"

Creators

  • 1. Lund University
  • 2. University of Southampton

Description

In this folder you can find some software related to the paper entitled "Development and selective grain make plasticity ‘take the lead’ in adaptive evolution"

 By: Miguel Brun-Usan1,2*, Alfredo Rago1,2, Christoph Thies1, Tobias Uller2, Richard A. Watson1

 1- Institute for life sciences / Electronics and computer sciences. University of Southampton (UK)
 2-Department of Biology, Lund University, 22362, Sweden.
 *- This author has coded the program and is the corresponding author. E-mail: m.brunusan@gmail.com

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

 This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details: <http://www.gnu.org/licenses/>.

Within this folder you can find some modules written in Fortran 95 language: 
1 master program: grns2.f90
2 inter-dependent modules : 
    start.mod.f90   :  Declares and initializes general variables and input parameters (can be     changed manually).
    development.mod.f90 :  Performs the GRN dynamics. 
1 bash file to compile them:     
           grns.sh 

To compile: Download and install a fortran compiler: In Linux; type in terminal: 
"sudo apt-get install gfortran"  
 (give permissions to files and executables if necessary).
 Then type "grns.sh". To launch it, type: "./grns". Output datafiles are stored in the accessory folder "files", created automatically.

 The by-default settings of this basic version enable the user to explore the basic map-to-map correlations in a large ensemble of random developmental systems.
 The code version provided correspond to the GRN + Multi-linear (mixed model) described in the paper and based on:
 Draghi JA & Whitlock MC (2012). Phenotypic plasticity facilitates mutational variance, genetic variance, and evolvability along the major axis of environmental variation. Evolution 66(9), 2891-902.
Input: RandomDraghi16.dat file containing the random networks (16 genes) and associated parametrs (n=10000).
Output *.dat datafiles with phenotypic and fitness values which can be plotted (as shown in the paper figures) using the command-line drive graphic utility GnuPlot: <http://www.gnuplot.info>

Different settings can be manually introduced in the "start.mod.f90" module to explore the different maps, L117 ; L182-183 and L196-197.

Notes

Abstract (of the accompanying paper): Abstract Background: Biological evolution exhibits an extraordinary capability to adapt organisms to their environments. The explanation for this often takes for granted that random genetic variation produces at least some beneficial phenotypic variation in which natural selection can act. Such genetic evolvability could itself be a product of evolution, but it is widely acknowledged that the immediate selective gains of evolvability are small on short timescales. So how do biological systems come to exhibit such extraordinary capacity to evolve? One suggestion is that adaptive phenotypic plasticity makes genetic evolution find adaptations faster. However, the need to explain the origin of adaptive plasticity puts genetic evolution back in the driving seat, and genetic evolvability remains unexplained. Results: To better understand the interaction between plasticity and genetic evolvability, we simulate the evolution of phenotypes produced by gene-regulation network-based models of development. First, we show that the phenotypic variation resulting from genetic and environmental perturbation are highly concordant. This is because phenotypic variation, regardless of its cause, occurs within the relatively specific space of possibilities allowed by development. Second, we show that selection for genetic evolvability results in the evolution of adaptive plasticity and vice versa. This linkage is essentially symmetric but, unlike genetic evolvability, the selective gains of plasticity are often substantial on short, including within-lifetime, timescales. Accordingly, we show that selection for phenotypic plasticity can be effective in promoting the evolution of high genetic evolvability. Conclusions: Without overlooking the fact that adaptive plasticity is itself a product of genetic evolution, we show how past selection for plasticity can exercise a disproportionate effect on genetic evolvability and, in turn, influence the course of adaptive evolution.

Files

Basic_Code_XP-maps.zip

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