Experimental evolution offers great potential to gain insight into the molecular mechanism that contribute to the acquisition of complex traits. In the laboratory, evolution experiments start from a single clone cultivated for a determined amount of time in predefined conditions.
The clones submitted to these conditions will follow natural selection principles giving advantage to mutations that confer a benefit in the chosen condition leading to improved phenotypes. Fitness is tracked over time and after genotyped clones will show possible mutations.
Network-based methods in combination with OMICS data are often used to address research questions solely depending of the type of data used. Protein's and gene's function, motif detection, prioritization of gene list, gene-gene interactions and inference of sub-networks of the interaction network which are involved in a specific phenotype or active paths when the organism is exposed to a certain environment.
Identification of Adaptive Mutations in Bacterial Evolution Experiments short known as IAMBEE is a method created to exploit the temporal profile acquisition of mutations at the pathway level.
Evolution experiments aiming to study complex traits can be analyzed by IAMBEE, which takes advantage from the information gained from the trajectory of individual mutations along the evolution experiment to reduce the complexity at the moment of identify adaptive pathways or candidate genes.