Self-organizing maps: a powerful tool for capturing genetic diversity patterns of populations

Abstract

The maintenance of genetic diversity is fundamental to ensure the population’s viability and to perceive how the evolutionary factors act on these. Using self-organizing maps (SOM) may be interesting to organize the genetic diversity and evidence of the effects caused by dispersive and systematic factors. The objective of this work was to verify if the SOM are able to map the genetic drift, selection, migration and inbreeding effects over generations from the allelic (p and q) and genotypic (D, H and R) frequencies. Populations submitted to these factors were simulated by the software Genes. Afterward, the populations submitted to each factor were mapped by the SOM and analyzed. The topological map showed great efficiency in organizing the populations since it was possible to recognize the expected pattern of each effect tested. Thus, SOM have been shown to be efficient in organizing populations that are subject to a process that reduces variability, such as drift, inbreeding, and selection, and to processes that increase genetic variability, such as migration.