Computational prediction of the phenotypic effects of genetic variants: basic concepts and some application examples in Drosophila nervous system genes

Predicting the phenotypic impact of mutations is a central challenge in population and functional genetics. The analysis of DNA and amino acid sequence variation in an evolutionary context is a robust approach to infer the fitness effects of genetic variants. In this review, we discuss the most popular methods based on this approach, covering both theoretical and practical aspects, and introduce compelling software for predicting the functional effects of mutations, and to highlight functionally relevant nucleotide or amino acid candidate positions. Furthermore, we provide some examples of their application to Drosophila genes affecting significant aspects of the development, physiology and function of the nervous system.
This work was supported by grants of the Ministerio de Economía y Competitividad, Spain (CGL2016–75255), and by the Comissió Interdepartamental de Recerca I Innovació Tecnològica of Catalonia, Spain (2014SGR-1055). SG-R was supported by a Beatriu de Pinós Postdoctoral Fellowship (AGAUR; 2014 BP-B 00027), and SHA by the Consejo Nacional de Ciencia y Tecnología, México.