**Author details**

*Methods in Molecular Medicine*

frame [112].

**5. Conclusion**

**Conflict of interest**

approaches assist the clinical diagnosis.

precision medicine via the use of evolutionary insight.

The authors declare no conflict of interest.

from data analysis. Employing population MAF frequency filtering according to the mode of inheritance has decreased the number of variants to 19, 46, 3 for de novo heterozygous, homozygous, compound heterozygous variants respectively. Further prioritization approaches were applied by integrating pathogenicity prediction scores provided by PrimateAI and other tools, model organism phenotypes, and gene intolerance scores. Ultimately, the FZD6 gene was found to be the most prominent gene even though the gene does not have a high intolerance score. However, the potential functional impact of the mutation was supported by the examination of the evolutionary conservation of the disturbed amino acid region. The region was found to be evolutionarily conserved in other FZD6 orthologues including *Pan troglodytes*, *Macaca mulatta*, *Pongo abelii*, *Bos taurus*, *Canis lupus familiaris*, *Rattus norvegicus*, *Mus musculus*, *Xenopus laevis*. The index case had a homozygous 8 bp deletion on the FZD6 gene caused p.Gly559Aspfs\*16. Additionally, this mutation has previously been reported in two other Turkish families. It is also reported that all three families have a common ancestor. In this study, the pathogenicity mechanism for this mutation in nail dysplasia is provided for the first time. The mutation causes a frameshift and creates a premature stop codon at position 16 of the new reading

This case study demonstrated that the promising applications of evolutionary

Associating genomic variants with diseases is a multistep process. The early steps of this process are highly automated through the usage of several bioinformatics tools. However, the final prioritization step, which is the most critical step, is not completely automated. It requires a comprehensive interpretation together with integrative approaches. In this chapter, we aimed to explain the potential of integrating evolutionary principles into variant prioritization toward clinical utility. This chapter provides sufficient basic information to understand the required bioinformatics tools, various databases with increasing sequence data from individuals as well as model organism research. Finally, we conclude that the pre-evaluation of individual variations with evolutionary approaches can help shorten the diagnostic odyssey, hence saving time and resources. This chapter aims to contribute to the integration of evolutionary genetics to medical genomics. Further studies that combine theoretical and analytical approaches are needed to improve the field of

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Ugur Sezerman\*, Tugce Bozkurt and Fatma Sadife Isleyen Graduate School of Health Sciences, Biostatistics and Bioinformatics Program, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

\*Address all correspondence to: sezermanu@gmail.com

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
