Classification of feline hypertrophic cardiomyopathy-associated gene variants according to the American College of Medical Genetics and Genomics guidelines.

Introduction: The correct labeling of a genetic variant as pathogenic is important as breeding decisions based on incorrect DNA tests can lead to the unwarranted exclusion of animals, potentially compromising the long-term health of a population. In human medicine, the American college of Medical Genetics (ACMG) guidelines provide a framework for variant classification. This study aims to apply these guidelines to six genetic variants associated with hypertrophic cardiomyopathy (HCM) in certain cat breeds and to propose a modified criterion for variant classification. Methods: Genetic samples were sourced from five cat breeds: Maine Coon, Sphynx, Ragdoll, Devon Rex, and British Short- and Longhair. Allele frequencies were determined, and in the subset with phenotypes available, odds ratios to determine the association with HCM were calculated. In silico evaluation followed with joint evidence and data from other publications assisting in the classification of each variant. Results: Two variants, MYBPC3:c.91G > C [A31P] and MYBPC3:c.2453C > T [R818W], were designated as pathogenic. One variant, MYH7:c.5647G > A [E1883K], was found likely pathogenic, while the remaining three were labeled as variants of unknown significance. Discussion: Routine genetic testing is advised solely for the MYBPC3:c.91G > C [A31P] in the Maine Coon and MYBPC3:c.2453C > T [R818W] in the Ragdoll breed. The human ACMG guidelines serve as a suitable foundational tool to ascertain which variants to include; however, refining them for application in veterinary medicine might be beneficial.

VariantscanR: an R-package as a clinical tool for variant filtering of known phenotype-associated variants in domestic animals.

BACKGROUND: Since the introduction of next-generation sequencing (NGS) techniques, whole-exome sequencing (WES) and whole-genome sequencing (WGS) have not only revolutionized research, but also diagnostics. The gradual switch from single gene testing to WES and WGS required a different set of skills, given the amount and type of data generated, while the demand for standardization remained. However, most of the tools currently available are solely applicable for human analysis because they require access to specific databases and/or simply do not support other species. Additionally, a complicating factor in clinical genetics in animals is that genetic diversity is often dangerously low due to the breeding history. Combined, there is a clear need for an easy-to-use, flexible tool that allows standardized data processing and preferably, monitoring of genetic diversity as well. To fill these gaps, we developed the R-package variantscanR that allows an easy and straightforward identification and prioritization of known phenotype-associated variants identified in dogs and other domestic animals. RESULTS: The R-package variantscanR enables the filtering of variant call format (VCF) files for the presence of known phenotype-associated variants and allows for the estimation of genetic diversity using multi-sample VCF files. Next to this, additional functions are available for the quality control and processing of user-defined input files to make the workflow as easy and straightforward as possible. This user-friendly approach enables the standardisation of complex data analysis in clinical settings. CONCLUSION: We developed an R-package for the identification of known phenotype-associated variants and calculation of genetic diversity.