Data Sheet 5_Development and validation of animal variant classification guidelines to objectively evaluate genetic variant pathogenicity in domestic animals.docx

Assessing the pathogenicity of a disease-associated genetic variant in animals accurately is vital, both on a population and individual scale. At the population level, breeding decisions based on invalid DNA tests can lead to the incorrect inclusion or exclusion of animals and compromise the long-term health of a population, and at the level of the individual animal, lead to incorrect treatment and even life-ending decisions. Criteria to determine pathogenicity are not standardized, i.e., no guidelines for animal variants are available. Here, we aimed to develop and validate guidelines to be used by the community for Mendelian disorders in domestic animals to classify variants in categories based on standardized criteria. These so-called animal variant classification guidelines (AVCG) were based on those developed for humans by The American College of Medical Genetics and Genomics (ACMG). In a direct comparison, 83% of the pathogenic variants were correctly classified with ACMG, while this increased to 92% with AVCG. We described methods to develop datasets for benchmarking the criteria and identified the most optimal in silico variant effect predictor tools. As the reproducibility was high, we classified 72 known disease-associated variants in cats and 40 other disease-associated variants in eight additional species.

精准评估动物疾病相关遗传变异的致病性，无论在种群还是个体层面，均具有至关重要的意义。在种群层面，基于无效DNA检测的育种决策可能造成动物的错误留用或淘汰，损害种群的长期健康；在个体层面，则可能引发不当治疗乃至终结生命的决策。当前致病性判定标准尚未统一，尚无针对动物遗传变异的专用指南。本研究旨在开发并验证一套面向学界、适用于家养动物孟德尔遗传病的标准化变异分类指南。该指南即动物变异分类指南（Animal Variant Classification Guidelines, AVCG），其原型源自美国医学遗传学与基因组学学会（American College of Medical Genetics and Genomics, ACMG）针对人类遗传变异制定的分类标准。直接对比结果显示，采用ACMG标准时，83%的致病性变异可被正确分类，而使用AVCG标准时这一比例提升至92%。本研究还阐述了用于该标准基准测试的数据集构建方法，并筛选出性能最优的计算机模拟变异效应预测工具。鉴于该指南具备良好的可重复性，我们完成了72个猫类已知疾病相关变异，以及另外8个物种共40个疾病相关变异的分类工作。