Table 9_Development and validation of animal variant classification guidelines to objectively evaluate genetic variant pathogenicity in domestic animals.xlsx

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至关重要。在种群层面，基于无效DNA检测的育种决策可能导致动物被错误纳入或排除，损害种群的长期健康；而在个体层面，则会引发不当治疗乃至终结生命的决策失误。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属指南。本研究旨在开发并验证一套可供学界使用的家养动物孟德尔遗传病变异分类指南，该指南基于标准化判定准则将遗传变异划分为不同类别，即动物变异分类指南（Animal Variant Classification Guidelines, AVCG）。该指南借鉴了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同类标准。直接对比试验结果显示，采用ACMG指南可正确分类83%的致病性变异，而改用AVCG指南时，这一准确率提升至92%。本研究阐述了以该判定标准为基准构建数据集以开展性能验证的方法，并筛选出了最优的计算机模拟（in silico）变异效应预测工具。鉴于该方法重现性优异，我们对72个猫类已知疾病相关遗传变异，以及另外8个物种中的40个疾病相关遗传变异完成了分类。