Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria.
Institute of Veterinary Pathology, Justus-Liebig-University Giessen, Giessen, Germany.
Forensic Sci Int Genet. 2023 Sep;66:102893. doi: 10.1016/j.fsigen.2023.102893. Epub 2023 Jun 3.
Predicting the outward appearance of dogs via their DNA, also known as Canine DNA Phenotyping, is a young, emerging field of research in forensic genetics. The few previous studies published in this respect were restricted to the consecutive analysis of single DNA markers, a process that is time- and sample-consuming and therefore not a viable option for limited forensic specimens. Here, we report on the development and evaluation of a Massively Parallel Sequencing (MPS) based molecular genetic assay, the LASSIE MPS Panel. This panel aims to predict externally visible as well as skeletal traits, which include coat color, coat pattern, coat structure, tail morphology, skull shape, ear shape, eye color and body size from DNA using 44 genetic markers in a single molecular genetic assay. A biostatistical naïve Bayes classification approach was applied to identify the most informative marker combinations for predicting phenotypes. Overall, the predictive performance was characterized by a very high classification success for some of the trait categories, and high to moderate success for others. The performance of the developed predictive framework was further evaluated using blind samples from three randomly selected dog individuals, whose appearance was well predicted.
通过狗的 DNA 预测其外观，也称为犬 DNA 表型预测，是法医遗传学中一个年轻且新兴的研究领域。在这方面发表的少数先前研究仅限于对单个 DNA 标记的连续分析，这个过程既耗时又耗样，因此对于有限的法医样本来说不是可行的选择。在这里，我们报告了一种基于大规模平行测序（MPS）的分子遗传学检测方法——LASSIE MPS 面板的开发和评估。该面板旨在通过在单个分子遗传学检测中使用 44 个遗传标记，从 DNA 预测外部可见和骨骼特征，包括毛色、毛色图案、毛色结构、尾巴形态、颅骨形状、耳朵形状、眼睛颜色和体型。应用了一种生物统计学的朴素贝叶斯分类方法来识别用于预测表型的最具信息量的标记组合。总体而言，某些特征类别的分类成功率非常高，而其他特征类别的成功率则较高到中等。该开发的预测框架的性能还使用来自三个随机选择的狗个体的盲样进行了评估，这些个体的外观预测得很好。
