Table_1_Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs.docx

Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner.

运用少量具有祖先信息标记（AIMs）的集合，构成了一种经济高效的估算个体祖先比例的方法。本研究旨在从约60,000个猪的单核苷酸多态性（SNP）数据中生成少量且有效的AIMs，并从亚洲品种和欧洲家猪品种中估算三个祖先比例[华东猪（ECHP）、华南猪（SCHP）和欧洲商业猪（EUCP）]。总计186个10个纯种猪的样本被分为三组：ECHP、SCHP和EUCP。利用这些样本以及一个一对余SVM分类器，我们发现仅使用七个AIMs即可完全区分这三组。随后，我们运用监督式ADMIXTURE算法计算祖先比例，并发现当使用伪混合个体时，129个AIMs在祖先估算方面表现出色。此外，我们还应用了61个群体的969个样本来评估这129个AIMs的性能。我们还观察到，这129个AIMs与使用约60,000个SNP数据对三个祖先成分（ECHP、SCHP和EUCP）的估算高度相关，其皮尔逊相关系数（r）分别为0.94、0.94和0.99。我们的研究结果提供了一个使用少量猪AIMs进行分类和以高准确性和经济高效的方式估算祖先比例的实例。