Detection of hybridization and introgression is important in ecological research as in conservation and evolutionary biology. STRUCTURE is one of the most popular software to study introgression and allows estimating what proportion of the genome of each individual belongs to each ancestral population, even in cases where no reference sample from the ancestral nonadmixed populations is previously identified. In spite of its frequent use, some studies have indicated that ancestry estimates may not always be reliable. We simulated population data under different conditions with regard to the genetic differentiation between ancestral populations, number of loci considered, number of alleles per marker and hybridization rate, and analysed data with STRUCTURE. When reference samples were not included, the comparison of the known degree of admixture for each simulated individual and the value estimated with STRUCTURE revealed a strong underestimation of the level of introgression, classifying many admixed individuals as nonadmixed. This derives from an inaccurate estimation of the ancestral allele frequencies. When samples from the nonadmixed ancestral population were included as reference in the analyses, the bias in the estimations was reduced. The most accurate estimates were obtained when potentially admixed samples were few in relation to reference samples. Thus, whenever possible, a very large proportion of nonadmixed reference samples should be included in admixture assessments and different approaches should be combined. The misestimate of the amount of introgression can impair our understanding of the evolutionary history of species and misguide conservation efforts.

中文翻译：

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在没有参考样品的情况下使用 STRUCTURE 对正在进行的混合物进行有偏评估

杂交和基因渗入的检测在生态研究中很重要，就像在保护和进化生物学中一样。STRUCTURE 是研究基因渗入最流行的软件之一，它允许估计每个个体的基因组比例属于每个祖先群体，即使在先前未确定来自祖先非混合群体的参考样本的情况下也是如此。尽管经常使用，但一些研究表明，祖先估计可能并不总是可靠的。我们模拟了不同条件下的种群数据，包括祖先种群之间的遗传分化、考虑的基因座数量、每个标记的等位基因数量和杂交率，并使用 STRUCTURE 分析数据。当不包括参考样品时，每个模拟个体的已知混合程度与用 STRUCTURE 估计的值的比较揭示了对基因渗入水平的严重低估，将许多混合个体归类为非混合个体。这源于对祖先等位基因频率的不准确估计。当来自非混合祖先群体的样本被包括在分析中作为参考时，估计中的偏差就会减少。当潜在混合样品相对于参考样品很少时，获得了最准确的估计。因此，只要有可能，在混合物评估中应包括很大比例的未混合参考样品，并应结合不同的方法。