Department of Biological, Geological and Environmental Sciences (BiGeA), University of Bologna, Bologna, Italy.
Department for the Monitoring and Protection of the Environment and for Biodiversity Conservation, Unit for Conservation Genetics (BIO-CGE), Italian Institute for Environmental Protection and Research (ISPRA), Via Ca' Fornacetta, 9 - 40064 Ozzano dell'Emilia, Bologna, Italy.
BMC Genomics. 2021 Aug 18;22(1):623. doi: 10.1186/s12864-021-07915-5.
The low cost and rapidity of microsatellite analysis have led to the development of several markers for many species. Because in non-invasive genetics it is recommended to genotype individuals using few loci, generally a subset of markers is selected. The choice of different marker panels by different research groups studying the same population can cause problems and bias in data analysis. A priority issue in conservation genetics is the comparability of data produced by different labs with different methods. Here, we compared data from previous and ongoing studies to identify a panel of microsatellite loci efficient for the long-term monitoring of Apennine brown bears (Ursus arctos marsicanus), aiming at reducing genotyping uncertainty and allowing reliable individual identifications overtimes.
We examined all microsatellite markers used up to now and identified 19 candidate loci. We evaluated the efficacy of 13 of the most commonly used loci analyzing 194 DNA samples belonging to 113 distinct bears selected from the Italian national biobank. We compared data from 4 different marker subsets on the basis of genotyping errors, allelic patterns, observed and expected heterozygosity, discriminatory powers, number of mismatching pairs, and probability of identity. The optimal marker set was selected evaluating the low molecular weight, the high discriminatory power, and the low occurrence of genotyping errors of each primer. We calibrated allele calls and verified matches among genotypes obtained in previous studies using the complete set of 13 STRs (Short Tandem Repeats), analyzing six invasive DNA samples from distinct individuals. Differences in allele-sizing between labs were consistent, showing a substantial overlap of the individual genotyping.
The proposed marker set comprises 11 Ursus specific markers with the addition of cxx20, the canid-locus less prone to genotyping errors, in order to prevent underestimation (maximizing the discriminatory power) and overestimation (minimizing the genotyping errors) of the number of Apennine brown bears. The selected markers allow saving time and costs with the amplification in multiplex of all loci thanks to the same annealing temperature. Our work optimizes the available resources by identifying a shared panel and a uniform methodology capable of improving comparisons between past and future studies.
微卫星分析的低成本和快速性使得许多物种的多个标记得以发展。由于在非侵入性遗传学中，建议使用少数基因座对个体进行基因分型，因此通常会选择标记的子集。研究同一群体的不同研究小组选择不同的标记面板可能会导致数据分析中的问题和偏差。保护遗传学中的一个优先事项是不同实验室使用不同方法产生的数据的可比性。在这里，我们比较了以前和正在进行的研究的数据，以确定一组用于长期监测阿平宁棕熊（Ursus arctos marsicanus）的微卫星基因座，旨在减少基因分型的不确定性，并允许随着时间的推移进行可靠的个体识别。
我们检查了迄今为止使用的所有微卫星标记，并确定了 19 个候选基因座。我们分析了来自意大利国家生物库的 113 只不同熊的 194 个 DNA 样本，评估了 13 个最常用的基因座的功效。我们根据基因分型错误、等位基因模式、观察到的和预期的杂合度、鉴别力、不匹配对的数量和身份识别的概率，比较了 4 个不同标记子集的数据。通过评估每个引物的低分子量、高鉴别力和低基因分型错误发生率，选择了最佳的标记集。我们使用完整的 13 个 STR（短串联重复）校准了等位基因调用，并验证了以前研究中获得的基因型之间的匹配，分析了来自 6 个不同个体的侵入性 DNA 样本。实验室之间等位基因大小的差异是一致的，显示出个体基因分型的实质性重叠。
所提出的标记集由 11 个熊特异性标记和增加的 cxx20 组成，cxx20 是不易发生基因分型错误的犬科基因座，以防止对阿平宁棕熊数量的低估（最大化鉴别力）和高估（最小化基因分型错误）。选择的标记可以通过在相同的退火温度下对所有基因座进行多重扩增来节省时间和成本。我们的工作通过确定一个共享的面板和一个统一的方法来优化可用资源，从而能够提高过去和未来研究之间的比较。
