Consequences of genotyping errors for estimation of clonality: a case study on Populus euphratica Oliv. (Salicaceae)
Consequences of genotyping errors for estimation of clonality: a case study on Populus euphratica Oliv. (Salicaceae)
复制标题
DOI：
10.1007/s10682-010-9389-y
复制
发表时间：
2010-05
影响因子：
1.9
通讯作者：
M. Schnittler;P. Eusemann
中科院分区：
文献类型：
--
作者：
M. Schnittler;P. Eusemann
一项研究包括8个微卫星位点的1,014株树，从7个部分克隆胡杨定位的立场，被用来证明如何基因分型误差影响估计的克隆性。阈值为0（相同的多位点基因型构成一个克隆），我们确定了602种基因型。阈值为1（补偿一个等位基因中的错误）将这个数字降低到563。基因分型错误可以看似合并（1型错误），分裂真正存在的克隆（2型），或将一个独特的基因型转换为另一个独特的基因型（3型）。我们使用上下文信息（性别和空间位置）来估计第1类错误。对于0和1的阈值，估计值低于0.021，表明标记物系统的分辨率较高。通过对随机抽取的41棵树进行重复基因分型估计基因分型错误率（0.158），并通过对第二队列的40棵树进行重复基因分型估计基因分型错误率（0.368）。对于后一个队列，这些偏差中的大多数被证明是错误的，但在602个获得的多位点基因型中有8个可能代表体细胞突变，对应于0.013的突变率。不同的克隆性和均匀性的种群的基因分型错误的模拟表明，基因型的数量总是被高估的系统具有高分辨率，这种错误增加的克隆性和均匀性。与阈值0相比，允许阈值1补偿了大多数基因分型错误，并导致更精确的克隆性估计。这降低了标记系统的分辨率，但与上下文信息的比较可以帮助检查分辨率是否足以应用更高的阈值。我们建议模拟程序，以调查不同的阈值和错误率的标记系统的行为，以获得克隆性的最佳估计。
A study including eight microsatellite loci for 1,014 trees from seven mapped stands of the partially clonalPopulus euphraticawas used to demonstrate how genotyping errors influence estimates of clonality. With a threshold of 0 (identical multilocus genotypes constitute one clone) we identified 602 genotypes. A threshold of 1 (compensating for an error in one allele) lowered this number to 563. Genotyping errors can seemingly merge (type 1 error), split really existing clones (type 2), or convert a unique genotype into another unique genotype (type 3). We used context information (sex and spatial position) to estimate the type 1 error. For thresholds of 0 and 1 the estimate was below 0.021, suggesting a high resolution for the marker system. The rate of genotyping errors was estimated by repeated genotyping for a cohort of 41 trees drawn at random (0.158), and a second cohort of 40 trees deviating in one allele from another tree (0.368). For the latter cohort, most of these deviations turned out to be errors, but 8 out of 602 obtained multilocus genotypes may represent somatic mutations, corresponding to a mutation rate of 0.013. A simulation of genotyping errors for populations with varying clonality and evenness showed the number of genotypes always to be overestimated for a system with high resolution, and this mistake increases with increasing clonality and evenness. Allowing a threshold of 1 compensates for most genotyping errors and leads to much more precise estimates of clonality compared with a threshold of 0. This lowers the resolution of the marker system, but comparison with context information can help to check if the resolution is sufficient to apply a higher threshold. We recommend simulation procedures to investigate the behavior of a marker system for different thresholds and error rates to obtain the best estimate of clonality.