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A computer simulation analysis of the accuracy of partial genome sequencing and restriction fragment analysis in estimating genetic relationships: an application to papillomavirus DNA sequences

机译:计算机模拟分析部分基因组测序和限制性片段分析在估计遗传关系中的准确性:在乳头瘤病毒DNA序列中的应用

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Background Determination of genetic relatedness among microorganisms provides information necessary for making inferences regarding phylogeny. However, there is little information available on how well the genetic relationships inferred from different genotyping methods agree with true genetic relationships. In this report, two genotyping methods – restriction fragment analysis (RFA) and partial genome DNA sequencing – were each compared to complete DNA sequencing as the definitive standard for classification. Results Using the Genbank database, 16 different types or subtypes of papillomavirus were selected as study samples, because numerous complete genome sequences were available. RFA was achieved by computer-simulated digestion. The genetic similarity of samples, based on RFA, was determined from the proportion of fragments that matched in size. DNA sequences of four specific genes (E1, E6, E7, and L1), representing partial genome sequencing, were also selected for comparison to complete genome sequencing. Laboratory error was not taken into account. Evaluation of the correlation between genetic similarity matrices (Mantel's r) and comparisons of the structure of the derived dendrograms (partition metric) indicated that partial genome sequencing (for single genes) had higher agreement with complete genome sequencing, achieving a maximum Mantel's r = 0.97 and a minimum partition metric = 10. RFA had lower agreement, with a maximum Mantel's r = 0.60 and a minimum partition metric = 18. Conclusions This simulation indicated that for smaller genomes, such as papillomavirus, partial genome sequencing is superior to restriction fragment analysis in representing genetic relatedness among isolates. The generalizability of these results to larger genomes, as well as the impact of laboratory error, remains to be demonstrated.
机译:背景技术确定微生物之间的遗传相关性提供了推断系统发育所必需的信息。但是,关于从不同基因分型方法推断出的遗传关系与真实遗传关系的一致性的信息很少。在本报告中,将两种基因分型方法(限制性片段分析(RFA)和部分基因组DNA测序)分别与完整的DNA测序进行比较,作为分类的权威标准。结果利用Genbank数据库,选择了16种不同类型或亚型的乳头瘤病毒作为研究样本,因为可获得许多完整的基因组序列。 RFA是通过计算机模拟消化实现的。基于RFA的样品遗传相似性是由大小匹配的片段比例确定的。还选择了代表部分基因组测序的四个特定基因(E1,E6,E7和L1)的DNA序列进行比较,以进行完整的基因组测序。没有考虑实验室错误。评估遗传相似性矩阵之间的相关性(Mantel's r)和比较衍生树状图的结构(分区度量),表明部分基因组测序(对于单个基因)与完整基因组测序具有更高的一致性,最大Mantel's r = 0.97最小分区指标=10。RFA具有较低的一致性,最大Mantel r = 0.60,最小分区指标=18。结论该模拟表明,对于较小的基因组,例如乳头瘤病毒,部分基因组测序优于限制性片段分析代表分离株之间的遗传相关性。这些结果对更大基因组的普遍性以及实验室误差的影响仍有待证明。

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