计算机模拟基因组-基因组杂交值准确且精确地预测用于分类原核生物的经验DNA-DNA杂交值
In Silico Genome-Genome Hybridization Values Accurately and Precisely Predict Empirical DNA-DNA Hybridization Values for Classifying Prokaryotes
摘要：
近50年来，微生物学家一直通过核酸再结合动力学来确定原核基因组的相关性。然而，这些方法在技术上具有挑战性，难以复制，并且-考虑到生成单个数据点所需的时间和资源-不具有成本效益。在后基因组时代，测序全原核基因组的成本不再是限制因素，我们认为，计算预测的输出值从传统的DNA-DNA杂交实验使用全基因组序列的成对比较是有价值的。虽然存在其他计算全基因组分类方法，但它们在与DNA-DNA杂交不同的尺度上预测值，为定义微生物物种的多相方法引入了另一个度量。我们的目标是开发一种基于计算机模拟BLAST的管道，该管道将以高水平的确定性预测基于湿实验室的DNA-DNA杂交值的值。在这里，我们报告一个这样的方法，产生的估计是准确和精确的DNA-DNA杂交值，他们的目的是模仿。
英文摘要：
For nearly 50 years microbiologists have been determining prokaryotic genome relatedness by means of nucleic acid reassociation kinetics. These methods, however, are technically challenging, difficult to reproduce, and - given the time and resources it takes to generate a single data-point - not cost effective. In the post genomic era, with the cost of sequencing whole prokaryotic genomes no longer a limiting factor, we believed that computationally predicting the output value from a traditional DNA-DNA hybridization experiment using pair-wise comparisons of whole genome sequences to be of value. While other computational whole-genome classification methods exist, they predict values on widely different scales than DNA-DNA hybridization, introducing yet another metric into the polyphasic approach of defining microbial species. Our goal was to develop an in silico BLAST based pipeline that would predict with a high level of certainty the value of the wet lab-based DNA-DNA hybridization values. Here we report on one such method that produces estimates that are both accurate and precise with respect to the DNA-DNA hybridization values they are designed to emulate.
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