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Measurements of DNA barcode label separations in nanochannels from time-series data

机译:从时间序列数据测量纳米通道中DNA条形码标签的分离

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摘要

We analyzed time-series data for fluctuations of intramolecular segments of barcoded E. coli genomic DNA molecules confined in nanochannels with sizes near the persistence length of DNA. These dynamic data allowed us to measure the probability distribution governing the distance between labels on the DNA backbone, which is a key input into the alignment methods used for genome mapping in nanochannels. Importantly, this dynamic method does not require alignment of the barcode to the reference genome, thereby removing a source of potential systematic error in a previous study of this type. The results thus obtained support previous evidence for a left-skewed probability density for the distance between labels, albeit at a lower magnitude of skewness. We further show that the majority of large fluctuations between labels are short-lived events, which sheds further light upon the success of the linearized DNA genome mapping technique. This time-resolved data analysis will improve existing genome map alignment algorithms, and the overall idea of using dynamic data could potentially improve the accuracy of genome mapping, especially for complex heterogeneous samples such as cancer cells.
机译:我们分析了限制在纳米通道内的条形码大肠杆菌基因组DNA分子的分子内片段波动的时间序列数据,其大小接近DNA的持久长度。这些动态数据使我们能够测量控制DNA骨架上标记之间距离的概率分布,这是用于纳米通道基因组作图的比对方法的关键输入。重要的是,这种动态方法不需要将条形码与参考基因组进行比对,从而消除了先前此类研究中潜在系统错误的来源。这样获得的结果支持了先前的证据,即标签之间距离的左偏概率密度,尽管偏度较小。我们进一步表明,标签之间的大部分大波动是短暂的事件,这为线性化DNA基因组作图技术的成功提供了更多启示。这种时间分辨的数据分析将改善现有的基因组图谱比对算法,并且使用动态数据的整体思路可能会提高基因组图谱的准确性,尤其是对于复杂的异质样品(例如癌细胞)。

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