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A study of the relationships between oligonucleotide properties and hybridization signal intensities from NimbleGen microarray datasets

机译:从NimbleGen微阵列数据集中研究寡核苷酸特性与杂交信号强度之间的关系

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Well-defined relationships between oligonucleotide properties and hybridization signal intensities (HSI) can aid chip design, data normalization and true biological knowledge discovery. We clarify these relationships using the data from two microarray experiments containing over three million probes from 48 high-density chips. We find that melting temperature (T-m) has the most significant effect on HSI while length for the long oligonucleotides studied has very little effect. Analysis of positional effect using a linear model provides evidence that the protruding ends of probes contribute more than tethered ends to HSI, which is further validated by specifically designed match fragment sliding and extension experiments. The impact of sequence similarity (SeqS) on HSI is not significant in comparison with other oligonucleotide properties. Using regression and regression tree analysis, we prioritize these oligonucleotide properties based on their effects on HSI. The implications of our discoveries for the design of unbiased oligonucleotides are discussed. We propose that isothermal probes designed by varying the length is a viable strategy to reduce sequence bias, though imposing selection constraints on other oligonucleotide properties is also essential.
机译:寡核苷酸特性与杂交信号强度(HSI)之间的明确关系可以帮助芯片设计,数据归一化和真正的生物学知识发现。我们使用来自两个微阵列实验的数据阐明了这些关系,该实验包含来自48个高密度芯片的三百万个探针。我们发现,解链温度(T-m)对HSI的影响最大,而研究的长寡核苷酸的长度几乎没有影响。使用线性模型进行的位置效应分析提供了证据,表明探针的突出末端对HSI的贡献要大于束缚末端,这已通过专门设计的匹配片段滑动和延伸实验得到了进一步验证。与其他寡核苷酸特性相比,序列相似性(SeqS)对HSI的影响并不明显。使用回归和回归树分析,我们基于它们对HSI的影响来对这些寡核苷酸特性进行优先排序。讨论了我们的发现对于无偏寡核苷酸设计的意义。我们建议通过改变长度设计的等温探针是降低序列偏差的可行策略,尽管对其他寡核苷酸特性施加选择约束也是必不可少的。

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