Table_4_Evaluating and Correcting Inherent Bias of microRNA Expression in Illumina Sequencing Analysis.xls

microRNA (miRNA) expression profiles based on the highly powerful Illumina sequencing technology rely on the construction of cDNA libraries in which adaptor ligation is known to deeply favor some miRNAs over others. This introduces erroneous measurements of the miRNA abundances and relative miRNA quantities in biological samples. Here, by using the commercial miRXplore Universal Reference that contains an equimolar mixture of 963 animal miRNAs and TruSeq or bulged adaptors, we describe a method for correcting ligation biases in expression profiles obtained with standard protocols of cDNA library construction and provide data for quantifying the true miRNA abundances in biological samples. Ligation biases were evaluated at three ratios of miRNA to 3′-adaptor and four numbers of polymerase chain reaction amplification cycles by calculating efficiency captures/correcting factors for each miRNA. We show that ligation biases lead to over- or under-expression covering a 105 amplitude range. We also show that, at each miRNA:3′-adaptor ratio, coefficients of variation (CVs) of efficiency captures calculated over the four number of amplification cycles using sliding windows of 10 values ranged from 0.1 for the miRNAs of high expression to 0.6 for the miRNAs of low expression. Efficiency captures of miRNAs of high and low expression in profiles are therefore differently impacted by the number of amplification cycles. Importantly, we observed that at a given number of amplification cycles, CVs of efficiency captures calculated over the three miRNA:3′-adaptor ratios displayed a steady value of 0.3 +/− 0.05 STD for miRNAs of high and low expression. This allows, at a given number of amplification cycles, accurate comparison of miRNA expression between biological samples over a substantial expression range. Finally we provide tables of correcting factors that allow to measure the abundances of 963 miRNAs in biological samples from TruSeq-based expression profiles and, an example of their use by characterizing miRNAs of the let-7, miR-26, miR-29, and miR-30 families as the more abundant miRNAs of the rat adult cerebellum.

基于高性能Illumina测序技术的微小RNA（microRNA, miRNA）表达谱分析，需依托cDNA文库的构建，而该过程中的接头连接步骤已知会对部分miRNA产生显著偏好性——相较于其他miRNA更倾向于优先连接特定miRNA，这会导致生物样本中miRNA丰度及相对含量的测量出现误差。本研究采用包含963种动物miRNA等摩尔混合物的商用miRXplore通用参考品，以及TruSeq接头或凸起接头，开发了一种可校正基于标准cDNA文库构建流程所获表达谱中连接偏好性的方法，并提供了用于定量生物样本中真实miRNA丰度的相关数据。

我们通过设置3种miRNA与3’接头的摩尔比、4种聚合酶链式反应（PCR）扩增循环数，针对每一种miRNA计算其捕获效率/校正因子，以此评估连接偏好性。研究发现，连接偏好性会导致表达量的高估或低估，其幅度范围可达10^5倍。此外，在每一种miRNA与3’接头的摩尔比条件下，基于4种扩增循环数、以10个值为滑动窗口计算得到的捕获效率变异系数（CV），在高表达miRNA中为0.1，在低表达miRNA中可达0.6。由此可见，扩增循环数对高、低表达miRNA的捕获效率影响存在差异。

值得注意的是，在固定的扩增循环数条件下，针对3种miRNA与3’接头摩尔比计算得到的捕获效率变异系数，在高、低表达miRNA中均稳定在0.3±0.05（标准差，STD）。这使得在固定扩增循环数的前提下，能够在较大的表达量范围内对不同生物样本的miRNA表达水平进行精准比较。最后，我们提供了校正因子表格，可用于基于TruSeq测序表达谱定量生物样本中963种miRNA的丰度，并通过将let-7、miR-26、miR-29及miR-30家族鉴定为大鼠成年小脑中丰度最高的miRNA，展示了该校正因子的应用实例。