Bioinformatics Graduate Program, Boston University, Boston, Massachusetts 02215, USA Section of Computational Biomedicine, Boston University Medical Center, Boston, Massachusetts 02118, USA.
Section of Computational Biomedicine, Boston University Medical Center, Boston, Massachusetts 02118, USA.
RNA. 2015 Feb;21(2):164-71. doi: 10.1261/rna.046060.114. Epub 2014 Dec 17.
Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log2 number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.
小 RNA 测序可以提供前所未有的 miRNA 转录组细节。测序碱基技术相对较高的成本和较低的通量可以通过多重化来弥补。然而，多重化涉及到增加测序样本数量和减少每个样本的读取数（即降低覆盖深度）之间的权衡。为了评估由于多重化导致的不同测序深度对 miRNA 差异表达和检测的影响，我们使用 Illumina HiSeq 2000 对临床采集的肺组织样本的小 RNA 进行了多重化测序，每个泳道的样本数分别为 1、3、6、9 或 12。如预期的那样，随着多重化样本数量的增加，每个样本获得的读数数量减少。此外，在归一化后，来自不同多重化的重复样本高度相关（R > 0.97）。在检测样本组之间的差异 miRNA 表达时，平均表达> 1 每百万（RPM）的 miRNA 具有与多重化程度无关的可重复倍数变化估计值（信号与噪声）。检测到的 miRNA 数量与对齐到 miRNA 基因座的 log2 读取数强烈相关（R = 0.96）。然而，在测序深度更大的样本中检测到的大多数额外 miRNA 处于具有较低倍数变化可重复性的表达范围内。这些发现阐明了在降低测序深度的情况下增加多重化样本数量与降低测序深度之间的权衡，并将有助于设计大规模的临床研究，探索 miRNA 表达及其在疾病中的作用。
