鉴定和纠正小 RNA 深度测序中 RNA 连接酶活性的偏倚。

Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing.

机构信息

Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.

出版信息

Nucleic Acids Res. 2011 Nov;39(21):e141. doi: 10.1093/nar/gkr693. Epub 2011 Sep 2.

Abstract

Deep sequencing of small RNAs (sRNA-seq) is now the gold standard for small RNA profiling and discovery. Biases in sRNA-seq have been reported, but their etiology remains unidentified. Through a comprehensive series of sRNA-seq experiments, we establish that the predominant cause of the bias is the RNA ligases. We further demonstrate that RNA ligases have strong sequence-specific biases which distort the small RNA profiles considerably. We have devised a pooled adapter strategy to overcome this bias, and validated the method through data derived from microarray and qPCR. In light of our findings, published small RNA profiles, as well as barcoding strategies using adapter-end modifications, may need to be revisited. Importantly, by providing a wide spectrum of substrate for the ligase, the pooled-adapter strategy developed here provides a means to overcome issues of bias, and generate more accurate small RNA profiles.

摘要

深度测序的小 RNA(sRNA-seq)现在是小 RNA 分析和发现的金标准。已经报道了 sRNA-seq 的偏差,但它们的病因仍不清楚。通过一系列全面的 sRNA-seq 实验,我们确定了主要的偏差原因是 RNA 连接酶。我们进一步证明,RNA 连接酶具有强烈的序列特异性偏差,这极大地扭曲了小 RNA 图谱。我们设计了一种汇集衔接子的策略来克服这种偏差,并通过来自微阵列和 qPCR 的数据验证了该方法。鉴于我们的发现,发表的小 RNA 图谱,以及使用衔接子末端修饰的条形码策略,可能需要重新考虑。重要的是,通过为连接酶提供广泛的底物谱,这里开发的汇集衔接子策略提供了一种克服偏差问题并生成更准确的小 RNA 图谱的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/764e/3241666/b614b85e09bb/gkr693f1.jpg

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