Halász László, Karányi Zsolt, Boros-Oláh Beáta, Kuik-Rózsa Tímea, Sipos Éva, Nagy Éva, Mosolygó-L Ágnes, Mázló Anett, Rajnavölgyi Éva, Halmos Gábor, Székvölgyi Lóránt
MTA-DE Momentum, Genome Architecture and Recombination Research Group, Research Centre for Molecular Medicine, University of Debrecen, 4032 Debrecen, Hungary.
Department of Biochemistry and Molecular Biology, University of Debrecen, 4032 Debrecen, Hungary.
Genome Res. 2017 Jun;27(6):1063-1073. doi: 10.1101/gr.219394.116. Epub 2017 Mar 24.
The impact of R-loops on the physiology and pathology of chromosomes has been demonstrated extensively by chromatin biology research. The progress in this field has been driven by technological advancement of R-loop mapping methods that largely relied on a single approach, DNA-RNA immunoprecipitation (DRIP). Most of the DRIP protocols use the experimental design that was developed by a few laboratories, without paying attention to the potential caveats that might affect the outcome of RNA-DNA hybrid mapping. To assess the accuracy and utility of this technology, we pursued an analytical approach to estimate inherent biases and errors in the DRIP protocol. By performing DRIP-sequencing, qPCR, and receiver operator characteristic (ROC) analysis, we tested the effect of formaldehyde fixation, cell lysis temperature, mode of genome fragmentation, and removal of free RNA on the efficacy of RNA-DNA hybrid detection and implemented workflows that were able to distinguish complex and weak DRIP signals in a noisy background with high confidence. We also show that some of the workflows perform poorly and generate random answers. Furthermore, we found that the most commonly used genome fragmentation method (restriction enzyme digestion) led to the overrepresentation of lengthy DRIP fragments over coding ORFs, and this bias was enhanced at the first exons. Biased genome sampling severely compromised mapping resolution and prevented the assignment of precise biological function to a significant fraction of R-loops. The revised workflow presented herein is established and optimized using objective ROC analyses and provides reproducible and highly specific RNA-DNA hybrid detection.
染色质生物学研究已广泛证明了R环对染色体生理和病理的影响。该领域的进展得益于R环作图方法的技术进步,这些方法很大程度上依赖于单一方法——DNA-RNA免疫沉淀(DRIP)。大多数DRIP方案采用的是少数实验室开发的实验设计,而没有关注可能影响RNA-DNA杂交作图结果的潜在问题。为了评估该技术的准确性和实用性,我们采用了一种分析方法来估计DRIP方案中固有的偏差和误差。通过进行DRIP测序、qPCR和受试者工作特征(ROC)分析,我们测试了甲醛固定、细胞裂解温度、基因组片段化模式以及游离RNA去除对RNA-DNA杂交检测效率的影响,并实施了能够在嘈杂背景中高置信度区分复杂和微弱DRIP信号的工作流程。我们还表明,一些工作流程表现不佳并产生随机结果。此外,我们发现最常用的基因组片段化方法(限制性酶切消化)导致编码开放阅读框(ORF)上长DRIP片段的过度富集,并且这种偏差在第一个外显子处增强。有偏差的基因组采样严重损害了作图分辨率,并阻碍了将精确的生物学功能赋予相当一部分R环。本文提出的修订工作流程是使用客观的ROC分析建立和优化的,可提供可重复且高度特异性的RNA-DNA杂交检测。