Department of Epigenetics and Molecular Carcinogenesis The University of Texas MD Anderson Cancer Center Science ParkSmithvilleTexas78957 USA.
Present Address: College of Biology Hunan University Changsha410082 China.
J Biomol Tech. 2022 Nov 14;33(3). doi: 10.7171/3fc1f5fe.7910785e. eCollection 2022 Oct 15.
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) is a powerful method commonly used to study global protein-DNA interactions including both transcription factors and histone modifications. We have found that the choice of ChIP-Seq library preparation protocol plays an important role in overall ChIP-Seq data quality. However, very few studies have compared ChIP-Seq libraries prepared by different protocols using multiple targets and a broad range of input DNA levels.
In this study, we evaluated the performance of 4 ChIP-Seq library preparation protocols (New England Biolabs [NEB] NEBNext Ultra II, Roche KAPA HyperPrep, Diagenode MicroPlex, and Bioo [now PerkinElmer] NEXTflex) on 3 target proteins, chosen to represent the 3 typical signal enrichment patterns in ChIP-Seq experiments: sharp peaks (H3K4me3), broad domains (H3K27me3), and punctate peaks with a protein binding motif (CTCF). We also tested a broad range of different input DNA levels from 0.10 to 10 ng for H3K4me3 and H3K27me3 experiments.
Our results suggest that the NEB protocol may be better for preparing H3K4me3 (and potentially other histone modifications with sharp peak enrichment) libraries; the Bioo protocol may be better for preparing H3K27me3 (and potentially other histone modifications with broad domain enrichment) libraries, and the Diagenode protocol may be better for preparing CTCF (and potentially other transcription factors with well-defined binding motifs) libraries. For ChIP-Seq experiments using novel targets without a known signal enrichment pattern, the NEB protocol might be the best choice, as it performed well for each of the 3 targets we tested across a wide array of input DNA levels.
染色质免疫沉淀结合高通量测序(ChIP-Seq)是一种常用的研究方法,用于研究包括转录因子和组蛋白修饰在内的全局蛋白质-DNA 相互作用。我们发现,ChIP-Seq 文库制备方案的选择对整体 ChIP-Seq 数据质量起着重要作用。然而,很少有研究比较过使用多种靶标和广泛的输入 DNA 水平,通过不同的方案制备 ChIP-Seq 文库。
在这项研究中,我们评估了 4 种 ChIP-Seq 文库制备方案(New England Biolabs [NEB] NEBNext Ultra II、Roche KAPA HyperPrep、Diagenode MicroPlex 和 Bioo [现为 PerkinElmer] NEXTflex)在 3 种靶标蛋白上的性能,这 3 种靶标蛋白分别代表了 ChIP-Seq 实验中 3 种典型的信号富集模式:尖锐峰(H3K4me3)、宽域(H3K27me3)和具有蛋白结合基序的点状峰(CTCF)。我们还测试了 H3K4me3 和 H3K27me3 实验中从 0.10 到 10ng 的广泛不同的输入 DNA 水平。
我们的结果表明,NEB 方案可能更适合制备 H3K4me3(和可能具有尖锐峰富集的其他组蛋白修饰)文库;Bioo 方案可能更适合制备 H3K27me3(和可能具有宽域富集的其他组蛋白修饰)文库,而 Diagenode 方案可能更适合制备 CTCF(和可能具有明确定义的结合基序的其他转录因子)文库。对于使用新型靶标且没有已知信号富集模式的 ChIP-Seq 实验,NEB 方案可能是最佳选择,因为它在我们测试的 3 种靶标中,在广泛的输入 DNA 水平范围内表现良好。