Since the introduction of next generation sequencing technologies, the field of epigenomics has evolved rapidly. However, most commonly used assays are enrichment-based methods and thus only semi-quantitative. Nucleosome occupancy and methylome sequencing (NOMe-seq) allows for quantitative inference of chromatin states with single locus resolution, but this requires high sequencing depth and is therefore prohibitively expensive to routinely apply to organisms with large genomes. To overcome this limitation, we introduce guidedNOMe-seq, where we combine NOMe profiling with large scale sgRNA synthesis and Cas9-mediated region-of-interest (ROI) liberation. To facilitate quantitative comparisons between multiple samples, we additionally develop an R package to standardize differential analysis of any type of NOMe-seq data. We extensively benchmark guidedNOMe-seq in a proof-of-concept study, dissecting the interplay of ChAHP and CTCF on chromatin. In summary we present a cost-effective, scalable, and customizable target enrichment extension to the existing NOMe-seq protocol allowing genome-scale quantification of nucleosome occupancy and transcription factor binding at single allele resolution.
guidedNOMe-seq quantifies chromatin states at single allele resolution for hundreds of custom regions in parallel.
guidedNOMe-seq 可以并行地对数百个自定义区域进行单等位基因分辨率的染色质状态定量分析
阅读:3
作者:Schwaiger Michaela, Mohn Fabio, Bühler Marc, Kaaij Lucas J T
| 期刊: | BMC Genomics | 影响因子: | 3.700 |
| 时间: | 2024 | 起止号: | 2024 Jul 29; 25(1):732 |
| doi: | 10.1186/s12864-024-10625-3 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
