Genomics

Dataset Information

0

Fine Resolution Mapping of TF binding and Chromatin Interactions


ABSTRACT: Monitoring the location of transcription factors (TFs) binding to DNA is key to understanding transcriptional regulation. The main tool for mapping TF binding is ChIP-seq and its variants. However, current ChIP-based methods are hampered by at least one of the following limitations: large input requirements, low spatial resolution, and limited compatibility with high-throughput automation. Here, we describe SLIM-ChIP (Short fragment enriched, Low input, Indexed, MNase ChIP), which overcomes these challenges by combining enzymatic fragmentation of chromatin and on-bead indexing of immobilized TF-DNA complexes. We show that SLIM-ChIP reproduces high resolution binding map of yeast Reb1 similarly to the high-resolution TF mapping methods ChIP-exo and ORGANIC. Yet, SLIM-ChIP requires substantially less input material, and is fully compatible with high-throughput procedures. We further demonstrate the robustness and flexibility of SLIM-ChIP by probing Abf1 and Rap1 in yeast and CTCF in mouse embryonic stem cells. Finally, we show that the unique combination of high resolution and preservation of DNA protection patterns by SLIM-ChIP provide an additional layer of information on the chromatin landscape surrounding the bound TF. We used this information to identify a class of Reb1 sites in which the proximal -1 nucleosome tightly interacts with Reb1 and unlike in most Reb1 sites is refractory to remodeling by the RSC complex. Importantly, the interaction of Reb1 with the -1 nucleosome prevents transcription initiation and can serve as a more general mechanism for maintaining unidirectional transcription. Altogether, SLIM-ChIP is an attractive solution for mapping DNA binding proteins in a more informative context regarding their surrounding chromatin occupancy landscape at a single cell level.

ORGANISM(S): Mus musculus Saccharomyces cerevisiae

PROVIDER: GSE108948 | GEO | 2018/03/06

REPOSITORIES: GEO

Similar Datasets

2013-12-14 | E-GEOD-45672 | biostudies-arrayexpress
2021-12-31 | GSE183622 | GEO
| PRJNA238170 | ENA
2013-12-14 | GSE45672 | GEO
| PRJEB4933 | ENA
| PRJNA429230 | ENA
2015-09-04 | E-GEOD-67869 | biostudies-arrayexpress
| PRJNA266322 | ENA
| PRJNA327876 | ENA
2014-03-10 | E-GEOD-54963 | biostudies-arrayexpress