GRHL and PGR control WNT4 expression in the mammary gland via 3D looping of conserved and species-specific enhancers [4C-Seq]

This dataset belongs to a study in which we functionally dissect the cis-acting enhancer network and spatiotemporal transcriptional mechanisms that regulate WNT4 expression in the mouse mammary gland and the human breast. As part of these efforts, we performed 4C chromatin conformation capture in BC44 and HC11 (two mouse mammary epithelial cell lines) using the Wnt4 promoter as a viewpoint. 1x10e6 BC44 or HC11 cells were crosslinked with 2% (v/v) formaldehyde in PBS/10% FBS for 10min at RT in 15cm cell culture dishes while shaking. Cells were isolated by using a cell scraper, lysed for 10min in lysis buffer and homogenized with a dounce-homogenizer. Nuclei were digested with 200U DpnII (NEB) in DpnII buffer (NEB) complemented with 0.3% SDS and 2% Triton X-100 for 4hr, an additional 200U DpnII O/N and another 200U DpnII for 4 hr the following day at 37C while shaking. The first ligation was performed with 100U T4 DNA ligase O/N at 16C in a total volume of 15ml. Following decrosslinking and phenol/chloroform extraction, the DNA was digested with NlaIII in Cutsmart buffer (NEB) O/N at 37C while shaking. After digestion a second ligation was carried out with T4 DNA ligase (Thermo Scientific) in a total volume of 15ml O/N at 16C. DNA was isolated via phenol/chloroform extraction and purified with the ChIP DNA Clean & Concentrator Kit (Zymo Research). 50-100ng DNA template per reaction and 1ug in total was used to amplify PCR-specific libraries for the Wnt4 promoter viewpoint with the Expand Long Template PCR system (Sigma) using specific primers. Successful reactions were pooled and purified with the High-pure PCR Product Purification Kit (Sigma). Equal amounts of libraries were combined, and all library preparation and sequencing steps were performed by MAD: Dutch Genomics Service & Support Provider, Swammerdam Institute for Life Sciences, University of Amsterdam. Paired-end sequencing (for cost-effectiveness, only single reads needed for analysis) was performed on a NextSeq550. For processing raw 4C-seq data, the publicly available 4C mapping pipeline for mapping (mm9) and filtering 4C data was used (https://github.com/deWitLab/4C_mapping) using default settings. The R package PeakC was used to analyze processed triplicates of 4C-seq data and identify significantly interacting regions within a window size of 400kb (https://github.com/deWitLab/peakC).