Chromosome conformation capture (3C) assays are used to map chromatin interactions genome-wide. Chromatin interaction maps provide insights into the spatial organization of chromosomes and the mechanisms by which they fold. Hi-C and Micro-C are widely used 3C protocols that differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a systematic evaluation of 3C experimental parameters. We identified optimal protocol variants for either loop or compartment detection, optimizing fragment size and cross-linking chemistry. We used this knowledge to develop a greatly improved Hi-C protocol (Hi-C 3.0) that can detect both loops and compartments relatively effectively. In addition to providing benchmarked protocols, this work produced ultra-deep chromatin interaction maps using Micro-C, conventional Hi-C and Hi-C 3.0 for key cell lines used by the 4D Nucleome project.
Akgol Oksuz B • Yang L • Abraham S • Venev SV • Krietenstein N • Parsi KM • Ozadam H • Oomen ME • Nand A • Mao H • Genga RMJ • Maehr R • Rando OJ • Mirny LA • Gibcus JH • Dekker J
All experimental conditions investigated are reported here for documentation purposes. Users interested in using Hi-C or Micro-C data from this project for alternative analyses are advised to use only datasets generated with the optimal cross-linking conditions of 1% Formaldehyde + 3mM DSG. Other datasets may be obtained with non-optimal cross-linking conditions (as demonstrated in the paper). The authors further advise users to carefully select digestion enzymes and library size to fit their needs.
Datasets from optimized protocols at high sequencing depth
For deeply sequenced data, the study authors recommend the following datasets for in situ Hi-C 3.0 (with cross-linking 1% Formaldehyde and 3mM DSG, enzymes DpnII and DdeI) and Micro-C (with cross-linking 1% Formaldehyde and 3mM DSG):
Other datasets with optimal cross-linking
For other conditions with optimal cross-linking (1% Formaldehyde and 3mM DSG), the study authors advise the following datasets (note that most have lower sequencing depth):