University of Massachusetts Medical School Faculty Publications
UMMS Affiliation
Program in Systems Biology; Department of Biochemistry and Molecular Pharmacology
Publication Date
2016-11-27
Document Type
Article Preprint
Disciplines
Biochemistry | Computational Biology | Genetic Phenomena | Genomics | Structural Biology | Systems Biology
Abstract
Chromosome conformation capture-based methods such as Hi-C have become mainstream techniques for the study of the 3D organization of genomes. These methods convert chromatin interactions reflecting topological chromatin structures into digital information (counts of pair-wise interactions). Here, we describe an updated protocol for Hi-C (Hi-C 2.0) that integrates recent improvements into a single protocol for efficient and high-resolution capture of chromatin interactions. This protocol combines chromatin digestion and frequently cutting enzymes to obtain kilobase (Kb) resolution. It also includes steps to reduce random ligation and the generation of uninformative molecules, such as unligated ends, to improve the amount of valid intra-chromosomal read pairs. This protocol allows for obtaining information on conformational structures such as compartment and TADs, as well as high-resolution conformational features such as DNA loops.
Keywords
Hi-C, chromosome conformation capture, paired-end sequencing, genomics
Rights and Permissions
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.
DOI of Published Version
10.1101/090001
Source
bioRxiv 090001; doi: https://doi.org/10.1101/090001. Link to preprint on bioRxiv service.
Related Resources
Now published in Methods; doi:10.1016/j.ymeth.2017.04.004
Journal/Book/Conference Title
bioRxiv
Repository Citation
Belaghzal H, Dekker J, Gibcus JH. (2016). HI-C 2.0: An Optimized Hi-C Procedure for High-Resolution Genome-Wide Mapping of Chromosome Conformation [preprint]. University of Massachusetts Medical School Faculty Publications. https://doi.org/10.1101/090001. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1537
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Included in
Biochemistry Commons, Computational Biology Commons, Genetic Phenomena Commons, Genomics Commons, Structural Biology Commons, Systems Biology Commons