Abstract
Hi-C is a methodology developed to reveal chromosomal interactions from a genome-wide perspective. Here, we described a protocol for generating Hi-C sequencing libraries in resting and activated human naive CD4 T cells to investigate activation-induced chromatin structure re-arrangement in T cell activation followed by a section reviewing the general concepts of Hi-C data analysis.
References
Tessarz P, Kouzarides T (2014) Histone core modifications regulating nucleosome structure and dynamics. Nat Rev Mol Cell Biol 15(11):703–708
Negre N et al (2011) A cis-regulatory map of the drosophila genome. Nature 471(7339):527–531
Li G et al (2012) Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell 148(1–2):84–98
Apostolou E et al (2013) Genome-wide chromatin interactions of the Nanog locus in pluripotency, differentiation, and reprogramming. Cell Stem Cell 12(6):699–712
Dekker J, Rippe K, Dekker M, Kleckner N (2002) Capturing chromosome conformation. Science 295(5558):1306–1311
Weiner BM, Kleckner N (1994) Chromosome pairing via multiple interstitial interactions before and during meiosis in yeast. Cell 77(7):977–991
Lieberman-Aiden E et al (2009) Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326(5950):289–293
Dixon JR et al (2015) Chromatin architecture reorganization during stem cell differentiation. Nature 518(7539):331–336
Dixon JR et al (2012) Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485(7398):376–380
Rao SS et al (2014) A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159(7):1665–1680
Jin F et al (2013) A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature 503(7475):290–294
Duan Z et al (2012) A genome-wide 3C-method for characterizing the three-dimensional architectures of genomes. Methods 58(3):277–288
Li W, Gong K, Li Q, Alber F, Zhou XJ (2015) Hi-corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data. Bioinformatics 31(6):960–962
Hu M et al (2012) HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinformatics 28(23):3131–3133
Servant N et al (2015) HiC-pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol 16:259
Lun AT, Smyth GK (2015) diffHic: a bioconductor package to detect differential genomic interactions in Hi-C data. BMC Bioinformatics 16:258
Sauria ME, Phillips-Cremins JE, Corces VG, Taylor J (2015) HiFive: a tool suite for easy and efficient HiC and 5C data analysis. Genome Biol 16:237
Heinz S et al (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38(4):576–589
Hu M et al (2013) Bayesian inference of spatial organizations of chromosomes. PLoS Comput Biol 9(1):e1002893
Lajoie BR, Dekker J, Kaplan N (2015) The Hitchhiker's guide to Hi-C analysis: practical guidelines. Methods 72:65–75
Dekker J, Marti-Renom MA, Mirny LA (2013) Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data. Nat Rev Genet 14(6):390–403
Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10(3):R25
Li R, Li Y, Kristiansen K, Wang J (2008) SOAP: short oligonucleotide alignment program. Bioinformatics 24(5):713–714
Imakaev M et al (2012) Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat Methods 9(10):999–1003
Acknowledgment
This is dedicated to the memory of Dr. Daniel R. Salomon. This work was supported by NIH grant 5U19 AI063603 and Mendez National Institute of Transplantation Foundation.
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Meng, X., Riley, N., Thompson, R., Sharma, S. (2018). Investigate Global Chromosomal Interaction by Hi-C in Human Naive CD4 T Cells. In: Head, S., Ordoukhanian, P., Salomon, D. (eds) Next Generation Sequencing. Methods in Molecular Biology, vol 1712. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7514-3_15
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DOI: https://doi.org/10.1007/978-1-4939-7514-3_15
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