SnapShot: Chromosome Conformation Capture

SnapShot: Chromosome Conformation Capture

SnapShot: Chromosome Conformation Capture Ofir Hakim and Tom Misteli National Cancer Institute, NIH, Bethesda, MD 20892, USA CROSSLINK Protein Protei...

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SnapShot: Chromosome Conformation Capture Ofir Hakim and Tom Misteli National Cancer Institute, NIH, Bethesda, MD 20892, USA CROSSLINK Protein

Protein

CUTTING Endonuclease digestion Sonication Biotin dCTP fill in

LIGATION

Immunoprecipitation

Immunoprecipitation biotinilated linkers

B B B

B B

B

REVERSE CROSSLINKS

B

B

B

B

B

B

DETECTION

Multiplexed amplification

Digestion with four base cutter

Sonicate

Ligation

Pull down

Mmel digestion

B B

PCR with specific primers

PCR with universal primers

PCR with specific primers Inverse PCR

Pull down

B

Contact library

B

B

B

B B

COMPUTATIONAL ANALYSIS

Chromatin-associated factors Gene

3c

5c

Principle

Contacts between two defined regions3,17

All against all

Coverage

Commonly < 1Mb

Detection

Locus-specific PCR

Limitations

4c

Hi-c

All contacts with a point of interest14

All against all

Commonly < 1Mb

Genome-wide

HT-sequencing

HT-sequencing

Low throughput and coverage

Limited coverage

Limited to one viewpoint

Examples

Determine interaction between a known promoter and enhancer

Determine comprehensively higher-order chromosome structure in a defined region

All genes and genomic elements associated with a known LCR

All intra- and interchromosomal associations

Derivatives

PCR with TaqMan probes7 or melting curve analysis1

Circular chromosome conformation capture20, openended chromosome conformation capture19, inverse 3C12, associated chromosome trap (ACT)11, affinity enrichment of baitligated junctions2

Yeast 5,15, tethered conformation capture9

1068

4,18

Cell 148, March 2, 2012 ©2012 Elsevier Inc.

chIP-loop

chIA-PeT

Contacts between two defined regions associated with a given protein8

All contacts associated with a given protein6

Genome-wide

Commonly < 1Mb

Genome-wide

HT-sequencing

Locus-specific qPCR

HT-sequencing

10

Rely on one chromatin-associated factor, disregarding other contacts

DOI 10.1016/j.cell.2012.02.019

Determine the role of specific transcription factors in the interaction between a known promoter and enhancer

Map chromatin interaction network of a known transcription factor

ChIA-PET combined 3C-ChIP-cloning (6C),16 enhanced 4C (e4C)13

See online version for legend and references.

SnapShot: Chromosome Conformation Capture Ofir Hakim and Tom Misteli National Cancer Institute, NIH, Bethesda, MD 20892, USA The organization of the genome in the nuclear space is nonrandom and affects genome functions, including transcription, replication, and repair. Specific genomic regions, from the same or different chromosomes, frequently physically associate with each other and with nuclear structures, giving rise to an intricately compartmentalized nucleus. Examples of genome interactions are the association of an enhancer with a promoter or the clustering of genes such as rDNA genes in the nucleolus. Genome interactions have traditionally been studied using fluorescence in situ hybridization (FISH), which allows visualization of the spatial relationship between distinct genes or genome regions. Limitations of this method are that only known interactions can be interrogated, only very few loci can be probed in an experiment, and resolution is limited to the optics of the microscope. The family of chromosome conformation capture techniques is a set of biochemical approaches to determine the physical interaction of genome regions. C-technology approaches invariably involve five steps: (1) formaldehyde fixation to crosslink chromatin at sites of physical interaction, (2) cleavage of chromatin by restriction enzyme or sonication, (3) ligation under dilute conditions favoring ligation between DNA ends captured on the same complex over ligations from random collisions, (4) detection of ligation junctions using variable molecular biology steps depending on the variant of the methods, and (5) computational analysis to determine interaction frequencies captured in the ligation of the crosslinked chromatin. C-technologies (3C, 4C, 5C, Hi-C) differ in their manner of detection and scope of what interactions they can probe. The 3C method tests the interaction between two known sites in the genome, 4C allows probing of unknown interactors of a known bait sequence, 5C identifies all regions of interaction within a given genome domain, and Hi-C probes all occurring interactions in an unbiased fashion genome-wide. Additional variants (ChIA-PET, ChIP-Loop) incorporate a protein precipitation step, allowing identification of genome interactions that involve a specific protein of interest. The choice of method strongly depends on the specific nature and scope of the biological question, but also on the availability of resources, including the amount of starting material and sequencing capacity. Many derivatives of the standard C-techniques have been developed, often inspired by the specific biological question addressed or with the goal of improving specificity or reducing background. C-technologies are population-based methods. They produce relative contact probabilities rather than absolute contact frequencies. The population-based nature is due to the fact that each genomic locus gives one pair-wise ligation junction in one cell. To allow high coverage and quantitative appraisal of contact profiles, thousands to millions of genome equivalents (cells) containing multiple ligation junctions must be included and combined in each experiment. Correlations between C contacts and DNA FISH have indicated that an interchromosomal association that occurs in 3%–5% of cells in a population will typically be detected as positive in most C methods. More frequent associations generally result in stronger signals; however, the strength of signal may also reflect the affinity of the physical interactions and not its frequency. A critical step in data analysis is to determine whether an interaction, detected as a ligation junction, is specific. The contact frequency decreases exponentially and is inversely related to the linear genomic distance up to a few Mb away from the reference point. Therefore, the frequency of a specific contact in the vicinity of a locus is expected to be higher than the background of random collisions. A good indicator of specificity beyond the Mb range is the detection of a given interaction as clusters of signals from adjacent restriction fragments. The resolution of C methods is determined by the nature of the restriction enzyme(s) used and, in the case of methods that use sequencing for detection, also by the number of sequencing reads. The frequency of recognition sequences of a four base-pair (bp) endonuclease is, in principle, sixteen times higher than the frequency of recognition sequence of a six bp cutter. The use of a four bp cutter is expected to increase the resolution of contacts in the Mb range, where multiple ligation events are captured for specific contacts and the background collisions. Beyond this range, however, where clusters of restriction fragments define contact regions in the range of tens to hundreds of kb, the advantage of using a four bp cutter is expected to be diminished. Although many genome-wide assays have used dedicated microarrays, hi-throughput sequencing is becoming the method of choice for global detection of ligation junctions. Sequencing depth is a technical barrier for resolution in some approaches such as Hi-C and ChIA-PET. PCR-based technologies overcome this limitation by amplifying a subset of contacts, with the tradeoff of reduced coverage. The pairwise nature of ligation products imposes a power of two relationship between the increase in resolution and the increase in required sequencing depth. Genomic coverage per sequencing depth depends also on the size of the inspected genome. For example, similar sequencing power provides tens of kb contact resolution in yeast, but only Mb resolution in the human genome. References Abou El Hassan, M., and Bremner, R. (2009). A rapid simple approach to quantify chromosome conformation capture. Nucleic Acids Res. 37, e35.

1

Bantignies, F., Roure, V., Comet, I., Leblanc, B., Schuettengruber, B., Bonnet, J., Tixier, V., Mas, A., and Cavalli, G. (2011). Polycomb-dependent regulatory contacts between distant Hox loci in Drosophila. Cell 144, 214–226.

2

Dekker, J., Rippe, K., Dekker, M., and Kleckner, N. (2002). Capturing chromosome conformation. Science 295, 1306–1311.

3

Dostie, J., Richmond, T.A., Arnaout, R.A., Selzer, R.R., Lee, W.L., Honan, T.A., Rubio, E.D., Krumm, A., Lamb, J., Nusbaum, C., et al. (2006). Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements. Genome Res. 16, 1299–1309.

4

Duan, Z., Andronescu, M., Schutz, K., McIlwain, S., Kim, Y.J., Lee, C., Shendure, J., Fields, S., Blau, C.A., and Noble, W.S. (2010). A three-dimensional model of the yeast genome. Nature 465, 363–367.

5

Fullwood, M.J., Liu, M.H., Pan, Y.F., Liu, J., Xu, H., Mohamed, Y.B., Orlov, Y.L., Velkov, S., Ho, A., Mei, P.H., et al. (2009). An oestrogen-receptor-alpha-bound human chromatin interactome. Nature 462, 58–64.

6

Hagège, H., Klous, P., Braem, C., Splinter, E., Dekker, J., Cathala, G., de Laat, W., and Forné, T. (2007). Quantitative analysis of chromosome conformation capture assays (3C-qPCR). Nat. Protoc. 2, 1722–1733.

7

Horike, S., Cai, S., Miyano, M., Cheng, J.F., and Kohwi-Shigematsu, T. (2005). Loss of silent-chromatin looping and impaired imprinting of DLX5 in Rett syndrome. Nat. Genet. 37, 31–40.

8

Kalhor, R., Tjong, H., Jayathilaka, N., Alber, F., and Chen, L. (2011). Nat. Biotechnol. 30, 90–98.

9

Lieberman-Aiden, E., van Berkum, N.L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B.R., Sabo, P.J., Dorschner, M.O., et al. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293.

10

Ling, J.Q., Li, T., Hu, J.F., Vu, T.H., Chen, H.L., Qiu, X.W., Cherry, A.M., and Hoffman, A.R. (2006). CTCF mediates interchromosomal colocalization between Igf2/H19 and Wsb1/ Nf1. Science 312, 269–272.

11

12

Lomvardas, S., Barnea, G., Pisapia, D.J., Mendelsohn, M., Kirkland, J., and Axel, R. (2006). Interchromosomal interactions and olfactory receptor choice. Cell 126, 403–413.

Schoenfelder, S., Sexton, T., Chakalova, L., Cope, N.F., Horton, A., Andrews, S., Kurukuti, S., Mitchell, J.A., Umlauf, D., Dimitrova, D.S., et al. (2010). Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells. Nat. Genet. 42, 53–61.

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1068.e1  Cell 148, March 2, 2012 ©2012 Elsevier Inc.  DOI 10.1016/j.cell.2012.02.019

SnapShot: Chromosome Conformation Capture Ofir Hakim and Tom Misteli National Cancer Institute, NIH, Bethesda, MD 20892, USA References Simonis, M., Klous, P., Splinter, E., Moshkin, Y., Willemsen, R., de Wit, E., van Steensel, B., and de Laat, W. (2006). Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture-on-chip (4C). Nat. Genet. 38, 1348–1354.

14

Tanizawa, H., Iwasaki, O., Tanaka, A., Capizzi, J.R., Wickramasinghe, P., Lee, M., Fu, Z., and Noma, K. (2010). Mapping of long-range associations throughout the fission yeast genome reveals global genome organization linked to transcriptional regulation. Nucleic Acids Res. 38, 8164–8177.

15

16

Tiwari, V.K., and Baylin, S.B. (2009) Cold Spring Harb. Protoc. 2009, pdb.prot5168.

Tolhuis, B., Palstra, R.J., Splinter, E., Grosveld, F., and de Laat, W. (2002). Looping and interaction between hypersensitive sites in the active beta-globin locus. Mol. Cell 10, 1453–1465.

17

Umbarger, M.A., Toro, E., Wright, M.A., Porreca, G.J., Baù, D., Hong, S.H., Fero, M.J., Zhu, L.J., Marti-Renom, M.A., McAdams, H.H., et al. (2011). The three-dimensional architecture of a bacterial genome and its alteration by genetic perturbation. Mol. Cell 44, 252–264.

18

Würtele, H., and Chartrand, P. (2006). Genome-wide scanning of HoxB1-associated loci in mouse ES cells using an open-ended Chromosome Conformation Capture methodology. Chromosome Res. 14, 477–495.

19

Zhao, Z., Tavoosidana, G., Sjölinder, M., Göndör, A., Mariano, P., Wang, S., Kanduri, C., Lezcano, M., Sandhu, K.S., Singh, U., et al. (2006). Circular chromosome conformation capture (4C) uncovers extensive networks of epigenetically regulated intra- and interchromosomal interactions. Nat. Genet. 38, 1341–1347.

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1068.e2  Cell 148, March 2, 2012 ©2012 Elsevier Inc.  DOI 10.1016/j.cell.2012.02.019