The 4C technique: the ‘Rosetta stone’ for genome biology in 3D?

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Despite considerable efforts, the spatial link between the nuclear architecture and the genome remains enigmatic. The 4C method, independently innovated in four different laboratories, might in combination with other methods change that. As this method is based on the unbiased identification of sequences interacting with specific baits, there are unique opportunities for unravelling the secrets of how the genome functions in 3D.

Introduction

As this issue of Current Opinion in Cell Biology makes abundantly clear, pivotal nuclear processes, such as gene transcription, RNA processing and replication, are all likely to be affected by how the chromosomes are folded and how they interact with each other in interphase nuclei. Much of the earlier progress in this research area has been made by DNA/RNA FISH analysis comparing physical proximity with structural hallmarks of the nucleus [1, 2]. The major pitfall of the FISH method, namely its low resolution, was avoided by the invention of the 3C method [3]. This approach has proven very useful to detect very close physical proximity of interacting sequences from remote locations within formaldehyde-crosslinked chromatin [4, 5•, 6, 7, 8]. However, the 3C approach does not allow screening of interactions without prior knowledge of two different interacting sequences. To deal with this shortcoming, four laboratories each independently developed an unbiased variant of the 3C method: circular 3C [9••], 3C-on-chip [10••], open-ended 3C [11] and ‘olfactory receptor’ 3C [12]. For simplification, these methods are here collectively termed ‘4C’, with the common sequence of interest being termed ‘bait’ and the interacting sequences ‘interactors’. Two additional methods, termed ACT [13] and 5C [14], also study unknown interactions from known baits. Although an interesting option, the 5C method has yet to be tested in genome-wide screens. As the ACT method failed to document numerous intra-chromosomal interactions that both 3C [8] and 4C [9••] analyses have documented, it clearly has limitations not experienced with the 4C method.

Here we review the 4C technique and its potential to resolve some of the old and new enigmas associated with the genome function in the 3D perspective.

Section snippets

The 4C technique: opportunities and pitfalls

All the 4C methods have one feature in common: the generation of circular DNA molecules under favourable conditions (Figure 1, Table 1). The generation of circular DNA and the strategic positioning of inverse primers within the bait allow the amplification of interacting DNA sequences without any prior knowledge of their identities. Despite the similar strategies used, the methods differ fundamentally in their details, such as what restriction enzyme(s) are used, at what stage the circular DNA

A web of chromosomal interactions

Despite these and other pitfalls of the different 4C methods (see also footnote to Table 1), several salient features of the interactors have been emerging. Common to all the 4C and 5C results is the conclusion that the closer the sequences are to each other along the linear DNA, the higher the frequency of interaction. While this conclusion seems logical, high-resolution 4C analysis using Mse I (recognizing 4-bp sites) reveals that the issue is more complex than that. Thus, although relatively

Outlook

While the 4C technology undoubtedly provides great opportunities for understanding how the genome functions in the 3D context, the few studies using this technique have only scratched the surface. For example, the H19 ICR baits, encompassing a mere 1.5 kb, have uncovered an accumulated number of genome-wide interactors that exceeds 1100 (Zhao et al., unpublished). By extrapolation, the genome might be capable of establishing tens of millions of different physical interactions in a single

Disclosure

Rolf Ohlsson and colleagues have applied for a patent on the 4C technology discussed in the article.

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

Acknowledgements

This work was supported by the Swedish Science Research Council, the Swedish Cancer Research Foundation, the Swedish Pediatric Cancer Foundation, HEROIC and the Lundberg Foundation.

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