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The linear sequence of the genome has been extremely valuable in mapping regulatory elements relative to the genes they control. However, it has become increasingly evident that characterizing the three-dimensional organization of the genome is critical to get a better understanding of long-range regulation. Early studies using fluorescent in situ hybridization (FISH) revealed that individual chromosomes occupy distinct spaces in the nucleus with minimal intermingling between territories [1]. Recent advances using chromosome conformation capture (3C) techniques have confirmed these findings and further improved the depth at which we can determine the organization of chromosomes and the physical interactions that occur within and between them [2,3]. Variations of the 3C technique include: Hi-C, to capture all pair-wise interactions; 5C, to capture interactions within and between loci of interest; and 4C-Seq, to capture all interactions with a single locus of interest. The choice of technique depends on the biological question being asked and the scale at which this needs to be examined. While Hi-C has been instrumental in characterizing higher-order organization of chromosomes in the nucleus, it lacks the resolution that is required for analysis of specific interactions, such as between enhancers and promoters. This can be achieved with 4C-Seq, which allows interrogation of interactions from a single viewpoint or bait, to the rest of the genome. Several studies have used 4C-Seq to better understand phenomena such as X chromosome inactivation [4], enhancer-promoter interactions [5,6], organization of antigen receptor loci [7], choice of translocation partners [8,9] and collinear transcriptional regulation [10]. Here we aim to focus on the current state of the 4C-Seq method and the limitations and challenges of the associated computational analysis.
Analysis of 4C-Seq data can be complicated by several technical biases intrinsic to the method. The first bias to consider is that the majority of 4C-seq signal is found on the bait chromosome with lower coverage in trans . This bias does not represent noise but is in agreement with the chromosome territory model, which would predict fewer interchromosomal interactions than intrachromosomal interactions. Second, there is a decrease in signal along the cis chromosome as a function of distance from the bait. Third, similar to other 3C-based techniques, 4C-Seq relies on using restriction enzymes to digest the chromatin, and the frequency of...