5C analysis of the Epidermal Differentiation Complex locus reveals distinct chromatin interaction networks between gene-rich and gene-poor TADs in skin epithelial cells

In the mouse genome, there are 33 large (more than 0.5 Mbp) lineage-specific gene loci containing at least 10 functionally related genes [27–29] (Fig 1). Large lineage-specific gene loci are present on a vast majority of chromosomes and harbour the olfactory receptor family genes (chromosomes 2, 7, 9, 10, 14, 16, 17, 19), immunoglobulin kappa and heavy chain genes (chromosomes 6 and 12, respectively), keratinocyte-specific genes (chromosomes 3, 11, 15 and 16), as well as some other gene families (Fig 1A and 1B).

To correlate the genomic location of such loci to the distinct TADs genome-wide, we used the TAD maps generated using Hi-C technology for mouse embryonic stem cells [9]. Interestingly, this analysis revealed that among 24 lineage-specific loci occupying between 0.5–1.6 Mbs in the genome, 21 loci were localized within single TADs on the corresponding chromosomes, while only 3 loci were spread between two neighbouring TADs (Fig 1A and 1B). Epithelial-specific gene loci, such as Keratin type I and type II [KtyI/II] loci, Keratin-associated protein [KAP] locus having size between 0.75–1 Mbs, were localized within individual TADs on mouse chromosomes 11, 15 and 16, respectively (Fig 1B).

However, 100% lineage-specific loci of larger size (>1.6 Mb) including Epidermal Differentiation Complex [EDC] locus [34] were occupying several (from two to four) TADs on the corresponding chromosomes (Fig 1A and 1B). Because TADs were defined as genomic regions with a higher frequency of spatial contacts within the domains compared to inter-domain interactions [9, 10, 12], these data raised the questions whether large multi-TAD lineage-specific gene loci display any unique features in the chromatin interaction patterns between functionally related genes localized in different TADs and how such interactions are regulated.

To address this question, we focused on the EDC locus occupying ~3.1 Mb in one of the most gene-dense regions of mouse chromosome 3 [29]. Its central domain consists of the co-regulated genes involved in the control of terminal keratinocyte differentiation and epidermal barrier acquisition, including Loricrin (Lor), the Small proline-rich (Sprr) gene family, Involucrin (Ivl), Late cornified envelope (Lce) gene family and Fillagrin-like (Flg-like) gene family [33, 36, 38] (Fig 2A). The S100 family genes flank the 5’- and 3’-ends of the EDC [38] (Fig 2A). In addition to the gene-rich domains, the EDC locus in mice contains a gene-poor region (“desert”) separating the part of S100 family genes at 5’ of the EDC and the Lor gene at central EDC domain, while another gene-poor domain separates the 3’-flank of the EDC from the neighbouring gene-rich domain on chromosome 3 (Fig 2A, S1 Table).

To study the potential connection between gene activity and spatial chromatin folding in the EDC locus at higher resolution, we correlated gene expression determined by microarray profiling with data obtained with Chromosome Conformation Capture Carbon Copy (5C) technology in freshly plated neonatal epidermal keratinocytes. Consistently with the data demonstrating specific roles for many genes that constitute the central EDC domain in the control of epidermal barrier formation [39–42], microarray showed that in epidermal keratinocytes most of these genes were expressed at much higher levels compared to thymocytes, used as the control in which those genes were inactive (S1A Fig, S1 Table).

5C is well-suited for analyses of the spatial genome folding, as it allows the simultaneous detection of the spatial chromatin looping contacts and identification of TADs [17, 43]. For the 5C analysis, 381 forward and 382 reverse 5C probes were designed in an alternating scheme using the tools from my5C software suite [44] to interrogate HindIII sites with the unique anchoring regions at the EDC and its flanking regions (mm9, chromosome 3: 89.9–95.2 Mbp) (Fig 2B, S2 Table). The designed probe pool interrogated 145,542 potential pair-wise spatial chromatin contacts within this 5.3 Mbp genomic region. Two biological 5C library replicates were generated and analyzed for each cell type.

Consistently with previous studies using 5C and Hi-C technologies [9–11, 45], the raw 5C data for both replicates (shown as heatmaps with all reverse probes plotted as columns and forward probes as rows (Fig 2C, S1B Fig), clearly demonstrated that neighbouring chromatin regions interact to each other frequently, creating a black “diagonal” in the middle part of the heatmaps. Raw 5C data showed high similarity between the biological replicates for both cell lineages (Fig 2C, S1B Fig), and the raw 5C counts highly correlated between the replicates (for keratinocyte libraries—Pearson correlation coefficient 0.88; for thymocyte libraries—Pearson correlation coefficient 0.94), indicating a high quality of our 5C data (Fig 2C, S1B Fig). However, the correlations between the keratinocyte and thymocyte libraries were much lower (Pearson correlation coefficient 0.61), indicating lineage-specific differences in folding of the locus between both cell types.

Correction of the 5C data for non-biological biases associated with this technology was performed as described previously [17, 43] (see Materials and Methods for details) (S2–S5 Figs). The corrected data were binned (bin size 150kb with the step size of 15kb) to account for the differences in the 5C probe coverage in the different parts of the 5.3 Mbp genomic region (Fig 2D, S2E Fig, S3E Fig, S4E Fig, S5E Fig and S6A Fig). The heatmaps representing 5C data clearly showed several consecutive chromatin regions with high spatial self-associations (visible as darker “triangles” above a black “diagonal”) corresponding to the distinct TADs in keratinocytes and thymocytes (Fig 2D, S6A Fig) [9, 10, 17]. To define the positions of the TAD boundaries, we performed the insulation index analysis on each replicate data set separately, as described elsewhere [17, 46] (see Materials and Methods for details) (Fig 2D, S6A Fig, S3 Table). This analysis identified the boundaries separating TADs in the 5.3 Mbp region in keratinocytes and thymocytes (Fig 2D, S3 Table). The accuracy of the TAD boundary calculations performed by comparing the determined boundary midpoint positions between the replicates (S3 Table) indicated that TAD boundary positions were determined with the accuracy of about +/- 100 kb.

5C data revealed that 5.3 Mbp chromatin domain containing EDC locus on mouse chromosome 3 is organized into seven distinct TADs (Fig 2D, S3 Table). We calculated density of the protein-coding genes in these TADs and correlated the results to the average gene density in the mouse genome (75 kb per gene). Based on these analyses, we defined the gene-rich (21–36 Kb per gene) and gene-poor (166–400 Kb per gene) TADs in the EDC locus (S1 and S3 Tables). 5’-flanking region of the EDC locus containing the S100 family genes constituted the part of the gene-rich TAD1, which also harbours neighbouring non-EDC genes including the house-keeping Rps27 gene. Gene-poor domain of the EDC separating S100 family genes from its central domain constituted the TAD2. In turn, the central EDC domain and its 3’ flank region were organized into two distinct TADs: Lor gene was located at the boundary between TAD2 and TAD3, which also contained the Ivl gene, Sprr gene family and the major part of the Lce gene family, while TAD4 encompassing the remaining part of the Lce gene family, Flg-like gene family, 3’-flanking part of S100 gene family, and the part of Tdpoz gene family. The chromatin domain located further outside of the 3’-end of the EDC locus was organized into gene-poor TAD5 containing the remaining part of the Tdpoz gene family, as well as into gene-rich TAD6 and part of the TAD7, respectively (Fig 2D, S3 Table).

These data were quite consistent with the Hi-C data obtained from mouse embryonic stem cells [9] (Fig 1B, S1 Table), as well as with 5C data obtained from thymocytes. In thymocytes, the border between TAD T1 and TAD T2 (90.8 Mb), as well as between TAD T2 and TAD T3 (92.1 Mb) were only slightly shifted compared to keratinocytes (90.7 Mb and 90.9 Mb, respectively) (S6A and S3 Tables). Similar to keratinocytes, the central EDC domain in thymocytes was organized into TAD3 (92.1–92.7 Mb) and TAD4 (92.7–93.9 Mb) (S6A Fig, S3 Table). However, TAD T4 and TAD5 in thymocytes did not show clear separation and the border between them was rather softened (Fig 2D, S6A Fig, S3 Table). The borders between the TAD 4/5 and TAD 6 (93.9 Mb), as well as between TAD6 and TAD7 (94.8 Mb) in thymocytes were quite similar compared to the corresponding borders in keratinocytes (Fig 2D, S6A Fig, S3 Table).

Importantly, the TAD borders were weaker in thymocytes versus keratinocytes, while the frequency of the spatial inter-chromatin contacts both within and between different TADs in keratinocytes was substantially higher in comparison to thymocytes (Fig 2D, S6A Fig). Interestingly, we observed high frequency of the spatial chromatin contacts between the gene-poor TAD2 and TAD5, flanking the gene-rich TAD3 and TAD4 in keratinocytes, while such interactions were not seen in thymocytes (Fig 2D, S6A Fig). Such high frequency of contacts was not observed on the heat map between TAD1 and TAD3, separated by the gene-poor TAD2 in keratinocytes (Fig 2D). These data suggested that the gene-poor TADs at the 5.3 Mbp chromatin domain on mouse chromosome 3 appears to be segregated into transcriptionally-inactive compartment spatially separated from the transcriptionally active gene-rich TADs in keratinocytes, which is quite consistent with the model proposing the existence of the compartments A and B topologically separated in the nucleus based on the differences in their transcription activity [9, 45]. Importantly, such separation was not observed for the transcriptionally inactive gene-rich and gene-poor TADs in thymocytes (S6A Fig), presumably incorporated into compartment B in these cells.

To validate the 5C data, we performed 3D-FISH analysis of the distances between loci located in the distinct EDC domains in the freshly plated primary epidermal keratinocytes and thymocytes, as well as in cryo-sections of P0.5 mouse skin in situ. First, we checked if the central part of the EDC is indeed organized into two adjacent gene-rich TAD3 and TAD4 in both cell types (Fig 2D, S6A Fig). For the 3D FISH analysis, we have chosen the BAC probes depicting the regions within the TAD3 near its 5’ and 3’ borders (probes A and B, respectively), or located within the adjacent TAD4 (probe C) (S4 Table, Fig 2D–2F, S6B Fig). We expected that the spatial distances between the regions located within the same TAD should be shorter in comparison to the distances between the regions located in the different TADs, when the similar linear genomic distances separate such regions [9, 10].

Indeed, 3D-FISH analyses demonstrated that despite the fact that the genomic distances between the centers of the regions covered by the probes A and B located within the same TAD3 were slightly longer (716,849 bp) compared to the distances between the regions covered by the probes B and C (638,779 bp) located in the TAD3 and TAD4, respectively (S4 Table), spatial distances between the centers of the 3D FISH signals generated by the probes A and B were significantly shorter compared to the distances between the probes B and C in all cell populations (Fig 2D–2F, S6A Fig, S5 Table). Thus, this analysis confirmed the folding of the EDC central domain into two separate TADs both in keratinocytes and thymocytes.

Importantly, 3D-FISH data also showed that the spatial distances between the 3D-signals were rather similar in basal epidermal keratinocytes in situ and in the freshly isolated epidermal keratinocytes (Fig 2F, S6B Fig, S5 Table), thus confirming that the cell isolation procedure for 5C does not significantly alter the spatial organization of the EDC locus. However, 3D FISH analysis also revealed that the distances between the probes A—B and B—C were significantly larger in thymocytes compared to keratinocytes (p<0.0001, Mann-Whitney U-test) (S6B Fig, S5 Table), demonstrating that chromatin in the transcriptionally inactive domains of the EDC locus in thymocytes is less condensed and likely to be more randomly folded compared to the active locus in keratinocytes.

Next, we checked whether gene-poor TAD2 and TAD5 are indeed located closely to each other in keratinocytes, as this has been suggested by the 5C data (Fig 2D). We performed the 3D-FISH analysis of the basal epidermal KCs in situ using the probes covering the centre of the TAD2 (probe D) and TAD5 (probe E) (Fig 2D, S4 Table). TAD2 and TAD5 are separated from each other in the genome by the gene-rich TAD3 and TAD4 (Fig 2D). 3D-FISH data showed that despite the genomic distances between the regions covered by the probes D and E were much longer (2,610,522 bp) compared to the distances between the probes B and C that depict TAD3 and TAD4 (638,779 bp), the spatial distances between the probes D and E, as well as between the probes B and C, were quite similar (Fig 2F, S5 Table). These data demonstrated close association of the gene-poor TAD2 and TAD5 in keratinocytes, thus demonstrating the consistence with the 5C results.

Thus, 3D-FISH analyses confirmed the organization of the central and 3’-flanking regions of the EDC into two separate gene-rich TADs in both cell lineages, as well as the compartmentalization of the gene-poor TAD2 and TAD5 in keratinocytes. Furthermore, this analysis also confirmed the less condensed and potentially more randomly spatially organized the transcriptionally inactive locus in thymocytes in comparison to the active locus in keratinocytes. The concordance between the 5C and 3D-FISH data, as well as between 3D-FISH data obtained from isolated keratinocytes and basal epidermal keratinocytes in situ suggested that the gene-rich and gene-poor TADs in the EDC locus and its neighbouring regions indeed form a unique and relatively stable spatial composition that might serve as a platform for the control of lineage-specific transcription.

To further characterise the spatial chromatin interaction network at the EDC locus and distinguish “true” chromatin interactions in the EDC locus from the random background interactions, we used an approach described previously [17, 43], which is based on the establishment of the background baseline defining the expected frequency of the random chromatin contacts normalized to the genomic distances separating the interacting fragments. This approach allowed identifying interactions reproducible in both 5C replicates with significantly higher interaction frequency compared to the background: 1139 “true” interactions in keratinocytes and 1033 interactions in thymocytes; q-value<0.05; (Fig 3A, S6 Table, S6C Fig, S7 Table). The reproducibility of the called 5C interactions between both replicates was similar to the previously published 5C datasets [11, 17, 43]. To compare the common and cell-type specific 5C interactions between keratinocytes and thymocytes, we also identified a subset of the interactions that were interrogated in all four 5C libraries after the 5C dataset normalization. This approach revealed 338 keratinocyte-specific 5C interactions, 747 thymocyte-specific interactions, while only 136 interactions were common between both cell types (S6D Fig, S8–S10 Tables). Thus identification of the “true” 5C interactions in keratinocytes and thymocytes further demonstrated that spatial organization of the EDC locus is largely lineage-specific.

To further characterize the patterns of the 5C interactions in the transcriptionally active EDC locus in keratinocytes and to check if there are differences in the frequency of the “true” 5C spatial contacts within and between different TADs, we used the 5C contact sets reproducible in both keratinocyte libraries (S3A Fig, S6 Table). Interestingly, we identified substantially more 5C interactions between different TADs (799 or 70.15%), than within the individual TADs (340 or 29.85%) (Fig 3A). Analyses of the 5C interactions between different TADs revealed that gene–rich TAD3 and TAD4 harbouring the majority of genes activated during terminal keratinocyte differentiation interact equally extensively with the gene-rich TAD1 and gene-poor TAD2 (S6E Fig). However, TAD1 harbouring a part of the S100 family genes showed a markedly decreased number of interactions with neighbouring gene-poor TAD2 compared to more distantly located TAD3 and TAD4 (S6E Fig). Remarkably, gene-poor TAD5 showed preferential interactions with gene-poor TAD2, which, in turn, interacted quite extensively with the gene-rich TAD3 and TAD4 (S6E Fig). Gene-rich TAD6 that does not contain keratinocyte-specific genes also interacted quite extensively with TAD1, TAD2, TAD3 and TAD4, while showed only very limited number of interactions with neighbouring gene-poor TAD5 (S6E Fig).

Next, we checked the frequency of the inter-TAD and intra-TAD 5C interactions at the EDC locus as a function of the genomic distances separating contacting fragments in keratinocytes. Surprisingly, we found that the frequency of all detected spatial contacts within the TADs were generally only slightly higher in comparison to the contacts between the TADs (S6F Fig) Such extensive chromatin interaction network between different neighbouring gene-rich TADs harbouring the lineage-specific genes, as well as lineage-specific folding of the EDC locus suggests the functional relevance of these contacts for coordination of the gene expression in keratinocytes during execution of epidermal differentiation program.

5C analysis demonstrated that majority of all 1139 “true” 5C interactions in keratinocytes (47.3%) involve the contacts between the gene promoters and non-promoter chromatin domains, while considerably lower number of interactions were involving either two promoters (26.3%) or two non-promoter chromatin domains (26.4%), respectively (Fig 3B). Thus, vast majority of the 5C contacts (73.6%) involve the non-promoter elements (possibly including gene enhancers) at the EDC locus in keratinocytes.

To further characterize the 5C interactions between gene promoters and enhancers, we identified putative gene enhancers in the EDC locus and its neighbouring regions by performing ChIP-seq analysis for enhancer-specific histone modifications with anti-H3K4me1 and anti-H3K27ac antibodies on the freshly isolated FACS sorted basal (Integrin 6 alpha high, Sca1 high) mouse epidermal keratinocytes. ChIP-seq analyses revealed 16 regions in the EDC locus and its neighbouring regions with the high levels of both H3K4me1 and H3K27ac modifications, serving as the signatures of active enhancers [3, 47, 48] (Fig 3C, S11 Table).

Interestingly, the putative active enhancers were identified exclusively in the gene-rich TADs: TAD1 (E1-E7), TAD3 (E8), TAD4 (E9-E11), TAD6 (E12-E14) and TAD7 (E15-E16) (Fig 3C). Among these enhancers, two groups of closely located enhancers (within less than 10 kb distance from end to end for each enhancer: E2/E3 and E4-E7) formed two clusters (potential super-enhancers) within the TAD1, while the enhancers within other TADs were quite distantly located from each other and did not show clustering (serving probably as typical enhancers) (Fig 3C, S11 Table). Moreover, lack of any enhancers was seen in the gene-poor TAD2 and TAD5.

To identify spatial interaction network between the enhancers and gene promoters, we assigned the 5C interactions involving the restriction fragments within 10 kb of each enhancer to either corresponding individual enhancers (E1, E8-E16) or to the clusters of closely located enhancers (E2/E3 and E4-E7). We found that 22% (252 out of 1139) of all 5C looping interactions at the EDC were anchored to the fragments bearing the gene enhancers (S12 Table). Then we assigned the closest gene transcription start sites (TSSs) located not further than 10 kb away from the restriction fragments anchoring the 5C interactions on the opposite side of the enhancers (Fig 4A, S13 Table). Our analysis revealed that about 52% (144 out of 273) of the 5C interactions involving gene enhancers were the interactions between gene enhancers and promoters, consistently with the data showing the involvement of the gene enhancers in long-range spatial contacts with the target promoters [43, 49, 50].

All enhancer-bearing regions, except the one for E16, were engaged in multiple spatial chromatin interactions with the regions anchoring gene promoters, revealing the potential enhancer-promoter regulatory network (Fig 4A, S12 Table). All enhancers or enhancer clusters except E8 were involved in the long-range contacts with multiple gene promoters, consistently with data obtained from other cell types [16, 43, 51] (Fig 4A, S13 Table). In turn, some gene promoters in the EDC locus were involved in the long-range spatial contacts with several enhancers. For instance, Ivl gene was involved in contacts with the enhancer clusters E2/E3 and E4-E7, while the S100a11 gene was interacting with enhancers E9 and E11 (Fig 4B, S13 Table), consistently with observations that gene promoters might interacts with several enhancers [17, 43, 49].

Enhancers were frequently involved in the spatial interactions not only with the gene promoters located in the same TADs, but also with the gene promoters located in the different TADs. For instance, in addition to the interactions with multiple gene promoters in the TAD1, a cluster of the enhancers E2/E3 (located in TAD1) were interacting with the regions containing Sprr3 and Ivl gene promoters in the TAD3, the Crct1, Lce3d, S100a10 and S100a11 gene promoters in the TAD4, the Pi4kb, Pogz, Them5 and Tuft1 gene promoters in TAD6, as well as with the Bnipl gene promoter in the TAD7 (Fig 4C, S14 Table). Enhancer E9, located in the TAD4, spatially contacted the promoter regions of Flg, Rptn, S100a10, S100a11, Tchh and Tchhl1 genes in the same TAD, as well as to the promoter regions of Ints3, Npr1 and Pglyrp4 genes in the TAD1, the promoter of Sprr2h gene in the TAD3, and promoters of Cgn, Lingo4 and Them5 genes in the TAD6 (Fig 4D, S14 Table). These data were quite intriguing, as many recent studies demonstrated that the contacts between promoters and enhancers are mostly constrained by the same TADs [15–17].

Interestingly, we also found a relatively low number of interactions between the enhancers located in gene-rich TADs with distinct chromatin domains located in gene-poor TAD2 and TAD5 (Fig 4A, S12 Table). The vast majority of such interactions involved distal elements not associated with any gene promoters in the TAD2 and TAD5, although interaction between the Tdpoz3 gene promoter (TAD5) and the E14 enhancer located in TAD6 was also seen (S14 Table).

Next, we compared the frequency of promoter-enhancer contacts between and within TADs as a function of genomic distances separating interacting regions [17, 52]. We found that all promoter-enhancer spatial interactions within the TADs were connecting the regions separated by genomic distances of up to 0.6 Mb, while the inter-TAD interactions were much longer connecting the regions separated from each other by 0.5 Mb-5.1 Mb distances (Fig 4E). As expected, the frequencies of short-range intra-domain contacts were higher compared to the long-range inter-TAD contacts. However, several inter- and intra- domain contacts found between the promoters and enhancers separated by similar genomic distances had comparable frequencies (Fig 4E). Thus, our data revealed the organization of the enhancer-promoter network in the EDC locus with a high frequency of short-range contacts within gene-rich TADs and less frequent, but extensive long-range promoter-enhancer interactions between gene-rich TADs, while gene-poor TADs were lacking of any enhancers.

To gain further insights about the proteins that could be potentially involved in the control of higher-order chromatin folding and promoter-enhancer interactions at the EDC locus in keratinocytes, we correlated the 5C interaction data with the ChIP-seq data for the binding of the chromatin architectural proteins CTCF and cohesin subunit Rad21, known to control the higher-order chromatin folding in all studied cell types [4, 53]. We also correlated 5C data with ChIP-seq data for the binding of ATP-dependent chromatin remodeler Brg1/Smarca4, known to regulate nuclear positioning of the EDC locus in keratinocytes during epidermal development [36].

We found a heterogeneous distribution in the binding patterns for these proteins at the EDC locus (Fig 5A and 5B). CTCF and Rad21 showed high frequency of the binding in the gene-rich TAD1, TAD4, TAD6 and TAD7, while lower frequency of binding was seen in the TAD3 and TAD2 and lack of binding was detected in TAD5 (Fig 5A and 5B). We found CTCF binding within 100kb of all the TAD border midpoints, except the border between TADs 5 and 6, where it was found within 160kb (Fig 5A), consistent with recently established role for CTCF in the TAD organization [9, 15, 21]. Similarly to CTCF and Rad21, Brg1 binding was abundant in all gene-rich, but not gene-poor TADs (Fig 5A and 5B).

A substantial fraction of the 5C interactions showing CTCF, Rad21 and Brg1 binding (between 38% and 50% of all interactions for the individual proteins) (Fig 5C), suggested that they might be involved in the control of the higher-order chromatin folding at the EDC locus in keratinocytes. Exact Fisher statistical test showed the enrichment for the regions bound by CTCF in all significant 5C looping interactions in comparison to all background 5C interactions (Fig 5D). This was consistent with a well-established role of CTCF in the control of higher-order chromatin folding in different cell types [4, 53, 54].

We further analyzed the pair-wise combinations of the chromatin architectural protein binding in the regions anchoring the 5C interactions at the EDC locus in keratinocytes. Consistently with the previously published data, our analysis revealed most frequent presence of the cohesin subunit Rad21 in the regions anchoring the 5C interactions that were also anchored to the CTCF binding regions (76.6%) (Fig 5E). Brg1 was also frequently seen in the regions involved in the 5C interactions anchoring CTCF-bound regions (63.4%) (Fig 5E). CTCF, and Brg1 were present in the regions anchoring 59.4%, and 56.5% of the 5C interactions anchored to the Rad21 binding regions respectively (Fig 5E). These data demonstrates that CTCF, Rad21 and Brg1 frequently present in the regions anchoring the same 5C interactions, suggesting that they might functionally cooperate in the control of establishment of the spatial interacting network within the EDC locus and its genomic neighbourhood in keratinocytes.

Next we check if CTCF, Rad21, and Brg1 are involved in spatial contact between gene promoters and enhancers. We found that CTCF, Rad21 and Brg1 were even more frequently bound to the bases of the 5C loops involving gene enhancers than in the bases of all significant 5C loops (Fig 5C and 5F). Exact Fisher statistical test demonstrated highly significant enrichment of this protein binding in the regions anchored to the enhancer spatial interactome (Fig 5G), supporting their involvement in establishing promoter-enhancer contacts in keratinocytes. This is consistent with the role of Rad21 together with or independently from CTCF that has been well documented in several cell types [4, 53]. Moreover, Brg1 binding has also been reported to be frequently associated with active enhancers [55, 56], and promoter-enhancer spatial interactions [57]. Thus, our data suggest the important role for CTCF, Rad21 and Brg1 in organization of the 5C interactome within and between gene-rich TADs in the EDC locus in keratinocytes and in establishing promoter-enhancer spatial network in this locus.

All animal studies were performed under protocol approved by the University of California Berkley Institutional Animal Care and Use Committee and the UK Home Office Project Licence. C57Bl/6 mice were purchased from Charles River. The skin tissue samples were collected from P1.5-P3.5 C57Bl/6 animals as previously described [64, 65]. Keratinocytes were isolated for micro-array, 5C, 3D FISH and ChIP-seq analysis from the skin of the new born C57BL/6 animals. Primary thymocytes were isolated from the C57Bl/6 animals. For the FISH analysis of 3D preserved nuclei, skin samples were processed as previously described [66, 67]]

Primary epidermal keratinocytes was isolated from the skin of the new-born C57Bl/6 mice as previously described [68, 69]. Briefly, the skin was removed from the neonatal mice and incubated with 0.25% trypsin in Hanks Balanced Salt solution overnight at 4 C, followed by separation of dermis from epidermis. Epidermis was placed into pre-chilled low calcium primary keratinocyte culture (EMEM, 4% chelated FBS, 0.05mM CaCl₂, 0.4ug/ml hydrocortison, 5ug/ml insulin, 10mg/ml EGF, 10⁻¹⁰ M cholera toxin, 2x10^-9 T3, 2mM L-glutamin, 100U/ml penicillin, 100ug/ml streptomycin) and triturated to obtain the single cell suspension. The cells were filtered through a 70 μm silicon strainer and were either seeded at high density at the low calcium primary keratinocyte medium onto collagen solution (0.97X Hanks Balanced Salt Solution (HBSS), 9.70μg/mL Bovine Serum Albumin (BSA), 19.40 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 0.97 X Vitrogen-100 Collagen) coated culture dishes for 15 hours at 32°C in the atmosphere of 8% carbon dioxide and 90% humidity, or were used for FACS to isolated viable basal keratinocyte population.

Primary thymocytes were isolated from C57Bl/6 mouse thymi as described in [70]. The thymi were transferred into pre-chilled T cell medium (RPMI medium 1640 (ATCC modification), 10% foetal bovine serum, 0.1x 2-mercaptoethanol) and crushed to release total thymus T cell population. The cells were filtered through a 70 μm cell strainer, pelleted by centrifugation and re-suspended in Red Blood Cell lysis buffer (Sigma) for 3 min. Cell were then washed with the pre-chilled T-cell medium, re-suspended in the medium, filtered through a 70 μm cell strainer and counted using haemocytometer.

RNA was isolated from the primary keratinocytes plated on the collagen solution coated dishes for 15 hours at 32°C and 8% CO₂ or primary thymocytes using TRI Reagent solution and TURBO-DNA-free kit (Invitrogen). Total RNA was amplified with Arcturus Ribo-Amp PLUS system (Applied Biosystems) as previously described [36]. RNA was converted into labelled cDNA and micro-array analysis was performed by MoGene (St Louis, MO, USA) using 41K Whole Mouse Genome 60-mer oligo micro-arrays (Aglinent Technologies). Micro-array datasets were analysed using the distribution of background intensity and signal intensity values (Agilent Feature Extraction software version 7.5).

Two 3C templates were constructed for freshly plated epidermal keratinocytes and primary thymocytes according to [71] with modifications. Briefly, epidermal keratinocytes isolated from mouse epidermis were seeded in the low calcium primary keratinocyte medium at high density on the collagen coated plate for 15 hours at 32°C, 8% CO₂ and 90% humidity. The primary thymocytes were isolated as described above. Cells were washed twice with the growth medium and fixed with 1% formaldehyde (Electron Microscopy Systems) in the growth medium for 10 minutes at room temperature with gentle mixing every 2 minutes. The glycine was added to a final concentration of 125 mM. Quenching was initiated at room temperature and the cells were placed on ice for 5 min. The medium was removed and cells were washed ones with ice cold PBS and then fresh ice cold PBS was added. Cross-linked cells were collected, counted, pelleted by centrifugation in aliquots and quick-frozen. Cells were stored at -80°C.

Per a 5C library, the frozen pallet of 6x10⁷ cells 1.2 ml of lysis buffer (10 mM Tris-HCl, pH 8.0, 10 mM sodium chloride, 0.2% (vol/vol) Igepal C-630 (Sigma)) supplemented with 120 ul of protease inhibitor cocktail (Sigma) was added and cells were incubated on ice for 30 minutes. Cells were lysed using a 5 ml dounce homogenizer, washed twice with ice cold 1x NEBuffer2 buffer (10 mM Tris-HCl, 50 mM NaCl, 10 mM MgCl2, 1 mM DTT), and re-suspended in 630 ul of 1x NEBuffer2. Nuclear suspension was divided into 50 ul aliquots. To the nuclear suspension 312 ul of 1xNEBuffer2 was added. SDS was then added to a final concentration of 0.1% and lysates were incubated at 65°C for 10 min. Triton X-100 was then added to a final concentration of 1% to quench SDS. To each aliquot of solubilized chromatin 800 U of HindIII enzyme (New England Biolabs) was added and the digestion was performed overnight at 37°C with shaking. HindIII was inactivated by incubating lysates at 65°C for 30 min after addition of SDS to a final concentration of 1.56%. Ligation was performed under diluted conditions that promote intra-molecular ligation at 16°C for 4 hr in ligation buffer (1% Triton X-100, 0.1 mg/ml BSA, 1 mM ATP, 50 mM Tris-HCl (pH 7.5]) 10 mM MgCl2, 10 mM DTT) with 10 ul of T4 DNA ligase (Invitrogen). To reverse crosslinks, samples were then treated with 63.5 mg/ml Proteinase K (Invitrogen) at 65°C. Four hours later, Proteinase K was added again to 127 mg/ml and then incubated overnight at 65°C. DNA was purified by subjecting samples to a series of phenol and phenol-chloroform extractions before precipitation with ethanol. Pellets were re-suspended in 1–2 ml TE Buffer, pH8.0 and precipitation with ethanol. Pellets were re-suspended in 500 ul of TE buffer and treated with DNase-free RNase at final concentration of 100 ng/ul for 1 hour at 37°C. 3C templates were further purified using Amicon Ultra Centrifugal 30K Filter for DNA Purification and Concentration (Millipore). Using the Millipore columns, samples were washed twice with 1X TE buffer. Following sample recovery from Millipore columns, initial sample volume was then restored with 1X TE buffer, pH 8.0.

The concentration of the 3C template was assessed by gel electrophoresis with high molecular weight DNA ladder as a standard (Invitrogen) using TotalLab Quant gel densitometry software. Controls for DNA integrity (undigested chromatin control) and restriction digestion (no ligase control) were also checked and passed the quality control. The quality of the 3C templates were further assessed by running the PCR with series of 2-fold dilutions of the templates with forward (ATGGAGACCTGCCGCCGGCTCATCACAC) and reverse (CGTGCTGTGACTTCGCACTTTTCTGATC) primers amplifying the product of head to head ligation of two HindIII sites located 1164bp apart as described in [71] using Quant gel densitometry software (Total lab).

Two independent 5C libraries were constructed for each cell type as described in [71] with modifications. 5C probes were designed at HindIII restriction sites using the my5Csuite primer design tools [44]. An alternating scheme was pursued in which reverse and forward probes were designed against every other fragment. Probes were excluded if unique mapping could not be achieved for fragments spanning highly repetitive sequences. Probe setting were as follows: U-BLAST, 3; S-BLAST, 50; MER, 800; MIN, FRAGSIZE, 100; MAX FRAGSIZE, 50000; OPT_TM, 65: and OPT_PSIZE, 40. The universal T7 sequence was tethered to all forward primers (TAATACGACTCACTATAGCC) and the reverse complement to the universal T3 sequence was tethered to all reverse probes (TATTAACCCTCACTAAAGGGA). In total, 381 forward probes and 382 reverse probes were designed, spanning 5.3 Mb EDC containing locus (Fig 1B, S2 Table).

To construct 5C libraries, first probes were annealed to the 3C templates at 48°C for 16 hours. Each multiplex annealing reaction contained 1xNEBuffer4 (New England Biolabs), 560 ng of 3C template and 0.4 fmole of each 5C probe. The annealed probes were nick ligated with 10 U of Taq ligase in 1x Taq ligase buffer (New England Biolabs) at 48°C for 1 hour. The resulting 5C library was amplified by PCR with 25 cycles using universal T7 (TAATACGACTCACTATAGCC) and T3 (TATTAACCCTCACTAAAGGGA) primers. 15 ligation reactions amplified in 6 PCR reactions each were performed to generate each 5C library. The PCR reactions for each 5C library were pooled before further processing. 5C library amplification reactions produced the products of expected size (101 bp), while the negative control PCR reactions (included no 5C template control, no ligation control or no 5C probe control) did not yield any PCR product.

5C libraries were size fractioned (101 bp) and purified from the agarose gel using QIAquick gel purification kit (QIagene). 3’ A-tails were added using dATP and Taq polymerase, followed by subsequent ligation to bar-coded custom designed adaptor oligonucleotide [72] for Illumina pair-end sequencing. Adaptor-modified 5C libraries were purified after separation in the agarose gel using QIAquick gel purification kit (Qiagene). The purified libraries were amplified by 18 cycles of PCR with PE1.0 and PE2.0 primers (Illumina). The amplified libraries (233 bp) were purified from the agarose gel, quantified using Nanodrop 1000 spectrophotometer (Thermo Fisher) and send for the sequencing on the HiSeq 2000 system at the EMBL Genome Core Facility (Heidelberg, Germany).

The 5C library sequencing data sets were de-multiplexed using Novobarcode (Novocraft). The reads were aligned to the pseudo-genome consisting of all 5C probes (S2 Table) using Bowtie [73]. To account for poor quality reads, sequences were required to have only one unique alignment. After mapping, interactions were counted when both paired end reads could be uniquely mapped to the 5C probe pseudo-genome. Only interactions between forward-reverse probe pairs were considered as true counts.

Next, we performed the data correction to remove the technical biases associated with the 5C technology as described in [17, 43] with some modifications. First, we removed the probes that performed significantly differently in comparison to the overall probe sets. A global average relationship between interaction frequency and genomic distance was calculated using Loess smoothing for each replicate dataset. Contact profile for each probe across the interrogated region was compared to this average. We removed the probes with the individual Loess of more or less than 0.85 of the scaled Z score distance from the global Loess. We removed 38 probes for the replicate 1 and 37 probes for the replicate 2 for the downstream analysis (S15 Table, S2B, S3B, S4B and S5B Figs).

After this step, we removed the signal interaction with very high contact frequency in comparison to their neighbors. We removed such interactions if they have a Z score of 25 or more (S16 Table, S2C, S3C, S4C and S5C Figs). Z score was calculated as described in [17]. Finally, we normalized the profile of each probe so they could be quantitatively compared to each other as described in [17], but we calculated a global average relations between interaction frequency and genomic distance with Loess smoothing for each replicate separately (S2D, S3D, S4D and S5D Figs).

TAD boundary positions were identified by calculating an insulation score along the locus as described in [17, 46]. The normalized 5C data were binned at 150 kb with 15 kb step size. Next, we calculated the combined number of interactions across each bin by summing all interactions up to 500 kb upstream of the bin and up to 500 kb downstream of the bin. The sum for each bin was divided by the average sum for all bins to yield insulation score. The insulation score was plotted along the whole locus to obtain an insulation profiles (Fig 2D, S6A Fig). Local minima in these profiles indicate the position of the TAD boundaries. The local minima in the insulation profile were detected by identifying the bins with the lowest insulation score in a local 435 kb window. The mid-points of these bins were set as the TAD boundaries. The average position of the midpoint between the replicate was used as the TAD boundaries in the manuscript (S3 Table).

To detect the “true” statistically significant chromatin looping interactions between the individual restriction fragments, we applied a “5 C peak calling approach as described before [17, 43]. We called the significant 5C peaks for the 5C libraries separately. Peaks were defined as normalized ligation frequencies (signals) that are significantly higher than expected for the genomic distances separating the interacting fragments. Expected values were calculated as the average interaction frequency for each genomic distance by using Loess smoothing (alpha value 0.01). This provides a weighted average and a weighted standard deviation for each genomic distance. We assumed that the large majority of interactions were not significant looping contacts, and we interpreted these weighted averages as the expected interaction frequencies for given genomic distances. We then transformed observed 5C interaction frequencies into a Z score by calculating the (observed value-expected value)/standard deviation. The calculated Z score distribution was fit to a Weibull distribution. p values were calculated for each Z score and transformed into q values for false discovery rate analysis. We used q-value threshold of 0.05 for the 5C peak calling. Only 5C peaks reproducible in both replicates in KCs or TCs were used for subsequent analysis (S6 and S7 Tables).

3D FISH analysis of the spatially preserved nuclei in the mouse skin tissue and freshly isolated primary keratinocytes [74] and thymocytes was performed as previously described with modifications [36, 67, 74, 75]. Primary keratinocytes were seeded overnight on the collagen coated cover slips. The adherent cells were fixed with formaldehyde and prepared for 3D FISH as described in [75]. Primary thymocytes were seeded on the slides coated with 1 mg/ml of Poly-L-lysine hydrobromide per [75]. 20 μm sections of the frozen skin sample with structurally preserved nuclei were used for the 3D analysis.

BAC based probes were prepared for the selected regions (S4 Table) by nick-translation using in house synthesized Bio-dUTP, FITC-dUTP, Cy3-dUTP or Dig-dUTP as described in [76]. After hybridization the samples were stained with Cy5-streptavidin or anti-Dig-Cy3 antibodies (S17 Table) when needed. DNA was stained with DAPI (Sigma). 3D images were collected using a Zeiss LSM510 confocal microscope. Nuclei were scanned with a z-axial distance of 200 nm, yielding separate stacks of 8-bit grey scale images, with pixel size 100–200 nm, for each fluorescent channel. For each optical section, images were collected sequentially for all fluorophores and the axial chromatic shift corrected for in each channel as described in [77]. Images were processed and analyzed using ImageJ (NIH). Inter-locus distances were calculated after correction for chromatic aberration, as previously described [36]. The differences between the inter-locus distances in different samples were analyzed using Mann-Whitney U-test.

For ChIP analysis new born C57Bl6 total keratinocyte single cell suspension was prepared as described above. To ensure analysis of viable cells with intact chromatin, keratinocytes were stained with UV Live/Dead Fixable Dye (Life Technologies) for 30 min on ice prior fixation with 1% PFA for 10 min at RT. Fixed cells were labeled with CD49f-PE and Sca-1-FITC antibodies (S17 Table) for 1 hour on ice. CD49f+/Sca-1+ basal keratinocytes were gated after exclusion of dead (UV Live/Dead Fixable Dye-positive, Life Technologies) cells and sorted on a MoFlo XDP cell sorter (Beckman Coulter), as described in [78]. Sorted cells were pelleted at 2.000 g and stored at -80°C.

ChIP was performed using FACS sorted epidermal keratinocytes isolated from newborn mouse skin anti-H3K27ac, anti-Rad21 and anti-CTCF antibodies (S17 Table) using ChIP-IT High Sensitivity kit (Active Motif) as described in [36, 79].

ChIP with anti-H3K4me1 antibodies (S17 Table) was performed using Micrococcal nuclease (MNase) digestion epidermal keratinocyte chromatin as per [80]. 1x10⁶ cells were used per MNase digestion and 1μg of the antibodies per IP comprising pre-cleared chromatin corresponding to 5x10⁵ cells.

Indexed ChIP-Seq libraries from immune-precipitated and control input chromatin were generated using NEBNext ChIP-Seq Library Prep Master Mix Set (New England BioLabs) for Illumina and NEBNext Multiplex Oligos for Illumina (New England BioLabs).

The libraries were sequenced on the HiSeq 2500 system (Illumina), producing 30–70 million reads per library. Sequencing reads were aligned to the mm9 mouse genome assembly [73]. Specific areas of protein binding or histone modification presence were identified with MACS using default parameters [81]. The normalized ChIP-seq signals together with the previously published ChIP-seq signals for Brg1 were visualized using UCSC genome browser (http://genome.ucsc.edu↗) [82, 83].

High confidence H3K4Me1 ChIP-seq peaks were merged if they were located within 5 kb end-to-end distances from each other and the same operation was applied to the H3K27ac ChIP-seq peaks. Enhancers were defined as merged H3K4me1 and H3K27ac peaks located within 2 kb end-to-end distance. We did not exclude putative enhancers located near gene promoters, as recent studies indicate that gene promoters could poses gene enhancer activity and enhancers could be located close to gene promoters [58, 61]. The positions of the gene enhancers were visualized using UCSC genome browser (http://genome.ucsc.edu↗) [82, 83].

An enrichment of selected non-histone protein binding in the regions anchoring 5C interactions at EDC locus or interactions involving gene enhancers at the locus were calculated for the extended 5C fragments to include nearest adjacent fragments interrogated by the 5C probes on the opposite strand as described in [11].

Raw and processed 5C data are available at the GEO database (GSE102519). All other relevant data are within the paper and its Supporting Information files.