Characteristics of functional enrichment and gene expression level of human putative transcriptional target genes

Background Transcriptional target genes show functional enrichment of genes. However, how many and how significantly transcriptional target genes include functional enrichments are still unclear. To address these issues, I predicted human transcriptional target genes using open chromatin regions, ChIP-seq data and DNA binding sequences of transcription factors in databases, and examined functional enrichment and gene expression level of putative transcriptional target genes. Results Gene Ontology annotations showed four times larger numbers of functional enrichments in putative transcriptional target genes than gene expression information alone, independent of transcriptional target genes. To compare the number of functional enrichments of putative transcriptional target genes between cells or search conditions, I normalized the number of functional enrichment by calculating its ratios in the total number of transcriptional target genes. With this analysis, native putative transcriptional target genes showed the largest normalized number of functional enrichments, compared with target genes including 5–60% of randomly selected genes. The normalized number of functional enrichments was changed according to the criteria of enhancer-promoter interactions such as distance from transcriptional start sites and orientation of CTCF-binding sites. Forward-reverse orientation of CTCF-binding sites showed significantly higher normalized number of functional enrichments than the other orientations. Journal papers showed that the top five frequent functional enrichments were related to the cellular functions in the three cell types. The median expression level of transcriptional target genes changed according to the criteria of enhancer-promoter assignments (i.e. interactions) and was correlated with the changes of the normalized number of functional enrichments of transcriptional target genes. Conclusions Human putative transcriptional target genes showed significant functional enrichments. Functional enrichments were related to the cellular functions. The normalized number of functional enrichments of human putative transcriptional target genes changed according to the criteria of enhancer-promoter assignments and correlated with the median expression level of the target genes. These analyses and characters of human putative transcriptional target genes would be useful to examine the criteria of enhancer-promoter assignments and to predict the novel mechanisms and factors such as DNA binding proteins and DNA sequences of enhancer-promoter interactions. Electronic supplementary material The online version of this article (10.1186/s12864-017-4339-5) contains supplementary material, which is available to authorized users.

and CCAAT enhancer-binding protein α (C/EBPα) play a critical role in the expression 64 of myeloid-specific genes and the generation of monocytes and macrophages [1,2]. The 65 transcription factor GATA-3 is essential for early T cell development and the 66 differentiation of naive CD4 + T cells into Th2 effector cells [3]. E2A, EBF1, PAX5, and 67 Ikaros are among the most important transcription factors that control early 68 development in mice, thereby conditioning homeostatic B cell lymphopoiesis [4]. 69 We previously examined the differentiation of monocytes and macrophages in 70 mice, and discovered that the transcription factor IRF8 was essential for cellular 71 differentiation [5]. An analysis of transcription factor-binding sites (TFBS) revealed that 72 IRF8 regulated the expression of KLF4 through the IRF8 transcriptional cascade. 73 Functional enrichment analyses revealed that the target genes of IRF8 showed 74 functional enrichment for antigen presentation, whereas those of KLF4 showed 75 functional enrichments for phagocytosis and locomotion. These results suggested that 76 the transcriptional cascades of IRF8 and KLF4 included different functional modules of 77 target genes. 78 Functional enrichments of transcriptional cascades of IRF8 and KLF4 appeared to 79 be related to the cellular functions of monocytes and macrophages. Although several 80 transcription factors were expressed in monocytes and macrophages, the number of 81 these transcriptional target genes that resulted in functional enrichments remains 82 unknown. Whether transcriptional target genes in other human cells show functional 83 enrichments remain unclear. If the transcriptional target genes showed significant 84 functional enrichment, analyzing transcriptional target genes would be useful in 85 identifying genes involved in a specific cellular function. Using the budding yeast, 86 previous studies examined the functional enrichments on a genome-scale genetic 87 interaction map using the GeneMANIA algorithm [6][7][8]. Using bacterial systems, the 88 analyses of functional enrichments of predicted regulatory networks were performed 89 using Gene Ontology annotations [9]. Various databases of functional annotations of 90 genes and pathways exist. Analysis of functional enrichments is expected to be useful 91 for understanding the association of genes involved in similar functions and same 92 pathways, and for predicting unknown gene functions such as non-protein-coding 93 RNAs. In addition, the extent of enhancer contribution to functional enrichments of 94 transcriptional target genes remains unknown. 95 In this study, transcriptional target genes were predicted using public databases of 96 open chromatin regions of human monocytes, naive CD4 + T, CD20 + B cells, HUVEC, 97 8 cellular components. The numbers of functional enrichments of Gene Ontology 143 annotations in target genes of a transcription factor were 2,902, 4,077, and 2,778 in 144 monocytes, CD4 + T cells, and CD20 + B cells, respectively. An examination of 145 functional enrichments of highly expressed genes (top 30% expression level), 146 independent of transcriptional target genes, revealed 237, 301, and 239 'unique' Gene 147 Ontology annotations in monocytes, CD4 + T cells, and CD20 + B cells, respectively 148 (Table 1). Further, the examination of functional enrichments of highly expressed target 149 genes (top 30% expression level) in target genes revealed 1, 271, 1,654, and 1,192 150 'unique' Gene Ontology annotations in monocytes, CD4 + T cells, and CD20 + B cells, 151 respectively i.e., These numbers were four times larger than functional enrichments 152 identified by gene expression information alone, independent of transcriptional target 153 genes, suggesting that transcriptional target genes were frequently associated with 154 similar functions or pathways (Table S3 and S4). 155 Functional enrichments of transcriptional target genes from other databases were 156 also examined (Table 1). KEGG, Target genes of transcription factors, Disease Ontology, 157 GO Slim, Pathway Commons, Cellular biomarkers, Target genes of microRNAs, 158 Protein domains, and WikiPathways had 95, 16, 127, 12, 242, 17, 97, 303, and 105 159 unique functional annotations, respectively. The numbers of functional enrichments of 160 transcriptional target genes in the other annotation databases except for microRNAs and 161 Protein domains were significantly higher than gene expression information alone, 162 independent of transcriptional target genes, as well as Gene Ontology annotations 163 (Table 1). The functional enrichments of transcriptional target genes from Pathway 9 Commons for monocytes, CD4 + T cells, and CD20 + B cells are shown in Table 2 and  165   Table S5. Functional enrichments were found to be related to cellular functions, e.g., 166 interferon signaling, GMCSF (Granulocyte-macrophage colony-stimulating factor, a 167 kind of cytokine)-mediated signaling events, antigen processing-cross presentation in 168 monocytes; TCR (T-cell receptor) signaling in naive CD4 + T cells, 169 a kind of cytokine)-mediated signaling events, and downstream signaling in naive CD8 + 170 T cells in CD4 + T cells; interferon alpha/beta signaling, IL8-and CXCR2 (Chemokine 171 receptor type 2, a kind of cytokine)-mediated signaling events, and BCR (B cell antigen 172 receptor) signaling pathway in CD20 + B cells. WikiPathways, KEGG and GO also 173 revealed that functional enrichments were associated with cellular functions (Table S6, 174 S7 and S8). 175 176

Effect of enhancer-promoter association rules on functional enrichments 177
To understand the effect of 'promoter and extended regions for 178 enhancer-promoter association (EPA)' on the functional enrichments of target genes, the 179 rule of extended regions was modified according to four criteria ( Figure 3A and see 180 Methods) [11], and functional enrichments were investigated. 181 According to the association rule (1), the means of target genes were 177, 217, 182 and 175 in monocytes, CD4 + T cells, and CD20 + B cells, respectively, whereas the 183 corresponding medians were 55, 58, and 37, respectively (Table S9). The numbers of 184 functional enrichments of Pathway Commons annotations using promoter regions were 185 (Table S10). With the use of EPA (association rule 1), the numbers of functional 187 enrichments of Pathway Commons annotations were 3, 087, 7,216, and 3,900, 188 representing 3.07-, 4.00-, and 4.75-fold increases, respectively, in the three cells types. 189 Additionally, the numbers of 'unique' Pathway Commons annotations with promoter 190 regions were 321, 415, and 329 in monocytes, CD4 + T cells, and CD20 + B cells, 191 respectively; the corresponding numbers with the use of EPA (association rule 1) were 192 364, 437, and 364, representing 1.13-, 1.05-, and 1.11-fold increases, respectively, in the 193 three cell types. The normalized numbers of functional enrichments of Pathway 194 Commons annotations were 44.75, 84.51, and 59.32, representing 1.84-, 2.80-, and 195 3.32-fold increases, respectively, in the three cell types (association rule 1, Table 3). 196 Other cell types also showed the same tendencies (Table 3). 197 The normalized numbers of the functional enrichments of transcriptional target 198 genes showed association rule (4) as the highest number, followed by association rule 199 (1) and (2) in the three cell types. Although association rule (3) was the longest among 200 the four criteria, it showed the lowest number of functional enrichments in the three cell 201 types ( Figure 3A and Table 3). ChIP-seq data of 19 TF in H1-hESC (Human embryonic 202 stem cells) also showed almost the same tendency (difference between association rule 203 (4) and (1) was not statistically significant, probably due to a large number of 204 transcriptional target genes predicted using 19 TF ChIP-seq data. Several thousands of 205 target genes of each TF were predicted. Some of them would be indirect interactions 206 between TF and genome DNA, which were identified by ChIP-seq experiments. (Table  207 S11, see Additional file). 208 Differences in functional enrichments using Pathway Commons were examined 209 between promoters versus EPA (association rule 1) (Table 4 and Table S12). A 210 comparison of 321 and 364 functional enrichments using the promoters and EPA, 211 respectively, in monocytes revealed that 152 (47% in promoters, 42% in extended 212 regions) of them were common. For example, IFN-gamma (Interferon gamma) pathway, 213 GMCSF (Granulocyte-macrophage colony-stimulating factor, a kind of 214 cytokine)-mediated signaling events, and PDGF (Platelet-derived growth factor) 215 receptor signaling network were enriched using extended regions (association rule 1) as 216 opposed to promoters (Table S12). The comparison of 415 (promoters) and 437 217 (extended regions) functional enrichments in CD4 + T cells revealed that 163 of them 218 (39% in promoters, 37% in extended regions) were common. IFN-gamma pathway, 219 TCR (T-cell receptor) signaling in naive CD4 + T cells, and IL3 (Interleukin-3, a kind of 220 cytokine)-mediated signaling events were enriched using extended regions. The 221 comparison of 329 (promoters) and 364 (extended regions) functional enrichments in 222 CD20 + B cells revealed that 171 of them (52% in promoters, 47% in extended regions) 223 were common. IL5-mediated signaling events, IL4-mediated signaling events, and 224 cytokine signaling in immune system were enriched in CD20 + B cells using extended 225 regions. Only about 40% of functional enrichments of Pathway Commons annotations 226 were unchanged between promoters and EPA. EPA significantly affected the functional 227 enrichments of transcriptional target genes. Journal papers showed that frequent 228 functional enrichments were related to the cellular functions in the three cell types 229 (Table 4). These results showed that new functional enrichments related to cellular functions were identified using extended regions for enhancer-promoter association. 231 Effect of CTCF-binding sites on functional enrichments 233 CTCF have the activity of insulators to block the interaction between enhancers 234 and promoters [12]. Recent studies identified a correlation between the orientation of 235 CTCF-binding sites and chromatin loops ( Figure 3B) [13]. Forward-reverse (FR) 236 orientation of CTCF-binding sites are frequently found in chromatin loops. To examine 237 the effect of forward-reverse orientation of CTCF-binding sites on functional 238 enrichments of target genes, 'promoter and extended regions for enhancer-promoter 239 association (EPA)' were shortened at the genomic locations of forward-reverse 240 orientation of CTCF-binding sites, and transcriptional target genes were predicted from 241 the shortened regions using TFBS (see Methods). The numbers of functional 242 enrichments of target genes were investigated. According to EPA (association rule 4) 243 that were shortened at genomic locations of forward-reverse orientation of 244 CTCF-binding sites, the means of target genes were 67, 64, and 77 in monocytes, CD4 + 245 T cells, and CD20 + B cells, respectively, whereas the corresponding medians were 23, 246 21, and 20, respectively (Table S13). The normalized numbers of functional 247 enrichments of Pathway Commons annotations using EPA were 71.42, 108.08, and 248 90.99 in monocytes, CD4 + T cells, and CD20 + B cells, respectively (Table 5). With the 249 use of EPA shortened at forward-reverse orientation of CTCF-binding sites, the 250 normalized numbers of functional enrichments of Pathway Commons annotations were 251 196.58, 220.54, and 220.77, representing 2.75-, 2.04-, and 2.43-fold increases, respectively, in the three cells types. Additionally, the normalized numbers of functional 253 enrichments of 'unique' Pathway Commons annotations with EPA were 5.09, 5.34, and 254 6.00 in monocytes, CD4 + T cells, and CD20 + B cells, respectively; the corresponding 255 normalized numbers with the use of EPA shortened at forward-reverse orientation of 256 CTCF-binding sites were 9.88, 10.72, and 9.10, representing 1.94-, 2.01-, and 1.52-fold 257 increases, respectively, in the three cell types (Table S14). Other cell types also showed 258 the same tendencies ( annotations. These increases were also significant, compared with EPA shortened at 263 CTCF-binding sites without the consideration of their orientation. Transcriptional target 264 genes predicted from EPA shortened at forward-reverse orientation of CTCF-binding 265 sites tend to include similar function of genes significantly. 266 Differences in functional enrichments obtained using EPA versus EPA shortened 267 at forward-reverse orientation of CTCF-binding sites were examined using the 268 functional enrichments of Pathway Commons (Table 6 and Results in Additional file). 269 Transcriptional target genes predicted from EPA shortened at the CTCF-binding sites 270 tended to include the similar function of genes. About 40 -80% of functional 271 enrichments were unchanged between promoters and EPA shortened at forward-reverse 272 orientation of CTCF-binding sites, and the functional enrichments observed in EPA 273 promoters included various immunological terms. Journal papers showed that the top 275 five frequent functional enrichments were related to the cellular functions in the three 276 cell types (Table 6). These results showed that new functional enrichments related to 277 cellular functions were identified using forward-reverse orientation of CTCF-binding 278 sites. 279 280

Comparison of expression levels of putative transcriptional target genes 281
To examine the relationship between functional enrichments and expression 282 levels of target genes, the expression levels of target genes predicted from promoters 283 and three types of 'promoter and extended regions for enhancer-promoter assignment 284 (EPA)' were investigated in monocytes, CD4 + T, H1-hESC and iPSC ( Figure 4). Median 285 expression levels of the target genes of the same transcription factor binding sequences 286 were compared between promoters and three types of EPA. Red and blue dots in Figure  287 4 show statistically significant difference of the distribution of expression levels of 288 target genes between promoters and EPA. Additionally, "red dots" show the median 289 expression level of target genes of a TFBS was 'higher' in EPA than promoters, and 290 "blue dots" show the median expression level of target genes of a TFBS was 'lower' in 291 EPA than promoters. The ratios of red dots were higher in EPA (association rule 4) that 292 were shortened at forward-reverse orientation of CTCF-binding sites versus promoters 293 (left graph in Figure 4) than EPA (association rule 4) versus promoters (right graph) in 294 monocytes and CD4 + T cells. The ratios of blue dots were higher in EPA (association 295 rule 4) that were shortened at forward-reverse orientation of CTCF-binding sites versus promoters (left graph) than EPA (association rule 4) versus promoters (right graph) in 297 H1-hESC and iPSC. Moreover, the ratio of the sum of median expression levels 298 between the three types of EPA and promoters in monocytes and CD4 + T cells was the 299 highest in EPA shortened at forward-reverse orientation of CTCF-binding sites (Table  300 S16). Conversely, the ratio of the sum of median expression levels between the three 301 types of EPA and promoters in H1-hESC and iPSC was the lowest in EPA shortened at 302 forward-reverse orientation of CTCF-binding sites. 303 EPA shortened at forward-reverse orientation of CTCF-binding sites changed (i.e. 304 increased or decreased) the expression levels of target genes more than the other types 305 of EPA. This implied that gene expression tended to be activated in monocytes and 306 CD4 + T cells, but repressed in H1-hESC and iPSC by enhancers. EPA shortened at 307 forward-reverse orientation of CTCF-binding sites also showed the highest normalized 308 number of functional enrichments of transcriptional target genes, as shown in the 309 previous paragraphs. The median expression level of human putative transcriptional target genes was 332 changed according to the criteria of enhancer-promoter assignments, and was correlated 333 with the normalized number of functional enrichments. The median expression level of 334 transcriptional target genes was 'decreased' significantly in transcriptional target genes 335 predicted using enhancers, compared with those predicted using promoters in H1-hESC 336 and iPSC, and the median expression level was 'increased' significantly in target genes 337 predicted using enhancers, compared with those predicted using promoters in 338 monocytes and CD4 + T cells. These results implied that transcription factors bound in 339 enhancers act as repressors in H1-hESC (ES) and iPSC, but those act as activators in monocytes and CD4 + T cells. The change of functional roles of transcription factors 341 depending on the cell types would be analyzed and reported elsewhere. 342 The median expression level was increased significantly in target genes predicted 343 using enhancers, compared with those predicted from promoters in immune cells using It is difficult to predict enhancer-promoter associations using a single parameter, 366 so that machine learning methods to combine several parameters have been proposed 367 [17][18][19]. These methods showed high accuracy in predicting enhancer-promoter 368 associations (I tried to use some of the tools, but they did not work properly. I am 369 waiting for the authors to update the tools). However, molecular mechanisms of 370 enhancer-promoter interactions are not clearly understood. CTCF has been found to 371 bind at chromatin interaction anchors and form chromatin interactions [12]. About 372 20-40% of chromatin interaction anchors included DNA binding sequences of CTCF, 373 when I examined public Hi-C experimental data [20,21]. Among 33,939 RefSeq 374 transcripts, 7,202 (21%), 4,404 (13%), and 6,921 (20%) (p-value < 10 -5 in the search for 375 CTCF-binding motifs using FIMO) to 9,608 (28%), 5,806 (17%), and 9,137 (27%) 376 (p-value < 10 -4 ) of transcripts had forward-reverse orientation of CTCF-binding sites 377 within 1 Mb from transcriptional start sites in the three immune cell types, respectively. To investigate whether the normalized numbers of functional enrichments of 524 transcriptional target genes correlate with the prediction of target genes, a part of target 525 genes were changed with randomly selected genes with high expression level (top 30% 526 expression level), and functional enrichments of the target genes were examined. First, 527 5%, 10%, 20%, 40%, and 60% of target genes were changed with randomly selected 528 genes with high expression level in monocytes, CD4 + T cells, and CD20 + B cells. 529 Second, as another randomization of target genes, the same number of 5%, 10%, 20%, 530 40%, and 60% of target genes were selected randomly from highly expressed genes, 531 then added them to the original target genes, and functional enrichments of the target 532 genes were examined. All analyses were repeated three times to estimate standard errors 533 ( Figure 2A and B, Figure S1 and S2, and Table S1). The same analysis was performed 534 using DNase-DGF data and ChIP-seq data of 19 TF in H1-hESC. Transcriptional target 535 genes were predicted from promoter (Tables S2).  regions for enhancer-promoter association (association rule 4) were shortened at the 551 genomic locations of CTCF-binding sites that were the closest to a transcriptional start 552 site, and transcriptional target genes were predicted from the shortened enhancer 553 regions using TFBS. Furthermore, promoter and extended regions for 554 enhancer-promoter association (association rule 4) were shortened at the genomic 555 locations of forward-reverse orientation of CTCF-binding sites. When forward or 556 reverse orientation of CTCF-binding sites were continuously located in genome 557 sequences several times, the most external forward-reverse orientation of 558 CTCF-binding sites were selected. 559

Figure 2. Effect of randomly selected genes on functional enrichments. (a) Effect of 882
randomly selected genes on functional enrichments using DNase-DGF data. 883 Transcriptional target genes were predicted using DNase-DGF data in human 884 monocytes, CD4 + T, CD20 + B, other four somatic and two stem cells (H1-hESC and 885 iPSC) (see also Figure S1). To test whether slight changes of transcriptional target genes 886 were reflected in the normalized number of their functional enrichments, the ratio of 887 randomly selected genes in the target genes of each TF was changed between 5% and 888 60%. In the left part of the graphs, randomly selected genes were replaced with the 889 target genes where the total number of target genes was unchanged. In the right part of 890 the graphs, randomly selected genes were added to the target genes where the total 891 number of target genes was increased. The result of Gene Ontology annotation was 892 shown. The results of Pathway Commons and KEGG were shown in Figure S1. Native 893 target genes showed the most functional enrichments in most cell types. (b) Effect of 894 randomly selected genes on functional enrichments using ChIP-seq data. Transcriptional 895 target genes were predicted using ChIP-seq data of 19 TF in H1-hESC. The results of 896 nine functional annotation databases were shown and the result of target genes of 897 microRNAs was shown in Figure S2. Native target genes showed the most functional 898 enrichments using most annotation databases except for low frequent functional 899 annotations. Putative transcriptional target genes tend to include similar function of 900 genes. 901 orientation exist in >60% neighboring TAD boundaries (Figure S4D), suggesting that the boundary reverse-forward CBS pairs play an important role in the formation of most of TADs. For example, there is a CBS pair in the reverse-forward orientation in a Chr12 genomic region of H1-hESC cells, located at or very close to each of the six TAD boundaries (boundaries 1-6), except for boundary 5, which has only one closely located CBS in the forward orientation ( Figure S4E). These data, taken together, strongly suggest that directional binding of CTCF to boundary CBS pairs in the reverse-forward orientations causes opposite topological looping and thus appears to function as insulators.
The Human b-globin Locus Provides an Additional Example of CBS Orientation-Dependent Topological Chromatin Looping Based on the location and orientation of CBSs, as well as their CTCF/cohesin occupancy, we identified four CCDs (domains 1-4) in the well-characterized b-globin cluster ( Figure 5A). The b-globin gene cluster is located between CBS3 (5 0 HS5) and CBS4 (3 0 HS1) in domain1 ( Figure 5A) (Hou et al., 2010;Splinter et al., 2006). We generated a series of CBS4/5 mutant K562 cell lines using CRISPR/Cas9 with one or two sgRNAs (Li et al.,  Figure S4 and Tables S1, S2 and S6.

2015) (Figures S2B and S2C
CRISPR cell lines D3, D7, and of 38 clones screened) in which nal CBS4 (3 0 HS1) was dele ure S2B), chromatin-looping in between CBS3 (5 0 HS5) in th orientation and the boundary CBS5 in the reverse ori domain1 persisted, although its interaction with (3 0 HS1) region was abolished ( Figures S5A and S5 pected, the interactions between CBS6/7 and C domain2 were unchanged ( Figure S5C). Strikingly, h the CBS4 (3 0 HS1) and CBS5 double-knockout CRISP C2, C4, and C14 (out of 49 clones screened) (Figure S chromatin-looping interactions between CBS3 (5 0 HS5 ward orientation of domain1 and CBS8/9 in the rever tion of the neighboring domain2 were observed, sugg these two domains merge as a single domain in CR lines with CBS4/5 double knockout ( Figure S5B). when CBS8 was used as an anchor, this reverse-orie in domain2 establishes new long-range chromatin-loo actions with CBS1-3 in the forward orientation of dom CBS4/5 double-deletion CRISPR cell lines (Figure conclude that cross-domain interactions can be e after deletion of CBSs up to the boundary of topol mains, but not after deletion of the internal CBS in th locus.
To further test the functional significance of this or of CBSs, we again performed CRISPR/cas9-media fragment editing in the HEK293T cells and screened 19

CTCF-mediated DNA Looping
Forward Orientation of CTCF-binding Sites orientation exist in >60% neighboring TAD boundaries (Figure S4D), suggesting that the boundary reverse-forward CBS pairs play an important role in the formation of most of TADs. For example, there is a CBS pair in the reverse-forward orientation in a Chr12 genomic region of H1-hESC cells, located at or very close to each of the six TAD boundaries (boundaries 1-6), except for boundary 5, which has only one closely located CBS in the forward orientation ( Figure S4E). These data, taken together, strongly suggest that directional binding of CTCF to boundary CBS pairs in the reverse-forward orientations causes opposite topological looping and thus appears to function as insulators.
The Human b-globin Locus Provides an Additional Example of CBS Orientation-Dependent Topological Chromatin Looping Based on the location and orientation of CBSs, as well as their CTCF/cohesin occupancy, we identified four CCDs (domains 1-4) in the well-characterized b-globin cluster ( Figure 5A). The b-globin gene cluster is located between CBS3 (5 0 HS5) and CBS4 (3 0 HS1) in domain1 ( Figure 5A) (Hou et al., 2010;Splinter et al., 2006). We generated a series of CBS4/5 mutant K562 cell lines using CRISPR/Cas9 with one or two sgRNAs (Li et al.,  Figure S4 and Tables S1, S2 and S6.

2015) (Figures S2B and S2
CRISPR cell lines D3, D7, and of 38 clones screened) in whic nal CBS4 (3 0 HS1) was del ure S2B), chromatin-looping in between CBS3 (5 0 HS5) in th orientation and the boundary CBS5 in the reverse or domain1 persisted, although its interaction with (3 0 HS1) region was abolished ( Figures S5A and S5 pected, the interactions between CBS6/7 and C domain2 were unchanged ( Figure S5C). Strikingly, h the CBS4 (3 0 HS1) and CBS5 double-knockout CRISP C2, C4, and C14 (out of 49 clones screened) (Figure S chromatin-looping interactions between CBS3 (5 0 HS5 ward orientation of domain1 and CBS8/9 in the rever tion of the neighboring domain2 were observed, sugg these two domains merge as a single domain in C lines with CBS4/5 double knockout ( Figure S5B) when CBS8 was used as an anchor, this reverse-ori in domain2 establishes new long-range chromatin-loo actions with CBS1-3 in the forward orientation of dom CBS4/5 double-deletion CRISPR cell lines (Figure conclude that cross-domain interactions can be e after deletion of CBSs up to the boundary of topo mains, but not after deletion of the internal CBS in th locus.
To further test the functional significance of this o of CBSs, we again performed CRISPR/cas9-medi fragment editing in the HEK293T cells and screened 1  Tables   939   940   Tables are attached in   Validated targets of C-MYC transcriptional activation 11 IL8-and CXCR2-mediated signaling events 10 Antigen processing-Cross presentation 9 BCR signaling pathway 9 IL6-mediated signaling events 9 Cell junction organization 9 ER-Phagosome pathway 8 Regulation of CDC42 activity 8 CXCR4-mediated signaling events 8 CDC42 signaling events 8 Syndecan-4-mediated signaling events 8 Noncanonical Wnt signaling pathway 7 Class I MHC mediated antigen processing & presentation 7   Table 3. Normalized number of functional enrichments of putative transcriptional target genes using promoter and extended regions for enhancer-promoter association. * Wilcoxon signed-rank test p < 0.05