bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

1 Discovery of biased orientation of human DNA motif sequences

2 affecting enhancer-promoter interactions and transcription of genes

3

4 Naoki Osato1*

5

6 1Department of Bioinformatic Engineering, Graduate School of Information Science

7 and Technology, Osaka University, Osaka 565-0871, Japan

8 *Corresponding author

9 E-mail address: [email protected], [email protected]

10

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11 Abstract

12 Chromatin interactions have important roles for enhancer-promoter interactions

13 (EPI) and regulating the transcription of genes. CTCF and cohesin proteins are located

14 at the anchors of chromatin interactions, forming their loop structures. CTCF has

15 insulator function limiting the activity of enhancers into the loops. DNA binding

16 sequences of CTCF indicate their orientation bias at chromatin interaction anchors –

17 forward-reverse (FR) orientation is frequently observed. DNA binding sequences of

18 CTCF were found in open chromatin regions at about 40% - 80% of chromatin

19 interaction anchors in Hi-C and in situ Hi-C experimental data. Though the number of

20 chromatin interactions was about seventy thousand in Hi-C at 50kb resolution, about

21 twenty millions of chromatin interactions were recently identified by HiChIP at 5kb

22 resolution. It has been reported that long range of chromatin interactions tends to

23 include less CTCF at their anchors. It is still unclear what proteins are associated with

24 chromatin interactions.

25 To find DNA binding motif sequences of transcription factors (TF), such as CTCF,

26 and repeat DNA sequences affecting the interaction between enhancers and promoters

27 of genes and their expression, first I predicted TF bound in enhancers and promoters

28 using DNA motif sequences of TF and experimental data of open chromatin regions in

29 monocytes and other cell types, which were obtained from public and commercial

30 databases. Second, transcriptional target genes of each TF were predicted based on

31 enhancer-promoter association (EPA). EPA was shortened at the genomic locations of

32 FR or reverse-forward (RF) orientation of DNA motif sequence of a TF, which were

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33 supposed to be at chromatin interaction anchors and acted as insulator sites like CTCF.

34 Then, the expression levels of the transcriptional target genes predicted based on the

35 EPA were compared with those predicted from only promoters.

36 Total 287 biased orientation of DNA motifs (159 FR and 153 RF orientation, the

37 reverse complement sequences of some DNA motifs were also registered in databases,

38 so the total number was smaller than the number of FR and RF) affected the expression

39 level of putative transcriptional target genes significantly in CD14+ monocytes of four

40 people in common. The same analysis was conducted in CD4+ T cells of four people.

41 DNA motif sequences of CTCF, cohesin and other transcription factors involved in

42 chromatin interactions were found to be a biased orientation. Transposon sequences,

43 which are known to be involved in insulators and enhancers, showed a biased

44 orientation. The biased orientation of DNA motif sequences tended to be co-localized in

45 the same open chromatin regions. Moreover, for ~85% of FR and RF orientations of

46 DNA motif sequences, EPI predicted from EPA that were shortened at the genomic

47 locations of the biased orientation of DNA motif sequence were overlapped with

48 chromatin interaction data (Hi-C and HiChIP) significantly more than other types of

49 EPAs.

50

51 Keywords: transcriptional target genes, gene expression, transcription factors, enhancer,

52 enhancer-promoter interactions, chromatin interactions, CTCF, cohesin, open chromatin

53 regions, co-location of transcription factors, homodimer, heterodimer, complex

54

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55 Background

56 Chromatin interactions have important roles for enhancer-promoter interactions

57 (EPI) and regulating the transcription of genes. CTCF and cohesin proteins are located

58 at the anchors of chromatin interactions, forming their loop structures. CTCF has

59 insulator function limiting the activity of enhancers into the loops (Fig. 1A). DNA

60 binding sequences of CTCF indicate their orientation bias at chromatin interaction

61 anchors – forward-reverse (FR) orientation is frequently observed (de Wit et al. 2015;

62 Guo et al. 2015). About 40% - 80% of chromatin interaction anchors of Hi-C and in situ

63 Hi-C experiments include DNA binding motif sequences of CTCF. Though the number

64 of chromatin interactions was about seventy thousand in Hi-C at 50kb resolution

65 (Javierre et al. 2016), about twenty millions of chromatin interactions were recently

66 identified by HiChIP at 5kb resolution (Mumbach et al. 2017). However, it has been

67 reported that long range of chromatin interactions tends to include less CTCF at their

68 anchors (Jeong et al. 2017). Other DNA binding proteins such as ZNF143, YY1, and

69 SMARCA4 (BRG1) are found to be associated with chromatin interactions and EPI

70 (Bailey et al. 2015; Barutcu et al. 2016; Weintraub et al. 2017). CTCF, cohesin, ZNF143,

71 YY1 and SMARCA4 have other biological functions as well as chromatin interactions

72 and EPI. The DNA binding motif sequences of the transcription factors (TF) are found

73 in open chromatin regions near transcriptional start sites (TSS) as well as chromatin

74 interaction anchors.

75 DNA binding motif sequence of ZNF143 was enriched at both chromatin

76 interaction anchors. ZNF143’s correlation with the CTCF-cohesin cluster relies on its

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77 weakest binding sites, found primarily at distal regulatory elements defined by the

78 ‘CTCF-rich’ chromatin state. The strongest ZNF143-binding sites map to promoters

79 bound by RNA polymerase II (POL2) and other promoter-associated factors, such as the

80 TATA-binding protein (TBP) and the TBP-associated protein, together forming a

81 ‘promoter’ cluster (Bailey et al. 2015).

82 DNA binding motif sequence of YY1 does not seem to be enriched at both

83 chromatin interaction anchors (Z-score < 2), whereas DNA binding motif sequence of

84 ZNF143 is significantly enriched (Z-score > 7; Bailey et al. 2015 Figure 2a). In the

85 analysis of YY1, to identify a protein factor that might contribute to EPI, (Ji et al. 2015)

86 performed chromatin immune precipitation with mass spectrometry (ChIP-MS), using

87 antibodies directed toward histones with modifications characteristic of enhancer and

88 promoter chromatin (H3K27ac and H3K4me3, respectively). Of 26 transcription factors

89 that occupy both enhancers and promoters, four are essential based on a CRISPR

90 cell-essentiality screen and two (CTCF, YY1) are expressed in >90% of tissues

91 examined (Weintraub et al. 2017). These analyses started from the analysis of histone

92 modifications of enhancer and promoter marks rather than chromatin interactions. Other

93 protein factors associated with chromatin interactions may be found from other

94 researches.

95 As computational approaches, machine-learning analyses to predict chromatin

96 interactions have been proposed (Schreiber et al. 2017; Zhang et al. 2017). However,

97 they were not intended to find DNA motif sequences of TF affecting chromatin

98 interactions, EPI, and the expression level of transcriptional target genes, which were

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99 examined in this study.

100 DNA binding proteins involved in chromatin interactions are supposed to affect

101 the transcription of genes in the loops formed by chromatin interactions. In my previous

102 analysis, the expression level of human putative transcriptional target genes was

103 affected, according to the criteria of enhancer-promoter association (EPA) (Fig. 1B;

104 (Osato 2018)). EPI were predicted based on EPA shortened at the genomic locations of

105 FR orientation of CTCF binding sites, and transcriptional target genes of each TF bound

106 in enhancers and promoters were predicted based on the EPI. The EPA affected the

107 expression levels of putative transcriptional target genes the most among three types of

108 EPAs, compared with the expression levels of transcriptional target genes predicted

109 from only promoters (Fig. 2). The expression levels tended to be increased in

110 monocytes and CD4+ T cells, implying that enhancers activated the transcription of

111 genes, and decreased in ES and iPS cells, implying that enhancers repressed the

112 transcription of genes. These analyses suggested that enhancers affected the

113 transcription of genes significantly, when EPI were predicted properly. Other DNA

114 binding proteins involved in chromatin interactions, as well as CTCF, may locate at

115 chromatin interaction anchors with a pair of biased orientation of DNA binding motif

116 sequences, affecting the expression level of putative transcriptional target genes in the

117 loops formed by the chromatin interactions. As experimental issues of the analyses of

118 chromatin interactions, chromatin interaction data are changed, according to

119 experimental techniques, depth of DNA sequencing, and even replication sets of the

120 same cell type. Chromatin interaction data may not be saturated enough to cover all

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121 chromatin interactions. Supposing these characters of DNA binding proteins associated

122 with chromatin interactions and avoiding experimental issues of the analyses of

123 chromatin interactions, here I searched for DNA motif sequences of TF and repeat DNA

124 sequences, affecting EPI and the expression level of putative transcriptional target genes

125 in CD14+ monocytes and CD4+ T cells of four people and other cell types without using

126 chromatin interaction data. Then, putative EPI were compared with chromatin

127 interaction data.

128

129 Results

130 Search for biased orientation of DNA motif sequences

131 Transcription factor binding sites (TFBS) were predicted using open chromatin

132 regions and DNA motif sequences of transcription factors (TF) collected from various

133 databases and journal papers (see Methods). Transcriptional target genes were predicted

134 using TFBS in promoters and enhancer-promoter association (EPA) shortened at the

135 genomic locations of DNA binding motif sequence of a TF acting as insulator such as

136 CTCF and cohesin (RAD21 and SMC3) (Fig. 1B). To find DNA motif sequences of TF

137 acting as insulator, other than CTCF and cohesin, and repeat DNA sequences affecting

138 the expression level of genes, EPI were predicted based on EPA shortened at the

139 genomic locations of the DNA motif sequence of a TF or a repeat DNA sequence, and

140 transcriptional target genes of each TF bound in enhancers and promoters were

141 predicted based on the EPI. The expression levels of the putative transcriptional target

142 genes were compared with those predicted from promoters using Mann Whiteney U test,

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143 two-sided (p-value < 0.05) (Fig. 2A). The number of TF showing a significant

144 difference of expression level of their putative transcriptional target genes was counted.

145 To examine whether the orientation of a DNA motif sequence, which is supposed to act

146 as insulator sites and shorten EPA, affected the number of TF showing a significant

147 difference of expression level of their putative transcriptional target genes, the number

148 of the TF was compared among forward-reverse (FR), reverse-forward (RF), and any

149 orientation (i.e. without considering orientation) of a DNA motif sequence shortening

150 EPA, using chi-square test (p-value < 0.05). To avoid missing DNA motif sequences

151 showing a relatively weak statistical significance by multiple testing collection, the

152 above analyses were conducted using monocytes of four people independently, and

153 DNA motif sequences found in monocytes of four people in common were selected.

154 Total 287 of biased (159 FR and 153 RF) orientation of DNA binding motif sequences

155 of TF were found in monocytes of four people in common, whereas only one any

156 orientation of DNA binding motif sequence was found in monocytes of four people in

157 common (Fig. 2B; Table 1; Supplemental Table S1). FR orientation of DNA motif

158 sequences included CTCF, cohesin (RAD21 and SMC3), ZNF143 and YY1, which are

159 associated with chromatin interactions and EPI. SMARCA4 (BRG1) is associated with

160 topologically associated domain (TAD), which is higher-order chromatin organization.

161 The DNA binding motif sequence of SMARCA4 was not registered in the databases

162 used in this study. FR orientation of DNA motif sequences included SMARCC2, a

163 member of the same SWI/SNF family of proteins as SMARCA4.

164 The same analysis was conducted using DNase-seq data of CD4+ T cells of four

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165 people. Total 265 of biased (158 FR and 139 RF) orientation of DNA binding motif

166 sequences of TF were found in T cells of four people in common, whereas only four any

167 orientation (i.e. without considering orientation) of DNA binding motif sequences were

168 found in T cells of four people in common (Supplemental Fig. S1 and Supplemental

169 Table S2). Biased orientation of DNA motif sequences in T cells included CTCF,

170 cohesin (RAD21 and SMC3), ZNF143, YY1, and SMARC. Biased orientation of DNA

171 motif sequences in T cells and monocytes (using H3K27ac histone modification marks,

172 which is described in the next paragraph) included JUNDM2 (JDP2), which is involved

173 in histone-chaperone activity, promoting nucleosome, and inhibition of histone

174 acetylation (Jin et al. 2006). JDP2 forms a homodimer or heterodimer with various TF

175 (https://en.wikipedia.org/wiki/Jun_dimerization_protein). Among 287, 61 of biased

176 orientation of DNA binding motif sequences of TF were found in both monocytes and T

177 cells in common (Supplemental Table S5). For each orientation, 31 FR and 34 RF

178 orientation of DNA binding motif sequences of TF were found in both monocytes and T

179 cells in common. Without considering the difference of orientation of DNA binding

180 motif sequences, 84 of biased orientation of DNA binding motif sequences of TF were

181 found in both monocytes and T cells. As a reason for the increase of the number (84)

182 from 61, a TF or an isoform of the same TF may bind to a different DNA binding motif

183 sequence according to cell types and/or in the same cell type. About 50% or more of

184 alternative splicing isoforms are differently expressed among tissues, indicating that

185 most alternative splicing is subject to tissue-specific regulation (Wang et al. 2008)

186 (Chen and Manley 2009) (Das et al. 2007). The same TF has several DNA binding

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187 motif sequences and in some cases one of the motif sequences is almost the same as the

188 reverse complement sequence of another motif sequence of the same TF. For example,

189 RAD21 had both FR and RF orientation of DNA motif sequences, but the number of the

190 FR orientation of DNA motif sequence was relatively small in the genome, and the RF

191 orientation of DNA motif sequence was frequently observed and co-localized with

192 CTCF. I previously found that a complex of TF would bind to a slightly different DNA

193 binding motif sequence from the combination of DNA binding motif sequences of TF

194 composing the complex in C. elegans (Tabuchi et al. 2011). From another viewpoint of

195 this study, the expression level of putative transcription target genes of some TF would

196 be different, depending on the genomic locations (enhancers or promoters) of DNA

197 binding motif sequences of the TF in monocytes and T cells of four people.

198 Moreover, using open chromatin regions overlapped with H3K27ac histone

199 modification marks known as enhancer and promoter marks, the same analyses were

200 performed in monocytes and T cells. H3K27ac histone modification marks were used in

201 the analysis of EPI, but were not used in the analysis of TF as insulator like CTCF and

202 cohesin in this study, since new biased orientation of DNA motif sequences were found

203 in this criterion. When H3K27ac histone modification marks were used in the analysis

204 of TF as insulator like CTCF and cohesin, the number of biased orientation of DNA

205 motif sequences was decreased. Total 241 of biased (141 FR and 120 RF) orientation of

206 DNA binding motif sequences of TF were found in monocytes of four people in

207 common, whereas only one any orientation of DNA binding motif sequence was found

208 (Supplemental Table S3). Though the number of biased orientation of DNA motif

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209 sequences was reduced, JDP2 was found in monocytes as well as T cells. CTCF,

210 RAD21, SMC3, ZNF143, YY1, and SMARCC2 were also found. For T cells using

211 H3K27ac histone modification marks, total 195 of biased (107 FR and 110 RF)

212 orientation of DNA binding motif sequences of TF were found in T cells of four people

213 in common, whereas only six any orientation of DNA binding motif sequences were

214 found (Supplemental Table S4). Though the number of biased orientation of DNA motif

215 sequences was reduced, CTCF, RAD21, SMC3, YY1, and SMARCC2 were found.

216 Scores of CTCF, RAD21, and SMC3 were increased compared with the result of T cells

217 without using H3K27ac histone modification marks, and they were ranked in the top six.

218 As summary of the results with and without H3K27ac histone modification marks, total

219 386 of biased (223 FR and 214 RF) orientation of DNA motif sequences were found in

220 monocytes of four people in common. Total 348 of biased (202 FR and 198 RF)

221 orientation of DNA motif sequences were found in T cells of four people in common.

222 Total number of these results in monocytes and T cells was 590 biased (368 FR and 359

223 RF) orientation of DNA motif sequences. Biased orientation of DNA motif sequences

224 found in both monocytes and T cells were listed in Supplemental Table S5.

225 To examine whether the biased orientation of DNA binding motif sequences of

226 TF were observed in other cell types, the same analyses were conducted in other cell

227 types. However, for other cell types, experimental data of one sample were available in

228 ENCODE database, so the analyses of DNA motif sequences were performed by

229 comparing with the result in monocytes of four people. Among the biased orientation of

230 DNA binding motif sequences found in monocytes, 69, 82, 56, and 53 DNA binding

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231 motif sequences were also observed in H1-hESC, iPS, Huvec and MCF-7 respectively,

232 including CTCF and cohesin (RAD21 and SMC3) (Table 2; Supplemental Table S6).

233 The scores of DNA binding motif sequences were the highest in monocytes, and the

234 other cell types showed lower scores. The results of the analysis of DNA motif

235 sequences in CD20+ B cells and macrophages did not include CTCF and cohesin,

236 because these analyses can be utilized in cells where the expression level of putative

237 transcriptional target genes of each TF show a significant difference between promoters

238 and EPA shortened at the genomic locations of a DNA motif sequence acting as

239 insulator sites. Some experimental data of a cell did not show a significant difference

240 between promoters and the EPA (Osato 2018).

241 Instead of DNA binding motif sequences of TF, repeat DNA sequences were also

242 examined. The expression levels of transcriptional target genes of each TF predicted

243 based on EPA that were shortened at the genomic locations of a repeat DNA sequence

244 were compared with those predicted from promoters. Three RF orientation of repeat

245 DNA sequences showed a significant difference of expression level of putative

246 transcriptional target genes in monocytes of four people in common (Table 3). Among

247 them, LTR16C repeat DNA sequence was observed in iPS and H1-hESC with enough

248 statistical significance considering multiple tests (p-value < 10-7). The same as CD14+

249 monocytes, biased orientation of repeat DNA sequences were examined in CD4+ T cells.

250 Three FR and two RF orientation of repeat DNA sequences showed a significant

251 difference of expression level of putative transcriptional target genes in T cells of four

252 people in common (Supplemental Table S7). MIRb and MIR3 were also found in the

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253 analysis using open chromatin regions overlapped with H3K27ac histone modification

254 marks, which are enhancer and promoter marks. MIR and other transposon sequences

255 are known to act as insulators and enhancers (Bejerano et al. 2006; Rebollo et al. 2012;

256 de Souza et al. 2013; Jjingo et al. 2014; Wang et al. 2015).

257

258 Co-location of biased orientation of DNA motif sequences

259 To examine the association of 287 biased (FR and RF) orientation of DNA

260 binding motif sequences of TF, co-location of the DNA binding motif sequences in open

261 chromatin regions was analyzed in monocytes. The number of open chromatin regions

262 with the same pairs of DNA binding motif sequences was counted, and when the pairs

263 of DNA binding motif sequences were enriched with statistical significance (chi-square

264 test, p-value < 1.0 × 10-10), they were listed (Table 4; Supplemental Table S8; Fig. 3A).

265 Open chromatin regions overlapped with histone modification of enhancer and

266 promoter marks (H3K27ac) (total 26,095 regions) showed a larger number of enriched

267 pairs of DNA motifs than all open chromatin regions (Table 4; Supplemental Table S8;

268 Fig. 3A). H3K27ac is known to be enriched at chromatin interaction anchors (Phanstiel

269 et al. 2017). As already known, CTCF was found with cohesin such as RAD21 and

270 SMC3 (Table 4; Fig. 3A). Top 30 pairs of FR and RF orientations of DNA motifs

271 co-occupied in the same open chromatin regions were shown (Table 4). Total number of

272 pairs of DNA motifs was 492, consisting of 115 unique DNA motifs, when the pair of

273 DNA motifs were observed in more than 80% of the number of open chromatin regions

274 with the DNA motifs. Biased orientation of DNA binding motif sequences of TF tended

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275 to be co-localized in the same open chromatin regions.

276 To examine the association of 265 biased orientation of DNA binding motif

277 sequences of TF in CD4+ T cells, co-location of the DNA binding motif sequences in

278 open chromatin regions was analyzed. Top 30 pairs of FR and RF orientations of DNA

279 motifs co-occupied in the same open chromatin regions were shown (Supplemental

280 Table S9; Supplemental Fig. S2). Total number of pairs of DNA motifs was 332,

281 consisting of 118 unique DNA motifs, when the pair of DNA motifs were observed in

282 more than 60% of the number of open chromatin regions with the DNA motifs

283 (chi-square test, p-value < 1.0 × 10-10). Among them, 12 pairs of DNA motif

284 sequences including a pair of CTCF, SMC3, and RAD21 in T cells were found in

285 monocytes in common (Supplemental Table S9).

286

287 Pairs of biased orientation of DNA motif sequences surrounding genes

288 CTCF and cohesin are found in chromatin interaction anchors and are considered

289 to form homodimers. TF are also known to form heterodimers with another TF. In this

290 study, if the DNA binding motif sequence of only the mate to a pair of TF was found in

291 EPA, EPA was shortened at one side, which is the genomic location of the DNA binding

292 motif sequence of the mate to the pair, and transcriptional target genes were predicted

293 using the EPA shortened at the side. In this analysis, the mate to both heterodimer and

294 homodimer of TF can be used to examine the effect on the expression level of

295 transcriptional target genes predicted based on the EPA shortened at one side. To

296 examine whether biased orientation of DNA motif sequences tend to be found as a pair

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297 of the same TF or different TF in upstream and downstream of genes, the enrichment of

298 pairs of biased orientation of DNA motif sequences was investigated. The number of

299 genes with a pair of FR or RF orientation of DNA motif sequences was counted using

300 all pairs of the DNA motif sequences, and statistical tests (chi-square test) were

301 conducted. The total number of genes (transcripts) with a biased orientation of DNA

302 motif sequence in their upstream or/and downstream was about 20,000. This is almost

303 the same way of analysis as co-location of biased orientation of DNA motif sequences,

304 and the analysis here used the number of genes instead of open chromatin regions. Fig.

305 3B and Supplemental Fig. S3 showed that not only pairs of the same TF, but also pairs

306 of different TF were found in upstream and downstream of genes. DNA motif sequences

307 of CTCF and cohesin (RAD21 and SMC3) were enriched near the same genes, but

308 cohesin tended to be found with another TF near the same genes as well. The number of

309 some pairs of biased orientation of DNA motif sequences in genome sequences was

310 small, though they showed statistical significance (Supplemental material 2). The result

311 of the analysis seems to be different between monocytes and T cells and between using

312 H3K27ac histone modification marks and not using them (Supplemental Fig. S3). Some

313 of these TF would form homodimers or heterodimers directory or indirectly composing

314 a complex structure, contributing to make chromatin interactions (Fig. 5).

315

316 Comparison with chromatin interaction data

317 To examine whether the biased orientation of DNA motif sequences is associated

318 with chromatin interactions, enhancer-promoter interactions (EPI) predicted based on

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319 enhancer-promoter associations (EPA) were compared with chromatin interaction data

320 (Hi-C). Due to the resolution of Hi-C experimental data used in this study (50kb), EPI

321 were adjusted to 50kb resolution. EPI were predicted based on three types of EPA: (i)

322 EPA shortened at the genomic locations of FR or RF orientation of DNA motif sequence

323 of a TF, (ii) EPA shortened at the genomic locations of DNA motif sequence of a TF

324 acting as insulator sites such as CTCF and cohesin (RAD21, SMC3) without

325 considering their orientation, and (iii) EPA without being shortened by the genomic

326 locations of a DNA motif sequence. EPA (i) showed a significantly higher ratio of EPI

327 overlapped with chromatin interactions (Hi-C) using DNA binding motif sequences of

328 CTCF and cohesin (RAD21 and SMC3) than the other two types of EPAs (n = 4,

329 binomial test, two-sided) (Supplemental Fig. S4). Total 59 biased orientation (40 FR

330 and 23 RF) of DNA motif sequences including CTCF, cohesin, and YY1 showed a

331 significantly higher ratio of EPI overlapped with Hi-C chromatin interactions (a cutoff

332 score of CHiCAGO tool > 1) than the other types of EPAs in monocytes (Supplemental

333 Table S10). When comparing EPI predicted based on only EPA (i) and (iii) with

334 chromatin interactions, total 174 biased orientation (101 FR and 84 RF) of DNA motif

335 sequences showed a significantly higher ratio of EPI predicted based on EPA (i)

336 overlapped with the chromatin interactions than EPI predicted based on EPA (iii)

337 (Supplemental material 2). The difference between EPI predicted based on EPA (i) and

338 (ii) seemed to be difficult to distinguish using the chromatin interaction data and the

339 statistical test in some cases. However, as for the difference between EPI predicted

340 based on EPA (i) and (iii), a larger number of biased orientation of DNA motif

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341 sequences was found to be correlated with chromatin interaction data. Chromatin

342 interaction data were obtained from different samples from DNase-seq, open chromatin

343 regions, so individual differences seemed to be large from the results of this analysis.

344 Since, for some DNA motif sequences of transcription factors, the number of EPI

345 overlapped with chromatin interactions was small, if higher resolution of chromatin

346 interaction data (such as HiChIP, in situ DNase Hi-C, and in situ Hi-C data, or a tool to

347 improve the resolution such as HiCPlus) is available, the number of EPI overlapped

348 with chromatin interactions would be increased and the difference of the numbers

349 among three types of EPA would be larger and more significant (Rao et al. 2014;

350 Ramani et al. 2016; Mumbach et al. 2017; Zhang et al. 2018).

351 After the analysis of CD14+ monocytes, to utilize HiChIP chromatin interaction

352 data in CD4+ T cells, the same analysis for CD14+ monocytes was performed using

353 DNase-seq data of four donors in CD4+ T cells (Mumbach et al. 2017). EPI predicted

354 based on EPA were compared with HiChIP chromatin interaction data in CD4+ T cells.

355 The resolutions of HiChIP chromatin interaction data and EPI were adjusted to 5kb. EPI

356 were predicted based on the three types of EPA in the same way as CD14+ monocytes

357 using top 60% of all the transcript (gene) excluding transcripts not expressed in T cells.

358 The criteria of the analysis were determined to include known DNA motif sequences

359 involved in chromatin interactions such as CTCF and cohesin in the result, and the

360 result was consistent with that using Hi-C chromatin interaction data. EPA (iii) showed

361 the highest ratio of EPI overlapped with chromatin interactions (HiChIP) using DNA

362 binding motif sequences of CTCF and cohesin (RAD21 and SMC3), compared with the

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363 other two types of EPAs (n = 4, binomial test, two-sided) (Fig. 4). Total 121 biased

364 orientation (73 FR and 58 RF) of DNA motif sequences including CTCF, cohesin,

365 ZNF143, and SMARC showed a significantly higher ratio of EPI overlapped with

366 HiChIP chromatin interactions (more than 1,000 counts for each interaction) than the

367 other types of EPAs in T cells (Table 5). When comparing EPI predicted based on only

368 EPA (i) and (iii) with the chromatin interactions, total 226 biased orientation (132 FR

369 and 123 RF) of DNA motif sequences showed a significantly higher ratio of EPI

370 predicted based on EPA (i) overlapped with the chromatin interactions than EPI

371 predicted based on EPA (iii) (Supplemental material 2). As expected, the number of EPI

372 overlapped with chromatin interactions (HiChIP) was increased, compared with Hi-C

373 chromatin interactions. Most of biased orientation of DNA motif sequences (85%) were

374 found to be correlated with chromatin interactions, when comparing EPI predicted

375 based on EPA (i) and (iii) with HiChIP chromatin interactions.

376 Though the ratios of EPI overlapped with chromatin interactions were increased

377 by using many chromatin interaction data including lower score and count of chromatin

378 interactions (a cutoff score of CHiCAGO tool > 1 for Hi-C and more than 1,000 counts

379 for HiChIP), the ratios of EPI overlapped with chromatin interactions showed the same

380 tendency among the three types of EPAs. The ratio of EPI overlapped with Hi-C

381 chromatin interactions was increased using H3K27ac marks in both monocytes and T

382 cells. The ratio of EPI overlapped with HiChIP chromatin interactions was also

383 increased using H3K27ac marks. Chromatin interaction data were obtained from

384 different samples from DNase-seq, open chromatin regions in CD4+ T cells, so

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385 individual differences seemed to be large from the results of this analysis, and

386 (Mumbach et al. 2017) suggested that individual differences of chromatin interactions

387 were larger than those of open chromatin regions. ATAC-seq data, open chromatin

388 regions were available in CD4+ T cells in the paper, however, when using ATAC-seq

389 data, the result of the analysis of biased orientation of DNA motif sequences was

390 different from DNase-seq data, and not included a part of CTCF and cohesin. Thus,

391 DNase-seq data collected from ENCODE and Blueprint projects were employed in this

392 study.

393

394 Discussion

395 To find DNA motif sequences of transcription factors (TF) and repeat DNA

396 sequences affecting the expression level of human putative transcriptional target genes,

397 the DNA motif sequences were searched from open chromatin regions of monocytes of

398 four people. Total 287 biased [159 forward-reverse (FR) and 153 reverse-forward (RF)]

399 orientation of DNA motif sequences of TF were found in monocytes of four people in

400 common, whereas only one any orientation (i.e. without considering orientation) of

401 DNA motif sequence of TF was found to affect the expression level of putative

402 transcriptional target genes, suggesting that enhancer-promoter association (EPA)

403 shortened at the genomic locations of FR or RF orientation of the DNA motif sequence

404 of a TF or a repeat DNA sequence is an important character for the prediction of

405 enhancer-promoter interactions (EPI) and the transcriptional regulation of genes.

406 When DNA motif sequences were searched from monocytes of one person, a

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407 larger number of biased orientation of DNA motif sequences affecting the expression

408 level of human putative transcriptional target genes were found. When the number of

409 donors, from which experimental data were obtained, was increased, the number of

410 DNA motif sequences found in all people in common decreased and in some cases,

411 known transcription factors involved in chromatin interactions such as CTCF and

412 cohesin (RAD21 and SMC3) were not identified by statistical tests. This would be

413 caused by individual difference of the same cell type, low quality of experimental data,

414 and experimental errors. Moreover, though FR orientation of DNA binding motif

415 sequences of CTCF and cohesin is frequently observed at chromatin interaction anchors,

416 the percentage of FR orientation is not 100, and other orientations of the DNA binding

417 motif sequences are also observed. Though DNA binding motif sequences of CTCF and

418 cohesin are found in various open chromatin regions, DNA binding motif sequences of

419 some TF would be observed less frequently in open chromatin regions. The analyses of

420 experimental data of a number of people would avoid missing relatively weak statistical

421 significance of DNA motif sequences of TF in experimental data of each person by

422 multiple testing correction of thousands of statistical tests. A DNA motif sequence was

423 found with p-value < 0.05 in experimental data of one person and the DNA motif

424 sequence found in the same cell type of four people in common would have p-value <

425 0.054 = 6.25 × 10-6. Actually, DNA motif sequences with p-value slightly less than 0.05

426 in monocytes of one person were observed in monocytes of four people in common.

427 EPI were compared with chromatin interactions (Hi-C) in monocytes. EPAs

428 shortened at the genomic locations of DNA binding motif sequences of CTCF and

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429 cohesin (RAD21 and SMC3) showed a significant difference of the ratios of EPI

430 overlapped with chromatin interactions, according to three types of EPAs (see Methods).

431 Using open chromatin regions overlapped with ChIP-seq experimental data of histone

432 modification of an enhancer mark (H3K27ac), the ratio of EPI not overlapped with

433 Hi-C was reduced. (Phanstiel et al. 2017) also reported that there was an especially

434 strong enrichment for loops with H3K27 acetylation peaks at both ends (Fisher’s Exact

435 Test, p = 1.4 × 10-27). However, the total number of EPI overlapped with chromatin

436 interactions was also reduced using H3K27ac peaks, so more chromatin interaction data

437 would be needed to obtain reliable results in this analysis. As an issue of experimental

438 data, data for chromatin interactions and open chromatin regions were came from

439 different samples and donors, so individual differences would exist in the data.

440 Moreover, the resolution of chromatin interaction data used in monocytes was about

441 50kb, thus the number of chromatin interactions was relatively small (72,284 at 50kb

442 resolution with a cutoff score of CHiCAGO tool > 1 and 16,501 with a cutoff score of

443 CHiCAGO tool > 5). EPI predicted based on EPA shortened at the genomic locations of

444 DNA binding motif sequence of TF that were found in various open chromatin regions

445 such as CTCF and cohesin (RAD21 and SMC3) tended to be overlapped with a larger

446 number of chromatin interactions than TF less frequently observed in open chromatin

447 regions. Therefore, to examine the difference of the numbers of EPI overlapped with

448 chromatin interactions, according to the three types of EPAs, the number of chromatin

449 interactions should be large enough.

450 As HiChIP chromatin interaction data were available in CD4+ T cells, biased

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451 orientation of DNA motif sequences of TF were examined in T cells using DNase-seq

452 data of four people. The resolutions of chromatin interactions and EPI were adjusted to

453 5kb by fragmentation of genome sequences. In monocytes, the resolution of Hi-C

454 chromatin interaction data was converted by extending anchor regions of chromatin

455 interactions to 50kb length and merging the chromatin interactions overlapped with

456 each other. Fragmentation of genome sequences may affect the classification of

457 chromatin interactions of which anchors are located near the border of a fragment, but

458 the number of chromatin interactions would not be decreased, compared with merging

459 chromatin interactions. The number of HiChIP chromatin interactions was 19,926,360

460 at 5kb resolution, 666,149 at 5kb resolution with chromatin interactions (more than

461 1,000 counts for each interaction), and 78,209 at 5kb resolution with chromatin

462 interactions (more than 6,000 counts for each interaction). As expected, the number of

463 EPI overlapped with chromatin interactions was increased, and 46 – 85% of biased

464 orientation of DNA motif sequences of TF showed a statistical significance in EPI

465 predicted based on EPA shortened at the genomic locations of the DNA motif sequence,

466 compared with the other types of EPAs or EPA not shortened. False positive predictions

467 of EPI would be decreased by using H3K27ac marks and other features. The ratio of

468 EPI overlapped with Hi-C chromatin interactions was increased using H3K27ac marks

469 in both monocytes and T cells. The ratio of EPI overlapped with HiChIP chromatin

470 interactions was also increased using H3K27ac marks. However, the number of biased

471 orientation of DNA motif sequences showing a higher ratio of EPI overlapped with

472 HiChIP chromatin interactions than the other types of EPAs was decreased using

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473 H3K27ac marks (Supplemental material 2).

474 Though the number of known DNA binding proteins and TF involved in

475 chromatin interactions would be less than 30 or so, about 300 DNA binding proteins

476 showed enrichment of biased orientation of their DNA binding sequences, and known

477 DNA binding proteins involved in chromatin interactions were found in the biased

478 orientation of DNA binding sequences. JUNDM2 (JDP2) found in T cells and

479 monocytes is not known DNA binding proteins involved in chromatin interactions.

480 JDP2 is involved in histone and nucleosome-related functions such as

481 histone-chaperone activity, promoting nucleosome, and inhibition of histone acetylation

482 (Jin et al. 2006). JDP2 forms a homodimer or heterodimer with various TF

483 (https://en.wikipedia.org/wiki/Jun_dimerization_protein). Thus, the main function of

484 JDP2 may not be associated with chromatin interactions, but it forms a homodimer or

485 heterodimer with TF, potentially forming a chromatin interaction through the binding of

486 JDP2 and another TF, like chromatin interactions formed by YY1 (Weintraub et al.

487 2017). In the analysis of HiChIP chromatin interaction data, JDP2 was in the list of

488 biased orientation of DNA motif sequences showing a higher ratio of EPI overlapped

489 with HiChIP chromatin interactions than the other types of EPAs, using chromatin

490 interactions with more than 6,000 counts for each interaction (Supplemental material 2).

491 When forming a homodimer or heterodimer with another TF, TF may bind to genome

492 DNA with a specific orientation of their DNA binding sequences. From the analysis of

493 biased orientation of DNA motif sequences of TF, TF forming heterodimer would also

494 be found. If the DNA binding motif sequence of only the mate to a pair of TF was found

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495 in EPA, EPA was shortened at one side, which is the genomic location of the DNA

496 binding motif sequence of the mate to the pair, and transcriptional target genes were

497 predicted using the EPA shortened at the side. In this analysis, the mate to both

498 heterodimer and homodimer of TF can be used to examine the effect on the expression

499 level of transcriptional target genes predicted based on the EPA shortened at one side.

500 For heterodimer, biased orientation of DNA motif sequences may also be found in

501 forward-forward or reverse-reverse orientation.

502 I reported that the ratio of the number of functional enrichment of putative

503 transcriptional target genes in the total number of putative transcriptional target genes

504 changed according to the types of EPAs, in the same way as gene expression level

505 (Osato 2018). JDP2 showed a higher ratio of functional enrichment of putative

506 transcriptional target genes using EPA shortened at the genomic locations of FR

507 orientation of the DNA binding motif sequence, compared with the other types of EPAs

508 (RF or any orientation) in monocytes and T cells, among monocytes, T cells and CD20+

509 B cells. While the genome-wide analysis of functional enrichment of putative

510 transcriptional target genes takes computational time, the genome-wide analysis of gene

511 expression level is finished with less computational time. The analysis of gene

512 expression level can be used for a cell type and experimental data where the expression

513 levels of transcriptional target genes predicted based on EPA are significantly different

514 from those predicted from only promoter.

515 It has been reported that CTCF and cohesin-binding sites are frequently mutated

516 in cancer (Katainen et al. 2015). Some biased orientation of DNA motif sequences

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517 would be associated with chromatin interactions and might be associated with diseases

518 including cancer.

519 The analyses in this study revealed novel characters of DNA binding motif

520 sequences of TF and repeat DNA sequences, and would be useful to analyze TF

521 involved in chromatin interactions and/or forming a homodimer, heterodimer or

522 complex with other TF, affecting the transcriptional regulation of genes.

523

524 Methods

525 Search for biased orientation of DNA motif sequences

526 To examine transcriptional regulatory target genes of transcription factors (TF),

527 bed files of hg38 of Blueprint DNase-seq data for CD14+ monocytes of four donors

528 (EGAD00001002286; Donor ID: C0010K, C0011I, C001UY, C005PS) were obtained

529 from Blueprint project web site (http://dcc.blueprint-epigenome.eu/#/home), and the bed

530 files of hg38 were converted into those of hg19 using Batch Coordinate Conversion

531 (liftOver) web site (https://genome.ucsc.edu/util.html). Bed files of hg19 of ENCODE

532 H1-hESC (GSM816632; UCSC Accession: wgEncodeEH000556), iPSC (GSM816642;

533 UCSC Accession: wgEncodeEH001110), HUVEC (GSM1014528; UCSC Accession:

534 wgEncodeEH002460), and MCF-7 (GSM816627; UCSC Accession:

535 wgEncodeEH000579) were obtained from the ENCODE websites

536 (http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeUwDgf/;

537 http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeUwDnase/).

538 As high resolution of chromatin interaction data using HiChIP became available

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539 in CD4+ T cells, to promote the same analysis of CD14+ monocytes in CD4+ T cells,

540 DNase-seq data of four donors were obtained from a public database and Blueprint

541 projects web sites. DNase-seq data of only one donor was available in Blueprint project

542 for CD4+ T cells (Donor ID: S008H1), and three other DNase-seq data were obtained

543 from NCBI Gene Expression Omnibus (GEO) database. Though the peak calling of

544 DNase-seq data available in GEO database was different from other DNase-seq data in

545 ENCODE and Blueprint projects where 150bp length of peaks were usually predicted

546 using HotSpot (John et al. 2011), FASTQ files of DNase-seq data were downloaded

547 from NCBI Sequence Read Archive (SRA) database (SRR097566, SRR097618, and

548 SRR171574). Read sequences of the FASTQ files were aligned to the hg19 version of

549 the human genome reference using BWA (Li and Durbin 2009), and the BAM files

550 generated by BWA were converted into SAM files, sorted, and indexed using Samtools

551 (Li et al. 2009). Peaks of the DNase-seq data were predicted using HotSpot-4.1.1.

552 To identify transcription factor binding sites (TFBS) from the DNase-seq data,

553 TRANSFAC (2013.2), JASPAR (2010), UniPROBE, BEEML-PBM, high-throughput

554 SELEX, Human Protein-DNA Interactome, and transcription factor binding sequences

555 of ENCODE ChIP-seq data were used (Wingender et al. 1996; Newburger and Bulyk

556 2009; Portales-Casamar et al. 2010; Xie et al. 2010; Zhao and Stormo 2011; Jolma et al.

557 2013; Kheradpour and Kellis 2014). Position weight matrices of transcription factor

558 binding sequences were transformed into TRANSFAC matrices and then into MEME

559 matrices using in-house scripts and transfac2meme in MEME suite (Bailey et al. 2009).

560 Transcription factor binding sequences of TF derived from vertebrates were used for

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561 further analyses. Transcription factor binding sequences were searched from each

562 narrow peak of DNase-seq data using FIMO with p-value threshold of 10−5 (Grant et al.

563 2011). TF corresponding to transcription factor binding sequences were searched

564 computationally by comparing their names and gene symbols of HGNC (HUGO Gene

565 Nomenclature Committee) -approved gene nomenclature and 31,848 UCSC known

566 canonical transcripts

567 (http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/knownCanonical.txt.gz), as

568 transcription factor binding sequences were not linked to transcript IDs such as UCSC,

569 RefSeq, and Ensembl transcripts.

570 Target genes of a TF were assigned when its TFBS was found in DNase-seq

571 narrow peaks in promoter or extended regions for enhancer-promoter association of

572 genes (EPA). Promoter and extended regions were defined as follows: promoter regions

573 were those that were within distance of ±5 kb from transcriptional start sites (TSS).

574 Promoter and extended regions were defined as per the following association rule,

575 which is the same as that defined in Figure 3A of a previous study (McLean et al. 2010):

576 the single nearest gene association rule, which extends the regulatory domain to the

577 midpoint between the TSS of the gene and that of the nearest gene upstream and

578 downstream without the limitation of extension length. Extended regions for EPA were

579 shortened at the genomic locations of DNA binding sites of a TF that was the closest to

580 a transcriptional start site, and transcriptional target genes were predicted from the

581 shortened enhancer regions using TFBS. Furthermore, promoter and extended regions

582 for EPA were shortened at the genomic locations of forward–reverse (FR) orientation of

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583 DNA binding sites of a TF. When forward or reverse orientation of DNA binding sites

584 were continuously located in genome sequences several times, the most external

585 forward–reverse orientation of DNA binding sites were selected. The genomic positions

586 of genes were identified using ‘knownGene.txt.gz’ file in UCSC bioinformatics sites

587 (Karolchik et al. 2014). The file ‘knownCanonical.txt.gz’ was also utilized for choosing

588 representative transcripts among various alternate forms for assigning promoter and

589 extended regions for EPA. From the list of transcription factor binding sequences and

590 transcriptional target genes, redundant transcription factor binding sequences were

591 removed by comparing the target genes of a transcription factor binding sequence and

592 its corresponding TF; if identical, one of the transcription factor binding sequences was

593 used. When the number of transcriptional target genes predicted from a transcription

594 factor binding sequence was less than five, the transcription factor binding sequence

595 was omitted.

596 Repeat DNA sequences were searched from the hg19 version of the human

597 reference genome using RepeatMasker (Smit, AFA & Green, P RepeatMasker at

598 http://www.repeatmasker.org) and RepBase RepeatMasker Edition

599 (http://www.girinst.org).

600 For gene expression data, RNA-seq reads mapped onto human hg19 genome

601 sequences were obtained, including ENCODE long RNA-seq reads with poly-A of

602 H1-hESC, iPSC, HUVEC, and MCF-7 (GSM26284, GSM958733, GSM2344099,

603 GSM2344100, GSM958734, and GSM765388), and UCSF-UBC human reference

604 epigenome mapping project RNA-seq reads with poly-A of naive CD4+ T cells

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605 (GSM669617). Two replicates were present for H1-hESC, iPSC, HUVEC, and MCF-7,

606 and a single one for CD4+ T cells. RPKMs of the RNA-seq data were calculated using

607 RSeQC (Wang et al. 2012). For monocytes, Blueprint RNA-seq RPKM data

608 (GSE58310, GSE58310_GeneExpression.csv.gz, Monocytes_Day0_RPMI) were used

609 (Saeed et al. 2014). Based on RPKM, UCSC transcripts with expression level among

610 top 30% of all the transcripts were selected in each cell type.

611 The expression level of transcriptional target genes predicted based on EPA

612 shortened at the genomic locations of DNA motif sequence of a TF or a repeat DNA

613 sequence was compared with the expression level of transcriptional target genes

614 predicted from promoter. For each DNA motif sequence shortening EPA, transcriptional

615 target genes were predicted using about 3,000 – 5,000 DNA binding motif sequences of

616 TF, and the expression level of putative transcriptional target genes of each TF was

617 compared between EPA and only promoter using Mann-Whitney test, two-sided

618 (p-value < 0.05). The number of TF showing a significant difference of expression level

619 of putative transcriptional target genes between EPA and promoter was compared

620 among forward-reverse (FR), reverse-forward (RF), and any orientation (i.e. without

621 considering orientation) of a DNA motif sequence shortening EPA using chi-square test

622 (p-value < 0.05). When a DNA motif sequence of a TF or a repeat DNA sequence

623 shortening EPA showed a significant difference of expression level of putative

624 transcriptional target genes among FR, RF, or any orientation in monocytes of four

625 people in common, the DNA motif sequence was listed.

626 Though forward-reverse orientation of DNA binding motif sequences of CTCF

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627 and cohesin are frequently observed at chromatin interaction anchors, the percentage of

628 forward-reverse orientation is not 100, and other orientations of the DNA binding motif

629 sequences are also observed. Though DNA binding motif sequences of CTCF and

630 cohesin are found in various open chromatin regions, DNA binding motif sequences of

631 some transcription factors would be observed less frequently in open chromatin regions.

632 The analyses of experimental data of a number of people would avoid missing relatively

633 weak statistical significance of DNA motif sequences in experimental data of each

634 person by multiple testing correction of thousands of statistical tests. A DNA motif

635 sequence was found with p-value < 0.05 in experimental data of one person and the

636 DNA motif sequence found in the same cell type of four people in common would have

637 p-value < 0.054 = 6.25 × 10-6.

638

639 Co-location of biased orientation of DNA motif sequences

640 Co-location of biased orientation of DNA binding motif sequences of TF was

641 examined. The number of open chromatin regions with the same pair of DNA binding

642 motif sequences was counted, and when the pair of DNA binding motif sequences were

643 enriched with statistical significance (chi-square test, p-value < 1.0 × 10-10), they were

644 listed. For histone modification of an enhancer mark (H3K27ac), bed files of hg38 of

645 Blueprint ChIP-seq data for CD14+ monocytes (EGAD00001001179) and CD4+ T cells

646 (Donor ID: S000RD) were obtained from Blueprint web site

647 (http://dcc.blueprint-epigenome.eu/#/home), and the bed files of hg38 were converted

648 into those of hg19 using Batch Coordinate Conversion (liftOver) web site

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649 (https://genome.ucsc.edu/util.html). Networks of co-locations of biased orientation of

650 DNA motif sequences were plotted using Cytoscape v3.71 with yFiles Layout

651 Algorithms for Cytoscape (Shannon et al. 2003).

652

653 Comparison with chromatin interaction data

654 For comparison of EPA in monocytes with chromatin interactions,

655 ‘PCHiC_peak_matrix_cutoff0.txt.gz’ file was downloaded from ‘Promoter Capture

656 Hi-C in 17 human primary blood cell types’ web site (https://osf.io/u8tzp/files/), and

657 chromatin interactions for Monocytes with scores of CHiCAGO tool > 1 and

658 CHiCAGO tool > 5 were extracted from the file (Javierre et al. 2016). In the same way

659 as monocytes, Hi-C chromatin interaction data of CD4+ T cells (Naive CD4+ T cells,

660 nCD4) were obtained.

661 Enhancer-promoter interactions (EPI) were predicted using three types of EPAs in

662 monocytes: (i) EPA shortened at the genomic locations of FR or RF orientation of DNA

663 motif sequence of a TF, (ii) EPA shortened at the genomic locations of any orientation

664 (i.e. without considering orientation) of DNA motif sequence of a TF, and (iii) EPA

665 without being shortened by a DNA motif sequence. EPI predicted using the three types

666 of EPAs in common were removed. First, EPI predicted based on EPA (i) were

667 compared with chromatin interactions (Hi-C). The resolution of chromatin interaction

668 data used in this study was 50kb, so EPI were adjusted to 50kb before their comparison.

669 The number and ratio of EPI overlapped with chromatin interactions were counted.

670 Second, EPI were predicted based on EPA (ii), and EPI predicted based on EPA (i) were

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671 removed from the EPI. The number and ratio of EPI overlapped with chromatin

672 interactions were counted. Third, EPI were predicted based on EPA (iii), and EPI

673 predicted based on EPA (i) and (ii) were removed from the EPI. The number and ratio of

674 EPI overlapped with chromatin interactions were counted. The number and ratio of the

675 EPI were compared two times between EPA (i) and (iii), and EPA (i) and (ii) (binomial

676 distribution, p-value < 0.025 for each test, two-sided, 95% confidence interval).

677 For comparison of EPA with chromatin interactions (HiChIP) in CD4+ T cells,

678 ‘GSM2705049_Naive_HiChIP_H3K27ac_B2T1_allValidPairs.txt’ file was downloaded

679 from Gene Expression Omnibus (GEO) database (GSM2705049). The resolutions of

680 chromatin interaction data and EPI were adjusted to 5kb before their comparison.

681 Chromatin interactions with more than 6,000 and 1,000 counts for each interaction were

682 used in this study.

683

684 Acknowledgements

685 The supercomputing resource was provided by Human Genome Center of the Institute

686 of Medical Science at the University of Tokyo. Computations were partially performed

687 on the NIG supercomputer at ROIS National Institute of Genetics. Publication charges

688 for this article were funded by JSPS KAKENHI Grant Number 16K00387. This

689 research was partially supported by the Platform Project for Supporting in Drug

690 Discovery and Life Science Research（Platform for Dynamic Approaches to Living

691 System）from Japan Agency for Medical Research and Development (AMED). This

692 research was partially supported by Development of Fundamental Technologies for

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693 Diagnosis and Therapy Based upon Epigenome Analysis from Japan Agency for

694 Medical Research and Development (AMED). This work was partially supported by

695 JST CREST Grant Number JPMJCR15G1, Japan.

696

33 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

697 Figures

A Promoter Gene Short Article

CTCF Binding Polarity Determines Chromatin a TSS 1 TSS 2 TSSLooping 3 Histone modification Short Article Graphical Abstract Authors CTCF ( ) Gene 2 Elzo de Wit, Erica S.M. Vos, Gene 1 ( CTCF) BindingCohesin PolarityEnhancer Determines ChromatinSjoerd J.B. Holwerda, ..., ( ) Patrick J. Wijchers, Peter H.L. Krijger, Wouter de Laat Short Article Gene 3 Looping Transcription factor (TF) Enhancer Graphical Abstract AuthorsCorrespondence The basal plus extension association rule [email protected] Elzo de Wit, Erica S.M. Vos, CTCF Binding Polarity Determines Chromatin Figure 4. The Role of CBS Location and Sjoerd J.B. Holwerda, ..., ForwardIn Brief Looping A b Orientation in CTCF-Mediated Genome- Patrick J. Wijchers, Peter H.L. Krijger, wide DNA Looping CCCTC-binding factor (CTCF) shapes the Short Article Enhancer Gene ReverseWouter de Laat Graphical Abstract Authors (A) Diagram of CTCF-mediated long-range chro- three-dimensional genome. Here, de Wit et al. provide direct evidence for CTCF Elzo de Wit, Erica S.M. Vos, matin-looping interactions between CBS pairs in CohesinCorrespondence Forward Orientation( of CTCF - binding ) Sites Reverse binding polarity playing an underlying role Sjoerd J.B. Holwerda, ..., the forward-reverse orientations. The color charts [email protected] ( ) in chromatin looping. Cohesin CTCF Binding Polarity Determines ChromatinPatrick J. Wijchers, Peter H.L. Krijger, ( represent 19,532 interactions ) of CBS pairs in K562 cells. The number and percentage of CBS pairs in In Briefassociation persists, but inverted CTCF Looping Wouter de Laat the forward-reverse (FR), forward-forward (FF), sites fail to loop, which can sometimes CCCTC-binding factor (CTCF) shapes the The two nearest genes associationreverse-reverse rule (RR), and reverse-forward (RF) lead to long-range changes in gene Correspondence three-dimensional genome. Here, de Wit Graphical Abstract Authors orientations are shown. expression. [email protected] et al. provide direct evidence for CTCF Elzo de Wit, Erica S.M. Vos, (B) The percentage of CBS pairs in the forward- B binding polarity playing an underlying role Figure 4. The Role of CBS Location and ForwardSjoerd J.B. Holwerda, ..., reverse orientations increases from 67.5% to In Brief c in chromatin looping. Cohesin Orientation in CTCF-Mediated Genome- Patrick J. Wijchers, Peter H.L. Krijger, 90.7% as the chromatin-loopingA strength is CCCTC-binding factor (CTCF) shapes the association persists, but inverted CTCF wide DNA Looping ReverseWouter de Laat enhanced. Enhancer Gene three-dimensional genome. Here, de Wit Highlights sites failAccession to loop, which Numbers can sometimes (A) Diagram of CTCF-mediated long-range chro- (C) Schematic of the two topological domains in the matin-looping interactions between CBS pairs in et al. provide direct evidence for CTCF ( )( )( d CTCF binding polarity ) determines chromatin looping lead to long-rangeGSE72720 changes in gene CohesinCorrespondence HoxD locus. The orientations of CBSs are indicatedForward Orientation of CTCF-binding Sites Reverse binding polarity playing an underlying role expression. the forward-reverse orientations. The color charts [email protected] by arrowheads. CTCF/cohesin-mediated looping in chromatin looping. Cohesin d Inverted or disengaged CTCF sites do not necessarily form represent 19,532 interactions of CBS pairs in K562 interactions and the two resulting topological do- Supplementary FigureThe 2: Computationally-defined single nearest gene regulatory association domains. The rule transcriptionnew chromatin start loops site (TSS) of cells. The number and percentage of CBS pairs in In Briefassociation persists, but inverted CTCF each gene is shown as an arrow. The corresponding regulatory domainmains for each (CCDs) gene are is also shown shown. in matching color the forward-reverse (FR), forward-forward (FF), sites fail to loop, which can sometimes 698 CCCTC-binding factor (CTCF) shapes the as a bracketed line. The association rule and relevant parameters used(D) in Cumulative a run ofd GREATCohesin patterns canrecruitment of CBSbe altered orientations to CTCF via the sites of to- is independent of loop reverse-reverse (RR), and reverse-forward (RF) lead to long-range changes in gene three-dimensional genome. Here, de Wit B web interface prior to execution. (a) The basal plus extension associationpologicalHighlights rule domains assignsformation a in basal the human regulatory genome. domain Accession Numbers orientations are shown. expression. to each gene regardless of genes nearby (thick line). The domain is then(E) extended Distribution to ofthe genome-wide basal regulatory orientation domain con- et al. provide direct evidence for CTCF d CTCF binding polarity determines chromatin looping GSE72720 (B) The percentage of CBS pairs in the forward- d Phenocopied linear but altered 3D chromatin landscape can binding polarity playing an underlying role of the nearest upstream and downstream genes. (b) The two nearest genesfigurationsassociation of CBS rule pairs extends located the in theregulatory boundaries reverse orientations increases from 67.5% to 699domain to theFigure TSS of the nearest 1. upstreamChromatin and downstream interactions genes. (c)betweenThe single twoaffect neighboring nearest and gene gene expression domains enhancerassociation in the rule human-promoter association. (A) Forward– in chromatin looping. Cohesin d Inverted or disengaged CTCF sites do not necessarily form 90.7% as the chromatin-looping strength is extends the regulatory domain to the midpoint between this gene’s TSS and the nearest gene’s TSS both upstream association persists, but inverted CTCF K562new genome. chromatin Note that loops the vast majority (90.0%) enhanced. and downstream. All regulatory domain extension rules limit extension to a user-defined maximum distance for genes Highlights sites failAccession to loop, which Numbers can sometimes of boundary CBS pairs between two neighboring (C) Schematic of the two topological domains in the that have no other genes nearby. lead to long-range changes in gene domainsd Cohesin are in recruitment the reverse-forward to CTCF sitesorientation. is independent of loop HoxD locus.d TheCTCF orientations binding polarity of CBSs determines are indicated chromatin looping GSE72720 expression. 700 reverse orientation of CTCFSee-binding alsoformationFigure S4 andsitesTables S1are, S2, S3frequently, S4, S5, found in chromatin interactionby arrowheads. CTCF/cohesin-mediated looping d Inverted or disengaged CTCF sites do not necessarily form CDEand S6. interactions and the two resulting topological do- d Phenocopied linear but altered 3D chromatin landscape can new chromatin loops mains (CCDs) are also shown. affect gene expression de Wit et al., 2015, Molecular Cell 60, 1–9 (D) Cumulatived Cohesin patterns recruitment of CBS orientations to CTCF sites of to- is independent of loop NovemberB 19, 2015 ª2015 Elsevier Inc. pological domains in the human genome. 701 anchors. CTCF can block the interactionhttp://dx.doi.org/10.1016/j.molcel.2015.09.023 between enhancers and promoters limiting the Highlightsformation Accession Numbers (E) Distribution of genome-wide orientation con- 2015)(Figures S2B and S2C). In the d CTCF binding polarity determines chromatin looping GSE72720 figurationsd of CBSPhenocopied pairs located linear in but the altered boundaries 3D chromatin landscape can CRISPR cell lines D3, D7, and D19 (out between twoaffect neighboring gene expression domains in the human of 38 clones screened) in which the inter- d Inverted or disengaged CTCF sites do not necessarily form K562new genome. chromatin Note that loops the vast majority (90.0%) 702 activity of enhancers to certainnal CBS4functional (30HS1) was domains deleted (Fig- (de Wit et al. 2015; Guo et al. 2015)of. boundary CBS pairs between two neighboring ure S2B), chromatin-loopingde Wit et al., 2015, Molecular interactions Cell 60, 1–9 domainsd Cohesin are in recruitment the reverse-forward to CTCF sitesorientation. is independent of loop November 19, 2015 2015 Elsevier Inc. Nature Biotechnology: doi: 10.1038/nbt.1630 ª See also Figure S4 and Tables S1, S2, S3, S4, S5, 14 between CBS3http://dx.doi.org/10.1016/j.molcel.2015.09.023 (50HS5) inSupplement the forward formation orientation exist in >60% neighboring TAD boundaries (Fig- orientation and the boundary CBS5 in theCDE reverse orientation in and S6. d Phenocopied linear but altered 3D chromatin landscape can ure S4D), suggesting that703 the boundary(B) reverse-forward Computationally CBS domain1- persisted,defined although regulatory its interaction with domains the CBS4 for enhancer-promoter association affect gene expression pairs play an important role in the formation of most of TADs. (3 HS1) region was abolished (Figures S5A and S5B). As ex- de Wit et al., 2015, Molecular Cell 60, 1–9 0 November 19, 2015 ª2015 Elsevier Inc. For example, there is a CBS pair in the reverse-forward orienta- pected, the interactions between CBS6/7 and CBS8/9 in http://dx.doi.org/10.1016/j.molcel.2015.09.023 tion in a Chr12 genomic region of H1-hESC cells, located at or domain2 were unchanged (Figure S5C). Strikingly, however, in 2015)(Figures S2B and S2C). In the 704 (McLean et al. 2010). The single nearest gene association rule extends the regulatoryCRISPR cell lines D3, D7, and D19 (out very close to each of the six TAD boundaries (boundaries 1–6), the CBS4 (30HS1) and CBS5 double-knockout CRISPR cell lines except for boundary 5, which has only one closely located C2, C4, and C14 (out of 49 clones screened) (Figure S2C), novel of 38 clones screened) in which the inter- nal CBS4 (3 HS1) was deleted (Fig- CBS in the forward orientation (Figure S4E). These data, taken chromatin-looping interactions between CBS3 (50HS5) in the for- 0 together, strongly suggest that directional binding of CTCF to ward orientation of domain1 and CBS8/9 in the reverse orienta- ure S2B), chromatin-loopingde Wit et al., 2015, Molecular interactions Cell 60, 1–9 705 domain to the midpoint between this gene’s TSS and the nearest gene’s TSS both November 19, 2015 ª2015 Elsevier Inc. boundary CBS pairs in the reverse-forward orientations causes tion of the neighboring domain2 were observed, suggesting that between CBS3http://dx.doi.org/10.1016/j.molcel.2015.09.023 (50HS5) in the forward opposite topological looping and thus appears to function as these two domains merge as a single domainorientation in CRISPR exist in cell >60% neighboring TAD boundaries (Fig- orientation and the boundary CBS5 in the reverse orientation in insulators. lines with CBS4/5 double knockout (Figureure S4D), S5B). suggesting Similarly, that the boundary reverse-forward CBS domain1 persisted, although its interaction with the CBS4 706 upstream and when downstream. CBS8 was used as anEnhancer anchor, thispairs reverse-oriented-promoter play an important CBS association role in the formation of was most of TADs.shortened(30HS1) regionat was the abolished (Figures S5A and S5B). As ex- The Human b-globin Locus Provides an Additional in domain2 establishes new long-range chromatin-loopingFor example, there inter- is a CBS pair in the reverse-forward orienta- pected, the interactions between CBS6/7 and CBS8/9 in Example of CBS Orientation-Dependent Topological actions with CBS1–3 in the forward orientationtion in of a domain1 Chr12 genomic in the region of H1-hESC cells, located at or domain2 were unchanged (Figure S5C). Strikingly, however, in Chromatin Looping CBS4/5 double-deletion CRISPR cell linesvery close(Figure to S5 eachC). of We the six TAD boundaries (boundaries 1–6), the CBS4 (30HS1) and CBS5 double-knockout CRISPR cell lines Based on the location and707 orientation genomic of CBSs, as well locations as their conclude of thatforward cross-domain-reverse interactions exceptorientation can be for established boundary of 5, whichDNA has onlybinding one closely motif located sequenceC2, C4, and C14 of (out a of 49 clones screened) (Figure S2C), novel CTCF/cohesin occupancy, we identified four CCDs (domains after deletion of CBSs up to the boundaryCBS of in topological the forward do- orientation (Figure S4E). These data, taken chromatin-looping interactions between CBS3 (50HS5) in the for- 1–4) in the well-characterized b-globin cluster (Figure 5A). The mains, but not after deletion of the internaltogether, CBS in strongly the b-globin suggest that directional binding of CTCF to ward orientation of domain1 and CBS8/9 in the reverse orienta- boundary CBS pairs in the reverse-forward orientations causes tion of the neighboring domain2 were observed, suggesting that b-globin gene cluster is located between CBS3 (50HS5) and locus. opposite topological looping and thus appears to function as these two domains merge as a single domain in CRISPR cell CBS4 (30HS1) in domain1708 (Figure 5A)transcription (Hou et al., 2010; Splinter factorTo further(e.g. test CTCF the functional in significancethe figure) of this organization. et al., 2006). We generated a series of CBS4/5 mutant K562 of CBSs, we again performed CRISPR/cas9-mediatedinsulators. DNA- lines with CBS4/5 double knockout (Figure S5B). Similarly, cell lines using CRISPR/Cas9 with one or two sgRNAs (Li et al., fragment editing in the HEK293T cells and screened 198 CRISPR when CBS8 was used as an anchor, this reverse-oriented CBS The Human b-globin Locus Provides an Additional in domain2 establishes new long-range chromatin-looping inter- 709 Example of CBS Orientation-Dependent Topological actions with CBS1–3 in the forward orientation of domain1 in the 906 Cell 162, 900–910, August 13, 2015 ª2015 Elsevier Inc. Chromatin Looping CBS4/5 double-deletion CRISPR cell lines (Figure S5C). We Based on the location and orientation of CBSs, as well as their conclude that cross-domain interactions can be established CTCF/cohesin occupancy, we identified four CCDs (domains after deletion of CBSs up to the boundary of topological do- 1–4) in the well-characterized b-globin cluster (Figure 5A). The mains, but not after deletion of the internal CBS in the b-globin b-globin gene cluster is located between CBS3 (50HS5) and locus. CBS4 (30HS1) in domain1 (Figure 5A) (Hou et al., 2010; Splinter To further test the functional significance of this organization et al., 2006). We generated a series of CBS4/5 mutant K562 of CBSs, we again performed CRISPR/cas9-mediated DNA- cell lines34 using CRISPR/Cas9 with one or two sgRNAs (Li et al., fragment editing in the HEK293T cells and screened 198 CRISPR

906 Cell 162, 900–910, August 13, 2015 ª2015 Elsevier Inc. bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

A CTCF RAD21 SMC3 30 30 30

20 20 20

10 10 10 Median2 Median2 Median2 binding sites of TF binding sites of TF binding sites of TF EPA shortened at DNA EPA shortened at DNA EPA EPA shortened at DNA EPA 0 0 0 0 10 20 30 0 10 20 30 0 10 20 30 Median1Promoter Median1Promoter Median1Promoter B

350 300 287

250

200 159 153 150

100

50 1 0 Biased Forward- Reverse- any orientation reverse (FR) forward (RF) orientation 710 (FR+RF)

711 Figure 2. Biased orientation of DNA motif sequences of transcription factors affecting

712 the transcription of genes. (A) Comparison of expression level of putative

713 transcriptional target genes. The median expression levels of target genes of the same

714 transcription factor binding sequences were compared between promoters and

715 enhancer-promoter association (EPA) shortened at the genomic locations of

716 forward-reverse orientation of DNA motif sequence of CTCF and cohesin (RAD21 and

717 SMC3) respectively in monocytes. Red and blue dots show statistically significant

718 difference (Mann-Whitney test) of the distribution of expression levels of target genes

719 between promoters and the EPA. Red dots show the median expression level of target

720 genes was higher based on the EPA than promoters, and blue dots show the median

721 expression level of target genes was lower based on the EPA than promoters. The

35 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

722 expression level of target genes predicted based on the EPA tended to be higher than

723 promoters, implying that transcription factors acted as activators of target genes. (B)

724 Biased orientation of DNA motif sequences of transcription factors in monocytes. Total

725 287 of biased orientation of DNA binding motif sequences of transcription factors were

726 found to affect the expression level of putative transcriptional target genes in monocytes

727 of four people in common, whereas only one any orientation (i.e. without considering

728 orientation) of DNA binding motif sequence was found to affect the expression level.

729

A

730

731

36 Reverse DDIT3_CEBPA UF1H3BETA AHR_ARNT SMARCC2 NEUROD1 ZNF263_1 ZNF263_2 HMGA2_1 HMGA2_2 ZSCAN18 RREB1_1 RREB1_2 SPDEF_1 SPDEF_2 NFKB1_1 NFKB1_2 RAD21_1 RAD21_2 RAD21_3 RAD21_4 ZNF658B SOX18_1 SOX18_2 ZNF84_1 ZNF84_2 GATA2_1 GATA2_2 EP300_1 EP300_2 EP300_3 P50_P50 POLR3A ZSCAN2 SMC3_1 SMC3_2 SREBF1 CTCF_1 CTCF_2 CTCF_3 CTCF_4 CTCF_5 CTCF_6 HEY1_1 HEY1_2 ZNF75A OTX2_1 OTX2_2 OTX2_3 BCL3_1 BCL3_2 ARID3A ZNF219 ZNF250 ZNF287 ZNF366 ZNF394 ZNF436 ZNF486 ZNF548 ZNF575 ZNF582 ZNF586 ZNF595 ZNF639 ZNF676 ZNF701 ZNF714 ZNF717 ZNF790 ZNF880 JDP2_1 JDP2_2 TRIM28 BATF_1 BATF_2 E2F1_1 E2F1_2 E2F1_3 E2F6_1 E2F6_2 E2F6_3 E2F6_4 TP53_1 TP53_2 MYOD1 SMAD3 CEBPE FOXO3 VAMP3 BACH1 SPI1_1 SPI1_2 BARX2 HNF1B NR3C1 DEAF1 FUBP1 MAZ_1 MAZ_2 TFCP2 FOXF2 SOAT1 ZNF73 SP1_1 SP1_2 SP1_3 SP1_4 MYCN GFI1B GCM1 MNX1 RARB EGR1 THRA ZACN CUX1 DUX1 MYF6 REST SRP9 NFYA FGF9 DLX3 ETV3 LHX6 LHX8 SPZ1 TBX5 E2F4 ELF1 ELF3 ELF4 KLF5 NFIA GLI1 IRF9 ZIC1 ZIC3 MAF EHF JUN IRF GC

AHR_ARNT ARID3A BACH1 BARX2 BATF_1 BATF_2 BCL3_1 BCL3_2 CEBPE CTCF_1 CTCF_2 CTCF_3 CTCF_4 CTCF_5 CTCF_6 CUX1 DDIT3_CEBPA DEAF1 DLX3 DUX1 E2F1_1 E2F1_2 E2F1_3 E2F4 E2F6_1 E2F6_2 E2F6_3 E2F6_4 EGR1 EHF ELF1 ELF3 ELF4 EP300_1 EP300_2 EP300_3 ETV3 FGF9 FOXF2 FOXO3 FUBP1 GATA2_1 GATA2_2 GC GCM1 GFI1B GLI1 HEY1_1 HEY1_2 HMGA2_1 HMGA2_2 HNF1B IRF IRF9 JDP2_1 JDP2_2 JUN KLF5 LHX6 LHX8 MAF MAZ_1 MAZ_2 MNX1 MYCN

Forward MYF6 MYOD1 NEUROD1 NFIA NFKB1_1 NFKB1_2 NFYA NR3C1 OTX2_1 OTX2_2 OTX2_3 P50_P50 POLR3A RAD21_1 RAD21_2 RAD21_3 RAD21_4 RARB REST RREB1_1 RREB1_2 SMAD3 SMARCC2 SMC3_1 SMC3_2 SOAT1 SOX18_1 SOX18_2 SP1_1 SP1_2 SP1_3 SP1_4 SPDEF_1 SPDEF_2 SPI1_1 SPI1_2 SPZ1 SREBF1 SRP9 TBX5 TFCP2 THRA bioRxivTP53_1 preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which TP53_2 TRIM28 wasUF1H3BETA not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made VAMP3 ZACN available under aCC-BY 4.0 International license. ZIC1 ZIC3 ZNF219 ZNF250 ZNF263_1 ZNF263_2 ZNF287 ZNF366 ZNF394 ZNF436 ZNF486 ZNF548 ZNF575 ZNF582 ZNF586 ZNF595 ZNF639 ZNF658B ZNF676 ZNF701 ZNF714 ZNF717 ZNF73 ZNF75A ZNF790 ZNF84_1 ZNF84_2 ZNF880 ZSCAN18 ZSCAN2 B 0 1000 2000 Score

ZSCAN2 ZSCAN18

ZNF880 0 1000 2000 ZNF84_2 ZNF84_1 ZNF790 ZNF75A ZNF73 ZNF717 ZNF714 ZNF701 ZNF676 ZNF658B ZNF639 ZNF595 ZNF586 ZNF582 ZNF575 ZNF548 ZNF486 ZNF436 ZNF394 ZNF366 ZNF287 ZNF263_2 ZNF263_1 ZNF250 ZNF219 ZIC3 ZIC1 ZACN VAMP3 UF1H3BETA TRIM28 TP53_2 TP53_1 THRA TFCP2 TBX5 SRP9 SREBF1 SPZ1 SPI1_2 SPI1_1 SPDEF_2 SPDEF_1 SP1_4 SP1_3 CTCF – SMC3 RAD21 – SMC3 SMC3 – SMC3 SP1_2 SP1_1 SOX18_2 SOX18_1 SOAT1 SMC3_2 SMC3_1 SMARCC2 SMAD3 RREB1_2 RREB1_1 REST Score RARB RAD21_4 RAD21_3 RAD21_2 RAD21_1 POLR3A P50_P50 OTX2_3 OTX2_2 OTX2_1 2000 NR3C1 NFYA CTCF – RAD21 RAD21 – RAD21 SMC3 – RAD21 NFKB1_2 NFKB1_1 NFIA NEUROD1

Reverse MYOD1 MYF6 1000 MYCN MNX1 MAZ_2 MAZ_1 MAF LHX8 LHX6 KLF5 0 JUN JDP2_2 JDP2_1 IRF9 IRF HNF1B HMGA2_2 HMGA2_1 HEY1_2 HEY1_1 GLI1 GFI1B GCM1 GC GATA2_2 GATA2_1 FUBP1 FOXO3 FOXF2 FGF9 ETV3 EP300_3 EP300_2 EP300_1 ELF4 ELF3 ELF1 EHF EGR1 E2F6_4 E2F6_3 E2F6_2 E2F6_1 E2F4 E2F1_3 E2F1_2 E2F1_1 DUX1 DLX3 DEAF1 DDIT3_CEBPA CTCF - CTCF RAD21 - CTCF SMC3 - CTCF CUX1 CTCF_6 CTCF_5 CTCF_4 CTCF_3 CTCF_2 CTCF_1 CEBPE BCL3_2 BCL3_1 BATF_2 BATF_1 BARX2 BACH1 ARID3A AHR_ARNT GC IRF JUN EHF MAF GLI1 IRF9 ZIC1 ZIC3 NFIA E2F4 ELF1 ELF3 ELF4 KLF5 DLX3 ETV3 LHX6 LHX8 SPZ1 TBX5 FGF9 NFYA SRP9 CUX1 DUX1 MYF6 REST ZACN THRA EGR1 MNX1 RARB GCM1 GFI1B MYCN SP1_1 SP1_2 SP1_3 SP1_4 ZNF73 SOAT1 FOXF2 TFCP2 DEAF1 FUBP1 MAZ_1 MAZ_2 BARX2 HNF1B NR3C1 SPI1_1 SPI1_2 BACH1 VAMP3 FOXO3 CEBPE SMAD3 MYOD1 E2F1_1 E2F1_2 E2F1_3 E2F6_1 E2F6_2 E2F6_3 E2F6_4 TP53_1 TP53_2 BATF_1 BATF_2 TRIM28 JDP2_1 JDP2_2 ARID3A ZNF219 ZNF250 ZNF287 ZNF366 ZNF394 ZNF436 ZNF486 ZNF548 ZNF575 ZNF582 ZNF586 ZNF595 ZNF639 ZNF676 ZNF701 ZNF714 ZNF717 ZNF790 ZNF880 BCL3_1 BCL3_2 OTX2_1 OTX2_2 OTX2_3 HEY1_1 HEY1_2 ZNF75A CTCF_1 CTCF_2 CTCF_3 CTCF_4 CTCF_5 CTCF_6 SMC3_1 SMC3_2 SREBF1 POLR3A ZSCAN2 EP300_1 EP300_2 EP300_3 P50_P50 GATA2_1 GATA2_2 ZNF84_1 ZNF84_2 SOX18_1 SOX18_2 ZNF658B NFKB1_1 NFKB1_2 RAD21_1 RAD21_2 RAD21_3 RAD21_4 RREB1_1 RREB1_2 SPDEF_1 SPDEF_2 ZSCAN18 HMGA2_1 HMGA2_2 ZNF263_1 ZNF263_2 NEUROD1 SMARCC2 AHR_ARNT UF1H3BETA DDIT3_CEBPA 732 Forward

733 Figure 3. Association of biased orientation of DNA binding motif sequences of

734 transcription factors. (A) Co-location of biased orientation of DNA binding motif

735 sequences of transcription factors. Co-locations of the DNA motif sequences in open

736 chromatin regions were examined in monocytes. When the same DNA motif sequence

37 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

737 of a TF was co-localized with DNA motif sequences of more than one TF in the same or

738 different open chromatin regions, these co-locations of DNA motif sequences were

739 connected to each other. Purple circles of TFs are known to be involved in chromatin

740 interactions. The line thickness is correlated with the number of open chromatin regions

741 with co-location of the same pair of DNA motif sequences. The size of a circle is

742 correlated with the number of unique TF co-localized with the TF of the circle, which is

743 the number of edges of the node. (B) Pairs of biased orientation of DNA binding motif

744 sequences of transcription factors enriched in upstream and downstream of genes. The

745 number of genes with a pair of forward-reverse orientation of DNA motif sequences

746 was counted using all pairs of the DNA motif sequences found in open chromatin

747 regions overlapped with H3K27ac histone modification marks in T cells, and statistical

748 tests (chi-square test) were conducted. The number of genes where a pair of

749 forward-reverse orientation of DNA motif sequences were enriched with p-value < 0.05

750 was counted and shown as heat map. Gray circles show pairs of DNA motif sequences

751 of CTCF and cohesin (RAD21 and SMC3). CTCF and cohesin are known to be

752 involved in chromatin interactions and have biased orientation of DNA binding motif

753 sequences to form chromatin loops. Other pairs of forward-reverse orientation of DNA

754 motif sequences were also enriched in upstream and downstream of genes.

755

38 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. ) ) )

* * * HiChIP HiChIP HiChIP 0.6 CTCF * 0.6 RAD21 * 0.6 SMC3 * 0.5 0.5 0.5 0.4 0.4 0.4 0.3 0.3 0.3 0.2 0.2 0.2 0.1 0.1 0.1 0 0 0 others any FR FR others any FR FR others any FR FR H3K27ac H3K27ac Ratio of EPI overlapped with interactions ( chromatin Ratio of EPI overlapped with interactions ( chromatin Ratio of EPI overlapped with interactions ( chromatin H3K27ac ) ) ) * * * 1 1 1 HiChIP CTCF * HiChIP RAD21 * HiChIP SMC3 * 0.8 0.8 0.8 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0 0 0 others any FR FR others any FR FR others any FR FR H3K27ac H3K27ac H3K27ac 756 Ratio of EPI overlapped with interactions ( chromatin Ratio of EPI overlapped with interactions ( chromatin Ratio of EPI overlapped with interactions ( chromatin 757 Figure 4. Comparison of enhancer-promoter interactions (EPI) with chromatin

758 interactions in T cells. EPI were predicted based on enhancer-promoter association

759 (EPA) shortened at the genomic locations of biased orientation of DNA binding motif

760 sequence of a transcription factor. Total 121 biased orientation (73 FR and 58 RF) of

761 DNA motif sequences including CTCF and cohesin showed a significantly higher ratio

762 of EPI overlapped with HiChIP chromatin interactions than the other types of EPAs in T

763 cells. The upper part of the figure is a comparison of EPI with HiChIP chromatin

764 interactions with more than 6,000 counts for each interaction, and the lower part of the

765 figure is a comparison of EPI with HiChIP chromatin interactions with more than 1,000

766 counts for each interaction. FR: forward-reverse orientation of DNA motif. any: any

767 orientation (i.e. without considering orientation) of DNA motif. others:

768 enhancer-promoter association not shortened at the genomic locations of DNA motif.

769 FR H3K27ac: EPI were predicted using DNA motif in open chromatin regions

770 overlapped with H3K27ac histone modification marks. * p-value < 10-4.

39 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

NATURE COMMUNICATIONS | DOI: 10.1038/ncomms7186 ARTICLE

interaction frequency measured by 3C assays between the PRMT6 promoter and a distal regulatory element B85 kb away (Fig. 4e

or and Supplementary Fig. 3). Interestingly, the rs2232015 SNP modulates a portion of the ZNF143 recognition motif that is shared with THAP11 and recently shown in vitro to be CTCF motif 22 ZNF143 motifs dispensable for ZNF143 binding . These results, while revealing that ZNF143 is required, may indicate that a complex of factors specify chromatin interactions. Similarly, the increased binding of ZNF143 to the chromatin caused by the variant C Enhancer Promoter Gene allele of the rs13228237 SNP leads to an increase in the chromatin RNA interaction frequency between the first intron of the ZC3HAV1 gene and two distal regulatory elements located B200 kb away DNA (Fig. 4f and Supplementary Fig. 3). Interestingly, this ZNF143- binding site is located B14 kb from the transcription start site of the ZC3HAV1 gene and may represent an unknown isoform of ZC3HAV1 gene. Consistently, a transcription start site was predicted from 50 cap analysis of gene expression data 89 bp from the rs13228237 in GM12878 by the ENCODE project (Supplementary Fig. 4). Expression quantitative trait loci (eQTL) analysis of the rs2232015 and rs13228237 SNPs using RNA-Seq data from lymphoblastoid cells (n 373) (ref. 40) 41¼ Nucleosome ZNF143 genotyped as part of the 1,000 Genomes Project reveals that the ZC3HAV1 expression is modulated by the rs13228237 SNP in CTCF POL2 Mediator lymphoblastoid cells (P 1.73 10 3; Fig. 4f). However, the /CoA ¼  À TF Cohesin rs2232015 SNP is not significantly associated with the expression of the PRMT6 gene (P 0.063; Fig. 4e). This coincides with a 771 repressed element and poised¼ promoter chromatin state at the Figure 5 | Schematic representation of chromatin interactions involving distal regulatory element looping to the PRMT6 promoter in the 772 Figuregene promoters. 5. SchematicZNF143 contributes representation the formation of of chromatin interactionsGM12878 involving cells (Supplementary gene promoters. Fig. 5), which contrasts with the interactions by directly binding the promoter of genes establishing looping active state at regulatory elements looping to the ZC3HAV1 with distal element bound by CTCF. 773 ZNF143 contributes the formation of chromatin interactionspromoter (Supplementary by directly bindingFig. 5). Interestingly, the the rs2232015 SNP is in strong linkage disequilibrium (r2Z0.95) with two to the fourth position of the ZNF143 DNA recognition sequence reported eQTLs captured by the rs1762509 and rs9435441 774 promoter(motif 1; Fig. of 4a) genes the most establishing prominent motiflooping found with within distalB85% elementSNPs 42,43bound. The by rs1762509 CTCF (Bailey and rs9435441 et al. SNPs lead to allele- of the top 500 sites. The rs13228237 SNP changes the fourteenth specific expression of the PRMT6 gene within the liver cells and position of a reported extension of a ZNF143 DNA recognition monocytes, respectively42,43. Consistently, the interacting distal 775 2015)sequence. 22,38 (motif 2; Fig. 4b), which is found within B25% of regulatory element looping to the PRMT6 promoter is in an active the top 500 sites. Consistent with the observation that the actual state within liver cells (Supplementary Fig. 5). This suggests that 776 ZNF143-binding sites are located at gene promoters, B43% and chromatin interactions are not sufficient to impact gene B76% of gene promoters (±2.5 kb of the transcription start site) expression, as recently reported at the b-globin locus44 and that bound by ZNF143 were found to contain motif 1 or motif 2 ZNF143 role in loop formation is not dependent on gene 4 (motif P values o1 10 À ) in GM12878 cells, respectively. transcription. Interesting, motif 2 appears to be the most prominent ZNF143 motif found at gene promoters and most closely resembles the ZNF143 motif characterized using in vitro methods22,39. The Discussion imposed changes to the DNA sequence based on the position- Cellular identity is dependent on lineage-specific transcriptional weighted matrix predict preferential binding of ZNF143 to the programmes set by master transcription factors acting at reference A and the variant C allele of the rs2232015 and regulatory elements that communicate with one another through rs13228237 SNPs, respectively, compared with the other alleles chromatin interactions1. Recently, the ENCODE project17 (Fig. 4a,b). In agreement, 242 reads from the ZNF143 ChIP-seq observed well-positioned and symmetrical nucleosomes flanking data, mapping to the rs2232015 SNP, contain the reference A the binding sites of CTCF, RAD21 and SMC3, which contrasted 8 allele and 136 reads contain the variant T allele (P 5.47 10 À ; the variability observed surrounding the binding sites of other Fig. 4c). Likewise, of the 25 reads mapping to the¼ rs13228237 transcription factors with the exception of ZNF143 (ref. 17). In SNP, five contain the reference G allele and 20 contain the variant agreement with this observation representing a unique feature of 3 C allele (P 4.08x10 À ; Fig. 4d). Importantly, the signal intensity chromatin-looping factors, we demonstrate that ZNF143 is of the ZNF143-binding¼ site containing the rs13228237 SNP is required at promoters to stimulate the formation of chromatin high (n 175) indicating that this SNP falls within the centre of interactions with distal regulatory elements (Fig. 5). This aligns the inferred¼ ZNF143-binding site and between the positive and with its reported role favouring POL2 occupancy at gene negative strand peaks of the unprocessed ChIP-Seq reads promoters22 and in the assembly of the pre-initiation (Fig. 4d). Allele-specific ChIP-quantitative PCR (qPCR) assays complex23. The fact that ZNF143 is ubiquitously expressed21 against ZNF143 in GM12878 cells validated the predicted allelic suggests that ZNF143 may be a regulator of the architectural imbalance for both SNPs (Fig. 4e,f and Supplementary Fig. 3). foundations of cell identity. Although the mechanisms accounting Consistent with ZNF143 being directly responsible for chromatin for cell type-specific ZNF143-binding profiles are unknown, loop formation, the decreased binding of ZNF143 to the chromatin interactions were recently reported to be set early chromatin caused by the variant allele at the rs2232015 SNP during lineage commitment6. In agreement, ZNF143 is required leads to a corresponding allele-specific reduction of the40 chromatin for zebrafish embryo development45, for stem cell identity and for

NATURE COMMUNICATIONS | 6:6186 | DOI: 10.1038/ncomms7186 | www.nature.com/naturecommunications 7 & 2015 Macmillan Publishers Limited. All rights reserved. bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

777 Tables

778 Table 1. Top 90 biased orientation of DNA binding motif sequences of transcription

779 factors in monocytes. TF: DNA binding motif sequences of transcription factors. Score:

780 –log10 (p-value).

781 Forward-reverse orientation

DNA motif of TF Score TF Score TF Score SRF 75.45 STAT5A 31.24 SMARCC2 21.86 IRF7 71.05 E2F8 30.62 ZNF695 21.78 MINI20 61.68 TP53 30.56 ZNF28 21.77 CTCF 61.62 STAT5B 29.94 ZNF316 21.66 E2F 59.32 STAT3 29.85 TBP 21.60 STAT1 58.94 FOS 29.75 NFIB 21.45 ZNF317 55.97 CEBPZ 29.42 PHOX2B 20.82 CEBPG 55.46 RAD21 28.67 DEC 20.62 ZNF623 54.71 SMAD2 28.60 ZNF709 20.58 ZNF93 54.23 GATA2 28.52 YY1 20.57 HMBOX1 52.99 KLF6 28.02 EIF5A2 20.55 SMAD2_SMAD3_SMAD4 50.66 HOXB1 27.62 ZNF148 20.45 FOXN2 49.88 GLI1 27.09 PAX5 20.05 SPEF1 49.52 GCM1 26.73 POU6F1 19.93 ZNF646 43.95 ZNF676 26.66 FOXO4 19.72 TFE3 42.46 TCF3 26.32 EBF 19.26 MYB 41.98 EHF 26.32 ZNF648 19.12 STAT4 40.54 TCF12 26.29 HENMT1 19.02 ZNF716 40.39 MEF2A 26.22 PARG 18.78 KLF14 39.64 HIC1 25.34 ZNF460 18.64 FOXA1 38.13 EGR2 24.92 SLC25A20 17.83 USF 37.74 NR2F2 24.86 KLF5 17.77 EN1 37.01 PLAGL1 24.65 XRCC4 17.53 ZNF219 35.37 REST 24.53 WT1 17.34 IKZF1 33.79 ZNF143 23.67 SULT1A2 17.34 ZIC1 33.60 YBX1 22.99 FUBP1 17.33 SMC3 33.37 PRDM15 22.63 DNAAF2 17.26 ESR2 32.07 ZNF92 22.22 ZNF521 17.25 TP63 31.98 ZNF214 22.11 XBP1 16.85 782 ZNF836 31.66 PTF1A 22.09 SP1 16.84 783

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784 Reverse-forward orientation TF Score TF Score TF Score RFX5 102.30 TFAP2B 34.55 ZNF449 27.96 TCF7 75.34 TBP 34.47 ZNF233 27.66 SRF 65.52 ZNF670 34.33 SOX2 26.46 ZNF28 63.89 ZNF350 34.30 RXRA 26.07 HNF1B 62.46 ZNF687 33.82 MYF6 25.85 ZNF225 62.18 NFKB2 33.05 MAFK 25.81 CEBPB 59.69 RFX3 32.74 CEBPZ 25.73 NFY 58.96 NFE2L3 32.69 POU2F2 25.59 ZNF286B 54.73 TRIM28 32.27 ETS2 25.05 CTCF 53.16 SP3 32.22 HSF1 24.76 PAX5 52.57 FLI1 32.15 AHR 23.56 STAT1 52.11 RBAK 31.92 PAX6 23.48 ISL1 49.73 NR2F1 31.80 IRF4 22.47 ETV7 47.08 NKX3-1 31.55 ETV3 21.90 KLF16 46.45 ZIC2 31.40 FOXP2 21.72 SP1 46.03 PARP1 31.19 CDX2 21.45 SMAD3 45.27 ZNF195 31.06 NFATC1 21.24 STAT5B 44.72 BDP1 30.84 SP4 21.14 TEAD1 43.00 SOX9 30.72 USF1 20.92 ZNF579 42.94 SP8 30.49 MSX2 20.84 ZBTB2 42.28 ZNF121 30.04 PPARG 20.70 ZNF343 41.01 ZNF202 30.01 MYEF2 20.23 DOBOX5 39.21 CD59 29.85 MYC_MAX 20.22 NANOG 38.84 RXRB 29.57 ZNF711 19.84 NFE2L2 38.53 STAT5A 29.31 ZBTB18 19.60 OBOX2 38.00 SOX11 29.09 HSF2 19.51 ZNF652 37.84 WT1 29.06 DNAAF2 19.00 ZNF30 37.59 CREM 28.65 IRF3 18.88 MYOG 36.34 ZNF316 28.34 TFAP2E 18.87 785 GABPB1_GABPB2 35.96 HAND1_TCF3 28.07 BCL11A 18.59 786

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787 Table 2. Top 30 forward-reverse orientation of DNA binding motif sequences of

788 transcription factors in MCF-7 and iPS cells. TF: DNA binding motif sequences of

789 transcription factors. Score: –log10 (p-value).

790 MCF-7 iPS

TF Score TF Score RAD21 16.21 ZIC3 19.32 SMC3 15.63 ZNF521 18.93 CTCF 15.12 TFE3 16.63 E2F 10.14 ZNF317 16.43 SLC25A20 9.62 NKX2-5 16.25 HOXA7 8.29 HES1 15.34 STAT5B 7.55 ZBTB24 14.21 REST 7.25 SMC3 13.76 SIRT6 7.05 FOS 13.69 KLF3 6.53 RAD21 13.05 YY1 5.30 ZNF836 11.64 PLAGL1 4.97 TBX5 11.48 ZNF219 4.91 CTCF 11.24 STAT1 4.43 STAT1 11.19 SNTB1 4.42 RUNX2 10.28 ETS 3.16 WT1 10.27 XRCC4 3.15 ZIC1 9.60 ZBTB6 3.12 MAX 8.55 DBP 2.53 KLF3 8.29 SETDB1 2.53 KLF14 8.25 RREB1 2.50 ZNF143 7.81 E2F5 2.38 E2F5 7.66 KLF5 2.33 SIRT6 7.56 SPEF1 2.22 EN1 7.49 ZNF143 2.20 YY1 7.02 ZNF460 2.19 STAT5B 6.73 FOS 2.18 MAZ 6.39 GATA2 1.97 ZNF148 6.20 MAZ 1.95 TCF3 5.73 791 PARG 1.94 EGR2 5.45 792

793

794 Table 3. Biased orientation of repeat DNA sequences in monocytes. Score: –log10

795 (p-value).

Forward-reverse (FR) orientation (using H3K27ac histone modification marks) Repeat DNA seq. Score MLT1F1 6.75 796

Reverse-forward (RF) orientation Repeat DNA seq. Score LTR16C 69.39 L1ME4b 23.90 797 AluSg 23.61

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798 Table 4. Top 30 of co-locations of biased orientation of DNA binding motif sequences

799 of transcription factors in monocytes. Co-locations of DNA motif sequence of CTCF

800 with another biased orientation of DNA motif sequence were shown in a separate table.

801 Motif 1,2: DNA binding motif sequences of transcription factors. # both: the number of

802 open chromatin regions including both Motif 1 and Motif 2. # motif 1: the number of

803 open chromatin regions including Motif 1. # motif 2: the number of open chromatin

804 regions including Motif 2. # others: the number of open chromatin regions not including

805 Motif 1 and Motif 2. Open chromatin regions overlapped with histone modification

806 marks (H3K27ac) were used (Total 26,095 regions).

Motif 1 Motif 2 # both # motif 1 # motif 2 # others p-value CTCF SMAD2 4527 781 4478 16309 0 CTCF RREB1 4379 929 4757 16030 0 CTCF ZNF263 4357 951 4875 15912 0 CTCF SP1 4321 987 4052 16735 0 CTCF RAD21 3804 1504 225 20562 0 CTCF KLF6 3695 852 3800 17748 0 CTCF SMC3 1259 178 1977 22681 0 807 CTCF RXRA 1220 259 2559 22057 0

Motif 1 Motif 2 # both # motif 1 # motif 2 # others p-value SMAD2 ZNF263 7427 1578 1805 15285 0 SMARCC2 ZNF263 7354 1192 1893 15656 0 RREB1 SP1 7208 1957 1165 15765 0 SIRT6 ZNF263 7126 1154 2121 15694 0 MAZ SP1 7052 909 1321 16813 0 MAZ ZNF263 7022 999 2225 15849 0 SP1 ZNF263 7009 1364 2223 15499 0 SMAD2 SP1 6925 2080 1448 15642 0 MAZ RREB1 6920 967 2245 15963 0 SIRT6 SMAD2 6766 1514 2239 15576 0 SIRT6 SMARCC2 6668 1612 1878 15937 0 PLAGL1 SMAD2 6637 1074 2368 16016 0 MAZ SMAD2 6627 1334 2378 15756 0 PARG SMAD2 6602 1012 2403 16078 0 PLAGL1 ZNF263 6571 1140 2661 15723 0 EGR2 RREB1 6565 787 2600 16143 0 KLF6 RREB1 6563 932 2573 16027 0 MAZ SMARCC2 6562 1459 1984 16090 0 RREB1 ZNF263 6551 1607 2681 15256 0 KLF6 SP1 6541 954 1832 16768 0 PLAGL1 RREB1 6496 1215 2640 15744 0 EGR2 SP1 6492 860 1881 16862 0 KLF6 SMAD2 6491 1004 2514 16086 0 PARG ZNF263 6390 1224 2842 15639 0 PLAGL1 SP1 6318 1393 2055 16329 0 KLF6 ZNF263 6304 1191 2928 15672 0 EGR2 SMAD2 6270 1082 2735 16008 0 EGR2 ZNF263 6253 1099 2979 15764 0 EGR2 MAZ 6219 1133 1742 17001 0 808 PARG RREB1 6219 1395 2917 15564 0

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809 Table 5. Comparison of enhancer-promoter interactions (EPI) with chromatin

810 interactions in T cells. TF: DNA binding motif sequence of a transcription factor. Score:

811 –log10 (p-value). Inf: p-value = 0. Score 1: Comparison of EPA shortened at the

812 genomic locations of FR or RF orientation of DNA motif sequence with EPA not

813 shortened. Score 2: Comparison of EPA shortened at the genomic locations of FR or RF

814 orientation of DNA motif sequence with EPA shortened at the genomic locations of any

815 orientation of DNA motif sequence.

816

817 Forward-reverse (FR) orientation Reverse-forward (RF) orientation

TF Score 1 Score 2 TF Score 1 Score 2 TF Score 1 Score 2 TF Score 1 Score 2 APEX1 13.57 3.85 PRDM15 Inf 3.21 BCL11B 101.77 5.58 ZFP2 323.31 6.24 AR Inf 8.30 RAD21 56.16 4.21 CEBPA 323.31 2.37 ZNF143 134.24 1.81 CDC5L 65.46 12.23 RARB 113.99 2.28 CREB3 139.16 13.51 ZNF174 159.72 7.65 CTCF 101.79 14.94 REL 104.66 7.95 CTCF 119.43 20.80 ZNF257 172.88 3.75 DDIT3_CEBPA 249.72 4.78 RREB 117.64 3.13 DBP 25.72 1.84 ZNF28 323.31 3.53 EBF1 48.10 2.27 RREB1 116.79 3.39 EGR1 247.74 1.65 ZNF282 100.44 4.02 EGR1 97.56 6.09 SMC3 90.56 17.59 EP300 135.93 6.30 ZNF300 Inf 3.91 EGR3 130.86 2.73 SOAT1 22.63 1.88 ESR1 101.75 9.30 ZNF341 94.91 5.59 EGR4 59.94 2.91 SOX18 113.13 6.71 ETS1 250.92 1.76 ZNF44 165.34 3.45 ELF5 119.97 2.85 SRP9 117.49 3.47 ETV1 272.94 3.43 ZNF484 301.75 12.63 EP300 28.41 15.12 TAL1 70.39 1.82 ETV3 323.31 2.99 ZNF526 82.28 4.67 ETV4 270.06 2.16 TCF7L2 93.32 8.22 FOS 101.53 9.02 ZNF580 55.73 2.98 FOXF2 42.79 5.16 TFCP2 260.99 4.13 FOXA 323.31 9.16 ZNF625 323.31 2.31 FOXN4 76.81 4.80 THRA 145.85 4.05 FOXA1 323.31 8.99 ZNF658 92.95 4.92 FOXO3 323.31 5.49 TP53 323.31 9.13 FOXG1 235.13 2.77 ZNF718 165.94 2.09 FOXO6 63.29 1.77 TP63 172.00 3.90 FOXN4 61.07 5.39 ZNF721 86.39 7.28 GATA 104.41 2.17 YBX1 164.76 5.23 FOXO3 306.90 5.33 ZNF773 219.31 13.43 GATA5 89.03 4.38 ZBTB7A 66.49 4.74 GATA1 314.93 1.91 ZNF777 137.69 1.96 GFI1B 184.13 11.81 ZFP14 97.38 5.25 HLTF 82.82 1.85 GLIS2 32.14 1.87 ZNF219 32.59 7.48 HOXA10 29.26 1.81 HBP1 281.23 3.05 ZNF253 323.31 21.30 HOXB6 197.15 2.21 HIC1 101.63 3.27 ZNF585A 185.37 6.09 IRF5 Inf 6.92 HOXA13 103.63 3.71 ZNF616 129.96 8.66 KLF13 148.08 4.91 HOXA2 323.31 5.81 ZNF639 193.43 1.77 KLF8 120.36 2.97 INSM2 323.31 2.02 ZNF681 323.31 35.04 NFE2L2 155.83 3.83 IRF 206.25 2.09 ZNF701 41.48 1.65 NFKB1 106.02 7.09 IRF5 39.54 3.78 ZNF721 225.60 5.52 NKX2-1 323.31 4.01 KLF1 146.64 3.51 ZNF75A 43.99 3.51 NKX2-4 Inf 5.73 LHX8 245.03 2.34 ZNF770 66.18 2.95 NKX2-5 323.31 5.80 MAF 66.63 3.85 ZNF786 323.31 15.68 NR4A1 116.75 2.99 MINI20 102.68 3.29 ZNF790 74.59 6.71 PPARGC1A 57.39 3.36 MYC 39.24 2.64 ZNF84 149.37 3.38 RAD21 41.87 3.16 MZF1 24.10 1.64 ZNF846 Inf 10.92 RUNX2 124.18 5.84 NFATC2 37.81 1.92 SIX6 95.00 3.28 NFKB1 195.32 11.43 SMARC 323.31 6.02 NR0B1 13.24 1.84 SRF 323.31 6.78 NR2C2 137.27 12.28 TAL1 124.35 4.80 OTX2 40.38 2.77 TCF12 74.48 2.21 P50_P50 131.79 6.49 ZBTB18 240.63 9.05 818 PITX1 37.22 2.17 ZBTB4 323.31 2.06

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819 References

820

821 Bailey SD, Zhang X, Desai K, Aid M, Corradin O, Cowper-Sal Lari R, Akhtar-Zaidi B, 822 Scacheri PC, Haibe-Kains B, Lupien M. 2015. ZNF143 provides sequence 823 specificity to secure chromatin interactions at gene promoters. Nat Commun 2: 824 6186. 825 Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble 826 WS. 2009. MEME SUITE: tools for motif discovery and searching. Nucleic 827 acids research 37: W202-208. 828 Barutcu AR, Lajoie BR, Fritz AJ, McCord RP, Nickerson JA, van Wijnen AJ, Lian JB, 829 Stein JL, Dekker J, Stein GS et al. 2016. SMARCA4 regulates gene expression 830 and higher-order chromatin structure in proliferating mammary epithelial cells. 831 Genome research 26: 1188-1201. 832 Bejerano G, Lowe CB, Ahituv N, King B, Siepel A, Salama SR, Rubin EM, Kent WJ, 833 Haussler D. 2006. A distal enhancer and an ultraconserved exon are derived 834 from a novel retroposon. Nature 441: 87-90. 835 Chen M, Manley JL. 2009. Mechanisms of alternative splicing regulation: insights from 836 molecular and genomics approaches. Nat Rev Mol Cell Biol 10: 741-754. 837 Das D, Clark TA, Schweitzer A, Yamamoto M, Marr H, Arribere J, Minovitsky S, 838 Poliakov A, Dubchak I, Blume JE et al. 2007. A correlation with exon 839 expression approach to identify cis-regulatory elements for tissue-specific 840 alternative splicing. Nucleic acids research 35: 4845-4857. 841 de Souza FS, Franchini LF, Rubinstein M. 2013. Exaptation of transposable elements 842 into novel cis-regulatory elements: is the evidence always strong? Mol Biol Evol 843 30: 1239-1251. 844 de Wit E, Vos ES, Holwerda SJ, Valdes-Quezada C, Verstegen MJ, Teunissen H, 845 Splinter E, Wijchers PJ, Krijger PH, de Laat W. 2015. CTCF Binding Polarity 846 Determines Chromatin Looping. Molecular cell 60: 676-684. 847 Grant CE, Bailey TL, Noble WS. 2011. FIMO: scanning for occurrences of a given 848 motif. Bioinformatics (Oxford, England) 27: 1017-1018. 849 Guo Y, Xu Q, Canzio D, Shou J, Li J, Gorkin DU, Jung I, Wu H, Zhai Y, Tang Y et al. 850 2015. CRISPR Inversion of CTCF Sites Alters Genome Topology and

46 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

851 Enhancer/Promoter Function. Cell 162: 900-910. 852 Javierre BM, Burren OS, Wilder SP, Kreuzhuber R, Hill SM, Sewitz S, Cairns J, 853 Wingett SW, Varnai C, Thiecke MJ et al. 2016. Lineage-Specific Genome 854 Architecture Links Enhancers and Non-coding Disease Variants to Target Gene 855 Promoters. Cell 167: 1369-1384 e1319. 856 Jeong M, Huang X, Zhang X, Su J, Shamim M, Bochkov I, Reyes J, Jung H, Heikamp 857 E, Presser Aiden A et al. 2017. A Cell Type-Specific Class of Chromatin Loops 858 Anchored at Large DNA Methylation Nadirs. bioRxiv. 859 Ji X, Dadon DB, Abraham BJ, Lee TI, Jaenisch R, Bradner JE, Young RA. 2015. 860 Chromatin proteomic profiling reveals novel proteins associated with 861 histone-marked genomic regions. Proc Natl Acad Sci U S A 112: 3841-3846. 862 Jin C, Kato K, Chimura T, Yamasaki T, Nakade K, Murata T, Li H, Pan J, Zhao M, Sun 863 K et al. 2006. Regulation of histone acetylation and nucleosome assembly by 864 transcription factor JDP2. Nat Struct Mol Biol 13: 331-338. 865 Jjingo D, Conley AB, Wang J, Marino-Ramirez L, Lunyak VV, Jordan IK. 2014. 866 Mammalian-wide interspersed repeat (MIR)-derived enhancers and the 867 regulation of human gene expression. Mob DNA 5: 14. 868 John S, Sabo PJ, Thurman RE, Sung MH, Biddie SC, Johnson TA, Hager GL, 869 Stamatoyannopoulos JA. 2011. Chromatin accessibility pre-determines 870 glucocorticoid receptor binding patterns. Nature genetics 43: 264-268. 871 Jolma A, Yan J, Whitington T, Toivonen J, Nitta KR, Rastas P, Morgunova E, Enge M, 872 Taipale M, Wei G et al. 2013. DNA-binding specificities of human transcription 873 factors. Cell 152: 327-339. 874 Karolchik D, Barber GP, Casper J, Clawson H, Cline MS, Diekhans M, Dreszer TR, 875 Fujita PA, Guruvadoo L, Haeussler M et al. 2014. The UCSC Genome Browser 876 database: 2014 update. Nucleic acids research 42: D764-770. 877 Katainen R, Dave K, Pitkanen E, Palin K, Kivioja T, Valimaki N, Gylfe AE, Ristolainen 878 H, Hanninen UA, Cajuso T et al. 2015. CTCF/cohesin-binding sites are 879 frequently mutated in cancer. Nature genetics 47: 818-821. 880 Kheradpour P, Kellis M. 2014. Systematic discovery and characterization of regulatory 881 motifs in ENCODE TF binding experiments. Nucleic acids research 42: 882 2976-2987. 883 Li H, Durbin R. 2009. Fast and accurate short read alignment with Burrows-Wheeler

47 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

884 transform. Bioinformatics (Oxford, England) 25: 1754-1760. 885 Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, 886 Durbin R, Genome Project Data Processing S. 2009. The Sequence 887 Alignment/Map format and SAMtools. Bioinformatics (Oxford, England) 25: 888 2078-2079. 889 McLean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB, Wenger AM, 890 Bejerano G. 2010. GREAT improves functional interpretation of cis-regulatory 891 regions. Nature biotechnology 28: 495-501. 892 Mumbach MR, Satpathy AT, Boyle EA, Dai C, Gowen BG, Cho SW, Nguyen ML, 893 Rubin AJ, Granja JM, Kazane KR et al. 2017. Enhancer connectome in primary 894 human cells identifies target genes of disease-associated DNA elements. Nature 895 genetics 49: 1602-1612. 896 Newburger DE, Bulyk ML. 2009. UniPROBE: an online database of protein binding 897 microarray data on protein-DNA interactions. Nucleic acids research 37: 898 D77-82. 899 Osato N. 2018. Characteristics of functional enrichment and gene expression level of 900 human putative transcriptional target genes. BMC Genomics 19: 957. 901 Phanstiel DH, Van Bortle K, Spacek D, Hess GT, Shamim MS, Machol I, Love MI, 902 Aiden EL, Bassik MC, Snyder MP. 2017. Static and Dynamic DNA Loops form 903 AP-1-Bound Activation Hubs during Macrophage Development. Molecular cell 904 67: 1037-1048.e1036. 905 Portales-Casamar E, Thongjuea S, Kwon AT, Arenillas D, Zhao X, Valen E, Yusuf D, 906 Lenhard B, Wasserman WW, Sandelin A. 2010. JASPAR 2010: the greatly 907 expanded open-access database of transcription factor binding profiles. Nucleic 908 acids research 38: D105-110. 909 Ramani V, Cusanovich DA, Hause RJ, Ma W, Qiu R, Deng X, Blau CA, Disteche CM, 910 Noble WS, Shendure J et al. 2016. Mapping 3D genome architecture through in 911 situ DNase Hi-C. Nat Protoc 11: 2104-2121. 912 Rao SS, Huntley MH, Durand NC, Stamenova EK, Bochkov ID, Robinson JT, Sanborn 913 AL, Machol I, Omer AD, Lander ES et al. 2014. A 3D map of the human 914 genome at kilobase resolution reveals principles of chromatin looping. Cell 159: 915 1665-1680. 916 Rebollo R, Romanish MT, Mager DL. 2012. Transposable elements: an abundant and

48 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

917 natural source of regulatory sequences for host genes. Annu Rev Genet 46: 918 21-42. 919 Saeed S, Quintin J, Kerstens HH, Rao NA, Aghajanirefah A, Matarese F, Cheng SC, 920 Ratter J, Berentsen K, van der Ent MA et al. 2014. Epigenetic programming of 921 monocyte-to-macrophage differentiation and trained innate immunity. Science 922 (New York, NY) 345: 1251086. 923 Schreiber J, Libbrecht M, Bilmes J, Noble W. 2017. Nucleotide sequence and DNaseI 924 sensitivity are predictive of 3D chromatin architecture. bioRxiv. 925 Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski 926 B, Ideker T. 2003. Cytoscape: a software environment for integrated models of 927 biomolecular interaction networks. Genome research 13: 2498-2504. 928 Tabuchi TM, Deplancke B, Osato N, Zhu LJ, Barrasa MI, Harrison MM, Horvitz HR, 929 Walhout AJ, Hagstrom KA. 2011. Chromosome-biased binding and gene 930 regulation by the Caenorhabditis elegans DRM complex. PLoS Genet 7: 931 e1002074. 932 Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, 933 Schroth GP, Burge CB. 2008. Alternative isoform regulation in human tissue 934 transcriptomes. Nature 456: 470-476. 935 Wang J, Vicente-Garcia C, Seruggia D, Molto E, Fernandez-Minan A, Neto A, Lee E, 936 Gomez-Skarmeta JL, Montoliu L, Lunyak VV et al. 2015. MIR retrotransposon 937 sequences provide insulators to the human genome. Proc Natl Acad Sci U S A 938 112: E4428-4437. 939 Wang L, Wang S, Li W. 2012. RSeQC: quality control of RNA-seq experiments. 940 Bioinformatics (Oxford, England) 28: 2184-2185. 941 Weintraub AS, Li CH, Zamudio AV, Sigova AA, Hannett NM, Day DS, Abraham BJ, 942 Cohen MA, Nabet B, Buckley DL et al. 2017. YY1 Is a Structural Regulator of 943 Enhancer-Promoter Loops. Cell 171: 1573-1588 e1528. 944 Wingender E, Dietze P, Karas H, Knuppel R. 1996. TRANSFAC: a database on 945 transcription factors and their DNA binding sites. Nucleic acids research 24: 946 238-241. 947 Xie Z, Hu S, Blackshaw S, Zhu H, Qian J. 2010. hPDI: a database of experimental 948 human protein-DNA interactions. Bioinformatics (Oxford, England) 26: 949 287-289.

49 bioRxiv preprint doi: https://doi.org/10.1101/290825; this version posted January 27, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

950 Zhang H, Li F, Jia Y, Xu B, Zhang Y, Li X, Zhang Z. 2017. Characteristic arrangement 951 of nucleosomes is predictive of chromatin interactions at kilobase resolution. 952 Nucleic acids research 45: 12739-12751. 953 Zhang Y, An L, Xu J, Zhang B, Zheng WJ, Hu M, Tang J, Yue F. 2018. Enhancing Hi-C 954 data resolution with deep convolutional neural network HiCPlus. Nat Commun 955 9: 750. 956 Zhao Y, Stormo GD. 2011. Quantitative analysis demonstrates most transcription factors 957 require only simple models of specificity. Nature biotechnology 29: 480-483.

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