1 Diversification of Reprogramming Trajectories Revealed by Parallel Single-Cell 2 Transcriptome and Chromatin Accessibility Sequencing

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1 Diversification of Reprogramming Trajectories Revealed by Parallel Single-cell 2 Transcriptome and Chromatin Accessibility Sequencing

3 Qiao Rui Xing1,2,19, Chadi El Farran1,3,19, Pradeep Gautam1,3, Yu Song Chuah1, Tushar Warrier1,3, 4 Cheng-Xu Delon Toh1, Nam-Young Kang4,5, Shigeki Sugii6,7, Young-Tae Chang4,5, Jian Xu3, 5 James J. Collins8,9,10,11, George Q. Daley8,12,13,14,15, Hu Li16,*, Li-Feng Zhang2,*, Yuin-Han 6 Loh1,3,17,18*

7 1 Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and 8 Aging, A*STAR Institute of Molecular and Cell Biology, Singapore 138673, Singapore 9 2 School of Biological Sciences, Nanyang Technological University, 637551, Singapore 10 3 Department of Biological Sciences, National University of Singapore, Singapore 117543, 11 Singapore 12 4 Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, A*STAR, 13 Singapore 138667, Singapore 14 5 Department of Chemistry, National University of Singapore, Singapore 117543, Singapore 15 6 Fat Metabolism and Stem Cell Group, Laboratory of Metabolic Medicine, Singapore Bioimaging 16 Consortium, A*STAR, 11 Biopolis Way, 138667 Singapore 17 7 Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, 8 College Road, 18 169857 Singapore 19 8 Howard Hughes Medical Institute, Boston, MA 02114, USA 20 9 Institute for Medical Engineering and Science Department of Biological Engineering, and 21 Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02114, USA 22 10 Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA 23 11 Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA 24 12 Stem Cell Transplantation Program, Division of Pediatric Hematology/Oncology, Boston 25 Children’s Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA 26 13 Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 27 Boston, MA 02115, USA 28 14 Harvard Stem Cell Institute, Boston, MA 02115, USA 29 15 Manton Center for Orphan Disease Research, Boston, MA 02115, USA 30 16 Center for Individualized Medicine, Department of Molecular Pharmacology & Experimental 31 Therapeutics, Mayo Clinic, Rochester, Minnesota 55905, USA 32 17 NUS Graduate School for Integrative Sciences and Engineering, National University of 33 Singapore, 28 Medical Drive, Singapore 117456, Singapore 34 18 Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, 35 Singapore 117593, Singapore 36 19These authors contributed equally to this work 37 38 39 40 41 *Correspondence: 42 Yuin-Han Loh, Epigenetics and Cell Fates Laboratory, A*STAR, Institute of Molecular and Cell 43 Biology, 61 Biopolis Drive Proteos, Singapore 138673, 44 Singapore; e-mail: [email protected] 45 Li-Feng Zhang, School of Biological Sciences, Nanyang Technological University, 60 Nanyang 46 Drive, Singapore, 637551, Singapore; e-mail: [email protected] 47 Hu Li, Center for Individualized Medicine, Department of Molecular Pharmacology & 48 Experimental Therapeutics, Mayo Clinic, 200 First St. SW Rochester, MN 55905, USA; e-mail: 49 [email protected] 1

50 Keywords: human cellular reprogramming, single-cell ATAC-Seq (scATAC-Seq), single-cell 51 RNA-Seq (scRNA-Seq), GDF3, BDD2-C8, CD13, CD44, CD201, stage-specific regulatory 52 networks, lineage specifiers, chromatin accessibility, FOSL1, TEAD4.

53 Running title: Parallel Single-cell Transcriptome and Chromatin Sequencing on Human Cellular 54 Reprogramming

56 SUMMARY

57 To unravel the mechanism of human cellular reprogramming process at single-cell

58 resolution, we performed parallel scRNA-Seq and scATAC-Seq analysis. Our analysis reveals that

59 the cells undergoing reprogramming proceed in an asynchronous trajectory and diversify into

60 heterogeneous sub-populations. BDD2-C8 fluorescent probe staining and negative staining for

61 CD13, CD44 and CD201 markers, could enrich for the GDF3+ early reprogrammed cells.

62 Combinatory usage of the surface markers enables the fine segregation of the early-intermediate

63 cells with diverse reprogramming propensities. scATAC-Seq analysis further uncovered the

64 genomic partitions and transcription factors responsible for the regulatory phasing of

65 reprogramming process. Binary choice between a FOSL1 or a TEAD4-centric regulatory network

66 determines the outcome of a successful reprogramming. Altogether, our study illuminates the

67 multitude of diverse routes transversed by individual reprogramming cells and presents an

68 integrative roadmap for identifying the mechanistic part-list of the reprogramming machinery.

70 INTRODUCTION

71 Somatic cells can be reverted to pluripotency by inducing the expression of four

72 transcription factors namely OCT4, SOX2, KLF4 and MYC in a process known as cellular

73 reprogramming1–6. Discovery of this phenomenon has raised the hopes for advancing the field of

74 regenerative medicine7. However, cellular reprogramming suffers from extremely low efficiency

75 especially for the human cells, resulting in a heterogeneous population in which few cells can be

76 characterized as pluripotent8–10. Although a handful of studies analyzed bulk population to

77 understand the reprogramming mechanisms11–17, ensemble measurement of the heterogeneous

78 population impedes the discerning of transcriptomic and epigenetic changes taking place in the

79 minority of cells undergoing the route towards successful reprogramming. Single-cell sequencing

80 technologies provide tools to decipher the types of cells present in a heterogeneous mixture18. In the

81 present study, we adopted the parallel genome-wide single-cell assays of scRNA-Seq and scATAC-

82 Seq19–21 to profile transcriptome and chromatin accessibility of human reprogramming cells across

83 various stages. We identified cellular diversification and trajectories where individual cell displays

84 different dynamics and potential for reprogramming. Moreover, with a set of cell surface markers

85 and a fluorescent probe BDD2-C8, we were able to enrich for the early-intermediary cells

86 undergoing route towards successful reprogramming. In addition, we identified the modulators

87 driving the changes in gene regulatory network and chromatin accessibility, as cells advanced

88 towards the diverse reprogramming trajectories. Of note, the pivot from FOSL1 to TEAD4-centric

89 regulatory networks is essential for the acquisition of the pluripotent state.

91 RESULTS

92 Single-cell Profiling of Cell-Fate Reprogramming

93 To study the heterogeneity of human reprogramming, we analyzed a total of 33468 scRNA-

94 Seq and scATAC-Seq libraries with good quality, including day 0 (BJ), day 2 (D2), day 8 (D8),

95 day12 (D12) and day 16 (D16) OSKM-induced reprogramming cells (Figure 1a and Supplementary

96 Table 1). On D16, cells were sorted using the TRA-1-60 marker to distinguish the successfully

97 reprogrammed (D16+) from the non-reprogrammed (D16-) cells (Figures 1a and S1a-b). The

98 generated iPSCs were characterized with immunostaining, DNA methylation, and terotoma assay

99 (Figures S1c-e). Two distinct approaches were used for scRNA-Seq library preparation.

100 Microfluidic cell capture-based assay (Fluidigm C1) reads the full-length transcripts from hundreds

101 of cells with high resolution, whereas the droplet-based assay (10X Genomics) probes the 3’ end of 3

102 the transcripts from thousands of cells albeit at a relatively low genomic coverage. In addition, we

103 have also screened for fluorescence probes to distinguish early-intermediate cells poised for

104 successful reprogramming (Figure 1a). The cumulative data enable us to characterize the sub-

105 populations in-depth and to construct a trajectory map of human reprogramming.

106 Majority of the capture-based scRNA-Seq libraries showed high exon mapping percentage

107 (>=75%) and gene detection rate (>=20%) and displayed even distribution over the gene-bodies

108 (Figure 1b-c, and Supplementary Table 1). Furthermore, epithelial and pluripotency genes were

109 progressively expressed with the advancement of reprogramming, as opposed to the mesenchymal

110 and fibroblast genes (Figure S1f). Similarly, majority of the 10X libraries were of good quality

111 (Figures S1g-h). Notably, t-SNE plot revealed a dynamic transcriptomic transition from the parental

112 BJ to D16+ cells (Figure 1d). Expectedly, ZEB1 (mesenchymal) and COL1A1 (somatic) were

113 abundantly expressed in the early time-points and non-reprogrammed cells (Figures 1e-f). On the

114 contrary, EPCAM (epithelial), and NANOG and LIN28A (pluripotent) were expressed highly in the

115 successfully reprogrammed cells (Figures 1e-f and S1i). Likewise, most of the scATAC-Seq

116 libraries passed the previously reported QC indices19, and exhibited enrichment over TSS regions

117 and nucleosomal distributions (Figure 1g-i and S1j-k, and Supplementary Table 1). Collectively, we

118 generated reliable libraries for tens of thousands of reprogramming cells, providing a rich resource

119 to decipher its deep molecular mechanisms.

120 Deciphering the Heterogeneous Subgroups with Diverse Reprogramming Potentials

121 Due to its high sensitivity, capture-based scRNA-Seq libraries were analyzed first to

122 decipher the heterogeneity. CellNet22 revealed the dynamics of reduced fibroblast similarity and

123 increased ESC correlation (Figure S2a). To determine the diverse populations present at each

124 reprogramming time-point, we clustered scRNA-Seq libraries using Reference Component Analysis

125 (RCA)23. Interestingly, BJ cells correlated significantly with the smooth muscle lineage, which was

126 also detected across the published BJ libraries (Figures S2b-c). D2 cells were marked by four 4

127 distinct subgroups (G1-G4), among which G1-3 cells displayed lower correlation to the fibroblasts

128 and mesenchymal stem cells (MSCs) (Figures 2a and S2d). D8 cells were distributed among three

129 discrete sub-populations (Figures 2b and S2d). D8 G1 cells corresponded to the fibroblasts, smooth

130 muscles, myocytes, and MSCs lineages, whilst G3 cells displayed substantial similarity to the

131 pluripotent stem cells (PSCs). Interestingly, D8 G2 cells represented the intermediate state. Two

132 sub-populations were present in the D16+ cells (Figures 2c and S2d). D16+ G2 cells were highly

133 associated with PSCs, while G1 cells maintained detectable correlation to the MSCs, adipose cells,

134 and endothelial cells, other than PSCs. In summary, RCA analysis strongly indicates that the

135 reprogramming cells are highly diverse, some of which may deviate from the route to pluripotency

136 and acquire alternative lineage cell-fates.

137 We then performed differential gene expression (DGE) analysis to evaluate the subgroup

138 specific genes (Figure 2d and Supplementary Table 2). Among D2 subgroups, G3 cells had the

139 most distinct transcriptomic profile with exclusive expression of a remarkable number of genes,

140 including ERBB3 (Figures 2d-e). Majority of D2 G1-2 genes, for example CDK1, were expressed

141 highly in D16+ G2, suggestive of their higher reprogramming propensity (Figures 2d-f). Among D8

142 subgroups, G1-2 specific genes were expressed highly in BJ and D16- but not the D16+ cells, such

143 as JUNB, LUM, COL1A1, and COL6A3 (Figure 2d). The opposite trend was observed for D8 G2-3

144 genes. RFC3 was vastly expressed in D8 G2-3 cells, whereas GDF3 was specifically expressed in

145 the G3 (Figures 2d-f). In agreement with the correlation to the differentiated lineages, D16+ G1

146 specific genes, including MMP2, were also expressed highly in the D16- cells, suggesting that

147 D16+ G1 cells were at most partially reprogrammed (Figures 2d-f). On the other hand, epithelial

148 genes and pluripotent genes including CDH1, NANOG and LIN28A, as well as genes associated

149 with mRNA splicing and transcription of the small RNAs including WBP11 and POLR3K, were

150 specifically expressed in D16+ G2 cells. Intriguingly, depletion of POLR3K and WBP11 resulted in

151 ablated reprogramming efficiency, indicating the functional importance of the D16+ G2 specific

152 genes for reprogramming (Figure S2e). Additionally, D8 G3 and D16+ G2 specific genes exhibited 5

153 high stemness score for PSCs, whereas D8 G1-2 and D16+ G1 specific genes significantly

154 associated with the differentiated lineages (Figures S2f-g).

155 To test the notion of the diverse reprogramming potentials, D8 subgroups were correlated to

156 the subgroups of various time-points (Figure S2h). Interestingly, G3 cells highly correlated with

157 D16+ G2 cells, whereas G2 cells represented an intermediate state in which the cells were

158 moderately correlated with all D16 cells. G1 cells, on the other hand, strongly correlated with D16-

159 and cells from the early time-points (BJ and D2). In-house devised classifier displayed a similar

160 correlation trend of the reprogramming time-points to the D8 subgroups (Figure 2g).

161 Pseudotemporal trajectory of reprogramming cells

162 We next analyzed 10X libraries to construct pseudotemporal map of cellular reprogramming.

163 CellNet and RCA of 10X libraries reproduced the reprogramming dynamics and diverse subgroups

164 with variable lineage correlations (Figures S3a-c). Resultant pseudotemporal trajectories24,25

165 consisted of 9 states and 4 branching events (Figures 3a and S3d). Notably, pseudotime highly

166 correlated with the reprogramming time-points (Figures 3a-c). We then traced the trajectory of RCA

167 subgroups. Interestingly, majority of the D2 G1-3 cells were found in state 3 (95% of G1, 65% of

168 G2, and 80% of G3), whereas G4 cells scattered across the early states (Figure S3e). Joint RCA

169 analysis demonstrated that D2 G1-2 cells clustered closer to the D8 G2 cells and correlated stronger

170 to the ESC fate, indicating their higher reprogramming propensity (Figures S3f-g). Of note, D8 G1

171 cells enriched across the different states other than state 9 (successfully reprogrammed) (Figures 3d-

172 e). On the contrary, D8 G3 cells were mostly found in state 9. D8 G2 cells distributed across the

173 intermediate (3-5) and late states (7-9). Intriguingly, state 4 comprised almost entirely of D8 G2

174 cells (544 vs. 627) (Figures 3d-e). Expectedly, D16+ G2 cells were the major constituents of state 9,

175 whereas cells of D16+ G1 were enriched in both state 8 (non-reprogrammed) and state 9,

176 corroborating their partially- and non-reprogrammed identities (Figures 3d and S3h). Further,

177 subgroup specific markers were expressed differentially along the pseudotime axis (Figure 3f). 6

178 RFC3 (D8 G2-3) and GDF3 (D8 G3), and NANOG and LIN28A (D16+ G2) were expressed highly

179 in the cells on the successful reprogramming trajectory, whereas MMP2 (D16+ G1) showed the

180 opposite trend. Next, we determined the gene expression patterns and significant biological

181 processes defining the trajectory (Figure S3i and Supplementary Table 3). At branching event 1,

182 cells with high levels of lineage genes advanced towards successful reprogramming, whereas cells

183 with abundant DNA replication genes deviated from the path (Figures 3g-h and S3i). Interestingly,

184 successfully reprogrammed cells at branching point 4 were highly active for DNA replication and

185 mRNA splicing, which were implicated to be essential for reprogramming26,27. On the other hand,

186 collagen and extracellular matrix related genes emerged to be detrimental for reprogramming at the

187 branching point 3 and 4, and lineage processes such as angiogenesis and epidermis development

188 contributed to the unsuccessful reprogramming at branching point 4. Together, these analyses

189 provide a plethora of data for identifying the novel processes and modulators affecting the

190 reprogramming trajectory at an unprecedented single-cell resolution.

191 Toolkits to enrich for early-intermediate cells with diverse reprogramming potentials

192 To enrich for the intermediate cells with high reprogramming potential, we conducted a

193 screen for a library of 34 DOLFA28,29 fluorescent dyes (Figure S4a). Candidate dyes differentially

194 stain the intermediate reprogramming cells with the accelerated dynamics upon treatment with a

195 TGFβ inhibitor30,31, A83-01. BDD1-A2, BDD2-A6, and BDD2-C8 were identified as the top hits,

196 which showed co-localized signal with TRA-1-60 (Figures S4a-c). Importantly, D8 cells enriched

197 with the candidate probes gave rise to a significantly higher number of TRA-1-60+ colonies

198 (Figures 4a and S4d). Among them, BDD2-C8 displayed the best performance in an alternative

199 reprogramming of MRC5 fibroblasts (Figure S4e). BDD2-C8 also precisely captured changes in

200 reprogramming efficiency upon depletion of the key modulators15 (Figure S4f). Single-cell qPCR

201 showed that BDD2-C8+ cells expressed higher levels of epithelial and pluripotent genes, and lower

202 levels of mesenchymal and somatic genes (Figure 4b). To further characterize, we prepared 192

203 scRNA-Seq libraries for D8 cells stained highly (D8BDD2-C8+) and lowly (D8BDD2-C8-) for BDD2-C8.

204 In the ensuing RCA analysis, D8BDD2-C8+ and D8BDD2-C8- cells clustered close to the D8 G2-3 and G1

205 respectively, which were substantiated by the similar expression profiles for the subgroup specific

206 genes (Figures 4c-d and S4g-h). GO enriched for D8BDD2-C8+ specific genes were related to cell

207 cycle, embryo development and stem cell population maintenance, whereas D8BDD2-C8- genes were

208 predominantly represented by epithelial to mesenchymal transition, extracellular matrix

209 organization, and development processes (Figure 4e and Supplementary Table 4). In terms of

210 structural complexes, D8BDD2-C8- genes were specifically enriched in the endoplasmic reticulum (ER)

211 lumen and Golgi (Figure S4i). Interestingly, BDD2-C8 were localized in the ER and Golgi (Figure

212 S4j). In addition, higher expression of secretory genes in the D8BDD2-C8- cells implicated its active

213 ER-Golgi secretion pathway (Figure S4k). Depletion of these genes indeed resulted in the retention

214 of BDD2-C8 (Figures S4l-m). This indicates that BDD2-C8 may be actively effluxed from BJ and

215 the non-reprogrammed cells (D8 G1) but retained in the pluripotent cells and intermediate cells with

216 high reprogramming potential, due to the differential ER-Golgi secretion activities.

217 We next identified surface markers with differential expression among D8 subgroups to

218 enrich for the intermediate cells with varying reprogramming potentials (Supplementary Table 4).

219 Shortlisted surface markers displayed higher expression in D8 G1/G2 and D16- cells than D8 G3

220 and D16+ cells respectively (Figures 4f-g). Majority of them were abundantly enriched in the

221 parental BJ cells, except for CD201. Expression dynamics of the surface markers were validated by

222 time-course FACS analysis (Figure 4h). Further, D8 cells stained negatively for the surface markers

223 exhibited lower expression of mesenchymal markers but higher epithelial and pluripotency genes,

224 including the D8 G3 marker GDF3 (Figure 4i). Noteworthy, negatively stained D8 populations

225 gave rise to more TRA-1-60+ colonies, indicating the capacity of surface markers to isolate early

226 reprogrammed cells with high stemness feature (Figure 4j). We then examined the similarity of

227 cells sorted by BDD2-C8 and the identified surface markers. Indeed, D8BDD2-C8+ cells demonstrated

228 lower level of CD13, CD44, and CD201 (Figure 4k-l). Of note, difference in the CD201 protein 8

229 amount was subtler, which could be due to its inconsistent expression across the D8 subgroups (G1-

230 2 like) with BDD2-C8 (G2-3 like). Of note, co-staining of CD13 and CD44 markers showed

231 extensive overlaps across the time-points (Figures 4m and S4n). Surface markers were verified in

232 an alternative reprogramming of MSCs induced by Sendai viruses (Figure S4o-p). D8 sorted MSC

233 reprogramming cells demonstrated the similar expression trends as BJ reprogramming (Figures 4n

234 and S4q). Importantly, CD13- MSCs resulted in a remarkably higher reprogramming efficiency

235 with or without the aid of TGF-beta inhibition (Figure 4o). Collectively, the fluorescent dye and

236 surface markers established the technological platforms to enrich for the minority of intermediate

237 cells primed for successful reprogramming.

238 Refined classification of the intermediate population

239 To decipher the intermediate reprogramming cells, we prepared 10X libraries on D8 cells

240 sorted with CD13. Majority of the libraries passed the QC thresholds (Figure S5a). Expectedly,

241 libraries showed 2 distinct groups with differential CD13 expression (Figures 5a and S5b). Notably,

242 majority of the genes that were expressed highly in CD13+ cells were correspondingly expressed in

243 the D8BDD2-C8- cells and vice versa (Figure S5c). The libraries demonstrated 8 clusters. Clusters 5-8

244 were mainly comprised of CD13+ cells (Figures 5b and S5d). Consistently, CellNet analysis

245 showed that clusters 1-4 correlated with ESCs, whereas the other clusters to the fibroblast state

246 (Figure S5e). RCA corroborated the association of CD13+ cells to the MSCs and Fibroblast

247 lineages (resembling G1) (Figure 5c). Interestingly, among the CD13- cells, cluster 1 showed the

248 highest correlation score to the PSCs, indicating similarity to the D8 G3 cells (Figure 5c). Whereas,

249 cells of cluster 3 and 4 showed resemblance to both the MSCs and ESCs, albeit at a lower

250 significance than cluster 1 in terms of the ESCs (Figure 5c). On the other hand, cells of cluster 2

251 and 7 exhibited a transitional intermediate profile (Figure 5c). We next used MAGIC32 for pairwise

252 comparison between CD13 and GDF3. Interestingly, cells with lower CD13 levels exhibited higher

253 expression of GDF3 and NANOG, among which cluster 1 and 4 exhibited the highest GDF3

254 expression (Figures 5d-e and S5f). Next, to trace the trajectory of the CD13 sub-clusters, we

255 aggregated the CD13 sorted 10X libraries with the other timepoints and performed pseudotemporal

256 analysis. Remarkably, D8 CD13+ and CD13- cells were enriched at the distinct trajectory states

257 (Figure 5f). Cells of cluster 1 and 4 concentrated in the branch shared by D16+ cells. Notably, cells

258 of cluster 3 were found at the unsuccessful reprogramming branch, whereas cluster 2 cells were

259 scattered.

260 DGE analysis demonstrated that cluster 7 had unique expression trends among the CD13+

261 clusters, which associated with epidermis development, and I-KB/NF-KB signaling (Figures 5g-h).

262 On the other hand, cluster 5, 6 and 8 specific genes related to extracellular matrix organization and

263 collagen catabolic process (Figure 5h). cluster 1 and 4 specific genes related to cell division,

264 heterochromatin assembly, embryonic development, organ development of multiple lineages, and

265 MAPK cascade, suggesting that reprogramming cells of cluster 1 and 4 might adopt an open

266 chromatin structure, especially at genes crucial for multi-lineage development and differentiation.

267 Mathematical imputation showed an extensive correlation between CD13 and CD44 (Figures S5g-

268 h). Interestingly, we detected a group of cells which were low in CD13 but high in CD201,

269 representing the D8 G2-like intermediate cells belonging mostly to cluster 2 and 7 (Figures 5i, and

270 S5i). To substantiate their existence, we performed time-course co-staining using CD13 and CD201

271 antibodies. A significant number of intermediate cells were CD13-CD201+, and their proportion

272 increased as reprogramming advanced (Figures 5j and S5j). Furthermore, CD13-CD201+ cells

273 corresponded to higher BDD2-C8 staining signals than CD13+CD201+ cells (Figure S5k). Hence,

274 we hypothesized that dual sorting with CD13 and CD201 markers would allow us to enrich for

275 successfully reprogrammed early-intermediary cells with higher purity.

276 We thus categorized D8 cells into double negative (CD13-CD201-), double positive

277 (CD13+CD201+) and intermediate (CD13-CD201+) cells, which were then subjected to gene

278 measurement (Supplementary Table 5). CD13+CD201+ cells expressed fibroblast and

279 mesenchymal genes and genes associated with extracellular matrix and cell adhesion (Figures 5k-l).

280 On the contrary, CD13-CD201- cells expressed genes related to pluripotency, epithelial lineage, cell

281 division, neuronal differentiation, and stem cell population maintenance. CD13-CD201+ cells

282 exhibited an intermediate transcription profile (Figures 5k-l). In addition, genes highly expressed in

283 CD13+CD201+ cells were mostly enriched in the D16- but not D16+ cells, whereas the opposite

284 was observed for CD13-CD201- specific genes (Figure S5l). Notably, depletion of genes highly

285 expressed in the CD13+CD201+ population resulted in more reprogrammed colonies (Figure 5m).

286 Importantly, enrichment of CD13-CD201- population gave rise to the highest reprogramming

287 efficiency, in comparison with the CD13-CD201+ (intermediate) and CD13+CD201+ cells (lowest)

288 (Figure 5n). We validated the presence of these distinct D8 populations in an alternative

289 reprogramming of BJ cells using Sendai viruses (Figures S5m-o). Altogether, concurrent use of

290 CD13 and CD201 antibodies enable us to dissect the precise populations differentially poised for

291 successful reprogramming.

292 Regulatory networks of Transcription Factors in cellular reprogramming

293 Transcription Factors (TFs) define the cell-selective regulatory network underlying the

294 cellular identity and function33. However, the stage-specific core regulatory networks of the human

295 cellular reprogramming remain elusive. To this end, we performed DGE analysis for TFs across the

296 pseudotemporal states, which were then categorized as Early Silenced, Late Silenced, Transient,

297 Early Expressed and Late Expressed (Figures 6a and S6a, and Supplementary Table 6). Notably,

298 many TFs exhibited similar expression trends in the D8 RCA subgroups and the D8 sorted libraries.

299 Specifically, Early Silenced TFs (e.g. FOSL1, CREB3L1, AHRR, DRAP1 and ELL2) showed higher

300 expression in the D8 BDD2-C8- and CD13+CD201+ populations, whereas Late Silenced TFs

301 exhibited the opposite trends (Figures 6a and S6b). Majority of Transient TFs exhibited higher

302 expression in CD13+CD201+ and CD13-CD201+ populations, including lineage associated factors

303 namely HAND1 (mesoderm), ASXL3 and NEUROG2 (neuroectoderm) (Figures 6a and S6c).

304 Contrastingly, Early Expressed TFs adopted higher expression in the cells of CD13-CD201- and

305 CD13-CD201+ (Figures 6a and S6d). CD13-CD201- cells expressed the highest level of Late

306 Expressed TFs, such as PRDM14, DNMT3B and LHX6.

307 To investigate how the regulatory TFs accessed its genomic targets, we then analyzed time-

308 course scATAC-Seq libraries of reprogramming cells (Figure 1a). Both batches of libraries showed

309 similar promoter accessibility profiles (Figure S6e). We also observed diminished accessibility on

310 the fibroblast-specific DHS and increased accessibility on the pluripotency-specific DHS as

311 reprogramming progressed (Figure S6f). Next, we utilized chromVAR34 to identify the TFs

312 determining the variable epigenomes accessibility. Correlation of scATAC-Seq libraries among

313 themselves resulted in three major clusters. The early cells consisting mostly of BJ and D2 cells

314 clustered together (Cluster II), while D8, D16+ and H1 cells shared similar accessibility profile

315 (Cluster I). A third cluster composed mainly of D8 and D16- cells (Cluster III) (Figure 6b). of note,

316 FOSL1 and its partners, CEBPA, ZEB1, PAX6, SOX8, SOX10, POU5F1 and TEAD4 were found

317 to be the TFs contributing to the reprogramming heterogeneity (Figure 6c and Supplementary Table

318 6). TFs were then categorized to open starting from the intermediate stage (Early open) or the late

319 stage (Late open), open transiently at the intermediate stage (Transient open), and close starting

320 from the intermediate stages of reprogramming (Close) which were either homogenously or

321 heterogeneously open in the early cells (Figure 6d and 6e). Particularly, Close TFs belonged mostly

322 to the FOS-JUN-AP1 complex, such as FOSL1 and JDP2 (Figures 6f and S6g). Intriguingly, motifs

323 of lineage specifiers (Mesendoderm: GATA1, SOX8 and HNF4G; Ectoderm: PAX6, NRL and

324 RXR) were found to be accessible only in the intermediate reprogramming cells, but not the H1

325 hESCs (Figures 6d, 6g and S6h). This observation corroborated with the model of counteracting

326 lineage specification networks underlying the induction of pluripotency35,36. On the contrary, Early

327 Open TFs (e.g. TEAD4 and POU5F1) exhibited accessibility starting from the D8 reprogramming

328 cells, whilst Late Open TFs (e.g. FOXL1, TCF4, and YY2) demonstrated accessibility in D16+

329 cells and ESCs exclusively (Figures 6d, 6h-i, S6i-k). Of note, TFs of FOX family and YY1 were 12

330 previously reported to be important for reprogramming37–39. Independently, we used SCENIC

331 analysis to infer the interaction between TFs and their target genes. Corroborating with our earlier

332 results, Silenced and Close TFs showed decrease in their regulon activity as reprogramming

333 progressed, whereas majority of Expressed and Open TFs displayed the opposite dynamics (Figure

334 S6l). Likewise, regulon activity of the Transient TFs was observed only in the intermediate cells.

335 Together, these data represent the compendium of TFs which regulate the networks of downstream

336 key modulators in the cellular reprogramming process.

337 Identification of key regulators for the intermediate stage of reprogramming

338 In order to deduce TFs essential for the intermediate cells to acquire pluripotency, we

339 further sub-clustered the D8 scATAC-Seq libraries (Figures S7a-b). Intriguingly, the most variable

340 motifs of D8 cells belonged to the FOS-JUN-AP1 and TEAD families (Figure 7a and

341 Supplementary Table 7). Strikingly, D8 cells were either accessible for FOSL1-JUN-AP1 or

342 TEAD4 motif (Figures 7b-c). Of note, FOSL1 and TEAD4 displayed a contrasting expression

343 pattern and regulon activity during reprogramming (Figures 7d-g). In D8, FOSL1 and TEAD4 were

344 exclusively expressed in the CD13+ and CD13- cells (Figure 7h).

345 Given its expression and motif accessibility at the early stage of reprogramming, FOSL1

346 was hypothesized to act as a roadblock. To verify, reprogramming efficiency was assessed upon the

347 depletion of FOSL1 by siRNA, which showed no effect on cell proliferation and lasted for about 4

348 days (Figures S7c-e). Remarkably, depletion of FOSL1 at day 1, 2, 3, or 5 post-OSKM induction

349 resulted in an increased reprogramming efficiency (Figure 7i). Specificity of the FOSL1 siRNA

350 construct was validated using a mutant construct which showed no effect (Figures S7f-g). Depletion

351 of FOSL1 in an alternative Sendai virus reprogramming reproduced the phenotypic change (Figures

352 S7h-i). Conversely, ectopic expression induced a drastic reduction in the number of reprogrammed

353 colonies (Figure 7j). Noteworthy, high reprogramming propensity of CD13- cells was negated by

354 the elevated FOSL1 level (Figure 7k). 13

355 Contrastingly, we posit that TEAD4 could serve as an effector. Indeed, depletion of TEAD4

356 resulted in the reduced number of reprogrammed colonies (Figure 7l). Specificity of siTEAD4 was

357 affirmed by the mutant construct with no phenotypic change (Figures S7j-k). Knock-down effect of

358 siTEAD4 lasted for around 5 days (Figure S7l). Interestingly, when knock-down was performed on

359 D5 cells, TEAD4 expression did not restore, which could be due to the perpetuations of the non-

360 reprogrammed state introduced by siTEAD4 (Figure S7m). Notably, depletion of TEAD4 only from

361 day 5 onwards induced the decreased reprogramming efficiency (Figure 7l). This established the

362 vital role of TEAD4 at the intermediate-late stages of reprogramming. In contrast, overexpression

363 of TEAD4 resulted in a significant increase in the number of reprogrammed colonies (Figure 7m).

364 Importantly, depletion of TEAD4 revoked the reprogramming potential of D8 CD13- cells (Figure

365 7n). Collectively, these analyses illustrate that the pivot from FOSL1 to TEAD4-directed regulatory

366 network is essential for successful reprogramming.

367 Mechanistic roles of FOSL1 and TEAD4 in cellular reprogramming

368 To find the direct targets of FOSL1, we prepared ChIP-Seq libraries for D8 cells, which

369 demonstrated the expected genomic distribution profile and enriched with FOSL1 motif and its

370 regulatory partners (Figures S8a-c). We also investigated the genomic binding profile of TEAD4 in

371 D8 cells and CD13 sorted D8 cells (Figures S8d-e). Majority of the D8 TEAD4 bound sites were

372 shared by both CD13+ and CD13- cells (Figures S8f). 1.7-fold higher numbers of TEAD4 bound

373 loci were detected in the CD13- than CD13+ cells (18550 vs. 10986 sites). In addition, CD13-

374 specific sites showed greater enrichment of TEAD4 motif and exclusive enrichment of pluripotency

375 associated OCT4-SOX2-TCF-NANOG motif, indicating the differential regulatory role of TEAD4

376 (Figures S8g).

377 Consistent with their contrasting roles, majority of loci highly enriched with FOSL1 were

378 distinctive from that with TEAD4 (Figure 8a). We next clustered BJ, D16- and D16+ scATAC-Seq

379 libraries, based on the accessibility of FOSL1 and TEAD4 bound sites (Figure 8b). Notably, FOSL1 14

380 specific sites exhibited higher accessibility in BJ and D16- cells, whereas CD13- specific and CD13

381 common TEAD4 bound sites were mostly accessible in D16+ cells (Figures 8b-c and S8h-i). these

382 differential accessible sites were annotated as the functional FOSL1 and TEAD4 targets

383 (Supplementary Table 8). Similar to the motif enrichment pattern, most of the D8 cells were either

384 accessible for FOSL1 (“FOSL1 ChIP only” cells) or CD13- TEAD4 bound sites (“TEAD4 ChIP

385 only” cells) (Figures 8d-e and S8k-l). We next asked if their binding has any consequence to the

386 transcription of target genes. To this end, we analyzed the expression of functional FOSL1 and

387 TEAD4 targets across the D8 CD13-CD201 sorted cells. Remarkably, majority of the D8 FOSL1

388 targets (e.g. TGFBR2, SMAD3, and COL5/7/21A1) were expressed highly in the CD13+CD201+

389 cells (Figure 8f). In contrast, D8 CD13-CD201- cells demonstrated high expression of the TEAD4

390 targets, including key pluripotent genes such as DNMT3B, LIN28A, SOX2, and PODXL which

391 codes for TRA-1-60 (Figure 8g). This was further substantiated at single-cell resolution using the

392 coupled NMF analysis of D8 scRNA-Seq and scATAC-Seq libraries, by which regulatory

393 connectivity between the accessible chromatin regions and expression of target genes were

394 established (Figure S8m). Notably, cluster 1 composed of “TEAD4 ChIP only” cells (scATAC-Seq)

395 and D8 RCA G3 cells (scRNA-Seq), whilst cluster 2 comprised of “FOSL1 ChIP only” cells

396 (scATAC-Seq) and D8 RCA G1 (scRNA-Seq) cells. Differential analysis demonstrated that

397 TEAD4 and its targets, such as TET1 and CDH1, were highly accessible and expressed in the

398 cluster 2 cells, whereas FOSL1 and its targets, such as MMP2 and SMAD3, displayed the opposite

399 trends (Figures S8m-n). Besides, interactome analysis revealed that cluster 1 genes associated with

400 splicing process, whereas cluster 2 genes related to ER-Golgi transport and extracellular matrix

401 organization, including FOSL1 targets MMP2 and several collagen genes (Figure S8o). More

402 importantly, downstream targets of FOSL1 and TEAD4 were themselves modulators of

403 reprogramming. For instance, knock-down of FOSL1 bound genes, MMP2 and SMAD3, resulted in

404 higher numbers of the reprogrammed colonies (Figure 8h). Conversely, depletion of TEAD4 targets,

405 PRDM14 and SOX2, showed the opposite effect (Figure 8i).

406 Taken together, we present the single-cell roadmap of the human cellular reprogramming

407 process, which reveals the diverse cell-fate trajectory of individual reprogramming cells (Figure 8j).

408 D2 cells consist of four subgroups, out of which CDK1+ cells showed greater propensity for

409 reprogramming. Among the three subgroups of D8 cells, G1 represents the unsuccessful

410 reprogramming cells, whereas G3 cells with GDF3 expression are highly primed for successful

411 reprogramming. G2 is the intermediary group between G1 and G3. In-house developed fluorescent

412 probe (BDD2-C8) and the identified surface markers (CD13, CD44 and CD201), enables the

413 segregation of the heterogeneous population based on their reprogramming potential. Moreover,

414 TFs analysis reveals the stage-specific regulatory networks of reprogramming. Importantly, we

415 describe the crucial switch from a FOSL1 to a TEAD4-centric expression which collectively

416 regulate genomic accessibility, cell-lineage transcription program, and network of functional

417 downstream modulators favoring the acquisition of the pluripotent state.

418

419 DISCUSSION

420 Heterogeneity of Cellular Reprogramming

421 Due to the inherent heterogeneity, Single-cell NGS techniques are more suited to

422 characterize the molecular and epigenetics signatures of reprogramming cells with diverse

423 trajectories. Several studies described the mouse reprogramming process at single-cell resolution40–

424 42. However, there have been reports for extensive differences between the mouse and human

425 reprogramming in terms of kinetics, modulators involved, and the molecular nature of the generated

426 iPSCs. In addition, this is the first study presenting a comprehensive human reprogramming

427 roadmap by integrating the transcriptomic changes and the alteration of accessible epigenetic

428 regions at single-cell resolution.

429 Our analyses also identify an early reprogramming marker GDF3, which marks the

430 intermediate cells primed for successful reprogramming. GDF3 was previously shown to be

431 expressed in pluripotent stem cells and played a role in regulating cell fate via BMP signaling

432 inhibition43. We also develop a fluorescent probe, BDD2-C8, and identify a panel of cell surface

433 markers, namely CD13, CD44 and CD201, to distinguish and characterize the diverse sub-

434 populations of the intermediate reprogramming cells. Interestingly, CD44 sorting was previously

435 reported as a mean to isolate reprogrammed cells in the mouse system44. Noteworthy, combinatorial

436 use of the surface markers enables a more refined segregation. The toolkits to decipher the

437 intermediate cells with different stemness capacity, will help deepen our understanding of the

438 mechanisms of reprogramming process. Additionally, the ability to enrich for early reprogramming

439 cells will help increase the success rate of iPSC generation from the cell lines or patient-derived

440 primary cells which are refractory to reprogramming.

441 Transcription Factors Contribute to the Heterogeneity of Cellular Reprogramming

442 Facilitated by the integrative analysis of transcriptomic and chromatin accessibility profiles,

443 TFs contributing to the heterogeneous reprogramming trajectories are identified. Accessible regions

444 with the motifs of FOS-JUN-AP1 and CEBPA are rapidly closed upon induction, which were

445 reported to act as repressors in mouse reprogramming45,46 (Figure 6). An earlier report showed that

446 FOSL1 lost many of its binding as early as day 2 of mouse reprogramming46. Our study reveals that,

447 in the human system, FOSL1 regulates myriad of genes which serve as barriers of reprogramming,

448 including MMP2, SMAD3, TGFBR2, and collagen genes. Strikingly, chromatin regions with the

449 motifs of lineage TFs are open in the intermediate cells, which might be due to the induction of ME

450 and ECT lineages driven by POU5F1 and SOX247. This is further supported by the replacement of

451 POU5F1 and SOX2 with the ME and ECT lineage specifiers, for both mouse and human

452 reprogramming35,36. We unravel for the first time the transitory epigenetic accessibility directed by

453 the lineage TFs, which contribute extensively to the diverse cell fate potentials observed during

454 cellular reprogramming.

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556

557 ACKNOWLEDGMENTS

558 We are grateful for Ahad Khalilnezhad for technical assistance and Lin Yang and Samantha Seah

559 for helpful discussion. H.L. is supported by Glenn Foundation for Medical Research, Mayo Clinic

560 Center for Biomedical Discovery and Mayo Clinic Cancer Center. Y-H.L. is supported by the [NRF

561 Investigatorship award -NRFI2018-02] and [JCO Development Programme Grant - 1534n00153]

562 grants. Y-H.L. and L-F.Z. are supported by the Singapore National Research Foundation under its

563 Cooperative Basic Research Grant administered by the Singapore Ministry of Health’s National

564 Medical Research Council [NMRC/CBRG/0092/2015]. We are grateful to the Biomedical Research

565 Council, Agency for Science, Technology and Research, Singapore for research funding.

566

567 AUTHOR CONTRIBUTIONS

568 Contribution: Q.R.X, C.E.F designed and performed research, analyzed data, and wrote the

569 paper; P.G, Y.S.C, C.X.D.T, T.W designed and conducted research; N.Y.K, S.S, Y.T.C, J.X, J.C,

570 H.L, L.F.Z analyzed data; and Y.H.L. designed research, analyzed data, and wrote the paper.

571

572 AUTHOR INFORMATION

573 The authors declare no competing financial interests.

574

575 FIGURE LEGENDS

576 Figure 1. Schematic of the single-cell systems used for de-convoluting the heterogeneity in

577 human cellular reprogramming

578 (a) Overview of the prepared single-cell NGS libraries at the indicated time-points of the human

579 cellular reprogramming. Two single-cell platforms were utilized for the study. Microfluidics

580 platform was used to prepare 439 single cell RNA-Seq and 891 single cell ATAC-Seq libraries

581 (Duplicates). 10x Genomics platform provided us with an additional 32138 cells for scRNA-Seq

582 analysis. (b) Quality control of Microfluidics-capture based scRNA-Seq libraries. Dotplot

583 demonstrates the exon mapping percentage (X-axis) of each scRNA-Seq libraries, along with its

584 corresponding detected gene rates (Y-axis). Axis crosses each other at the cutoff values that filter

585 the libraries. Blue dots represent libraries that passed the QC filters. (c) Average enrichment of

586 scRNA-Seq libraries over genebodies. (d) t-SNE plot of the prepared 10x scRNA-Seq libraries

587 based on total cellular transcriptomes. (e-f) Super-imposition of the single-cell expression levels of

588 MET genes: ZEB1 and EPCAM (e), and fibroblast and pluripotent genes: COL1A1 and NANOG (f),

589 on the tSNE plot. The expression ranges from no expression (grey) to high expression (red). (g)

590 Quality control of scATAC-Seq libraries. Dotplot demonstrating the library size (X-axis) of each

591 scATAC-Seq library, along with its corresponding contribution to its respective time-point’s HARs

592 (Y-axis). Red dots represent the cells that pass the QC filters. (h) Average enrichment profile of a

593 D16+ scATAC-Seq library around Transcription Start Sites (TSS) of the genome with a window of

594 -3K to 3K. Y-axis denotes the average normalized read counts of the library over the indicated

595 region in the genome (x-axis). (i) Histograms of insert size metric of a D16+ scATAC-Seq library

596 revealing a nucleosomal pattern, which is characteristic of a good ATAC-Seq library.

597 Figure 2. Identification of diverse reprogramming subgroups

598 (a-c) RCA clustering of D2 (a), D8 (b), and D16+ (c) cells based on the profile of the expressed

599 genes. The PCAs show subgroups of reprogramming cells at individual time points. Each color

600 represents a subgroup. (d) Heatmap showing dynamics of the genes differentially expressed among

601 4 subgroups of D2, 3 subgroups of D8, and 2 subgroups of D16+ cells, across the reprogramming

602 process. Color represents the expression level, ranging from dark blue (low) to dark red (high). The

603 expression values are Log10 (FPKM+1). The color code on top represents the time points (above)

604 and their respective subgroups (below). (e) Bar charts demonstrating the expression pattern of D2

605 (left), D8 (middle), and D16+ (right) subgroup specific genes. Color represents the expression level.

606 X-axis represents the percentage of cells with the expression within the indicated range. Red dotted 22

607 boxes highlight the subgroups with high expression of the respective gene. (f) Box plots showing

608 the single cell expression of the differentially expressed genes CDK1 (D2), GDF3 (D8), MMP2

609 (D16+), and LIN28A (D16+) across all the time points and their respective subgroups. Lines in the

610 box represent the median expression in the respective subgroups or time points. The expression

611 values are Log10 (FPKM+1). (g) Confusion matrix of the scRNA-seq libraries of all time points,

612 using Random Forest algorithm. Color represents the number of libraries from each time point

613 predicted to be similar to the indicated subgroups of D8. Scale ranges from dark blue (low number)

614 to dark red (high number).

615 Figure 3. Trajectories of cellular reprogramming

616 (a) Trajectory of reprogramming cells identified from the 10x scRNA-Seq libraries based on

617 DDRTree dimension reduction. Color represents the time points. (b) Pseudotime calculation based

618 on the DDRTree trajectory. Color indicates pseudotime, ranging from dark blue (early) to light blue

619 (late). The plot shows four branching events. “+succ” and “-succ” represents the successful and

620 unsuccessful braches. (c) Stacked columns indicating the percentage of cells belonging to the

621 respective time-points in the reprogramming trajectory states. Color represents the time points. (d)

622 Super-imposition of D8 subgroups (left) and D16+ subgroups (right) on the trajectory of

623 reprogramming. Color represents the subgroups. (e) Stacked columns revealing the percentage of

624 cells of the respective D8 subgroups in the indicated reprogramming trajectory states. Colors

625 represent the subgroups of D8 and grey color indicates cells of the other time points. (f) Super-

626 imposition of the expression of D8 subgroup genes (RFC3, GDF3) and D16+ subgroup genes

627 (NANOG, MMP2 and LIN28A) on the reprogramming trajectories. Expression ranges from purple

628 (low) to yellow (high). (g-h) GO analysis of the differentially expressed genes associated with the

629 unsuccessful (g) and successful (h) reprogramming branches. The enrichment score ranges from

630 white (no) to red (high). The braches are labelled in Fig.3b.

631 Figure 4. Identification of chemical dyes and surface markers for early-intermediate

632 reprogramming cells

633 (a) Quantification of TRA-1-60+ colonies yielded from D8 cells sorted with BDD2-C8 (top).

634 Representative images are shown below. n=3; error bar indicates SD. (b) Gene expression in the D8

635 BDD2-C8+ and BDD2-C8- cells, measured by single cell qRT-PCR. Student t-test (2-tails) was

636 applied (p<0.05). (c) RCA plot of D8, D8BDD2-C8+ and D8BDD2-C8- cells. (d) Expression heatmap of

637 the D8 differential genes in D8BDD2-C8+ and D8BDD2-C8- cells. Color code on top represents the time

638 points (above) and the subgroups or sorted cells (below). (e) GO terms enriched by the differential

639 genes of D8BDD2-C8+ and D8BDD2-C8- cells. (f) Heatmap showing the expression dynamics of the

640 surface markers. Color code on top represents the time point and their respective subgroups. (g)

641 Boxplots showing the surface markers expression across the time points and their respective

642 subgroups. Lines in the box represent the median expression. (h) Stacked histograms (top) showing

643 the fluorescence intensity (X-axis) of the surface markers. Red dotted boxes highlight the positively

644 stained cells. Quantifications are shown below. (i) Barchart exhibiting the relative expression levels

645 in the D8 sorted cells, normalized to that of D8 CD44+ cells. n=2; error bar indicates SD. (j)

646 Quantification of TRA-1-60+ colonies yielded from the D8 sorted cells. Representative images are

647 shown below. n=2; error bar indicates SD. (k) Boxplots showing the surface marker expression in

648 the D8BDD2-C8+ and D8BDD2-C8- cells. Lines represent the median expression. (l) Overlaid histograms

649 showing the surface marker staining intensity in the BDD2-C8+ and BDD2-C8- cells. Red dotted

650 boxes highlight the positively stained cells. The numbers on top indicate the percentage of

651 positively stained cells. (m) Barchart showing the distribution of co-staining signals of CD13 and

652 CD44 in the cells of various reprogramming time points and cell lines. (n) Barcharts exhibiting the

653 relative expression of the collagen/ mesenchymal genes (top) and pluripotent genes (bottom) in the

654 D8 CD13 sorted cells. n=2; error bar indicates SD. (o) Quantification of TRA-1-60+ colonies

655 yielded from D8 CD13 sorted cells (top). Representative images are shown below. n=2; error bar

656 indicates SD.

657 Figure 5. Refined classification and enrichment of early-intermediate reprogramming cells

658 (a) t-SNE plot generated by 10X libraries of D8 CD13 sorted cells. (b) t-SNE plot showing the

659 clusters among the CD13+ and CD13- cells. (c) RCA heatmap demonstrating the clustering of

660 CD13 sorted cells (column) based on their correlation to the cells of different lineages (row). Color

661 code on top indicates the CD13 antigen profile (below) and clusters (above). (d) MAGIC plot

662 showing the correlative expression of CD13 and GDF3 in the D8 CD13-sorted 10x libraries. Color

663 represents the expression level of NANOG. (e) Violin plot demonstrating the expression of GDF3

664 across the identified clusters. (f) Top: Reprogramming trajectory constructed by the 10X scRNA-

665 Seq libraries of various time points and the D8 CD13 sorted cells. Bottom: Super-imposition of

666 CD13 clusters on the reprogramming trajectory. (g) Heatmap showing the differentially expressed

667 genes of CD13 clusters. Genes highlighted in orange were expressed higher in D8 G2 and G3 than

668 G1. (h) Barcharts showing the GO terms enriched by the genes highly expressed in the indicated

669 CD13 clusters. (i) MAGIC plot showing the correlative expression of CD13 and CD201 in the

670 CD13 10X libraries. Color represents the expression level of GDF3. (j) Barchart showing the

671 distribution of co-staining signals across the various reprogramming time points and cell lines. (k)

672 Barchart exhibiting the relative gene expression in the D8 dual antibody sorted cells, normalized to

673 that in CD13+CD201+ cells. n=2; error bar indicates SD. (l) Left: Heatmap showing the

674 differentially expressed genes among the D8 dual antibody sorted cells. GO terms (Middle)

675 enriched by the differentially expressed genes, with the enrichment values and the related genes

676 indicated on the right. (m) Bar chart demonstrating the number of normalized TRA-1-60+ colonies

677 (Y-axis) upon the knock-down of genes highly expressed in CD13+ CD201+ or CD13-CD201+

678 cells, at day 5 of reprogramming. Representative images are shown above. n=3. Error bar indicates

679 SD. (n) Quantification of TRA-1-60+ colonies yielded from the D8 dual antibody sorted cells.

680 Representative images are shown above. n=2; error bar indicates SD.

681 Figure 6. Transcription factors critical for reprogramming

682 (a) Heatmap showing the expression dynamics of the transcription factors across the pseudotime

683 states. Color represents the expression level, ranging from purple (low) to yellow (high). Color code

684 on top represents the pseudotime states. Transcription factors were classified to 5 categories

685 according to the states when they were silenced or expressed. The representative TFs of each

686 category are listed on the right. (b) Correlation heatmap of scATAC-Seq libraries based on the

687 calculated JASPAR motifs deviations in the HARs peaks. Color represents the correlation value,

688 ranging from blue (no) to red (high). Side color bar indicates the time-point to which each scATAC-

689 Seq library belongs. (c) Plot indicating the significantly variable motifs in terms of accessibility

690 from the scATAC-Seq libraries. Y-axis represents the variability score assigned to each JASPAR

691 motif whereas the X-axis represents the motif rank. (d) Heatmap of scATAC-Seq libraries based on

692 the deviation scores of the significantly variable JASPAR motif. Color indicates the accessibility

693 level, ranging from dark blue (no enrichment) to dark red (high enrichment). Color code on top

694 represents the time points. Motifs were classified to 3 major types according to the dynamics of

695 accessibility across the time points. (e) t-SNE plot of scATAC-Seq libraries based on the deviation

696 scores of JASPAR motifs. (f-i) Super-imposition of motif enrichment scores for Close motif-

697 FOSL1 and CEBPA (f), Transient motif-GATA1:TAL1 (g), Open motif: Early Open-TEAD4 (h);

698 Late Open- FOXL1 (i) on the scATAC-Seq tSNE plot. Color indicates the accessibility level and

699 ranges from dark blue (no enrichment) to dark red (high enrichment).

700 Figure 7. Transcription factors contributing to the heterogeneity in chromatin accessibility of

701 the intermediate reprogramming cells

702 (a) Plot indicating the significantly variable motifs in terms of accessibility among D8 cells. Y-axis

703 represents the variability score assigned to each JASPAR motif whereas X-axis represents the motif

704 rank. (b) Heatmap showing clustering of D8 scATAC-Seq libraries based on the deviations scores

705 of the significantly variable JASPAR motif. (c) Super-imposition of motif enrichment scores for

706 FOSL1 and TEAD4 on the D8 scATAC-Seq tSNE plot. (d) Super-imposition of FOSL1 and TEAD4

707 expression on the reprogramming trajectory displayed in Figure 3a. (e) Dotplots indicating the 26

708 expression of FOSL1 and TEAD4 along the pseudotime. Smooth lines represent the mean

709 expression level at each pseudotime, regardless of the state. (f) Top: MAGIC plot showing

710 correlative expression of FOSL1 and TEAD4 in the 10X libraries. Bottom: Super-imposition of

711 GDF3 expression on the magic plot. (g) Top: tSNE plot based on the regulon activity matrix

712 generated by SCENIC. Bottom: Activity of FOSL1 and TEAD4 regulons across the time-points. (h)

713 Super-imposition of FOSL1 and TEAD4 expression on the D8 CD13 sorted tSNE plot. (i) Bar chart

714 demonstrating the number of normalized TRA-1-60+ colonies upon the knock-down of FOSL1 at

715 the indicated time-points of reprogramming. Representative images are shown below, n=3. Error

716 bar indicates SD. (j) Bar chart demonstrating the quantification of TRA-1-60+ colonies upon the

717 overexpression of FOSL1 at D5. Representative images are shown below, n=3. Error bar indicates

718 SD. (k) Bar chart demonstrating the quantification of TRA-1-60+ colonies yielded from D8 CD13-

719 cells with FOSL1 overexpression. Representative images are shown below, n=3. Error bar indicates

720 SD. (l) Bar chart demonstrating the number of normalized TRA-1-60+ colonies upon the knock-

721 down of TEAD4 at the indicated time-points of reprogramming. Representative images are shown

722 below, n=2. Error bar indicates SD. (m) Bar chart demonstrating the quantification of TRA-1-60+

723 colonies upon the overexpression of TEAD4. Representative images are shown below, n=3. Error

724 bar indicates SD. (n) Bar chart demonstrating the number of TRA-1-60+ colonies yielded from D8

725 CD13- cells with TEAD4 depletion. Representative images are shown below, n=3. Error bar

726 indicates SD.

727 Figure 8. Mechanistic role of FOSL1 and TEAD4 during reprogramming

728 (a) Heatmaps exhibiting the D8 FOSL1 and D8 TEAD4 ChIP-Seq enrichment over merged binding

729 loci of both these factors. (b) Left: t-SNE clustering of BJ, D16+, and D16- scATAC-Seq libraries

730 based on the deviation scores of common and specific sites identified from D8 FOSL1 ChIP-seq,

731 D8 CD13- TEAD4 ChIP-seq, and D8 CD13+ TEAD4 ChIP-seq. Right: Super-imposition of

732 deviation score for FOSL1 specific bound sites and TEAD4 CD13- specific bound sites on the

733 scATAC-Seq t-SNE plot. Color indicates the accessibility level. (c) MA plots of scATAC-Seq 27

734 revealing the differentially accessible FOSL1 bound sites (left) and CD13- specific TEAD4 bound

735 sites (right) between BJ and D16+ cells. X-axis denotes the mean of normalized counts in BJ cells.

736 Red dots denote the sites with significant accessibility changes. (d) Super-imposition of enrichment

737 scores for FOSL1 specific bound sites (left) and CD13- TEAD4 specific bound sites (right) on the

738 D8 scATAC-Seq tSNE plot. Color indicates the accessibility leve. (e) UCSC screenshots

739 illustrating the chromatin accessibility of FOSL1bound genes (MMP2 and SMAD3) and TEAD4

740 CD13- bound sites (TET1 and RFC3) in D8 “FOSL1 ChIP only” and D8 “TEAD4 ChIP only” cells.

741 The differentially accessible sites with highlighted with dotted rectangles. (f-g) Expression heatmap

742 of the differentially accessible genes bound by FOSL1 (f) in D8 and TEAD4 in D8 CD13- cells (g),

743 among the D8 dual antibody sorted cells. (h-i) Bar chart demonstrating the number of TRA-1-60+

744 colonies upon knock-down of FOSL1 targets (h) and TEAD4 targets (i) at D5. Representative

745 images are shown below. n=3. Error bar indicates SD. (j) Proposed model of the study.

20 BJ BJ scRNA-seq scATAC-seq D2 D8 10xGenomics Microfluidics-capture 0 D12

Oil tSNE2 D16- Day 2 -20 D16+

Cell Oil -40 Day 8 33468 cells -40 -20 0 20 40 tSNE1 e ZEB1 EPCAM Day 12 Enrichment of early-intermediate cells Transcription Factors

Surface markers Chemical screen Accessibility & ChIP-seq 25

Day 16 0 High tSNE2

-25

TRA-1-60- TRA-1-60+ Low

-25 0 25 -25 0 25 tSNE1 bc f COL1A1 NANOG 60 Enrichment over genebodies 1 50 0.8 25 40 25

30 0.6 0 High

20 0.4 tSNE2 20 40 60 80 100 120

Detected gene rate 10 0.2 -25 0 0 Low Exon mapping rate 0 20 40 60 80 100 -25 0 25 -25 0 25 gh i tSNE1

1200 70 D16+(No.52) D16+(No.52) 1 60 1000 0.8 50 800

40 0.6 600 RPM 30 400 0.4 Read Count % in HARs 20 0.2 200 2310 4 567 0 0 -3000 -1500 0 1500 3000 0 200 400 600 800 1000 Distance to TSS (bp) Insert-size (bp) Library size (Log10 )

Figure 1 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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-NC 4.0 International license. a b c D2 D8 D16+ 4 3 1 0 1 G1 G1 PC2 PC2 -1 G2 PC2 G1 G2 G3 -4 -1 G2 G3 G4 -3 -3 -8 -6-2 2 6 -5 0 5 -10 -5 0 PC1 PC1 PC1 d BJ D2 D8 D16- D16+ G1 G2 G3 G4 G1 G2 G3 G1 G2 Time points Subgroups ERBB3 GAA WNT1 CDC20 CDK1 UBE2C FOXF1 expressed FOSL1 MBD3 FOS D2 differentially D2 differentially ID1 ID1 JUNB LUM CARM1 PLAU GDF3 SNAI2 ENG TFAP2C FBLN1 TH TRIM32 COL1A1 CXADR COL1A1 TGFBR2 COL6A3 STRA6 expressed BMP1 CDKN2A D8 differentially D8 differentially COL7A1 EMP1 IGFBP5 MMP2 RUNX1 TGFBI CDK1 TNC CDH1 WNT5A CDC6 ZEB1 CDC73 DPPA4 EPCAM NASP JARID2 KRT7 expressed LIN28A NANOG 4

D16+ differentially D16+ differentially NODAL ORC6 POLR3K 2 RNASEH2A (FPKM+1)

SETD6 10 TEAD4 0 WBP11 Log ZSCAN10 HNRNPA1 SNRPD1 e g 020 0% 50% 100% 0% 50% 100% 0% 50% 100% BJ D2 D8 D16- D16+ D2G1 D16- D8G1 D2G2 D8 G1 60 59 39 64 16 CDK1 GDF3 D8G2 MMP2 D16+G1 D2G3 D8G3 D16+G2 D2G4 D8 G2 15 15 36 0 4 0% 50% 100% 0% 50% 100% 0% 50% 100% D2G1 D16- D8 G3 1013040 D8G1 D2G2 LIN28A ERBB3 RFC3 D8G2 D16+G1 D2G3 Predicted No. D8G3 D16+G2 02040 D2G4

f CDK1 GDF3 MMP2 LIN28A 4 4 3 3

3 3 2 2

2 2 (FPKM+1) 10 1 1

Log 1 1

0 0 0 0 BJ BJ BJ BJ D2 D2 D2 D2 D8 D8 D8 D8 D16- D16- D16- D16- D16+ D16+ D16+ D16+

Figure 2 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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-NC 4.0 International license. a b Pseudotime c

BJ D2 D8 D12 D16- D16+ 02040 100%

20 20 80% BJ D2 10 9 10 60% D8 +succ 4 +succ 7 -succ 3 D12 -succ 40% PC2 2 PC2 +succ 4 1 -succ -succ 8 D16- 0 5 0 2 +succ 3 6 20% D16+

1 -10 -10 0% -20 -10 0 10 -20 -10 0 10

PC1 PC1 State 1 State 2 State 3 State 4 State 5 State 6 State 7 State 8 State 9 d e

100% D8 G1 D8 G2 D8 G3 D16+ G1 D16+ G2 20 15 80% 15 D8 G1 10 60% D8 G2 10 D8 G3 5 Others 5 40% PC2 PC2 0 0 20%

-5 -5 0%

-20 -10 0 10 -10 0 10 PC1 PC1 State 1 State 2 State 3 State 4 State 5 State 6 State 7 State 8 State 9 f RFC3 GDF3 NANOG MMP2 LIN28A 20

high 10 (value+0.1) 10 PC2 0 Log Low

-10 -20 -10 0 10 -20 -10 0 10 -20 -10 0 10 -20 -10 0 10 -20 -10 0 10

PC1

g Unsuccessful branches h Successful branches -Log (P value) -Log (P value) 10 10 Branch point 20 36 Branch point 20 36 134 134 Cell adhesion Cell division Extracellular matrix organization Cell proliferation Heart development DNA replication Cytoskeleton organization Chromosome organization Cardiac septum morphogenesis Extracellular matrix organization Kidney development Collagen catabolic process Angiogenesis Cell adhesion Positive regulation of osteoblast differentiation Angiogenesis Glomerular visceral epithelial cell development Endothelial cell migration +ve. reg of canonical Wnt signaling pathway Skeletal system development Cell division Epidermis development Cell proliferation mRNA splicing, via spliceosome DNA damage response, detection of DNA damage

Figure 3 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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 a b under aCC-BY-NC 4.0 International license. c D8 FACS sort, D21 assay

12 BDD2-C8+BDD2-C8+ BDD2-C8- SALL4 DNMT3B 4 D8 BDD2-C8+ 8 RFC3 D8 BDD2-C8- genes

Pluripotent CDH1

4 PC2 D8G1 WNT5A 0 D8G2 SNAI2 D8G3 0 CD44 No. of TRA-1-60+ colonies No. of PLAUR -4

BDD2-C8- BDD2-C8+ -chymal genes D8 D8 Somatic/ Mesen Log2 expression -5 015 0 0 Low High PC1

d e f BJ D2D8 D16- D16+

D8 BDD2-C8- D8 BDD2-C8+ G1 G2 G3 G1 G2 G3 G4 G1 G2 G3 G1 G2 BDD2-C8- BDD2-C8+ CD13 1 D8 D8 CD44 Embryo development Regulation of transcription involved in CD59 G1/S transition of mitotic cell cycle CD201 0 Cellular response to cadmium ion Per row normalized Stem cell population maintenance g CD13 CD44 CD201 Epithelial- Mesenchymal Transition 2.5 3 Extracellular matrix organization 2 3 2 Inflammatory response 1.5 2

KRAS Signalling (FPKM+1) 1 10 1 1

D8 differentially expressed D8 differentially Response to hypoxia

Log 0.5 Cell-cell adhesion 0 0 0 Heart development BJ BJ BJ D2 D2 D2 D8 D8 D8 D16- D16- D16- D16+ D16+ D16+

-Log10 (p value) Log (FPKM+1) i 10 0 20 CD13+ CD44+ CD201+ 3.5 042 CD13- CD44- CD201- ** ** * 3 ** ** *** h CD13 CD44 CD201 2.5 ** ** ** * * * * * ** 2 * * * * ** * ** H1 1.5 * ** 1 D12 0.5 Relative expression D10 0

D8 ZEB1 ZEB2 CDH1 GDF3 SNAI1 SNAI2 LIN28A EPCAM NANOG POU5F1 D6 j 75 25 75 D4 m 60 20 60 Percentage (%) 0 20406080100 D2 45 15 45 H1 BJ D12 30 10 30 D8 01103 104 105 0103 104 105 0 03 104 105 5 15 100 CD13CD44 CD201 15 D4 80 D2 No. of TRA-1-60+ colonies No. of 0 0 0 60 CD13+ CD13- CD44+ CD44- CD201+ CD201- BJ 40 20 CD13+CD44+ CD13-CD44+

% of +ve cells 0 CD13+CD44- CD13-CD44- BJ BJ BJ D2 D4 D6 D8 H1 D2 D4 D6 D8 H1 D2 D4 D6 D8 H1 D10 D12 D10 D12 D10 D12

k CD13 CD44 CD201 200 250 200 n o 400 D8 Sendai repro (MSC) 150 D8 Sendai repro (MSC) 150 CD13+ CD13- 1.2 100 1000 200 100 FPKM 0.9 50 50 800 0.6 0 0 0 600 D8 BDD2-C8- D8 BDD2-C8+ D8 BDD2-C8- D8 BDD2-C8+ D8 BDD2-C8- D8 BDD2-C8+ 0.3 400 l Relative expression 0 Top 10% BDD2-C8 Bottom 10% BDD2-C8 200

SNAI1 TRA-1-60+ colonies No. of 15.2% 13.6% 79.8% 60 COL1A1 COL6A3 GAPDH 0 51.5% 52.9% 87.3% 50 CD13+ CD13- CD13+ CD13- 40 +A83-01 +A83-01

Count 30 20 10 Relative expression 0 103 104 105 0 103 104 105 0 103 104 105 0 CD13 CD44 CD201 GDF3 TEAD4 SALL4 LIN28A NANOG DNMT3B Figure 4 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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-NC 4.0 International license. abc d Correlation value NANOG CD13+ CD13- 1 2 3 4 5 6 7 8 00.20.1 0.3 40 40 Low high 0.6

20 20 Clusters CD13 MSC_Fetal Liver 0.4 MSC_Fetal Blood 0 0 MSC_Fetal Bone Marrow Fibroblast Foreskin GDF3 tSNE 2 tSNE 2 MSC MSC 0.2 -20 MSC -20 ESC iPSC ESC ESC ESC 0 -40 -40 -50 -25 0 25 ESC -50 -25 0 25 5 6 7 8 732 4 1Clusters 00.511.52 tSNE 1 tSNE 1 (G1) (G2) (G2) (G3) CD13

egGDF3 CD13 Clusters 8 3 7 6 5 2 4 High

3 UMI UMI 1 Low 2

0 1 12345678 AK4 FN1 AXL FLG LOX LIM2 IGF2 MGP IFI27 KRT8 PLAT SOX4 CAV1 FLNB CD44 CD83 SPP1 CD13 CD70 CD36 CD55 GDF3 PLAU JUNB MT1E RGS5 MT2A CSTB MT1X EMP2 RGS2 MT1G APOE SNAI2 TIMP1 TIMP3 C9orf3 LYPD2 PALLD CALB1 KRT18 CD201 SULF1 TDGF1 CD13 Clusters KRT6A TAGLN TEAD4 THBS1 MFAP5 CHPT1 ANXA1 GSTP1 PRSS3 ANXA2 SPARC HAND1 CENPF KDM1A MFGE8 HMGB2 ATP2B1 ARGFX IGFBP4 IGFBP6 IGFBP5 LEFTY2 LGALS1 TUBB4A MAD2L1 OLFML3 COL6A1 COL3A1 COL1A1 COL6A3 KCTD12 COL6A2 COL1A2 B3GNT7 ASRGL1 AKR1C1 CRABP2 MIR302B C9orf135 C12orf75 ALDH1A1 SCGB3A2 SOSTDC1 HIST1H4C SERPINB9 MIR205HG LINC00437 TNFRSF12A f hiD8-G2&G3 high -Log (P value) BJ D2 D8 CD13+ D8 CD13- 10 GDF3 D12 D16- D16+ 024 00.40.2 0.6 mitotic nuclear division 10 0.75 chromosome segregation nucleosome assembly pericentric heterochromatin assembly 0.5 PC2 Cluster 1&4 0 in utero embryonic development CD201 organ regeneration epithelial cell differentiation erythrocyte differentiation 0.25 -10 liver regeneration eye development -20 -10 0 10 20 brain development 0 0.5 1 1.5 2 CD13 -Log (P value) 1 2 3 4 5 6 7 8 10 0 5 10 15 20 25 j 10 Percentage (%) extracellular matrix organization 0 20406080100 collagen catabolic process cell adhesion BJ PC2 0 endodermal cell differentiation Cluster 5&6&8 D2 response to hypoxia Cluster 7 +ve reg. of cell migration D4 epidermis development D8 antigen process and presentation -10 reg. of I-KB/NF-KB signaling D12 cell division -10 0 10 CD13+CD201+ CD13-CD201+ PC1 sister chromatid cohesion CD13+CD201- CD13-CD201- k lm

Relative expression normalized to GAPDH 8 012345678 GO terms -Log10(p-value) Genes 7 D8 CD13+CD201+D8 CD13-CD201+D8 CD13-CD201- FOSL1 6 D8 CD13+CD201+ extracellular matrix organization 20.16 CNN1 D8 CD13-CD201+ CD44; SERPINE1; 5 collagen catabolic process 12.97 COL1A1;COL6A3; CD44 D8 CD13-CD201- LUM; FN1; FOSL1; 4 cell adhesion 11.23 CNN1; FBN1 3 LUM type I interferon signaling pathway 12.04 2 ISG20; ISG15; SNAI2 antigen processing via MHC class I 6.22 IRF1; IRF2; IRF9 1 ZEB1 TGFB1; TGFB2; TGFBR2; 0 response to hypoxia 7.53 SMAD3; MMP14; PLAU Normalized TRA-1-60+ colonies COL1A1 VEGFA; VEGFC; CD13; siNT2 CD44 siJUN angiogenesis 10.44 si siFBN1 siCNN1 FZD8; ELK3 COL6A3 n siCOL6A3 angiogenesis 6.21 MMP2; ID1; JUN;TGFBI CD201 epithelial to mesenchymal transition 2.99 BMP4; NOTCH1; SNAI1 epidermis development 2.62 KRT17; CRABP2; GJB5 CDH1 100 muscle filament sliding 4.11 TEAD4 cell adhesion 2.96 80 DNA replication 18.46 NANOG cell division 7.87 NANOG; KDM1A; MCM10; CDC25A cell proliferation 2.55 60 GDF3 protein localization to plasma membrane 1.89 F11R; TSPAN33; CDH1; TSPAN15 inner cell mass cell proliferation 1.56 GINS1;GINS4; SALL4 40 positive regulation of neuron differentiation 2.4 MEF2C; DNMT3B; LIN28A SALL4 cellular response to cadmium ion 2.4 MT1H; MT1X; MT1G; MT1F SMAD protein signal transduction 1.5 GDF3; SMAD1; LEFTY1 20 DNMT3B somatic stem cell population maintenance 1.43 POU5F1; SOX2; LIN28A; DPPA4

LIN28A No. of TRA-1-60+ colonies 0 Per row normalized CD13 + - - GAPDH CD201 + + - 00.41 Figure 5 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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 a under aCC-BY-NC 4.0 International license. 1236845 7 9JUNB States CREB3L1 CREBRF DOT1L DRAP1 EPAS1 FOSL1 FOXC2 FOXL1 Early silenced (-succ/+succ) HLX JUND JUN KLF2 KLF6 NFKBIA SNAI2 (+succ) ZEB1

Late silenced TCF4 TFEB ASCL2 CITED4 HAND1 KLF3 TEAD4 LMO2 JARID2 (-succ) MAF Transient SALL4 NEUROG2 TET1 HOXA1 KLF4

Early ZSCAN10 exp (+) SOX2 NANOG DNMT3B DNMT3L PRDM14 FOXA3 SP5 FOXD3 SRY (+suuc) Late exp FOXH1 TFCP2L1 HIF3A ZFP42 ZIC2 UMI OTX2 POU5F1B ZIC3 ZIC5 bce -2 20 POU5F1 JUNB FOSL2 5 FOS FOSL1 JUND 10 lse lse ICluster III Cluster II Cluster I 0.5 4 JDP2 NFE2 BJ D2 3 0 D8 -0.5 OCT4 PAX6 D16- Variability SOX10 CEBPA tSNE2 2 SRY ZEB1 D16+ BJ SOX8 TEAD4 H1 D2 -10 D8 1 D16- D16+ 0 H1 0 100 200 300 400 -10 0 10 Sorted TFs tSNE1 d BJ D2 D8 D16- D16+ H1

Deviation score POU1F1 POU2F1-2 -15 0 15 POU3F1-4 POU5F1B SP1/2/4 KLF5/14 SOX8 V NEUROG2 GATA1:TAL1 SOX10 NRL TFAP4 PAX6 III TAL1:TCF3 HNF4G IV TEAD1/3/4 MAFK III RXRA/B/G ELF5 CEBPA/G II VI RFX2-5 SNAI2 FOXA1 ZEB1 FOXB1 TCF4 FOXC1/2 CTCF VI FOXD1/2 ID4 NFE2 FOXF2 YY2 MAF:NFE2 FOXO3/4/6 SRY JDP2 FOXP2/3 TGIF1 FOXL1 PKNOX1 I JUNB/D FOS:JUN FOXI1 ESR1 FOS NKX2-3 Close I: Homo open in BJ & early Transient III: Open in intermediates & D16+ Open IV-V: Open early FOSL1/2 (D16+&hESC) II: Hete open in BJ & early (intermediates) Close in BJ & H1 (D16+&hESC) VI: Open late

f Deviation score Deviation score giDeviation score h Deviation score Deviation score -10 0 10 05 05 05 -5 010 FOSL1 CEBPA GATA1:TAL1 TEAD4 FOXL1

10 10 10 10 10

0 0 0 0 0 tSNE2 tSNE2 tSNE2 tSNE2 tSNE2

-10 -10 -10 -10 -10

-10 0 10 -10 0 10 -10 0 10 -10 0 10 -10 0 10 tSNE1 tSNE1 tSNE1 tSNE1 tSNE1

Figure 6 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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-NC 4.0 International license.

ab cDeviation score Deviation score 5 FOS:JUN -10 0 10 -4 0 4 JUNB FOSL1 TEAD4 FOSL2 4 FOSL1 Deviation score FOS 10 BATF:JUN -6 0 6 3 NFE2 JUNB 5 FOSL2 TEAD4 TEAD3 FOS 0 Variability 2 FOSL1

FOS:JUN tSNE2 BATF:JUN -5 1 NFE2 TEAD3 -10 TEAD4 0 0 100 200 300 400 -15 Sorted TFs -10 -50 5 -10-5 0 5 tSNE1

deExpression (UMI) f BJ D2 D8 g BJ D2 D8 G1 D8 G2 D8 G3 D12 D16- D16+ D12 D16- D16+ G1 D16+ G2 Low High State 1 State 2 State 3 State 4 State 5 1.2 State 6 State 7 State 8 State 9 20 FOSL1 1 20

FOSL1 0.8 0 10 0.6 FOSL1 10 tSNE2 0.4 -20 0.2 0 1 0.2 0.4 0.6 0.81 1.2 -40 -20 020 40

Relative expression TEAD4 tSNE1 -10 0 10203040 Pseudotime GDF3 20 TEAD4

PC2 00.5 1.5 2.5 TEAD4 1 FOSL1 10 10 High FOSL1 0.5 0 1

Regulon activity Low Relative expression 0 10203040 TEAD4 -10 Pseudotime -20 -10 0 10 0.25 0.5 0.75 1.251 TEAD4 PC1

i NT2 KD FOSL1 KD j *** h 6 400 UMI ***

FOSL1 Low High TEAD4 300 40 * 4 200 20 * 2 100 0 tSNE 2 No. of TRA-1-60+ Colonies No. of 0 -20 Normalized TRA-1-60+ colonies 0 D1 KD D2 KD D3 KD D5 KD OE GFP -40 OE FOSL1 -50 -25 0 25 -50 -25 0 25 siNT2 tSNE 1

siFOSL1

N.S. N.S. k lm2 n D8 CD13- * D8 CD13- * * 250 350 350 1.6 ** 300 300 200 1.2 250 250 150 200 200 0.8 150 150 100 100 100 0.4 50 50 50 No. of TRA-1-60+ colonies No. of 0 No. of TRA-1-60+ Colonies No. of No. of TRA-1-60+ Colonies No. of Normalized TRA-1-60+ colonies 0 0 0 D1 KD D2 KD D5 KD D7 KD D8 KD D10 KD siNT2 OE GFP siTEAD4 OE GFP siNT2 OE TEAD4 OE FOSL1

siTEAD4

Figure 7 bioRxiv preprint doi: https://doi.org/10.1101/829853; this version posted November 4, 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-NC 4.0 International license. a b D8 FOSL1 D8 TEAD4 BJ D16- D16+ D8 FOSL1 bound sites D8 TEAD4 bound sites (CD13-)

-4 -2 0 2 5 -5 -2 0 4 7 10 10 10

5 5 5

0 0 0 tSNE2 -5 -5 -5

-10 -10 -10

-30 -20 -10 0 10 20 30 -200 20 -200 20 -2.5K-5K 3’5’ 2.5K 5K -5K -2.5K 5’ 2.5K3’ 5K tSNE1 tSNE1 tSNE1

c d D8 cells D8 FOSL1 bound sites D8 TEAD4 bound sites (CD13- specific) D8 TEAD4 bound sites D8 FOSL1 bound sites 6 368 sites 2314 sites (CD13- specific)

4 5 4 2

0 0 0 -2 tSNE2 -4 -5 -4 -6 1009 sites 393 sites Log(D16+/BJ scATAC-seq reads) Log(D16+/BJ scATAC-seq reads) Log(D16+/BJ scATAC-seq 0.01 0.11 10 100 0.011 100 Mean of normalized counts Mean of normalized counts -10 -5 05 10 -10 -5 05 10 tSNE1

e 5kb hg19 h i D8 FOSL1 900 350 ChIP only 750 300 D8 TEAD4 250 ChIP only 600 200 450 MMP2 150 300 20kb hg19 100 D8 FOSL1 150 50 ChIP only 0 0

D8 TEAD4 TRA-1-60+ colonies No. of TRA-1-60+ colonies No. of siNT ChIP only siNT2 SOX2 siMMP2 si siSMAD3 SMAD3 siPRDM14 50kb hg19 D8 FOSL1 ChIP only

D8 TEAD4 ChIP only TET1 2kb hg19 D8 FOSL1 ChIP only j D8 TEAD4 ChIP only Transcriptome Chromatin accessibility

RFC3 OSKM fg D8 FOSL1 bound sites D8 TEAD4 bound sites (CD13-) BJ CD13 + - - CD13 + - - AP-1 CD201 + + - CD201 + + - CEBPA/G MAF D2 G3 G4 G1,2 CDK1+

TGFBR2 MMP2 CD13+ CD44+ COL5/7/21A1 COL5A1 n=165 COL7A1 G1 BDD2-C8- SMAD3 CDH1 FOSL1,COL6A3, COL21A1 MT1E CNN1, FBN1, CREB3L1 SMAD3, CD44 CD13-/CD13low TET1 CD201+ EPAS1 G2 FOSL1 TEAD4 n=122 RFC3 BDD2-C8+ D8 GATA1:TAL1 NR2F2 F11R MMP2, PRDM14 SOX8 MICALL2 JUN CD83 LIN28A NRL NFATC2 SOX2 PODXL G3 CD13- PAX6 SMAD3 GDF3+ CD201- HNF4G HOXA1 BDD2-C8+ RXRA/B/G MT1X FOSL1 TEAD4 OSNOCT4 n=234 DNMT3B TEAD4 LIN28A SOX2

n=27 SOX21 D16 TRA1-60+ Per row normalized Per row normalized D16- D16+ G2 OCT FOX 00.41 00.41 KLF5/14 YY2 SP1/2/4 SRY

Figure 8