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D Compared to LPS and Pic Stimulation Figure S1 A B 2h 8h 24h 48h Donor: D225 D235 mock D234 D223 100 HIV-GFP 50 0 PC2 : 12.51% LKO-GFP −50 −100 LPS −100 −50 0 50 100 PC1 : 29.79% pIC mock HIV-1-GFP CD86 GFP C 2 h 8 h D mock LPS pIC HIV-1-GFP LKO-GFP 100 2 48 2 48 2 48 2 48 2 48 (h) 75 - + + + - + - + GFP - + CD86 50 TREATMENT 25 TIME DONOR 0 rlog IFNK expression −25 −50 IFNB1 PC2 : 12.51% −75 IFNL1 10 −100 IFNA16 IFNA13 5 mock mock IFNA17 HIV-1-GFP HIV-1-GFP IFNA7 0 IFNA10 IFNA4 24 h 48 h TREATMENT 100 IFNA6 mock 75 IFNL4 LPS 50 IFNA21 pIC HIV-1-GFP 25 IFNA8 LKO-GFP 0 IFNA1 TIME (h) −25 IFNG 2 PC2 : 12.51% −50 IFNA5 8 −75 24 −100 IFNA2 48 −100 −50 0 50 100 −100 −50 0 50 100 IFNL2 DONOR PC1 : 29.79% PC1 : 29.79% IFNL3 D223 D225 mock mock IFNE D234 HIV-GFP-neg HIV-CD86-low IFNW1 D235 HIV-GFP-pos HIV-CD86-high IFNA14 Figure S1. IFN responses and DC maturation during HIV-1-GFP infection are delayed compared to LPS and pIC stimulation. Related to Figure 1. (A) Flow cytometry plots of DCs sorted for RNA-seq after infection with HIV-1-GFP at 2, 8, 24, and 48 h (MOI = 5). Plots show CD86 vs GFP expression and red boxes indicate sorted populations. Plots show representative data from 1 of 4 donors. (B) PCA plots for RNA-seq data from DCs that were either mock treated or infected with HIV-1-GFP. All time points were grouped by condition (shades of blue or red for mock and HIV-1-GFP, respectively) showing mean-centered contour lines to mark standard deviations. Marginal curves show the density of sample position for each donor. (C) PCA plots for RNA-seq samples as in (B) showing mean-centered contour lines for conditions separated by time (2, 8, 24, and 48 h). Color scale bars indicate mock, HIV-1-GFP, and specific populations. (D) Heat map of expression data for 22 human IFN genes from time series RNA-seq samples depicted in (A). Figure S2 2 h 8 h 30 A Donor: B 20 D183 D184 10 D185 0 40 PC2 : 5.05% −10 −20 20 mock mock HIV-1-GFP HIV-1-GFP 0 24 h 48 h PC2 : 5.05% 30 20 −20 10 0 −40 PC2 : 5.05% −10 −20 −40 −20 0 20 40 −40 −20 0 20 40 60 −40 −20 0 20 40 60 PC1 : 81.94% PC1 : 81.94% PC1 : 81.94% mock mock mock HIV-1-GFP HIV-GFP-neg HIV-CD86-low HIV-GFP-pos HIV-CD86-high C STAT1 STAT2 IRF1 IRF7 IRF9 OASL HLA-C ISG20 Treatment Time (h) Sort mock 2 all 8 all 24 all 48 all AC-seq HIV-1-GFP 2 all AT 8 all 24 GFP-neg GFP-pos 48 CD86-low CD86-high NF-κB ChIP-seq IRF3 ChIP-seq STAT1 ChIP-seq CD14+ rep 1 ENCODE CD14+ rep 2 D IFNB1 IFNL1 CXCL10 CXCL11 ISG15 LY6E USP18 IFIT1 Treatment Time (h) Sort mock 2 all 8 all 24 all 48 all AC-seq HIV-1-GFP 2 all AT 8 all 24 GFP-neg GFP-pos 48 CD86-low CD86-high NF-κB ChIP-seq IRF3 ChIP-seq STAT1 ChIP-seq CD14+ rep 1 ENCODE CD14+ rep 2 Figure S2. Time-dependent chromatin opening at IFN and ISG promoters occurs during HIV-1- GFP infection in DCs. Related to Figure 2. (A) PCA plots for ATAC-seq data from DCs that were either mock treated or infected with HIV-1-GFP. All time points were grouped by condition (shades of blue or red for mock and HIV-1-GFP, respectively) and contour lines extend outward from the condition mean to mark standard deviations. Marginal curves show the density of sample position for each donor. (B) PCA plots for ATAC-seq samples as in (A) showing mean-centered contour lines for conditions separated by time (2, 8, 24, and 48 h). Color scale bars indicate mock, HIV-1-GFP, and specific populations. (C-D) ATAC-seq tracks at the indicated gene start sites aligned with tracks from ENCODE ChIP-seq for NF-κB, STAT1, IRF3, and DNAse hypersensitivity data from independent CD14+ monocyte samples. Genes with accessible chromatin at baseline are shown in (C) compared to baseline inaccessible chromatin (D). ENCODE data is scaled equally for (C) and (D). ATAC-seq tracks represent merged files across 3 biological replicates and were visualized using IGV. Figure S3. TF activity estimates combined with multiple subsampling of prior information improves network inference. Related to Figure 3. (A) Joint plots for gene expression and estimated activities for the indicated TFs. Blue points are scaled to left y-axis and show rlog gene expression from 4 unique donors in series. 100 individual activity estimates are displayed as red lines and scaled on the right y-axis as normalized TF activity. The x-axis indicates time and stimulation condition. (B) Pearson correlation plots showing the relationship between estimated activity and rlog gene expression for the TFs shown in (A). (C) Precision/Recall performance measured against the TRRUST database for the final EN-ATAC (x 400) network (cyan) compared to 19 individual network runs generated from single subsamples of the prior (grey) and a network generated from random (red) (see STAR Methods). (D) AUPR curves for the networks shown as in (C) scored against the TRRUST database. (E) Proportional Venn diagrams displaying overlap between targets predicted in the final EN-ATAC network for the indicated IRF family members, NF-κB family members, and 97 “core” mammalian ISGs (Shaw et al., 2017). (F) Proportional Venn diagrams displaying overlap between targets of IRF3 predicted by the EN-ATAC network, IRF3 targets predicted by BBSR, and core mammalian ISGs. Figure S4 A B IRF2 IRF9 IRF3 IRF9 STAT2 IRF2 IRF8 CTCF IRF1 IRF7 IRF3 IRF1 CTCFL STAT1 IRF5 REL PRDM1 Interferon IRF7 IRF8 RELB RELA HIVEP1 NFKB1 EHF STAT2 PRDM1 SPI1 NFKB2 IRF4 BCL11A NFKB1 REL C IRF4 IRF5 HIVEP1 RELB D HIV-1-GFP LKO-GFP LPS pIC Inflammation RELA NFKB2 2h 8h 24h 48h Cluster 2h 8h 24h 48h 2h 8h 24h GFP- 24h GFP+ 48h GFP- 48h GFP+ 2h 8h 24h GFP- 24h GFP+ 48h CD86-low 48h CD86-high IRF2 IRF3 IRF7 STAT2 IRF9 IRF1 IRF8 NFKB1 PRDM1 E HIVEP1 RELA 24h GFP-neg 24h GFP-pos 48h CD86-low 48h CD86-high REL RELB SRF NFKB2 HIV-1-GFP ETV7 24h GFP-neg 24h GFP-pos 48h GFP-neg 48h GFP-pos THRB ETV5 MAFK NFIA LKO-GFP FLI1 CLOCK STAT6 2h 8h 24h 48h TLX1 CREM LPS HES1 SMARCC1 ZNF232 MAFG pIC TFAP2A <1 10 >100 - log (p) Figure S4. IRF and NF-κB family members populate dynamic areas of the network. Related to Figure 4. (A) Selected TF positions in the network as visualized by Gephi software. Edge line weights are reduced to accentuate nodes, with node size being relative to the number of direct connections. Color coding is consistent with cluster naming as in Figure 4. (B) HOCOMOCO motif sequence logos for top TFs in Cluster 5 (IRF & Interferon) and Cluster 8 (NF-κB and Inflammation). (C) HOCOMOCO motif sequence logos for IRF4 and IRF5 (D) Heat maps of hypergeometric tests for TF enrichment across all time series conditions for HIV-1- GFP, LKO-GFP, LPS, and polyI:C as compared to mock treatment. TFs were ranked by their weighted z-scores combined across all contrasts. Data is displayed as -log (p-value). (E) Network activity across the time series shown for HIV-1-GFP, LKO-GFP, LPS, and polyI:C as visualized by Gephi software. Red areas denote differential gene expression and track temporally with TF hypergeometric enrichment as shown in (D). Figure S5 A B C cGAS IRF3 HIVEP1 KLF13 control sh cGAS sh HIVEP1 sh1 HIVEP1 sh3 control sh cGAS sh KLF13 sh1 KLF13 sh2 n mock mock o i 1.5 1.5 1.5 1.5 ress 1.0 1.0 1.0 1.0 p ex 0.5 0.5 0.5 0.5 ve i at l HI 0.0 0.0 HI re 0.0 0.0 V V - - 1 1 -GFP -GFP IRF3 sh cGAS sh control sh control sh control sh control sh HIVEP1HIVEP1 sh1 sh3 KLF13KLF13 sh1 sh2 CD86 CD86 GFP GFP control sh control sh D cGAS sh E cGAS sh F HIVEP1 sh1 KLF13 sh1 IFNL1 HIVEP1 sh3 KLF13 sh2 * *** **** * *** **** * 500 ** 100 100 * * * ** * n o 400 80 80 i + + P 60 P 60 ress 300 GF GF 40 40 p % % ex 20 20 200 ve 0 0 i 0 0.5 1.5 5 0 0.5 1.5 5 at l 100 ** **** ** **** re 100 100 ** ** * 0 + + 80 80 6 6 60 60 CD8 CD8 40 40 IRF3 sh IRF3 sh cGAS sh cGAS sh % % control sh control sh 20 20 KLF13 sh1 KLF13 sh2 KLF13 sh1 KLF13 sh2 HIVEP1 sh1 HIVEP1 sh3 HIVEP1 sh1 HIVEP1 sh3 0 0 0 0.5 1.5 5 0 0.5 1.5 5 HIV-1-GFP HIV-1-GFP G NL(AD8) NL(AD8) +Vpx HIV-2-GFP +Vpx JK7312AS +Vpx R_IFN cGAMP R848 vs mock vs mock vs mock vs mock vs mock vs mock vs mock 1) Chromatin Modifiers 2) Reg of Cell Activation 3) Reg of Transcription 4) Undefined 5) Interferon 6) Metabolism 7) Undefined 8) Inflammation opology Network 9) Undefined T 10) RNA Processing IRF1 STAT2 IRF2 IRF2 IRF2 IRF3 RELA STAT2 IRF8 IRF3 STAT2 IRF3 STAT2 NFKB1 PKNOX2 IRF1 STAT2 IRF3 STAT2 IRF2 REL - log (p) IRF2 IRF2 IRF7 IRF1 IRF9 IRF1 IRF2 PLAGL1 IRF3 IRF1 IRF8 IRF7 IRF8 IRF3 >200 IRF8 IRF9 IRF8 IRF7 IRF8 IRF9 HIVEP1 IRF3 IRF7 IRF9 IRF9 IRF1 HIF1A NFKB2 FLI1 RELA PRDM1 RELA RELA RELA STAT2 ETS2 STAT1 RELA REL ELF2 IRF7 IRF9 STAT1 STAT4 STAT1 PRDM1 REL TFAP4 RELB TFAP2A PRDM1 ZBTB7B STAT1 PRDM1 SMARCC1 ZBTB7B IRF9 ELF2 REL HIVEP1 ZBTB7B STAT1 IRF1 ETV7 NFKB1 ELF2 NFKB1 STAT1 MYOD1 IRF7 20 TFAP4 MAFA RFX2 STAT4 NFKB1 STAT4 SMARCC1 ELF2 STAT6 HIVEP1 RFX2 SMARCC1 ETV7 IRF8 SMAD1 CLOCK STAT4 ELF2 NFKB2 RELB RFX2 KLF12 REL KLF14 SMARCC1 RFX2 EOMES MESP1 TF Enrichment STAT4 IRF5 RFX4 NFKB2 HIVEP1 NFATC1 TFAP2A CLOCK RELB NFKB2 ZBTB7B IRF5 NFKB1 ELF2 TFAP2D HIVEP1 IRF5 RELB STAT4 STAT5A PKNOX2 ZNF423 THRB THAP1 STAT6 TFAP2A ETS2 HEY2 <2 SP2 KLF1 STAT6 IRF5 RFX4 PROX1 SMAD2 TFAP2B ZNF148 SMARCC1 SRF MESP1 HOXA2 SRF RELA SMARCC1 NFKB1 THRB STAT6 NFKB2 THRB SP4 NFKB2 ESRRA ZNF148 MAFA REL HGNC:9982 Figure S5.
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