GATA1-Deficient Dendritic Cells Display Impaired CCL21-Dependent Migration toward Lymph Nodes Due to Reduced Levels of Polysialic Acid This information is current as of October 1, 2021. Maaike R. Scheenstra, Iris M. De Cuyper, Filipe Branco-Madeira, Pieter de Bleser, Mirjam Kool, Marjolein Meinders, Mark Hoogenboezem, Erik Mul, Monika C. Wolkers, Fiamma Salerno, Benjamin Nota, Yvan Saeys, Sjoerd Klarenbeek, Wilfred F. J. van IJcken, Hamida

Hammad, Sjaak Philipsen, Timo K. van den Berg, Taco W. Downloaded from Kuijpers, Bart N. Lambrecht and Laura Gutiérrez J Immunol 2016; 197:4312-4324; Prepublished online 4 November 2016; doi: 10.4049/jimmunol.1600103

http://www.jimmunol.org/content/197/11/4312 http://www.jimmunol.org/

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology

GATA1-Deficient Dendritic Cells Display Impaired CCL21-Dependent Migration toward Lymph Nodes Due to Reduced Levels of Polysialic Acid

Maaike R. Scheenstra,* Iris M. De Cuyper,* Filipe Branco-Madeira,†,‡ Pieter de Bleser,x Mirjam Kool,† Marjolein Meinders,* Mark Hoogenboezem,{ Erik Mul,{ Monika C. Wolkers,‖ Fiamma Salerno,‖ Benjamin Nota,* Yvan Saeys,x Sjoerd Klarenbeek,# Wilfred F. J. van IJcken,** Hamida Hammad,†,‡ Sjaak Philipsen,†† Timo K. van den Berg,* Taco W. Kuijpers,*,‡‡ Bart N. Lambrecht,†,‡,xx and Laura Gutie´rrez*,{{

Dendritic cells (DCs) play a pivotal role in the regulation of the immune response. DC development and activation is finely orchestrated through transcriptional programs. GATA1 is required for murine DC development, and data suggest that it might Downloaded from be involved in the fine-tuning of the life span and function of activated DCs. We generated DC-specific Gata1 knockout mice (Gata1- KODC), which presented a 20% reduction of splenic DCs, partially explained by enhanced apoptosis. RNA sequencing analysis revealed a number of deregulated involved in cell survival, migration, and function. DC migration toward peripheral lymph nodes was impaired in Gata1-KODC mice. Migration assays performed in vitro showed that this defect was selective for CCL21, but not CCL19. Interestingly, we show that Gata1-KODC DCs have reduced polysialic acid levels on their surface, which is a known determinant for the proper migration of DCs toward CCL21. The Journal of Immunology, 2016, 197: 4312–4324. http://www.jimmunol.org/

endritic cells (DCs) are key initiators and regulators of ular patterns, such as TLRs, which can induce the activation of DCs the immune response (1). Two major types of DCs have when recognizing their ligand. Activated DCs migrate to the lymph D been defined in mouse and human in the steady-state, nodes to activate T and B cells by Ag presentation on MHC class I that is, conventional DC (cDCs) and plasmacytoid DCs. Under in- (MHC-I) or MHC-II (9). Migratory DCs in the lymph nodes can be flammatory conditions, yet another type of DC, so-called inflam- distinguished from resident cDCs by their higher MHC-II expres- matory DC, derives from circulating monocytes (2). In mice, cDCs sion (2, 5, 9). Both cDC subtypes can activate CD4+ T cells through can be further subdivided into CD8a+CD24+Xcr1+ cDCs (also called MHC-II in the lymphoid organs. In addition, CD8a+ cDCs are by guest on October 1, 2021 cDC1) and CD11b+Sirp-a+ cDCs (also called cDC2) (3–8). Imma- specialized to cross-present Ag on the MHC-I molecule, and thereby ture DCs express several receptors for pathogen-associated molec- are capable of priming CD8+ cytotoxic T cells (3, 5, 9–11).

*Department of Blood Cell Research, Sanquin Research and Landsteiner Laboratory, (to S.P.), Netherlands Scientific Organization Grant ZonMW TOP 40-00812-98-12128 Academic Medical Center, University of Amsterdam, Amsterdam 1066CX, the Nether- (to S.P.), and Seventh Framework Programme, European Union research and develop- lands; †Laboratory of Immunoregulation, VIB, Ghent 9052, Belgium; ‡Department of ment funding program EU fp7 THALAMOSS 306201 (to S.P.). Internal Medicine, Ghent University, Ghent 9000, Belgium; xData Mining and Modeling M.R.S. and L.G. designed and performed experiments, analyzed data, and wrote the for Biomedicine, Department of Biomedical Molecular Biology, VIB Inflammation { manuscript; I.M.D.C. performed experiments, analyzed data, and revised the manu- Research Center, Ghent University, Ghent 9052, Belgium; Department of Molecular script; F.B.-M. performed experiments and revised the manuscript; W.F.J.v.I. per- Cell Biology, Sanquin Research and Landsteiner Laboratory, Academic Medical Center, ‖ formed RNA sequencing (RNA-Seq); B.N. performed RNA-Seq analysis; P.d.B. University of Amsterdam, Amsterdam 1066CX, the Netherlands; Department of He- and Y.S. performed RNA-Seq and principal component analysis; M.K., M.M., matopoiesis, Sanquin Research and Landsteiner Laboratory, Academic Medical Center, M.H., E.M., F.S., and S.K. performed experiments; M.C.W. and H.H. designed ex- University of Amsterdam, Amsterdam 1066CX, the Netherlands; #Experimental Animal periments and revised the manuscript; S.P., T.K.v.d.B., T.W.K., and B.N.L. partici- Pathology, The Netherlands Cancer Institute, Amsterdam 1066CX, the Netherlands; pated in discussions, designed experiments, and revised the manuscript. **Center for Biomics, Erasmus MC, Rotterdam 3015 CN, the Netherlands; ††Department of Cell Biology, Erasmus MC, Rotterdam 3015 CN, the Netherlands; The data presented in this article have been submitted to the Expression Om- ‡‡Department of Pediatric Hematology, Immunology and Infectious Disease, Emma nibus under accession number GSE69969. Children’s Hospital, Academic Medical Center, University of Amsterdam, Amsterdam xx Address correspondence and reprint requests to Dr. Laura Gutie´rrez, Department of 1105AZ, the Netherlands; Department of Pulmonary Medicine, Erasmus MC, {{ Hematology, Hospital Clı´nico San Carlos, Instituto de Investigacio´n Sanitaria San Rotterdam 3015 CN, the Netherlands; and Departamento de Hematologı´a, Hos- Carlos, Profesor Martı´n Lagos s/n, Room 1578, First Floor, Madrid 28040, Spain. pital Clı´nico San Carlos, Instituto de Investigacio´n Sanitaria San Carlos, Madrid E-mail address: [email protected] 28040, Spain The online version of this article contains supplemental material. ORCIDs: 0000-0001-8862-8000 (I.M.D.C.); 0000-0001-5245-9735 (F.B.-M.); 0000- 0003-4762-8770 (P.d.B.); 0000-0003-1436-3876 (M.K.); 0000-0002-7124- Abbreviations used in this article: BAC, bacterial artificial ; BM-DC, 0832 (M.M.); 0000-0002-8234-9972 (E.M.); 0000-0003-3242-1363 (M.C.W.); bone marrow–derived DC; cDC, conventional DC; Ct, cycle threshold; DC, dendritic 0000-0003-1634-947X (F.S.); 0000-0001-7500-5760 (B.N.); 0000-0002-0415- cell; Gata1-KODC, DC-specific Gata1 knockout mice; GO, ; IPA, 1506 (Y.S.); 0000-0002-1891-1940 (S.K.); 0000-0002-0421-8301 (W.F.J.v.I.); Ingenuity Pathway Analysis; KO, knockout; MHC-I, MHC class I; PCA, principal 0000-0002-3690-1201 (S.P.); 0000-0001-8443-900X (L.G.). component analysis; PIpropidium iodide, peripheral lymph node; PLN, periph- eral lymph node; PSA, polysialic acid; RNA-Seq, RNA sequencing; WT, wild Received for publication January 21, 2016. Accepted for publication September 29, type; WTlox, Gata1-lox male littermate; WTCre, CD11cCre male not bearing 2016. Gata1-lox allele. This work was supported by a VENI grant from the Netherlands Scientific Orga- nization (Grant VENI 863.09.012 to L.G.), an Ramo´n y Cajal fellowship from Copyright Ó 2016 by The American Association of Immunologists, Inc. 0022-1767/16/$30.00 the Spanish Ministerio de Economı´a y Competitividad (Grant RYC-2013-12587 to L.G.), Landsteiner Foundation for Blood Transfusion Research Grant LSBR 1040 www.jimmunol.org/cgi/doi/10.4049/jimmunol.1600103 The Journal of Immunology 4313

The development of DCs from hematopoietic progenitors is reporter transgene at the Rosa26 , and upon Cre recombination they tightly regulated by transcriptional programs (12, 13). The role of express nuclear-mCherry and surface-EGFP (36). We crossed R26R-RG several transcription factors in DC development has been studied mice with Gata1-lox|CD11cCre (BAC) mice, and used R26R-RG|Gata1- lox|CD11cCre (R26R-RG|Gata1-KODC) and R26R-RG|CD11cCre (R26R- using genetically modified mice and by reconstitution assays (14). RG|CD11cCre males not bearing Gata1-lox allele [WTCre]) mice for the Several transcription factors have been found to regulate DC subset generation of DCs in culture as specified later. differentiation. Mice deficient for IRF2, IRF4, , or RelB have Mice were used between 8 and 16 wk of age, unless stated otherwise. m a strong reduction in the CD11b+ cDC subset (15–18), whereas When indicated, LPS (Sigma) was administered (5 g/mouse) via i.v. in- jection, and mice were sacrificed after 24 h for further analysis. IRF8 and Batf3 deficiency results in a strong reduction in the Mice were kept specified pathogen-free with free access to food and + CD8a cDC subset (19, 20). IRF4 and IRF8 are important for the water at all times, under the guidelines for animal experimentation approved in vitro generation of bone marrow (BM)–derived DCs (BM-DCs), by the animal ethical comity of the Netherlands Cancer Institute (NKI, either in the presence of GM-CSF or Flt3L (20). Other tran- Amsterdam, the Netherlands), Erasmus MC, and VIB. scription factors, such as SPI1 (also known as PU.1), are involved Mouse BM-DC culture in the development and differentiation of both cDC subsets. PU.1 regulates Flt3 expression, which is essential for DC development BM was obtained by crushing the femur and tibia of both legs, after which the cells were filtered through a 40-mm filter (BD Biosciences) to obtain a single- (21). Loss of PU.1 in the DC lineage results in a general cDC defect, cell suspension. Cells were cultured at a density of 0.5 3 106/ml in RPMI with the CD8+ cDC subtype being more severely affected than the 1640 (Life Technologies) supplemented with 5% heat-inactivated FCS, 1% CD11b+ cDC subtype (14, 21, 22). GATA1 transcription factor, penicillin/streptomycin, 5 mM 2-ME, and 20 ng/ml GM-CSF (Peprotech). A m which exerts functions antagonistic to PU.1, is expressed in both total of 0.5 g/ml LPS (Santa Cruz Biotechnology) was added to the cells at day 7, and the cells were harvested for further analysis at days 8 and 10. cDCs and plasmacytoid DCs (23) and is required for proper dif- ferentiation (24). GATA1 belongs to the GATA family of transcrip- Cell purification and flow cytometry Downloaded from tion factors, characterized by two zinc finger domains for DNA Blood was drawn by heart puncture and collected in heparin-coated vials binding to the GATA consensus sequence (WGATAR), as well as (Sarstedt, Numbrecht,€ Germany). The scil Vet abc Plus+ automated he- motifs for –protein interactions (25). GATA1 is essential mocytometer was used to determine standard blood parameters. Spleen for differentiation of erythrocytes and megakaryocytes (25–27). In and lymph nodes were taken from the mice and digested in RPMI 1640 (Life Technologies), supplemented with 1.5 Wunsch€ activity units/ml these lineages, GATA1 regulates the transcription of cell-specific m

Liberase TL grade (Roche, U.K.), 0.5 g/ml Aggrastat (MSD), and 2 http://www.jimmunol.org/ and antiapoptotic genes (26, 28–31). Kunitz units/ml DNAse (Sigma) for 30 min at 37˚C. Single-cell suspen- Not much is known yet about the role of GATA1 in DCs. GATA1 sions were made using a 40-mm filter (BD Biosciences), and the cells were was found to be important for the lineage separation between DCs and washed with PBS/0.5 mM of EDTA. Blood and spleen samples were treated macrophages, being indispensable for DC commitment and differ- with an isotonic ammonium chloride buffer for 5 min at 4˚C to lyse the erythrocytes, after which lysis buffer was washed away with PBS. entiation from progenitors (24). It was also observed that GATA1 is Cells (from organs and cultured BM-DCs) were stained for different required for DC survival and function, in particular upon LPS stim- markers (for Abs used, see Table I). In addition, cells were incubated in a ulation of GM-CSF–cultured BM-DCs. In humans, DC differentia- HEPES buffer containing 2.5 mM of CaCl2 for Annexin V and propidium tion from blood monocytes was reported to coincide with the iodide (PI) staining. Samples were measured on a BD FACSCanto II or BD upregulation of GATA1 expression as a crucial cell fate factor for FACSFortessa flow cytometer (BD Biosciences) and analyzed with FlowJo software. by guest on October 1, 2021 the dichotomy between Langerhans cells and DC lineage devel- opment (26). The closely related GATA2 transcription factor has RNA extraction been recently linked to DC differentiation. Patients carrying mu- For RNA-Seq analysis, BM-derived GM-CSF DCs from R26R-RG|Gata1- tations in the GATA2 gene present with MonoMac disease (an KODC and R26R-RG|WTCre mice were used nonstimulated and stimulated autosomal dominant immunodeficiency caused by the lack of with LPS at day 7 as described earlier. At day 10, steady-state DCs and + + monocytes, DCs, B cells, and NK cells) and are prone to development LPS-stimulated DCs were harvested and sorted for GFP /mCherry cells. of myelodysplasia and/or leukemia (32). In addition, conditional This strategy allowed enriching for DCs that had undergone Cre-mediated recombination for both the WTCre and the R26R-RG|Gata1-KODC cultures. GATA2 loss in mice results in severely reduced DC numbers (33). Total RNA was extracted from the sorted DCs using the RNeasy-plus mini In this study, we dissect the role of GATA1 in DCs using a DC- kit (Qiagen). specific Gata1 knockout (KO) mouse (Gata1-KODC) model. We found that Gata1-KODC mice display a decrease in the splenic DC RNA-Seq compartment. RNA sequencing (RNA-Seq) revealed a number of RNA-Seq was performed according to manufacturer’s instructions (Illumina) deregulated genes involved in cell survival, migration, and function in using the TruSeq RNA sample prep kit v2. In brief, polyA-containing mRNA DC molecules were purified using oligo-dT attached to magnetic beads. After Gata1-KO DCs. Interestingly, we observed impaired DC migration ∼ DC purification, the mRNA was fragmented into 200-bp fragments using di- toward the lymph nodes in Gata1-KO mice upon LPS treatment valent cations under elevated temperature. The cleaved RNA fragments were and in aging mice. The migration defect was CCL21 dependent. This copied into first-strand cDNA using reverse transcriptase and random pri- phenomenon could be explained by reduced polysialic acid (PSA) mers. This was followed by second-strand synthesis using DNA polymerase surface expression levels in LPS-stimulated Gata1-KODC DCs. I and RNase H treatment. These cDNA fragments were end repaired, a single A base was added, and Illumina adaptors were ligated. The products were purified and size selected on gel and enriched by PCR. The PCR products Materials and Methods were purified by QIAquick PCR purification and used for cluster generation Mice according to the Illumina cluster generation protocols. The samples (n =2 for every condition) were sequenced for 36 bp on a HiSeq2000 and demul- Mice bearing a modified Gata1 allele flanked with loxP sites (34) were tiplexed using Narwhal (37). The reads were aligned using TopHat version crossed with mice expressing a constitutively active Cre recombinase 2.0.8 (38) against the University of California, Santa Cruz Genome Browser under the CD11c (CD11cCre [bacterial artificial chromosome mm10 reference genome, using Ensemblgenes.gtf version 73 (39). For RNA (BAC)]) from the Jackson Laboratory [B6.Cg-Tg(Itgax-cre)1-1Reiz/J, strain of R26R-RG|Gata1-KODC DCs, we obtained an average of 17.1 million reads 008068] (35). Because the Gata1 gene is X-linked, only Gata1-lox| for steady-state condition and 13.1 million reads for LPS-stimulated condi- CD11cCre (BAC) males were used to obtain DC-specific pancellular Gata1 tion, of which 93.7 and 91.3% aligned back, respectively, to the reference recombination, and we named them Gata1-KODC. Gata1-lox male litter- genome. For WTCre DC samples, we obtained an average of 17.3 million mates (WTlox) were used as controls. In addition, and to be able to sort an reads for steady-state condition and 18.9 million reads for LPS-stimulated enriched population of recombined DCs for RNA-Seq, we used the R26R- condition, with 93.2 and 93.3% alignment, respectively (Supplemental RG reporter strain (provided by S. Aizawa). These mice bear a conditional Fig. 2B). The data were submitted to GEO (accession number GSE69969). 4314 GATA1 DC-TRANSCRIPTOME MODULATES CCL21-DEPENDENT MIGRATION

RNA-Seq data analysis FluoroBlock filter (8.0-mm pores; Corning). The filters were placed in a 24-well plate, which contained 200 ng/ml CCL19 or CCL21 (BioLegend). For all 23,420 University of California, Santa Cruz Genome Browser mm10 The plates were placed in the F200-pro plate reader (Tecan, Ma¨nnedorf, annotated genes, the reads were counted that aligned to the exonic regions Switzerland), which was set to 37˚C. Fluorescence was measured every using “feature Counts” from Subread (version 1.4.3) (40). Differential 10 min for 3 h with an excitation wavelength of 485 nm and an emission assessment was done in the R environment (version 3.1.1) wavelength of 535 nm. with edgeR (version 3.6.8) (41), as earlier described (42). The following group comparisons were made: R26R-RG|Gata1-KODC versus WTCre CCL21 binding assay under steady-state condition, and R26R-RG|Gata1-KODC versus WTCre 5 lox DC under LPS condition. The p values were adjusted for multiple testing using A total of 1 3 10 cultured WT or KO BM-DCs was resuspended in FDR control (43), and adjusted p , 0.05 was considered significant. Two- HEPES buffer saline solution, as described earlier, and placed in a 96-well dimensional hierarchical clustering was done with significant genes using plate. Cells were incubated for 30 min with 20 ng/ml CCL21 on ice, after only default settings of the “heatmap.2” function from the gplots (version which the cells were fixed and permeabilized, using the fix/perm kit from 2.16) R package, using log2-transformed reads per kilobase per million BD Biosciences. Cells were incubated with CCL21 Ab (R&D Systems) for data. The normalized gene expression data were scaled by row (Z-score). 30 min on ice in perm/wash buffer, after which cells were incubated with a Gene Ontology (GO) gene set enrichment analyses were carried out with FITC-labeled anti-goat Ab (Life Technologies). Samples were measured the GOseq R package (version 1.16.2) (44). Enrichment of GO terms was on a BD FACSCanto II and analyzed with FlowJo software. assessed in each list of differentially expressed genes per contrast sepa- rately, taking length bias into account. The derived p values were adjusted Statistical analysis for multiple testing using Bonferroni correction, and adjusted p , 0.05 was Results are presented as the mean 6 SEM. Statistical significance was considered significant. assessed with two-sided Student t tests, as calculated with GraphPad Prism HOMER software suite was used, with default settings, to identify en- software, version 6.02. richment of known motifs in promoters of differentially regulated genes (45).

Principal component analysis (PCA) was performed using Fastq files that Downloaded from were equally processed with fastqc version 0.11.2 (46) and trimmomatic Results v0.33 (47). Mapping to the reference genome was done using TopHat2 v2.0.10 (38), and filtering was done with samtools v0.1.19 (48). Counting GATA1 loss in DCs results in a reduction of the splenic DC reads in features was done with htseq-count (49). PCA analysis was per- compartment formed in R. ComBat was used to correct for batch effects (50). Data sets Gata1-lox mice (34) were crossed with CD11c-Cre mice (35) to used are publicly available: cultured BM-derived M-CSF macrophages DC (GSM1520422 and GSM1520423) and cultured BM-derived GM-CSF DCs, generate DC-specific Gata1 KO mice (Gata1-KO ). CD11c-Cre treated or not with LPS (GSM1620172, GSM624287, and GSM722533). mice have been previously characterized by Caton et al. (35), and http://www.jimmunol.org/ from this study it was reported that the recombination efficiency in Quantitative RT-PCR DCs is 96% using a R26-EYFP reporter mouse. In addition, “leaky” Total RNAwas extracted from cultured WTlox and KODC cultured DCs with recombination in other lineages was also reported, for example, the RNeasy-plus mini kit (Qiagen) used according to the manufacturer’s 0.3% in granulocytes, 6% in T cells, 5% in B cells, and 12% in NK instructions. cDNA was synthesized with Superscript III RT (Invitrogen). Custom-made primers were used to amplify desired transcripts with SYBR cells. Of these, GATA1 is expressed only in a subset of granulocytes, green as a detection method with the StepOnePlus real-time PCR system that is, in eosinophils, whereas it is undetectable in lymphocytes (24). (Applied Biosystems): Gata1,fw59-CAGTCCTTTCTTCTCTCCCAC-39 We measured the complete blood counts of Gata1-KODC mice and rev 59-GCTCCACAGTTCACACACT-39. Input was normalized using and WT littermates (WTlox) on a Scil Vet abc Plus+ Hematology housekeeping genes (Hprt:fw59-AGCCTAAGATGAGCGCAAGT-39 by guest on October 1, 2021 9 9 9 analyzer. RBC and platelet counts, lineages that require Gata1 ex- and rev 5 -ATGGCGACAGGACTAGAACA-3 ; Ubc:fw5-AGGT- lox CAAACAGGAAGACAGACGTA-39 and rev 59-TCACACCCAAGAA- pression (25), were in the normal range in both WT and Gata1- DC CAAGCACA-39; and Gapdh:fw59-CCTGCCAAGTATGATGACAT-39 KO mice (Fig. 1A), indicating no recombination leakage in the and rev 59-GTCCTCAGTGTAGCCCAAG-39), and relative expression was megakaryocyte/erythroid lineages. DD calculated using the cycle threshold (Ct) value method ( Ct); that is, relative Gata1-KODC mice presented with a mild reduction in WBC expression = 22DCt,whereDCt = Ct 2 average Ct (51). target gene housekeeping genes counts, which was caused by a reduction in lymphocytes, because Protein extraction and Western blotting there were no differences in granulocyte numbers and only a mild DC Naive (CD44low) CD4+ and CD8+ T cells were sorted from wild type (WT) significant increase in monocytes in Gata1-KO mice (Fig. 1A). mouse spleens, and 5 3 106 cells were lysed in 100 ml of sample lysis By flow cytometry, we dissected the lymphocyte populations in the buffer. BM-DCs from WTlox and KODC mice were lysed with radio- blood and identified a reduction in T cells, which was specifically immunoprecipitation assay buffer (10 mM of Tris-HCL [pH 8], 1 mM of due to a decrease in CD4+ T cells and not CD8+ T cells (Fig. 1B) EDTA, 0.5 mM of EGTA, 140 mM of NaCl, 1% Triton X-100, 0.1% (see Table I for a list of Abs used). The T cell lineage in other organs NaDOC, 0.1% SDS) containing protease inhibitors. As control for GATA1 expression, we used I/11 mouse erythroid cell line; for protein extraction, was not affected, nor was the B cell lineage (data not shown). Be- 1 3 106 cells were lysed in 100 ml of sample lysis buffer. Protein con- cause the majority of blood lymphocytes are B cells, we sorted centrations were measured with BCA Protein Assay Reagent (Thermo splenic CD4+ and CD8+ T cells from WT animals to analyze GATA1 Scientific, Rockford, IL). Protein samples were separated using a 10% expression (Supplemental Fig. 1A). We were unable to detect full- SDS-polyacrylamide gel, after which they were transferred to a polyvi- nylidene difluoride membrane (Millipore, Billerica, MA). Membranes length GATA1, and observed very low levels of the short GATA1 were labeled with GATA1 (M20 or N6) Abs and thereafter with anti-goat isoform in both T cell subsets. All together, these results suggest or anti-rat IgG-HRP. Pierce ECL Western blotting substrate was used to that the specific reduction of CD4+ T cells in the blood is probably visualize HRP. Super RX films were developed in the medical film pro- not due to leaky recombination in the T cell lineage. cessor SRX-101A (Konic Minolta, Tokyo, Japan). As loading control, We next analyzed the cDC subtypes in different lymphoid or- GAPDH (Merck Millipore, Darmstadt, Germany) was used, followed by anti-mouse-IgG-IRDye 800CW-conjugated Ab (LI-COR, Lincoln, NE) and gans. First, we selected non-B cells after which DCs were gated visualized using LI-COR Odyssey Western blot detection system (Westburg, based on CD11c and MHC-II expression (Fig. 1C). We found a Leusden, the Netherlands). Protein levels were quantified using ImageJ. significant reduction of cDCs in the spleen of Gata1-KODC mice, Transwell migration whereas no differences were found in the blood and the lymph nodes (Fig. 1D). The splenic cDCs were further subdivided into 6 lox DC A total of 2 3 10 cultured WT or KO DCs was labeled with calcein- CD11b+ and CD8+ subsets (Fig. 1C), and we found that the reduc- AM (Invitrogen) for 30 min at 37˚C in HEPES-buffered saline solution tion of cDCs in the spleen was due to a decrease of both subsets in (134 mM of NaCl, 0.34 mM of Na2HPO4, 2.9 mM of KCl, 12 mM of DC + NaHCO3, 20 mM of HEPES, 5 mM of glucose, 1 mM of MgCl2 [pH 7.3]). Gata1-KO mice, although CD11b DCs were more strongly re- A total of 4 3 105 cells was added in the upper well of Transwell on a duced (Fig. 1D). The Journal of Immunology 4315

Table I. List of Abs

Ag Label Clone Supplier Annexin V FITC BD Pharmingen CCL21 — R&D Systems CCR7 PE 4B12 eBioscience CD3e eFluor780 17A2 eBioscience CD4 Allophycocyanin RM4-5 BD Pharmingen CD4 PE GK1.5 eBioscience CD8a PE-Cy7/PerCP-Cy5.5 53-6.7 BD Pharmingen CD11b Allophycocyanin-Cy7 M1/70 BD Pharmingen CD11c PE HL3 BD Pharmingen CD19 PE-Cy7 eBio1D3 eBioscience CD24 Pacific blue M1/69 eBioscience CD40 FITC 3/23 BD Pharmingen CD44 PerCP-Cy5.5/eV450-Pacific blue IM7 eBioscience CD86 PerCP GL-1 BioLegend GATA1 — M-20 Santa Cruz GATA1 — N6 Santa Cruz GAPDH — 6C5 Merck Millipore MHC-II FITC M5/114.15.2 eBioscience PI — BD Pharmingen PSA-NCAMa PE 2-2B Miltenyi Biotec Downloaded from Anti-goat IgG AF488 Life Technologies Anti-goat IgG HRP Thermo Fisher Anti-mouse IgG IRDye 800CW Li-Cor Anti-rat IgG HRP Dako aFrom supplier datasheet (http://www.miltenyibiotec.com/; order no. 130-093-274; date last accessed: October 2016): “The Anti- PSA-NCAM antibody recognizes an epitope on human, mouse, and rat PSA, which, in vertebrates, is found linked to the extra-

cellular domain of the neural cell adhesion molecule (NCAM, CD56).” However, it must be clarified that it recognizes PSA on http://www.jimmunol.org/ protein acceptors other than NCAM. NCAM, neural cell adhesion molecule.

Increased apoptosis in GM-CSF cultured Gata1-KODC DCs 8 d, and stimulated for 24 h with LPS, showed a small decrease in The reduction in the splenic DC compartment in Gata1-KODC mice live cells (Annexin Vand PI double-negative cells) and an increase in apoptotic cells (Annexin V and PI double-positive cells) in could be caused by either a block in DC differentiation, aberrant lox migration from the spleen, or enhanced apoptosis. The intrinsic role of comparison with WT DC cultures (Fig. 2D). Analysis on day 10, GATA1 in differentiation and survival has been well established in that is, 60 h in the presence of LPS, showed that, although the cells lox by guest on October 1, 2021 erythroid progenitor cells (26, 28–31). Furthermore, we previously were maintained in WT DC cultures, there was a clear reduction of live cells and a strong increase in the percentage of apoptotic and showed that induced ubiquitous deletion of Gata1 (ER-Cre under the DC Rosa26 promoter) affects megakaryopoiesis and erythropoiesis (52), dead cells in Gata1-KO cultures (Fig. 2D). as well as DC survival, whereas M-CSF BM-derived macrophages are These results corroborate previous data (24) and highlight the not affected by Gata1 recombination (24). To examine whether DC- requirement of Gata1 in the regulation of the life span of differ- specific GATA1 loss in committed DCs would result in enhanced entiated and activated DCs. lox apoptosis and/or defective differentiation, BM cells from WT and DC Gata1-KODC mice were cultured in the presence of GM-CSF to RNA-Seq analysis of Gata1-KO DCs in steady-state and generate DCs. The GM-CSF BM culture system is widely used for upon LPS stimulation DC studies. These GM-CSF–derived DCs do not resemble cDCs but We next analyzed the changes in the transcriptome of Gata1-KODC an inflammatory DC type, and the cultures also support the differen- BM-DCs by RNA-Seq analysis. Gata1-KODC mice were crossed tiation of monocyte-derived macrophages to some extent (53). We with R26R-RG reporter mice (36), which express EGFP on the outer characterized the cultures by flow cytometry using CD11b, CD11c, membrane and mCherry on the nuclear membrane upon recombi- and MHC-II. The cultures were very homogeneous based on expres- nation. BM-DCs from R26R-RG|WTCre and R26R-RG|Gata1-KODC sion of these markers and contained ,20% of macrophage-like cells mice were stimulated at day 7 and FACS-sorted for EGFP-mCherry based on lower CD11c and higher CD11b expression, or by using double-positive cells 60 h thereafter (Fig. 3A), after which mRNA F4/80 as a macrophage marker (Fig. 2A, Supplemental Fig. 1D, 1E). was extracted. This allowed us to enrich for DCs that underwent re- Cells were stimulated with LPS or left unstimulated at day 7 and combination, because Gata1 levels were downregulated 8- to 18-fold in harvested after 60 h for RNA extraction, protein isolation, and flow R26R-RG|Gata1-KODC DCs compared with WTCre (Fig. 3B). Fur- cytometry analysis. Both WTlox and Gata1-KODC cultured DCs thermore, PCA of our data sets in comparison with publicly available were equally activated as shown by increased expression of MHC-II RNA-Seq data sets of cultured GM-CSF DCs and G-CSF macro- and costimulatory molecules CD86 and CD40 (Fig. 2B). We phages show that all DC data sets separate clearly from macrophages, found a 2-fold reduction of Gata1 mRNA in Gata1-KODC cultures corroborating the DC identity of our samples (Supplemental Fig. 1F). in steady-state. WTlox DCs upregulated Gata1 expression upon LPS RNA-Seq analysis revealed minor changes between R26R-RG| stimulation, as previously described (23); however, Gata1-KODC Gata1-KODC and WTCre DC in steady-state cultures, that is, 15 genes DCs failed to do so. These results were confirmed at the protein were significantly upregulated and 15 genes significantly downreg- level, although to a lesser extent, probably because of the half-life ulated. However, upon LPS stimulation, 289 genes were significantly of GATA1 protein (Supplemental Fig. 1B). upregulated and 609 genes were significantly downregulated in To study the cell survival of WTlox and Gata1-KODC cultures, R26R-RG|Gata1-KODC DCs compared with WTCre (Fig. 3C, 3D, we used Annexin Vand PI staining. Gata1-KODC cells cultured for Supplemental Fig. 2B, Supplemental Table I). These results suggest 4316 GATA1 DC-TRANSCRIPTOME MODULATES CCL21-DEPENDENT MIGRATION

FIGURE 1. GATA1 loss in DCs results in a reduction of the splenic DC compartment. (A) Blood param- eters of Gata1-KODC and WTlox mice in the steady-state were determined using a Scil Vet abc Plus+ Hematol- ogy analyzer. Absolute numbers of erythrocytes, platelets, and WBCs were counted per liter. Further sub- division of lymphocytes, granulocytes, and monocytes are depicted as per- centage of WBCs. (B) Flow cytometry analysis of the lymphocytes in the bloodstream. T cells were selected for CD3 expression and further sub- divided into CD4+ and CD8+ T cells. Downloaded from (C) DC gating strategy from splenic tissue. First, all nucleated cells were selected, from which the non-B cells (CD19neg cells) were selected. Next, the CD11c+ MHC-II+ cells were se- lected as cDCs, which were further http://www.jimmunol.org/ subdivided into CD8+ or CD11b+ sub- sets. (D) The percentage of DCs is shown in different tissues, depicted as percentage of all nucleated cells. Splenic cDCs were further subdivided into CD8+ or CD11b+ subsets, depicted as percentage of all nucleated cells, setting values obtained for WTlox animals to 100%. At least three inde- pendent experiments, each including by guest on October 1, 2021 three mice per genotype, were used for the analysis. *p # 0.05, **p # 0.01.

a major role for GATA1 in transcriptional regulation of DC upon Fig. 2A). Interestingly, we observed 58 transcriptional regulators activation. that were affected upon LPS stimulation, of which 7 were upreg- HOMER transcription factor motif analysis revealed CEBP ulated and 51 were downregulated (Table II). These include Gata2, motif enrichment in the differentially expressed genes in steady-state Ikaros3 and Ikaros4, Irf8, Nfkb, Bach2, Vdr, Runx1,andRunx3,all conditions (Fig. 3C). Upon LPS stimulation, we identified ETS and with known roles in DC development and function, which could on CEBP motifs significantly enriched in the set of upregulated genes their own explain the DC deficiency observed in steady-state con- (Fig. 3D). Cooperation of CEBPa/ETS and GATA1 has been pre- ditions in vivo and the apoptosis observed in vitro. Not appearing in viously reported in eosinophils (54). A different set of enriched the IPA, but shown to be relevant for DC specification, Zbtb46 motifs was identified when taking downregulated genes, which in- (53, 65) was also downregulated significantly in Gata1-KODC cluded motifs for TAL1, bZIP, Maz (ZF), ETS, and TBP. Tran- DCs upon LPS stimulation. scription factors recognizing these motifs have been reported to This finding together with the HOMER motif enrichment interact directly or to cooperate with GATA1 or other GATA tran- analysis, in which the GATA motif was not found to be enriched, scription factors (55–64). GO term enrichment analyses revealed a supports the notion that transcriptional differences identified number of specific processes that were affected in R26R-RG|Gata1- in R26R-RG|Gata1-KODC DCs include many indirect GATA1 KODC DCs upon LPS stimulation. An increased representation of targets. metabolic processes was observed in the set of upregulated genes, DC migration toward the lymph nodes upon LPS stimulation is and in the set of downregulated genes we observed migration, DC proliferation, and DC differentiation, but also T cell activation and impaired in Gata1-KO mice CD4+ T cell activation to be affected (Supplemental Table II). The effect of Gata1 loss on the DC transcriptome was major in Ingenuity Pathway Analysis (IPA) allowed us to assign the dif- LPS-stimulated DCs, as shown by RNA-Seq analysis. Therefore, we ferentially expressed genes into functional categories (Supplemental studied the impact of DC-specific Gata1 loss in vivo in a sterile sepsis The Journal of Immunology 4317 Downloaded from http://www.jimmunol.org/ by guest on October 1, 2021

FIGURE 2. Increased apoptosis in GM-CSF cultured Gata1-KODC DCs. (A) Flow cytometry analysis of GM-CSF cultures of WTlox and Gata1-KODC DCs in steady-state and upon LPS stimulation. DCs are gated as MHC-IIhigh CD11c+.(B) Gated DCs were analyzed by flow cytometry for expression of the activation markers CD86, MHC-II, and CD40, which are depicted as mean fluorescence intensity (MFI). WT steady state (St. St.) is set to 100. (C) Relative expression of Gata1 mRNA in GM-CSF cultured DCs. (D) Cultured DCs treated or left untreated with LPS at day 7 were harvested at day 8 or 10 of culture. Cells were stained for Annexin V and PI and analyzed by flow cytometry. Cells were gated for live cells (Annexin Vneg,PIneg), early apoptotic cells (Annexin V+,PIneg), apoptotic cells (Annexin V+,PI+), or dead cells (Annexin Vneg,PI+). Bar graphs depicting all four populations at both days are shown. Representative dot plots are shown on the right. *p # 0.05, **p # 0.01, ***p # 0.001. RFE, relative fold enrichment. 4318 GATA1 DC-TRANSCRIPTOME MODULATES CCL21-DEPENDENT MIGRATION Downloaded from http://www.jimmunol.org/ by guest on October 1, 2021

FIGURE 3. RNA-Seq analysis of Gata1-KODC DCs in steady-state and upon LPS stimulation. (A) Graphic overview of the experiment. Mouse BM cells were cultured in the presence of GM-CSF. At day 7, half of the cells were stimulated with LPS, and the other half was left in steady-state condition (ST). At day 10, cells were harvested and sorted for RNA extraction. DCs from R26R-RG|WTCre and R26R-RG|KODC DC cultures were sorted for GFP+/mCherry+ cells. Dot plots of the sorting strategy are shown. (B) quantitative RT-PCR analysis of Gata1 expression levels are depicted for sorted GFP+/mCherry+ WTCre DCs, KODC cultures (before sorting), and sorted R26R-RG|KODC DCs. Gata1 levels were further reduced in the sorted R26R-RG|KODC cells, and these were used for RNA-Seq analysis. (C) Heat map (Z-scores) of significantly deregulated genes in R26R-RG|KODC DCs in steady state, including HOMER motif enrichment analysis for downregulated and upregulated genes. (D) Heat map (Z-scores) of significantly deregulated genes in R26R-RG|KODC DCs upon LPS stimulation, including HOMER motif enrichment analysis for downregulated and upregulated genes. *p # 0.05, **p # 0.01, ***p # 0.001. RFE, relative fold enrichment. model, 24 h after i.v. injection of LPS into WTlox and Gata1-KODC numbers in the peripheral lymph nodes (PLNs) (e.g., axillary and mice. After LPS treatment, both WTlox and Gata1-KODC splenic inguinal lymph nodes) of WTlox mice, this increase was not observed DCs were significantly lower compared with PBS controls. Inter- in the PLNs from Gata1-KODC mice (Fig. 4A). This might be be- estingly, we observed that, although LPS induces an increase in DC cause of increased apoptosis in Gata1-KODC mice or reduced DC The Journal of Immunology 4319

Table II. IPA of transcriptional regulators

Symbol Log Ratio Gene Name/Description Prdm8 26.3770 PR domain containing 8 Ikzf3 26.0240 IKAROS family zinc finger 3 (Aiolos) Insm1 25.7090 Insulinoma-associated 1 Nrarp 25.1290 NOTCH-regulated ankyrin repeat protein Myb 24.4890 v- avian myeloblastosis viral oncogene homolog Meis1 24.0850 Meis 1 Pou4f1 23.8220 POU class 4 homeobox 1 Bach2 23.5780 BTB and CNC homology 1, basic transcription factor 2 Ptrf 23.2420 Polymerase I and transcript release factor Vdr 23.1090 Vitamin D (1,25-dihydroxyvitamin D3) Zfp366 23.0920 Zinc finger protein 366 Tcf7 23.0860 Transcription factor 7, T cell specific Stat4 22.8500 Signal transducer and activator of transcription 4 Aff3 22.7920 AF4/FMR2 family, member 3 Satb1 22.7570 SATB homeobox 1 Sp6 22.7230 Sp6 transcription factor Cbfa2t3 22.6880 Core-binding factor, runt domain, a subunit 2; translocated to, 3 Ssbp3 22.5000 Single-stranded DNA binding protein 3 Zeb1 22.4930 Zinc finger E-box binding homeobox 1 Jdp2 22.4870 2 Downloaded from Kdm4a 22.4290 Lysine (K)-specific demethylase 4A Gata2 22.4120 GATA binding protein 2 Irf8 22.3680 IFN regulatory factor 8 Ncoa7 22.2690 coactivator 7 Ikzf4 22.2400 IKAROS family zinc finger 4 (Eos) Hdac11 22.1510 Histone deacetylase 11 2 Batf3 2.1360 Basic leucine zipper transcription factor, ATF-like 3 http://www.jimmunol.org/ Ciita 22.1350 Class II, MHC, transactivator Crem 22.0510 cAMP responsive element modulator Uhrf1 22.0260 Ubiquitin-like with PHD and ring finger domains 1 Rel 21.9660 v- avian reticuloendotheliosis viral oncogene homolog Ezh2 21.9430 Enhancer of zeste 2 polycomb repressive complex 2 subunit Stat5a 21.9260 Signal transducer and activator of transcription 5A Phc1 21.9140 Polyhomeotic homolog 1 (Drosophila) Smarce1 21.8770 SWI/SNF related Aebp2 21.7660 AE binding protein 2 Mkl1 21.7020 Megakaryoblastic leukemia (translocation) 1 Tcf4 21.6210 Transcription factor 4 by guest on October 1, 2021 Psmg4 21.5950 Proteasome (prosome, macropain) assembly chaperone 4 Nfil3 21.5780 NF, IL 3 regulated Runx3 21.5250 Runt-related transcription factor 3 Zbtb42 21.5050 Zinc finger and BTB domain containing 42 Sp140 21.4530 SP140 nuclear body protein Tfdp2 21.4530 Transcription factor Dp-2 ( dimerization partner 2) Ets2 21.4010 v-ets avian erythroblastosis virus E26 oncogene homolog 2 Hsf2 21.3970 Heat shock transcription factor 2 Nfkb1 21.3630 NF of k light polypeptide gene enhancer in B-cells 1 Foxp1 21.3350 Forkhead box P1 Runx2 21.2910 Runt-related transcription factor 2 Zkscan17 21.2790 Zinc finger protein 496 Jazf1 21.2380 JAZF zinc finger 1 Trim29 2.1090 Tripartite motif containing 29 Maged1 1.9030 Melanoma Ag family D, 1 St18 1.6580 Suppression of tumorigenicity 18, zinc finger Creg1 1.5720 Cellular of E1A-stimulated genes 1 Tanc2 1.3270 Tetratricopeptide repeat, ankyrin repeat and coiled-coil containing 2 Tfeb 1.3060 Transcription factor EB Lmo4 1.2520 LIM domain only 4 LPS KO versus WT: transcriptional regulators of significant differentially expressed genes. migration. As shown in Fig. 2E, there were slightly more apoptotic involved in cell survival but also in migration of DCs after acti- cells in the Gata1-KODC DC cultures compared with WTlox, and vation. This is in agreement with our RNA-Seq GO term enrich- no differences were observed in early apoptotic cells or dead cells ment analysis.

24 h upon LPS stimulation. DC Therefore, we next studied whether the reduced number of DCs Gata1-KO DCs display normal CCR7 expression but have in the PLN could be caused by a reduction in migratory DCs. Based impaired migration toward CCL21 on MHC-II expression, we further categorized the DCs in the PLN DC migration to the lymph nodes is dependent on the CCR7 (66), into migratory DCs (CD11c+|MHC-IIhigh) and resident DCs and upregulation of Ccr7 is correlated with the activation of DCs. (CD11c+|MHC-IImid) and identified a reduction in migratory DCs Furthermore, RNA-Seq analysis showed a reduction of mRNA (Fig. 4B). This indicates that GATA1-regulated genes are not only expression of Ccr7 in Gata1-KODC DCs. We therefore cultured DCs 4320 GATA1 DC-TRANSCRIPTOME MODULATES CCL21-DEPENDENT MIGRATION Downloaded from http://www.jimmunol.org/ by guest on October 1, 2021

FIGURE 4. Impaired migration capacity of Gata1-KODC DCs toward the lymph nodes is selective for CCL21. (A) Percentages of DCs in different tissues 24 h after PBS or LPS injection, depicted as percentage of all nucleated cells. Samples were normalized to WT-PBS. (B) DCs were subdivided in LN-resident DCs and migratory DCs based on MHC-II expression. (C) Expression of CCR7 on the surface of GM-CSF cultured DCs from WTlox or KODC mice. (D) Migration of GM-CSF cultured DCs toward CCL19 or CCL21 expressed in relative fluorescence units (RFU). (E) Expression of PSA on the surface of GM-CSF cultured DCs from WTlox or Gata1-KODC mice. (F) CCL21 binding assay. The percentage of cells binding CCL21 and the mean fluorescence intensity (MFI) of CCL21 binding are depicted in respective bar graphs. Representative histograms are shown. *p # 0.05, **p # 0.01, ***p # 0.001. with GM-CSF and analyzed the expression of CCR7 upon LPS We tested the response of WTlox and Gata1-KODC BM-DCs stimulation on the cell surface. Surprisingly, both WTlox and Gata1- toward CCL19 and CCL21, which are the only known ligands KODC DCs showed an equally strong upregulation of CCR7 after for CCR7 (67). As expected, steady-state DC migration toward LPS stimulation (Fig. 4C). To gain insight in the migration defect CCL19 and CCL21 was minimal. Gata1-KODC DCs appeared to observed in vivo, we performed in vitro migration assays using be even less responsive than WTlox DCs, as corroborated by the different chemoattractants. random migration observed in the absence of chemoattractant The Journal of Immunology 4321

(Supplemental Fig. 1C). Upon LPS stimulation, DCs upregulate (68–70). Interestingly, the RNA-Seq data revealed that St3Gal3,a the CCR7 receptor and become responsive to CCL19 and CCL21. sialyltransferase, was significantly downregulated in Gata1-KODC The migration toward CCL19 was increased in both WTlox and DCs upon LPS stimulation when compared with WTCre DCs. A Gata1-KODC DCs to similar levels. However, migration toward deficiency in sialic acid transfer further supports the lower surface CCL21 was strongly impaired in Gata1-KODC DCs (Fig. 4D). expression of PSA displayed by Gata1-KODC DCs upon LPS CCL19 and CCL21 are very similar to each other; however, stimulation and the consequent reduction in CCL21 binding ca- unlike CCL19, CCL21 contains a highly basic C-terminal tail that pacity (although moderate), which results in impaired (but not inhibits binding to CCR7 (68). After LPS stimulation, DCs highly abolished) migration toward CCL21. upregulate PSA decoration of their surface . PSA groups Steady-state DC influx to lymph nodes is defective in aging immobilize the tail of CCL21, thus enabling its binding to CCR7 DC (69, 70). Supporting this notion, it has been shown that enzymatic Gata1-KO mice depletion of PSA affects migration toward CCL21, but not to Adequate migration of DCs toward the lymph nodes is essential for CCL19 (68–70). We next measured PSA expression in our cultures maintaining the balance of the mounted immune response, and it is and observed that, as expected, PSA expression was highly induced essential that the steady-state flux of DCs toward lymph nodes is upon LPS activation on WTlox DCs. Although we observed some kept in balance throughout life. Because we have observed de- PSA induction in Gata1-KODC DCs upon LPS activation, it was fective migration of Gata1-KODC DCs toward lymph nodes as a significantly lower than in WTlox DCs (Fig. 4E). To ensure that the result of an acute response toward LPS stimulation, and we have decreased PSA levels indeed affected CCL21 binding, we per- identified that this defect is CCL21 selective, we hypothesized that formed a CCL21 binding assay. We found that the capacity of the steady-state influx of DC migration toward lymph nodes would Gata1-KODC DCs to bind CCL21 was significantly reduced, al- be impaired. To test this hypothesis, we allowed Gata1-KODC mice Downloaded from though moderately (Fig. 4F). These data explain the selective and WTlox littermates to age, and sacrificed them to analyze the DC defective migration of Gata1-KODC DCs toward CCL21, whereas compartment at around 40 wk of age. We did not observe notable leaving DC migration toward CCL19 intact. This is in agreement differences in organ sizes (data not shown), or in organ abso- with the glycosylation-specific effects on ligand binding to CCR7 lute cell numbers (Fig. 5C). Flow cytometry analysis of the DC http://www.jimmunol.org/ by guest on October 1, 2021

FIGURE 5. Defective steady-state in- flux of DCs toward lymph nodes as seen in aging Gata1-KODC mice. (A) The absolute number of DCs found in dif- ferent tissues of aged mice (around 40 wk of age). (B) The percentage of DCs in different tissues of aged mice, depicted as percentage of all nucleated cells. (C) Total number of cells isolated from dif- ferent tissues of aged mice. (D) cDCs from PLNs were further subdivided in- to CD8+ or CD11b+ subsets. Absolute cell numbers were depicted. (E)CD8+ or CD11b+ subsets from the PLNs were depicted as percentage of all nucle- ated cells. Values obtained for WTlox animals are set to 100%. **p # 0.01, ***p # 0.001. 4322 GATA1 DC-TRANSCRIPTOME MODULATES CCL21-DEPENDENT MIGRATION compartment in the spleen revealed, in contrast with young mice, Because CCL19 and CCL21 are the known ligands for CCR7 no significant differences in Gata1-KODC versus WTlox aged mice receptor (67), we assayed in vitro the migration capacity of Gata1- both in percentage and absolute numbers. DCs were significantly KODC DCs toward these chemoattractants. Steady-state DC mi- reduced in lymph nodes of Gata1-KODC aged mice compared with gration toward CCL19 and CCL21 was as expected minimal, with WTlox aged mice; this was not found in young mice (Fig. 5A, 5B, Gata1-KODC DCs apparently even less responsive than WTlox DCs, gating in Fig. 1C). Further subdivision into CD11b+ and CD8+ as corroborated by the random migration observed in the absence subsets revealed that the decrease of total cDCs in the PLN was of chemoattractant. GO-Term analysis of our RNA-Seq data revealed due to a decrease in both subsets, with CD11b+ DCs more strongly alterations in “motility pathways.” One of the genes important for affected (Fig. 5D, 5E). migration is myosin L chain kinase, and it is 4.1-fold downregulated Taken together, GATA1 loss in DCs affects DC survival and in Gata1-KODC DCs RNA-seq, which might explain this reduced migration capacity in homeostatic conditions and upon activation. motility. When we stimulated DCs with LPS, we observed a specific We identified a selective impairment of Gata1-KODC DCs to migrate migration defect of Gata1-KODC DCs toward CCL21. The two li- toward CCL21, which could be explained by lower expression of gands are highly similar; however, unlike CCL19, CCL21 contains PSA upon DC activation. In young mice, this defect is reflected by a highly basic C-terminal tail of 32 aa (67, 68). This C-terminal tail the initial DC reduction in spleen in homeostatic conditions, fol- of CCL21 autoinhibits binding to CCR7 (69). PSA, highly lowed by impaired influx of DCs in lymph nodes upon sterile in- expressed on activated DCs, fixes the C-terminal tail of CCL21, flammation. In aged mice, we observe abnormal DC homeostasis in thereby facilitating its binding to CCR7 (69, 70). Depletion of the PLNs, whereas the DC numbers in the spleen are within the PSA from the cell surface by Endo-neuraminidase treatment or normal range. The reason for this shift in DC homeostasis from small interfering RNA against St8sia4 sialyltransferase impairs spleen to PLN in aging mice might be because of the prolonged (or migration toward CCL21, but not toward CCL19 (68–70). Indeed, Downloaded from chronic) pressure of the net effect of migration and survival defects we found a reduced expression of PSA on the surface of Gata1- caused by GATA1 loss. However, no strong evidence for this is KODC DCs that could explain the defective migration toward provided. CCL21, whereas retaining normal migration toward CCL19. No- tably, the reduction of PSA surface levels in GATA1-KODC DCs Discussion had only a moderate reduction effect on CCL21 binding. This Transcription factor GATA1 is essential in the erythroid, eosin- suggests that there might be other determinants regulating CCL21 http://www.jimmunol.org/ ophilic, and megakaryocytic lineages (25–27, 29). It is also binding and selective DC migration, and we cannot exclude that expressed in mast cells, although GATA1 is dispensable in this they behave differently between Gata1-KODC and WT DCs. Such lineage (71). We previously reported that GATA1 is important for determinants might include a potential transient character of the the development of murine DCs (24, 27). Similarly, the role of interaction between PSA and the CCL21 tail, receptor trafficking GATA1 during human DC differentiation from monocytes was and downstream signaling (74), autocrine DC mechanisms that reported by another group (26). In this study, we further dis- block DC cell migration (and potentially CCL21 binding), or DC sected the role of GATA1 in DCs with the use of a DC-specific survival (75, 76). CCL21, and not CCL19, was found to be the Gata1 KO mouse model, a necessary step to understand the role of critical factor for DC homing to lymph nodes (77). The fact that by guest on October 1, 2021 GATA1 in DCs because previous studies used inducible ubiquitous proper DC migration toward CCL21 is dependent on the PSA deletion of Gata1. surface levels led several groups to identify the receptors that need Gata1-KODC mice displayed reduced numbers of DCs in the to be polysialylated to allow CCL21 to be recognized by CCR7. It spleen in the steady-state. Because GATA1 is linked to the positive has been suggested that PSA acceptor molecule Neuropilin-2 is regulation of cell survival in several cell types (28, 30), we hypoth- the relevant factor involved in this process (see Rey-Gallardo et al. esized this might also be a crucial function regulated by GATA1 in [68]), although downregulation in human monocyte-derived DCs DCs. Indeed, we found increased apoptosis in cultured BM-derived did not completely abrogate the capacity to migrate toward Gata1-KODC DCs. CCL21. Recently, it has been shown that CCR7 itself carries PSA RNA-Seq analysis of Gata1 KO DCs compared with WTCre modifications (78); however, we do not know at what extent PSA DCs in the steady-state and upon LPS stimulation revealed major downregulation affects either of the two PSA acceptors in Gata1- changes in the transcriptome in LPS-stimulated DCs, including KODC DCs compared with WT. Our study shows that proper sialylation deregulation of a plethora of other transcription regulators that are depends on transcriptional programs, in particular downstream of known to be essential in the DC lineage. GO term enrichment GATA1, which are induced upon DC activation (i.e., LPS stimu- analysis revealed pathways related to cell survival, cell migration, and lation). Defects in this regulatory process lead to defective migration of DC function. This led us to investigate the DC compartment in vivo DCs toward lymph nodes, not only upon an acute stimulus (i.e., LPS upon induction of sterile inflammation by i.v. injection of LPS. stimulation in vitro or in vivo) but also affecting the steady-state in- Interestingly, when we challenged the mice with LPS, we found flux of DCs toward lymph nodes, as shown by the reduced number of a migration defect of Gata1-KODC DCs toward the PLNs. DC DCs in lymph nodes in aging Gata1-KODC mice. migration toward the PLN is dependent on CCR7 receptor expres- PSA is a sugar molecule expressed on the cell surface of sion, which is strongly upregulated on the DC surface after activa- eukaryotic cells, with a complex biosynthesis involving multiple tion (66, 72, 73). DCs deficient for CCR7 expression are not able to sialyltransferases (79). For example, a group of sialyltransferases migrate to the lymph nodes (66, 72, 73). The expression of CCR7 is adds sialic acid with an a-2,3 linkage to galactose (i.e., St3gal typically correlated to upregulation of DC activation markers sialyltransferases, including St3gal3, which uses O-glycans as (e.g., MHC-II, CD86, and CD40) but can also be induced in an well as N-glycans as substrate), whereas other sialyltransferases add activation-independent manner, for example, after uptake of apo- sialic acid with an a-2,6 linkage to galactose or N-acetylgalactosamine ptotic cells (72). CCR7 protein expression on the surface of Gata1- (i.e., St6gal and St6galnac sialyltransferases including St6gal1, which KODC DCs was normal compared with WTlox DCs as shown by uses N-glycans as substrate). A peculiar type of sialyltransferase adds flow cytometry analysis. This suggested that there must be another sialic acid to other sialic acid units with an a-2,8 linkage, forming mechanism interfering with the proper migration of Gata1-KODC structures referred to as PSA (i.e., St8sia sialyltransferases including DCs toward the PLNs. St8sia4, which uses N-glycans as substrate) (80). Mice deficient for The Journal of Immunology 4323

St8sia4 completely lose PSA on the surface of DCs (81). RNA-Seq 17. Wu, L., A. D’Amico, K. D. Winkel, M. Suter, D. Lo, and K. Shortman. 1998. analysis revealed a number of sialyltransferases to be downregu- RelB is essential for the development of myeloid-related CD8alpha- dendritic DC cells but not of lymphoid-related CD8alpha+ dendritic cells. Immunity 9: 839–847. lated in Gata1-KO DCs, although only St3gal3 reached statistical 18. Tussiwand, R., B. Everts, G. E. Grajales-Reyes, N. M. Kretzer, A. Iwata, significance. St3gal3 is not directly involved in PSA modification; J. Bagaitkar, X. Wu, R. Wong, D. A. Anderson, T. L. Murphy, et al. 2015. Klf4 expression in conventional dendritic cells is required for T helper 2 cell responses. however, it is involved in the generation of carbohydrate Ag sialyl- Immunity 42: 916–928. Lewis. As opposed to models in which St8sia4 is depleted, in our 19. Hildner, K., B. T. Edelson, W. E. Purtha, M. Diamond, H. 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D WTlox - Steady State Gata1-KODC - Steady State F Live Live 30 5 5 10 10 GSM1520422_Macrophages GSM1520423_Macrophages

4 4 10 10

3 DCs 3 DCs

CD11c 10 CD11c 10 88.2 85.3 20

0 0 MF-like cells 3 3 -10 -10 20 3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 GSM722533_DC_WT 88.2 MHC-II MHC-II GSM722533_DC_WT DCs DCs 15 10 GSM1620172_DC_WT GSM1620172_DC_WT 5 5 10 10 MF-like MF-like 15.0 12.9 10 DC_KO_ST

4 4 pc2 10 10 DC_KO_ST DC_WT_ST DC_WT_ST

% F4/80 of DCs 0

F4/80 3 F4/80 3 10 10 5

0 0

3 3 -10 -10 0 3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 lox DC CD24 CD24 WT Gata1-KO DC_KO_LPS −10

DC_KO_LPS DC_WT_LPS E WTlox - Steady State Gata1-KODC - Steady State Live Live

5 5 DC_WT_LPS 10 10 −20

4 4 10 10 GSM624287_DC_LPS_6h

3 3 10 10 GSM624287_DC_LPS_6h CD11c CD11c DCs DCs 0 88.5 0 87.6 −50 −25 0 25 MF-like cells 3 3 -10 -10 20 pc1 3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 MHC-II MHC-II

15 DCs DCs of DCs neg

5 5 10 10 10

4 4 10 10 |MHC-II +

3 3 CD11b 10 CD11b 10 5 MF-like MF-like 0 12.3 0 15.8 %CD11b

3 -10 3 -10 0 3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 WTlox Gata1-KODC MHC-II MHC-II Supplemental Figure 1. Gata1 expression, random migration and GM-CSF BM-derived DC cultures A) Western Blot analysis of GATA1 expression in sorted splenic CD4+ and CD8+ T cells. GATA1 is barely detectable, while GATA1s is present in both T cell subsets, although at a lower amount compared to I/11 erythroid cell line. Anti-GATA1 antibody (M20) was used that recognises both GATA1 and GATA1s. Anti-GAPDH antibody was used as loading control (same membrane). B) Western Blot analyses of GATA1 expression in BM-derived GM-CSF cultures. GATA1 is not detectable in Steady State Gata1-KODC, while visible upon LPS, although at the same level than in Steady State (St. St.) WT cultures. GATA1s is detected in all samples, it is upregulated upon LPS, and quantitation shows a reduction in KO samples (average of 3 KO samples and 2 WT samples is depicted, representative gel is shown). Antibodies used on the same membrane were Anti-GATA1 (M20) that recognises both GATA1 and GATA1s, Anti-GATA1 (N6) that recognises only GATA1, and Anti-GAPDH as loading control. C) Bar graph representing random migration of WTlox and Gata1-KODC DCs without stimulus. Percentage is depicted. Although not significant, Gata1-KODC DCs display a tendency to reduction on random migration. D) GM-CSF BM-derived cultures analysis, using F4/80 as a macrophage (MF) marker. The percentage of F4/80 cells (MF-like cells) of CD11chigh cells is equal amongst WTlox and Gata1-KODC DCs, and lower than 20% on average. E) GM-CSF BM-derived cultures analysis. The percentage of MF-like cells within the CD11chigh population, measured as CD11b|MHC-IIlow is equal amongst WTlox and Gata1-KODC DCs, and lower than 20% on average. F) Principal Component Analysis (PCA) of our RNA-Seq data, and publicly available RNA-Seq data of cultured BM-derived M-CSF MFs (GSM1520423, GSM1520422) and GM-CSF DCs (GSM624287, GSM 722533 and GSM1620172). Analysis shows that BM-derived GM-CSF DCs (including our dataset) separate from BM-derived MFs. A Downregulated genes N = 599 Tinagl1 Scube1 Syt9 Scara3 Slco5a1 Ccl7 Sema7a Slc6a15 Ccl2 Slamf1 Mfsd2a Cd70 Tnfrsf13c Transporter Cytokine Ccl17 Transmembrane receptor Lif Rerg Enzyme Sod3 Cyp2s1 Bzw1 Hdc Categorised Translation regulator Dpysl5 Transcription regulator Prdm8 Ikzf3 Insm1 Nrarp Myb Ptprf Pdcd1 Dusp14 Dusp2 Adra1b Dusp5 Cxcr5 Phosphatase Gpr68 G-protein coupled receptor Gprc5a Non - categorised Celf6 Plat Gpr126 11 Peptidase Cdhr1 Adam Growth factor Tgfb3 Mmp25 Faim3 Ligand-dependent Ion channel Fgf1 Itga3 Adam19 Kinase Tgfb2 Dpp4 nuclear receptor Kctd14 Pard3b Prkcq Pdgfb Nr4a1 Kcnn1 Camk2b Pdgfc Nr4a2 Scn4b Mpp2 Nr4a3 Cacnb3 Flt3 P2rx5 Mylk

Upregulated genes N = 283

Apoe Nrxn2 Categorised Slc36a2 Colec12 Abcd2 Cxcl14 Tlr8 Abca9 Cytokine Nradd Gp6 Transporter Pira6 Plxnb3 Hal Transmembrane receptor Enzyme Gdpd3 Trim29 Acaa1b Maged1 Acot1 St18 Agmo Creg1 Tanc2 Transcription regulator Adamdec1 Ppef2 Non - categorised Ephx1 Ptpn18 Gm1821 Klk1b27 Phosphatase Hebp2 C1ra Mex3a F7 Peptidase Nes Ligand-dependent nuclear receptor Sycp1 Rxra Fgr Kinase Aatk Ryk Tgfbr2 Ednrb Prkcb Ion channel Ffar2 Ccr2 Kctd12b Growth factor Cysltr1 Best1 G-protein coupled receptor Igf1 Fpr2 P2rx7 Trpm2 Rasa3

B C DC RNA-Seq MA plot DC RNA-Seq MA plot 1 Sample Reads % aligned Uniquely mapped % Uniquely mapped Steady State LPS reads2 reads KO.ST1 18,321,398 93.97 12,243,848 66.82 KO.LPS1 13,783,768 90.34 8,889,752 64.49 KO.ST2 15,875,929 93.52 10,174,720 64.09 KO.LPS2 12,331,627 92.28 8,005,151 64.92 WT.ST1 15,335,890 92.77 9,855,387 64.26 WT.LPS1 14,499,114 93.43 8,488,443 58.54 WT.ST2 19,324,572 93.63 12,536,554 64.87 WT.LPS2 23,141,069 93.20 15,495,249 66.96

1Reads: Total reads from sequencer 2Uniquely mapped reads: Uniquely mapped to exonic regions of genes Log2 fold change (KO vs WT) Log2 fold change (KO vs WT) Significant differentially expressed genes (FDR adj. p-val. < 0.05) Contrast Total sig. genes Sig. Up Sig. Down Mean normalized counts Mean normalized counts ST KO vs WT 30 15 15 LPS KO vs WT 898 289 609

Supplemental Figure 2. RNA-Seq A) Ingenuity Pathway Analysis (IPA) of functional categories of differentially expressed genes in R26R-RG|KODC DCs upon LPS stimulation. Downregulated genes (upper pie charts) and upregulated genes (lower pie charts) are depicted. B) The RNA-Seq reads summary is depicted, including the number of differentially expressed genes comparing R26R-RG|Gata1-KODC and WTCre DCs in Steady State and upon LPS stimulation. C) MA Plots of RNA-Seq comparing R26R-RG|Gata1-KODC vs. WTCre DCs in Steady State and upon LPS stimulation. Red dots are significant differentially expressed genes. Supplemental Table I: Differentially expressed genes RNA-Seq LPS KO vs WT List of significant differentially expressed genes LPS KO vs WT DC comparison.

Log, log transformed; FC, fold change; CPM, counts per million; LR, log2 fold change ratio; FDR, false discovery rate.

Gene Name logFC logCPM LR P Value FDR 1110032F04Rik -3.93 2.36 10.58 0.0011 0.0219 1110038B12Rik -1.39 4.88 9.64 0.0019 0.0315 1190002N15Rik 1.66 4.32 15.93 0.0001 0.0027 1500012F01Rik -1.19 6.26 8.55 0.0035 0.0472 1700024P16Rik -3.07 4.50 12.23 0.0005 0.0114 1700026L06Rik 1.82 2.26 9.07 0.0026 0.0392 1700040N02Rik -8.09 0.47 20.55 0.0000 0.0004 1810033B17Rik 2.14 7.06 26.73 0.0000 0.0000 2010005H15Rik -3.01 2.04 14.55 0.0001 0.0047 2410006H16Rik -1.86 7.18 20.66 0.0000 0.0004 4930426L09Rik -4.42 1.84 11.81 0.0006 0.0135 4930503L19Rik -1.60 4.54 12.55 0.0004 0.0102 4930520O04Rik -2.43 4.89 16.13 0.0001 0.0025 4930525D18Rik -3.09 1.76 10.21 0.0014 0.0252 4930539E08Rik -2.87 1.67 17.25 0.0000 0.0015 4932438H23Rik -4.01 1.29 15.59 0.0001 0.0030 5430435G22Rik 1.58 6.38 12.42 0.0004 0.0107 5730420D15Rik -3.07 1.12 9.11 0.0025 0.0383 5730508B09Rik 1.45 3.99 9.14 0.0025 0.0381 6030468B19Rik -5.45 0.87 8.68 0.0032 0.0449 6330403A02Rik 2.64 2.37 11.68 0.0006 0.0142 6430548M08Rik 1.81 5.18 13.64 0.0002 0.0068 9130008F23Rik -3.05 2.35 20.30 0.0000 0.0004 A330009N23Rik -4.10 1.77 19.84 0.0000 0.0005 A330023F24Rik 1.81 2.15 8.68 0.0032 0.0449 A430078G23Rik 2.97 1.18 8.83 0.0030 0.0426 AA467197 -1.30 7.40 9.63 0.0019 0.0317 Aatk 2.14 4.89 16.16 0.0001 0.0024 AB124611 1.61 6.17 13.48 0.0002 0.0072 Abca9 2.92 4.34 18.11 0.0000 0.0011 Abcd2 3.05 5.48 21.05 0.0000 0.0003 Abhd6 -3.84 1.05 18.72 0.0000 0.0009 Abi3 1.34 6.29 13.36 0.0003 0.0074 Abi3bp -4.36 1.35 12.37 0.0004 0.0108 Ablim1 -2.35 3.75 16.91 0.0000 0.0018 Abp1 -2.99 3.33 10.08 0.0015 0.0264 Abtb2 -2.69 6.49 21.45 0.0000 0.0003 Acaa1b 5.96 0.56 28.63 0.0000 0.0000 Acer3 1.46 4.78 11.34 0.0008 0.0161 Acot1 5.40 0.30 10.57 0.0011 0.0219 Acp1 -1.92 2.79 12.04 0.0005 0.0124 Acsl1 1.62 9.46 11.71 0.0006 0.0140 Acss2 1.87 4.96 22.32 0.0000 0.0002 Actg1 -1.29 5.10 12.03 0.0005 0.0125 Actn1 -1.90 8.95 9.41 0.0022 0.0344 Adam11 -4.09 5.98 20.83 0.0000 0.0004 Adam19 -2.51 7.45 10.11 0.0015 0.0261 Adamdec1 3.93 0.94 13.02 0.0003 0.0085 Adcy6 -3.07 8.61 10.86 0.0010 0.0194 Gene Name logFC logCPM LR P Value FDR

Adgb -6.18 3.83 63.34 0.0000 0.0000 Adh7 3.38 2.74 13.91 0.0002 0.0061 Adora2a -1.59 7.02 15.60 0.0001 0.0030 Adra1b -5.98 -0.36 9.69 0.0019 0.0309 Adra2a -2.14 5.32 17.15 0.0000 0.0016 Adrbk2 -2.33 7.34 22.31 0.0000 0.0002 Aebp2 -1.77 7.56 14.85 0.0001 0.0042 Aff3 -2.79 3.56 17.15 0.0000 0.0016 Agmo 4.08 0.03 10.44 0.0012 0.0230 Agpat5 1.18 4.68 8.53 0.0035 0.0476 Agrn -1.56 7.29 13.02 0.0003 0.0085 AI836003 -4.33 2.65 36.08 0.0000 0.0000 AI854517 -4.03 2.17 17.03 0.0000 0.0017 Aif1 1.61 5.32 9.79 0.0018 0.0297 Akap2 -3.52 5.95 16.72 0.0000 0.0019 Akr1c13 1.48 4.11 10.74 0.0010 0.0204 Aldh18a1 -1.39 3.95 8.94 0.0028 0.0409 Aldh1a2 -2.10 7.04 11.42 0.0007 0.0157 Aldh2 1.32 8.60 9.43 0.0021 0.0342 Alox5ap 1.52 7.83 10.96 0.0009 0.0186 Ank -1.12 5.98 8.42 0.0037 0.0499 Ankrd33b -2.38 6.93 27.46 0.0000 0.0000 Ankrd37 2.75 4.76 33.84 0.0000 0.0000 Ankrd44 -1.81 8.00 8.97 0.0027 0.0407 Ankrd66 1.48 4.35 8.77 0.0031 0.0438 Antxr1 1.71 3.62 12.38 0.0004 0.0108 Aox1 2.63 0.91 8.94 0.0028 0.0408 Apoa1bp -1.35 6.77 12.24 0.0005 0.0113 Apobec3 -1.78 6.82 10.04 0.0015 0.0268 Apoc2 1.46 5.81 11.37 0.0007 0.0159 Apoe 3.82 11.51 33.25 0.0000 0.0000 Apol10b -6.42 2.23 15.35 0.0001 0.0034 Apol7c -4.71 7.36 10.83 0.0010 0.0197 Arap2 -1.91 6.46 20.96 0.0000 0.0004 Arc -2.60 6.69 12.67 0.0004 0.0097 Arhgap22 -1.68 5.85 12.44 0.0004 0.0106 Arhgap26 -2.72 6.13 36.42 0.0000 0.0000 Arhgap28 -2.42 4.57 16.29 0.0001 0.0023 Arhgef40 -2.54 7.78 18.52 0.0000 0.0009 Arid3b -1.30 4.86 8.60 0.0034 0.0463 Arl11 1.45 5.87 15.48 0.0001 0.0032 Arl14 -4.87 0.35 18.18 0.0000 0.0011 Arsg 2.11 2.59 13.49 0.0002 0.0072 Asah2 1.92 3.74 11.22 0.0008 0.0168 Asph -1.36 6.44 11.41 0.0007 0.0157 Atp13a2 1.46 8.11 12.47 0.0004 0.0105 Atp1a3 1.55 8.21 9.56 0.0020 0.0325 Atp2b4 -3.03 5.53 24.93 0.0000 0.0001 Auh -1.10 5.34 8.77 0.0031 0.0438 Avpi1 -1.83 5.17 20.79 0.0000 0.0004 AW011738 -2.06 3.45 16.70 0.0000 0.0019 B230378P21Rik 3.30 2.34 14.38 0.0001 0.0051 B3galnt1 -2.57 4.91 25.21 0.0000 0.0001 B3gnt5 -4.29 3.09 11.88 0.0006 0.0132 B4galt6 1.57 6.09 10.28 0.0013 0.0247 Bach2 -3.58 1.77 10.72 0.0011 0.0206

2 Gene Name logFC logCPM LR P Value FDR

Batf3 -2.14 5.88 25.05 0.0000 0.0001 BC022687 2.90 4.03 22.42 0.0000 0.0002 BC035044 -2.68 3.33 15.43 0.0001 0.0033 Bcas1 -2.93 1.93 8.61 0.0033 0.0461 Bcl2l14 -3.51 4.10 24.80 0.0000 0.0001 Bend4 -3.24 5.67 42.45 0.0000 0.0000 Best1 2.18 4.67 10.92 0.0009 0.0189 Bmyc -2.46 5.35 31.47 0.0000 0.0000 Bnip3 1.52 4.34 9.87 0.0017 0.0287 Bst1 1.36 8.17 8.95 0.0028 0.0408 Btla -3.46 1.60 17.61 0.0000 0.0013 Bzw1 -1.14 7.41 8.69 0.0032 0.0447 C1qa 1.87 7.42 12.72 0.0004 0.0095 C1qc 1.82 7.88 9.57 0.0020 0.0324 C1ra 1.57 4.28 11.89 0.0006 0.0131 Cacnb3 -2.69 10.18 11.92 0.0006 0.0130 Calcb -3.33 0.41 11.10 0.0009 0.0176 Calm1 -1.88 10.01 13.30 0.0003 0.0076 Calm4 -5.85 0.98 9.39 0.0022 0.0345 Calm5 -3.82 2.05 8.95 0.0028 0.0408 Camk1 1.19 5.48 10.05 0.0015 0.0268 Camk2b -5.37 1.88 24.05 0.0000 0.0001 Camk4 -3.55 4.00 22.23 0.0000 0.0002 Capn2 -1.24 6.81 10.31 0.0013 0.0244 Car2 -2.63 5.70 24.86 0.0000 0.0001 Cat 1.32 8.61 9.15 0.0025 0.0379 Catsperg1 -1.72 3.97 9.52 0.0020 0.0328 Cbfa2t3 -2.69 7.04 11.20 0.0008 0.0170 Cblb -2.11 7.84 17.53 0.0000 0.0014 Cbr3 1.44 4.13 10.13 0.0015 0.0259 Ccdc88c -2.14 3.96 15.07 0.0001 0.0038 Ccl17 -3.61 7.85 41.78 0.0000 0.0000 Ccl2 -5.06 6.70 39.17 0.0000 0.0000 Ccl22 -3.04 12.24 14.39 0.0001 0.0050 Ccl3 -1.42 6.13 9.97 0.0016 0.0275 Ccl7 -5.12 3.78 23.77 0.0000 0.0001 Ccnd2 -2.49 7.72 11.83 0.0006 0.0134 Ccr2 2.29 8.26 12.49 0.0004 0.0105 Ccr4 -1.87 2.30 9.79 0.0018 0.0297 Ccr7 -2.59 10.53 22.30 0.0000 0.0002 Cd1d2 -4.02 1.91 29.56 0.0000 0.0000 Cd200 -1.51 7.17 14.14 0.0002 0.0055 Cd200r1 1.53 6.69 10.74 0.0010 0.0204 Cd200r2 3.63 1.35 18.90 0.0000 0.0008 Cd22 1.83 4.80 12.37 0.0004 0.0108 Cd300lb 1.47 6.89 13.21 0.0003 0.0079 Cd300ld 1.16 6.02 9.59 0.0020 0.0321 Cd302 1.41 5.95 14.22 0.0002 0.0054 Cd34 -2.46 5.20 9.59 0.0020 0.0321 Cd38 2.20 7.55 24.94 0.0000 0.0001 Cd40 -1.47 6.02 10.46 0.0012 0.0229 Cd63 1.44 7.54 10.24 0.0014 0.0250 Cd70 -4.14 2.31 32.42 0.0000 0.0000 Cd72 -1.86 5.32 15.75 0.0001 0.0029 Cd80 -2.88 7.06 28.48 0.0000 0.0000 Cd83 -2.71 8.91 20.39 0.0000 0.0004

3 Gene Name logFC logCPM LR P Value FDR

Cd84 1.32 8.18 9.31 0.0023 0.0355 Cd86 -2.96 7.67 48.12 0.0000 0.0000 Cd8a -6.30 0.74 13.40 0.0003 0.0074 Cd93 1.40 6.92 11.87 0.0006 0.0132 Cd99l2 1.58 3.60 11.31 0.0008 0.0162 Cdc42ep4 -1.18 5.01 9.55 0.0020 0.0326 Cdh1 -1.88 4.45 9.90 0.0016 0.0283 Cdh23 -2.40 3.97 12.64 0.0004 0.0098 Cdhr1 -8.19 1.61 16.31 0.0001 0.0023 Cdk5r1 -2.29 3.63 9.39 0.0022 0.0345 Cdk6 -1.89 3.96 12.29 0.0005 0.0111 Cdo1 3.40 3.51 28.78 0.0000 0.0000 Cdon -4.01 2.71 18.99 0.0000 0.0008 Ceacam15 -2.85 6.16 15.43 0.0001 0.0033 Celf6 -9.19 1.72 36.36 0.0000 0.0000 Cenpa -1.98 5.46 10.55 0.0012 0.0221 Cep19 -1.47 3.79 9.66 0.0019 0.0313 Cfh 5.18 3.74 18.31 0.0000 0.0010 Chchd6 1.77 3.11 10.38 0.0013 0.0236 Chdh 2.18 1.87 10.03 0.0015 0.0269 Chi3l3 2.37 6.65 8.53 0.0035 0.0476 Chst11 -1.28 7.56 9.32 0.0023 0.0353 Chst3 -4.46 3.26 16.19 0.0001 0.0024 Ciita -2.13 7.52 14.83 0.0001 0.0042 Cish -2.31 6.30 24.44 0.0000 0.0001 Cldn10 -4.54 0.95 17.51 0.0000 0.0014 Cldn25 -1.35 6.98 11.01 0.0009 0.0183 Clec10a 5.06 5.47 67.01 0.0000 0.0000 Clec2i -1.72 5.12 11.75 0.0006 0.0138 Clec4a2 2.18 6.15 33.23 0.0000 0.0000 Clec4a3 2.36 5.65 30.36 0.0000 0.0000 Clec4b1 4.34 3.00 18.10 0.0000 0.0011 Clec4n 1.50 9.65 9.53 0.0020 0.0328 Cmc2 -1.48 5.23 13.30 0.0003 0.0076 Cmklr1 1.76 6.13 8.60 0.0034 0.0462 Cnn2 -2.63 8.31 22.70 0.0000 0.0002 Cnn3 -2.38 1.70 9.13 0.0025 0.0382 Coch -4.29 0.80 16.43 0.0001 0.0022 Col1a1 -7.11 1.60 12.76 0.0004 0.0094 Col24a1 3.16 2.70 11.31 0.0008 0.0162 Col27a1 -1.38 5.22 10.53 0.0012 0.0222 Colec12 3.48 5.32 63.62 0.0000 0.0000 Creg1 1.57 9.88 9.15 0.0025 0.0380 Crem -2.05 4.87 25.69 0.0000 0.0001 Crip1 -2.13 7.77 13.40 0.0003 0.0074 Csf3r 1.50 4.83 9.39 0.0022 0.0345 Csgalnact1 -4.43 1.60 17.18 0.0000 0.0016 Csrp1 -1.31 6.89 9.94 0.0016 0.0279 Cx3cl1 -3.07 7.96 13.02 0.0003 0.0085 Cxcl10 -3.18 4.09 26.94 0.0000 0.0000 Cxcl11 -2.78 1.32 8.67 0.0032 0.0451 Cxcl14 2.45 5.07 18.57 0.0000 0.0009 Cxcr5 -3.82 3.00 30.92 0.0000 0.0000 Cxxc5 -2.16 3.44 10.04 0.0015 0.0268 Cyb5r1 1.33 5.29 11.73 0.0006 0.0139 Cyp2s1 -5.31 2.42 23.46 0.0000 0.0001

4 Gene Name logFC logCPM LR P Value FDR

Cysltr1 2.00 4.56 14.14 0.0002 0.0055 Cystm1 -3.38 2.95 22.68 0.0000 0.0002 Cytip -3.13 10.17 28.01 0.0000 0.0000 D3Bwg0562e -2.88 3.25 16.04 0.0001 0.0026 D830031N03Rik -2.89 2.33 10.43 0.0012 0.0232 D930015E06Rik -2.34 8.09 20.41 0.0000 0.0004 Dact2 2.32 1.31 10.94 0.0009 0.0188 Dao -2.61 2.58 9.84 0.0017 0.0290 Dapk1 1.25 6.27 9.85 0.0017 0.0290 Dbn1 -4.91 2.24 15.84 0.0001 0.0028 Dclk2 -2.91 1.35 10.67 0.0011 0.0210 Dclre1c -1.33 6.67 8.66 0.0032 0.0452 Dcn -3.06 1.05 12.13 0.0005 0.0119 Dcun1d3 1.38 4.81 11.09 0.0009 0.0176 Dennd4a -1.61 7.21 10.47 0.0012 0.0228 Dgka -2.02 6.59 17.19 0.0000 0.0016 Dgkg -2.54 1.85 10.19 0.0014 0.0253 Dhcr7 1.31 5.19 9.39 0.0022 0.0345 Dhdh 1.57 5.17 13.05 0.0003 0.0084 Dhrs7 1.61 5.48 18.99 0.0000 0.0008 Dlc1 -5.91 1.00 21.45 0.0000 0.0003 Dlgap3 -2.81 1.78 10.56 0.0012 0.0220 Dmwd -2.99 2.62 19.29 0.0000 0.0007 Dnahc2 -1.60 5.10 9.13 0.0025 0.0382 Dnajc12 -1.29 4.54 8.73 0.0031 0.0443 Dnase1l3 -2.80 0.79 8.80 0.0030 0.0432 Dnase2a 1.31 6.60 11.26 0.0008 0.0165 Dok2 1.45 6.19 9.98 0.0016 0.0275 Dpf3 -3.67 1.05 9.80 0.0017 0.0297 Dpp4 -2.42 5.52 14.94 0.0001 0.0040 Dpysl5 -4.51 4.75 22.03 0.0000 0.0002 Dram1 1.50 5.99 10.10 0.0015 0.0262 Dscam -4.09 4.00 15.81 0.0001 0.0028 Dusp1 -2.01 6.52 21.36 0.0000 0.0003 Dusp14 -3.28 2.47 13.85 0.0002 0.0062 Dusp16 -1.21 6.26 9.77 0.0018 0.0299 Dusp2 -2.81 1.74 11.14 0.0008 0.0173 Dusp5 -2.64 6.39 25.53 0.0000 0.0001 E130311K13Rik -1.53 3.77 9.88 0.0017 0.0286 Ears2 -2.33 4.46 9.98 0.0016 0.0275 Ednrb 4.23 0.81 14.04 0.0002 0.0057 Efna2 -3.07 3.74 11.34 0.0008 0.0161 Elmo1 -2.58 5.80 29.79 0.0000 0.0000 Elovl7 -1.73 2.91 9.06 0.0026 0.0393 Emilin1 1.50 6.10 13.49 0.0002 0.0072 Emp1 -2.43 4.77 10.19 0.0014 0.0253 Enah -3.55 4.65 11.42 0.0007 0.0157 Enpp1 2.77 1.79 14.37 0.0001 0.0051 Enpp2 -3.80 6.63 24.31 0.0000 0.0001 Epb4.1l1 1.43 5.36 11.02 0.0009 0.0182 Ephx1 2.32 6.29 35.81 0.0000 0.0000 Eps8l2 -2.64 4.50 10.86 0.0010 0.0194 Erlin1 -1.75 6.12 9.69 0.0018 0.0309 Esam 2.43 1.33 11.12 0.0009 0.0176 Etnk2 -3.20 1.98 14.30 0.0002 0.0052 Ets2 -1.40 6.52 13.68 0.0002 0.0067

5 Gene Name logFC logCPM LR P Value FDR

Eva1b -1.10 5.09 8.71 0.0032 0.0446 Evi2a 1.34 6.10 9.61 0.0019 0.0319 Evi2b 1.26 6.68 8.97 0.0027 0.0407 Extl1 -4.04 4.35 10.46 0.0012 0.0229 Ezh2 -1.94 5.28 21.78 0.0000 0.0002 Ezr -1.55 7.46 15.32 0.0001 0.0034 F5 -3.68 4.35 14.39 0.0001 0.0050 F7 1.31 6.96 8.87 0.0029 0.0420 F730043M19Rik -1.65 4.32 11.91 0.0006 0.0131 Faim3 -7.59 0.73 17.84 0.0000 0.0012 Fam107b -1.36 6.63 11.38 0.0007 0.0159 Fam110a -2.39 4.71 32.10 0.0000 0.0000 Fam117a 1.86 3.95 9.35 0.0022 0.0350 Fam117b -1.22 6.65 9.32 0.0023 0.0353 Fam129a -2.48 7.34 12.01 0.0005 0.0125 Fam13a 2.92 1.25 17.63 0.0000 0.0013 Fam169b -1.67 3.60 11.54 0.0007 0.0150 Fam198b 2.05 2.82 10.10 0.0015 0.0262 Fam3b -3.18 1.34 11.61 0.0007 0.0146 Fam69c -6.21 1.20 18.21 0.0000 0.0010 Fam89a -3.82 3.95 18.49 0.0000 0.0009 Fanca 1.93 3.29 13.60 0.0002 0.0069 Fcgr4 1.64 5.57 15.09 0.0001 0.0038 Fcrls 2.95 6.07 14.74 0.0001 0.0044 Fdps -1.99 2.81 8.98 0.0027 0.0407 Ffar2 2.56 1.11 9.09 0.0026 0.0389 Fgd2 -2.64 4.96 18.25 0.0000 0.0010 Fgd4 1.37 5.36 10.27 0.0014 0.0247 Fgf1 -3.48 2.43 12.63 0.0004 0.0098 Fgfbp3 -2.07 2.10 8.57 0.0034 0.0468 Fgfr1 -1.39 5.50 9.67 0.0019 0.0311 Fgfr2 -3.57 1.47 9.06 0.0026 0.0393 Fgr 2.37 6.24 22.45 0.0000 0.0002 Flrt3 -2.83 5.74 20.56 0.0000 0.0004 Flt3 -4.64 4.40 20.24 0.0000 0.0005 Fnbp1l -1.88 6.93 12.48 0.0004 0.0105 Fndc5 -3.98 5.56 38.76 0.0000 0.0000 Focad 1.41 4.21 10.03 0.0015 0.0269 Foxp1 -1.33 5.80 12.85 0.0003 0.0090 Fpr2 1.86 7.53 12.78 0.0004 0.0093 Frmd5 -3.24 1.62 15.57 0.0001 0.0031 Fscn1 -3.29 10.88 11.32 0.0008 0.0162 Fut10 3.92 1.78 17.22 0.0000 0.0015 Fut8 -1.42 5.18 9.00 0.0027 0.0402 Fyn -2.71 6.48 40.62 0.0000 0.0000 Gas5 -1.51 6.42 14.97 0.0001 0.0040 Gata2 -2.41 5.77 22.24 0.0000 0.0002 Gatsl2 -2.46 6.96 8.95 0.0028 0.0408 Gatsl3 -2.02 6.38 24.01 0.0000 0.0001 Gbe1 1.95 4.97 25.35 0.0000 0.0001 Gbp2 -2.10 8.04 17.52 0.0000 0.0014 Gbp4 -1.42 5.64 11.63 0.0006 0.0145 Gbp8 -1.59 5.56 14.83 0.0001 0.0042 Gclm 2.02 7.21 17.79 0.0000 0.0012 Gdpd1 1.57 4.79 13.56 0.0002 0.0070 Gdpd3 7.34 6.39 98.72 0.0000 0.0000

6 Gene Name logFC logCPM LR P Value FDR

Gfod1 -1.97 5.36 16.76 0.0000 0.0019 Ggact -3.08 0.22 8.47 0.0036 0.0489 Gimap1 -3.08 3.17 14.84 0.0001 0.0042 Gins3 -2.45 5.20 35.25 0.0000 0.0000 Glipr1 1.47 7.78 11.42 0.0007 0.0157 Gls2 -4.04 3.41 32.53 0.0000 0.0000 Glud1 -1.41 7.81 11.07 0.0009 0.0177 Gm10432 -6.41 2.36 25.66 0.0000 0.0001 Gm11435 -2.19 4.62 26.83 0.0000 0.0000 Gm11545 1.68 3.79 9.72 0.0018 0.0305 Gm11974 -1.88 4.83 10.30 0.0013 0.0244 Gm13546 -2.46 6.97 19.17 0.0000 0.0007 Gm14137 -2.61 1.68 11.83 0.0006 0.0134 Gm14446 -2.29 4.79 8.73 0.0031 0.0443 Gm14492 -2.36 4.90 28.76 0.0000 0.0000 Gm15056 4.26 1.55 20.61 0.0000 0.0004 Gm15880 -3.38 0.91 14.16 0.0002 0.0055 Gm16617 -2.70 2.99 11.75 0.0006 0.0138 Gm1821 7.08 4.41 105.75 0.0000 0.0000 Gm266 -3.19 3.18 21.75 0.0000 0.0002 Gm4827 -3.43 1.10 10.25 0.0014 0.0250 Gm6377 -2.06 3.34 15.90 0.0001 0.0027 Gm8221 -5.05 4.41 13.20 0.0003 0.0079 Gnb4 -2.58 7.09 13.58 0.0002 0.0070 Gngt2 1.31 7.00 10.91 0.0010 0.0190 Gp6 2.45 4.56 27.74 0.0000 0.0000 Gpr126 -3.20 7.86 12.30 0.0005 0.0111 Gpr132 -2.15 8.12 11.42 0.0007 0.0157 Gpr162 1.74 3.11 10.25 0.0014 0.0249 Gpr183 -2.98 4.94 29.74 0.0000 0.0000 Gpr55 -2.39 4.90 17.57 0.0000 0.0013 Gpr65 -2.82 6.60 26.31 0.0000 0.0000 Gpr68 -3.75 6.50 64.46 0.0000 0.0000 Gprc5a -3.21 1.84 15.77 0.0001 0.0028 Gpx3 2.97 5.64 41.16 0.0000 0.0000 Grap -1.61 3.61 8.48 0.0036 0.0485 Grasp -4.12 6.16 65.20 0.0000 0.0000 Greb1 -3.90 1.81 11.47 0.0007 0.0154 Gsr 1.91 8.01 19.97 0.0000 0.0005 Gsta3 2.33 4.69 22.28 0.0000 0.0002 Gtpbp4 -1.41 7.13 11.10 0.0009 0.0176 Gys1 1.27 6.55 12.18 0.0005 0.0116 H2-DMb2 -1.16 5.78 9.32 0.0023 0.0354 H2-Ea-ps -1.77 5.76 8.84 0.0030 0.0426 H2-Ob -1.36 5.54 8.66 0.0033 0.0452 H2-T24 1.37 5.62 10.38 0.0013 0.0236 H60b 3.49 0.84 16.16 0.0001 0.0024 Haao -2.01 4.81 13.90 0.0002 0.0061 Hal 7.81 3.99 106.09 0.0000 0.0000 Havcr2 -1.99 2.84 8.68 0.0032 0.0449 Hdac11 -2.15 2.54 11.00 0.0009 0.0183 Hdc -5.05 4.27 29.31 0.0000 0.0000 Hddc3 2.20 3.29 9.70 0.0018 0.0308 Hebp1 2.50 4.72 20.86 0.0000 0.0004 Hebp2 5.68 3.18 51.96 0.0000 0.0000 Hectd2 -2.52 0.78 10.75 0.0010 0.0204

7 Gene Name logFC logCPM LR P Value FDR

Hepacam2 -3.01 4.96 28.93 0.0000 0.0000 Hip1r -3.75 4.82 60.77 0.0000 0.0000 Hjurp -2.40 1.70 11.48 0.0007 0.0154 Hk2 1.28 7.52 9.58 0.0020 0.0321 Hmgn3 -3.49 3.28 14.61 0.0001 0.0046 Hnmt 2.09 3.10 12.81 0.0003 0.0091 Hpse 1.90 6.21 26.47 0.0000 0.0000 Hs3st1 -3.67 1.61 11.38 0.0007 0.0159 Hsf2 -1.40 6.20 13.72 0.0002 0.0066 Hspa1a -3.42 5.27 12.00 0.0005 0.0126 Hspa1b -3.55 5.78 12.09 0.0005 0.0121 Hspa8 -2.48 6.27 24.96 0.0000 0.0001 Hspbap1 -1.81 4.22 13.48 0.0002 0.0072 Icam4 -3.77 1.07 13.51 0.0002 0.0072 Icos -2.58 1.32 8.58 0.0034 0.0465 Idh1 1.58 8.06 10.49 0.0012 0.0227 Idi1 -2.81 2.13 14.54 0.0001 0.0047 Ido1 -4.17 2.52 14.96 0.0001 0.0040 Ifitm1 -2.86 8.45 20.45 0.0000 0.0004 Ifitm6 2.10 3.95 9.34 0.0022 0.0351 Igf1 1.95 7.57 11.42 0.0007 0.0157 Igfbp4 -2.33 9.12 14.96 0.0001 0.0040 Igj -3.91 3.91 9.39 0.0022 0.0345 Igsf6 1.60 6.68 10.35 0.0013 0.0240 Ikzf3 -6.02 1.28 9.26 0.0023 0.0362 Ikzf4 -2.24 4.93 9.95 0.0016 0.0278 Il12b -2.38 8.32 20.48 0.0000 0.0004 Il12rb2 -3.05 5.54 35.53 0.0000 0.0000 Il15 -1.89 5.43 24.14 0.0000 0.0001 Il18r1 -2.38 5.61 10.09 0.0015 0.0262 Il18rap -2.75 4.70 15.77 0.0001 0.0028 Il1r2 -3.23 6.12 45.30 0.0000 0.0000 Il27ra 2.09 2.78 8.78 0.0030 0.0436 Il2ra -3.16 7.60 15.74 0.0001 0.0029 Il31ra -3.20 3.76 9.59 0.0020 0.0321 Il4ra -1.32 8.91 9.05 0.0026 0.0396 Il6 -3.11 6.28 47.66 0.0000 0.0000 Inadl -3.34 2.22 10.67 0.0011 0.0211 Inf2 -2.01 7.59 13.47 0.0002 0.0072 Insm1 -5.71 5.12 15.04 0.0001 0.0038 Ipcef1 2.37 3.04 10.22 0.0014 0.0251 Irf8 -2.37 10.22 18.88 0.0000 0.0008 Irs3 -6.70 0.51 12.62 0.0004 0.0099 Itfg3 1.44 7.21 13.25 0.0003 0.0078 Itga3 -7.54 1.34 26.09 0.0000 0.0000 Itga6 1.84 4.92 9.76 0.0018 0.0301 Itgax -2.43 8.49 19.20 0.0000 0.0007 Itgb2l -4.75 2.93 16.07 0.0001 0.0026 Itgb8 -3.41 2.84 9.35 0.0022 0.0349 Jazf1 -1.24 4.58 8.73 0.0031 0.0443 Jdp2 -2.49 5.57 26.12 0.0000 0.0000 Kansl3 -1.36 7.57 11.18 0.0008 0.0171 Kcnk6 -1.60 7.19 10.04 0.0015 0.0268 Kcnn1 -3.78 0.26 11.58 0.0007 0.0147 Kcp -2.18 3.06 8.74 0.0031 0.0442 Kctd12b 3.06 4.00 14.44 0.0001 0.0049

8 Gene Name logFC logCPM LR P Value FDR

Kctd14 -4.60 4.43 30.90 0.0000 0.0000 Kdm4a -2.43 8.85 14.11 0.0002 0.0056 Kirrel -6.47 2.59 23.87 0.0000 0.0001 Kit -2.03 4.72 9.87 0.0017 0.0287 Klf8 -2.82 2.47 9.26 0.0023 0.0362 Klhl8 -2.49 5.31 28.80 0.0000 0.0000 Klk1b27 2.31 3.16 10.18 0.0014 0.0254 Klra17 2.33 2.64 9.94 0.0016 0.0279 Klra2 1.99 3.57 9.59 0.0020 0.0321 Klrd1 -3.43 1.72 11.76 0.0006 0.0138 Klri2 -3.77 1.09 17.79 0.0000 0.0012 Krit1 -1.18 6.06 9.98 0.0016 0.0275 Krt222 -3.53 0.97 8.85 0.0029 0.0423 Ktn1 -2.34 7.98 27.03 0.0000 0.0000 L1cam -2.95 6.68 20.18 0.0000 0.0005 Lactb -1.86 7.27 13.96 0.0002 0.0060 Lad1 -3.74 3.96 23.13 0.0000 0.0001 Lama3 -5.29 0.79 22.57 0.0000 0.0002 Lama5 -3.12 4.96 9.71 0.0018 0.0306 Laptm4b -1.55 4.47 12.47 0.0004 0.0105 Ldlrad3 2.68 2.75 12.42 0.0004 0.0107 Leprel2 1.49 3.74 9.65 0.0019 0.0313 Lgalsl -2.57 2.59 8.61 0.0033 0.0461 Lif -3.44 5.12 29.83 0.0000 0.0000 Lilra5 3.00 2.51 20.53 0.0000 0.0004 Lilrb3 2.66 7.29 14.12 0.0002 0.0056 Lipa 2.18 10.14 18.71 0.0000 0.0009 Lmo4 1.25 6.79 10.59 0.0011 0.0219 Lnx2 -1.44 4.24 8.91 0.0028 0.0414 Lox 2.18 6.61 18.56 0.0000 0.0009 Lrig1 -2.90 2.36 15.31 0.0001 0.0034 Lrrc16a -2.04 3.91 13.41 0.0003 0.0074 Lrrc16b -3.50 1.63 11.25 0.0008 0.0166 Lrrc25 1.33 6.43 13.32 0.0003 0.0076 Lsp1 -2.23 10.01 15.27 0.0001 0.0035 Lst1 1.43 5.73 12.43 0.0004 0.0107 Ltb4r1 1.62 4.82 9.63 0.0019 0.0317 Lyplal1 3.54 2.46 28.64 0.0000 0.0000 Lyz1 2.86 3.68 27.16 0.0000 0.0000 Lyz2 2.60 13.50 16.74 0.0000 0.0019 Mad2l1 -1.94 3.34 11.59 0.0007 0.0147 Maged1 1.90 6.08 18.37 0.0000 0.0010 Mall -2.93 2.36 14.58 0.0001 0.0047 Maoa 2.05 4.97 17.26 0.0000 0.0015 Map3k14 -2.31 8.16 11.30 0.0008 0.0162 Mapk13 -2.35 3.27 14.20 0.0002 0.0054 March1 2.10 6.81 25.32 0.0000 0.0001 Mcm5 -1.61 4.45 10.48 0.0012 0.0227 Mdh1 -1.45 7.59 13.42 0.0002 0.0073 Meis1 -4.09 2.01 22.83 0.0000 0.0002 Mettl20 -1.54 3.71 10.23 0.0014 0.0251 Mettl21d 1.55 3.66 9.14 0.0025 0.0380 Mex3a 5.58 -0.20 11.34 0.0008 0.0161 Mex3b -2.99 5.42 33.98 0.0000 0.0000 Mfhas1 -2.15 6.82 18.33 0.0000 0.0010 Mfsd2a -3.68 0.23 12.84 0.0003 0.0090

9 Gene Name logFC logCPM LR P Value FDR

Mfsd6 -1.56 5.24 8.71 0.0032 0.0446 Mgst1 1.70 6.75 18.53 0.0000 0.0009 Mical1 -1.16 6.47 8.62 0.0033 0.0459 Mical2 -1.97 5.55 17.22 0.0000 0.0015 Mif4gd -1.20 6.71 10.82 0.0010 0.0197 Mkl1 -1.70 7.92 8.49 0.0036 0.0483 Mmp25 -3.51 8.77 15.67 0.0001 0.0029 Mpp1 1.18 6.85 9.51 0.0020 0.0331 Mpp2 -4.97 1.15 19.83 0.0000 0.0005 Mrps6 -1.67 3.99 12.71 0.0004 0.0095 Ms4a6c 1.77 6.56 9.17 0.0025 0.0376 Ms4a6d 1.69 8.20 14.24 0.0002 0.0054 Ms4a7 1.59 5.84 10.45 0.0012 0.0230 Msi2 -2.10 2.75 10.22 0.0014 0.0252 Msr1 1.89 7.95 13.70 0.0002 0.0066 Mthfd1l 2.03 4.23 19.08 0.0000 0.0007 Mtmr1 -1.41 6.86 8.95 0.0028 0.0408 Myb -4.49 2.17 20.12 0.0000 0.0005 Mycl1 -2.85 3.78 15.70 0.0001 0.0029 Mylk -4.14 7.11 25.05 0.0000 0.0001 Myo1g -2.65 9.74 27.99 0.0000 0.0000 Myo7a 1.71 5.40 13.46 0.0002 0.0072 Myof 1.43 8.86 8.82 0.0030 0.0430 N28178 -5.63 3.78 8.65 0.0033 0.0453 Naaa 1.31 7.23 10.13 0.0015 0.0259 Naip5 1.12 6.02 9.29 0.0023 0.0358 Naip6 1.90 3.93 17.12 0.0000 0.0016 Nap1l1 -1.61 6.35 9.47 0.0021 0.0336 Napepld 1.55 3.40 10.58 0.0011 0.0219 Nav2 2.30 4.47 26.30 0.0000 0.0000 Nbl1 -2.06 3.12 10.82 0.0010 0.0197 Nceh1 1.72 7.48 15.84 0.0001 0.0028 Nck2 -1.56 4.98 11.10 0.0009 0.0176 Nckap1 -1.65 4.07 12.66 0.0004 0.0097 Ncoa7 -2.27 6.60 16.38 0.0001 0.0022 Ndrg1 -2.19 7.65 26.17 0.0000 0.0000 Ndrg4 -3.21 3.74 35.62 0.0000 0.0000 Nek8 -2.81 3.24 16.74 0.0000 0.0019 Nes 5.33 2.47 23.84 0.0000 0.0001 Net1 -2.67 8.52 16.02 0.0001 0.0026 Nfam1 1.68 7.49 14.00 0.0002 0.0059 Nfil3 -1.58 7.99 8.67 0.0032 0.0451 Nfkb1 -1.36 8.13 9.12 0.0025 0.0383 Nhlrc2 -1.29 5.58 9.43 0.0021 0.0343 Niacr1 -2.07 4.76 9.03 0.0026 0.0397 Nipal1 -5.64 1.58 9.66 0.0019 0.0313 Nkain1 -3.13 3.52 21.56 0.0000 0.0003 Nlrp1b 2.56 3.99 11.80 0.0006 0.0136 Npl 2.17 4.44 23.73 0.0000 0.0001 Npr1 -3.94 7.81 20.20 0.0000 0.0005 Nr4a1 -3.06 2.40 13.23 0.0003 0.0079 Nr4a2 -2.90 5.11 29.19 0.0000 0.0000 Nr4a3 -2.73 6.14 26.86 0.0000 0.0000 Nradd 2.54 1.30 8.97 0.0027 0.0407 Nrarp -5.13 1.66 14.22 0.0002 0.0054 Nrep -2.38 3.11 8.70 0.0032 0.0447

10 Gene Name logFC logCPM LR P Value FDR

Nrg1 -2.69 5.26 20.57 0.0000 0.0004 Nrn1l -3.23 0.88 10.33 0.0013 0.0242 Nrp1 1.99 6.01 19.94 0.0000 0.0005 Nrxn2 3.45 0.17 12.86 0.0003 0.0090 Nsmaf -1.38 6.21 13.00 0.0003 0.0085 Nudt9 -1.38 6.62 14.48 0.0001 0.0049 Nup210 -1.21 6.43 9.54 0.0020 0.0326 Ocln -3.16 1.74 9.37 0.0022 0.0347 Ogfrl1 -1.48 7.07 8.78 0.0030 0.0436 Osgin2 -1.31 5.03 8.51 0.0035 0.0479 Osm -2.47 6.23 22.92 0.0000 0.0002 Oxct1 -1.17 6.58 8.61 0.0033 0.0461 P2rx5 -2.27 5.31 12.54 0.0004 0.0102 P2rx7 2.04 6.44 15.10 0.0001 0.0038 P2ry10 -2.71 5.79 10.18 0.0014 0.0254 Pafah1b3 -1.20 4.91 9.24 0.0024 0.0364 Pard3b -7.31 0.58 18.29 0.0000 0.0010 Parva -6.15 3.00 18.51 0.0000 0.0009 Parvb 1.36 5.57 10.55 0.0012 0.0221 Pcgf5 -2.03 6.26 19.05 0.0000 0.0007 Pcx 1.80 4.31 12.93 0.0003 0.0087 Pcyox1 1.67 6.74 13.02 0.0003 0.0085 Pcyt1b 2.39 2.62 8.90 0.0029 0.0416 Pdcd1 -3.79 3.05 12.54 0.0004 0.0102 Pdcd1lg2 -1.54 6.35 12.91 0.0003 0.0088 Pde4b -2.04 7.81 19.62 0.0000 0.0006 Pdgfb -2.50 5.99 29.82 0.0000 0.0000 Pdgfc -2.34 3.37 9.22 0.0024 0.0368 Pdk1 1.32 4.66 9.44 0.0021 0.0341 Pdlim4 -2.19 5.40 26.70 0.0000 0.0000 Pdlim7 -1.38 5.41 9.24 0.0024 0.0364 Pgd 1.45 9.05 9.47 0.0021 0.0336 Phactr1 -3.73 1.07 11.00 0.0009 0.0183 Phc1 -1.91 4.41 17.06 0.0000 0.0016 Phldb1 -1.87 5.65 16.55 0.0000 0.0021 Pip4k2a -1.74 8.19 11.97 0.0005 0.0127 Pira6 2.36 5.73 24.72 0.0000 0.0001 Pkib -2.92 7.69 24.82 0.0000 0.0001 Pkp3 -1.88 4.55 10.74 0.0010 0.0204 Pla1a -3.75 4.28 42.34 0.0000 0.0000 Pla2g15 1.15 6.86 8.74 0.0031 0.0442 Pla2g2d 3.98 1.54 17.87 0.0000 0.0012 Plat -4.61 4.32 22.35 0.0000 0.0002 Plcl1 -2.70 4.19 13.54 0.0002 0.0071 Pld4 2.97 8.40 40.11 0.0000 0.0000 Plek2 -4.89 1.18 19.14 0.0000 0.0007 Plekha5 -2.15 4.10 18.59 0.0000 0.0009 Plekhs1 -3.20 4.77 10.53 0.0012 0.0222 Plod1 1.15 6.33 8.49 0.0036 0.0484 Plod3 1.34 7.18 11.72 0.0006 0.0140 Plscr3 1.62 4.32 9.75 0.0018 0.0301 Plscr4 -3.63 1.87 11.08 0.0009 0.0177 Plxnb3 2.36 1.91 8.95 0.0028 0.0408 Pmaip1 -1.30 7.31 9.48 0.0021 0.0336 Pmepa1 -2.14 4.22 19.98 0.0000 0.0005 Pmvk -2.73 6.59 51.14 0.0000 0.0000

11 Gene Name logFC logCPM LR P Value FDR

Pnkd -1.61 6.63 8.74 0.0031 0.0442 Pold2 -1.23 4.43 8.70 0.0032 0.0447 Pole -2.76 3.48 10.30 0.0013 0.0245 Polm -1.24 4.57 8.95 0.0028 0.0408 Pou4f1 -3.82 1.78 23.42 0.0000 0.0001 Ppef2 3.28 0.77 13.62 0.0002 0.0069 Ppfia4 2.76 4.64 20.60 0.0000 0.0004 Ppfibp1 1.94 5.94 24.67 0.0000 0.0001 Ppp1r12a -1.31 7.62 10.31 0.0013 0.0244 Ppp1r3b 1.38 4.90 10.71 0.0011 0.0206 Ppp3cc -1.55 4.28 13.24 0.0003 0.0078 Prdm8 -6.38 0.87 13.88 0.0002 0.0061 Prdx1 1.68 10.12 11.26 0.0008 0.0165 Prickle2 2.84 2.50 15.75 0.0001 0.0029 Prkaa2 -2.73 2.57 14.23 0.0002 0.0054 Prkcb 1.73 8.55 15.74 0.0001 0.0029 Prkcq -6.17 0.46 11.91 0.0006 0.0131 Prodh -2.62 4.03 28.72 0.0000 0.0000 Pros1 3.01 4.25 11.60 0.0007 0.0146 Prph -4.01 2.51 13.40 0.0003 0.0074 Prr5l -3.00 6.45 12.82 0.0003 0.0091 Prrg4 -4.07 3.67 26.02 0.0000 0.0000 Prune2 1.36 5.72 11.88 0.0006 0.0132 Psmg4 -1.59 4.49 12.91 0.0003 0.0088 Pstpip2 1.36 6.04 11.32 0.0008 0.0162 Ptger2 1.39 4.65 9.33 0.0022 0.0351 Ptger4 -2.14 7.00 11.27 0.0008 0.0165 Ptgfrn 1.92 4.61 18.01 0.0000 0.0011 Ptgir 1.71 6.91 16.80 0.0000 0.0018 Ptgr1 1.89 7.63 12.32 0.0004 0.0110 Ptgs2 -2.52 7.51 12.96 0.0003 0.0087 Ptk6 -3.14 3.84 8.84 0.0030 0.0426 Ptplad2 1.69 5.99 15.64 0.0001 0.0030 Ptpn18 1.55 5.00 12.32 0.0004 0.0110 Ptpn3 -2.37 5.63 17.60 0.0000 0.0013 Ptpn4 -2.20 4.23 13.78 0.0002 0.0064 Ptprf -4.26 3.53 15.83 0.0001 0.0028 Ptrf -3.24 3.41 12.40 0.0004 0.0107 Pvrl1 -2.18 5.31 9.41 0.0022 0.0344 Pxdc1 -3.60 3.44 20.11 0.0000 0.0005 Pxmp2 -2.26 3.41 12.46 0.0004 0.0105 Pyroxd2 2.18 2.42 8.93 0.0028 0.0409 Rab11fip1 -1.63 7.26 12.56 0.0004 0.0102 Rab26 -3.82 2.97 13.02 0.0003 0.0085 Rab3il1 1.96 5.65 18.95 0.0000 0.0008 Rabgap1l -2.85 7.22 32.74 0.0000 0.0000 Raf1 1.38 7.86 10.92 0.0010 0.0189 Ramp3 -1.91 7.74 21.80 0.0000 0.0002 Rapgef2 -1.36 5.24 9.74 0.0018 0.0302 Rapgef5 -2.53 1.93 13.76 0.0002 0.0065 Rasa3 1.38 6.94 13.01 0.0003 0.0085 Rasd2 3.73 0.54 11.39 0.0007 0.0159 Rbbp8 -2.10 5.92 27.19 0.0000 0.0000 Rbpms2 -3.06 3.03 22.82 0.0000 0.0002 Rcsd1 -1.68 6.95 9.77 0.0018 0.0300 Reck -2.29 2.67 9.42 0.0021 0.0343

12 Gene Name logFC logCPM LR P Value FDR

Rel -1.97 7.08 14.14 0.0002 0.0055 Rell1 1.24 4.44 8.83 0.0030 0.0426 Relt -1.12 6.74 9.01 0.0027 0.0400 Rerg -6.11 0.10 11.39 0.0007 0.0159 Rftn1 -1.56 8.38 12.21 0.0005 0.0115 Rgs1 -2.05 8.43 9.87 0.0017 0.0287 Rgs10 -1.32 7.08 11.54 0.0007 0.0150 Rhob 1.10 6.95 8.50 0.0036 0.0482 Rhobtb1 -1.98 3.19 9.25 0.0024 0.0364 Rhof -1.93 5.21 17.64 0.0000 0.0013 Ripk2 -1.42 5.24 11.86 0.0006 0.0132 Rnasel 1.11 6.19 8.46 0.0036 0.0491 Rnd2 2.25 1.36 10.41 0.0013 0.0233 Rnf128 2.43 7.76 29.92 0.0000 0.0000 Rnf144b 1.89 5.44 9.20 0.0024 0.0371 Rnf152 -4.17 3.22 19.51 0.0000 0.0006 Rnf180 -2.99 4.23 23.63 0.0000 0.0001 Rnf19b -1.74 8.82 12.67 0.0004 0.0097 Rnf24 -1.48 4.67 11.58 0.0007 0.0147 Rnf43 -1.83 2.86 10.24 0.0014 0.0250 Rogdi -1.94 8.40 12.35 0.0004 0.0109 Rpl22l1 -1.65 4.20 10.61 0.0011 0.0216 Rps4y2 -2.61 0.79 10.24 0.0014 0.0250 Rragb -3.61 0.74 11.11 0.0009 0.0176 Rragc 1.25 7.76 9.01 0.0027 0.0400 Rras2 -1.64 5.82 19.96 0.0000 0.0005 Rtn1 -3.02 3.79 13.12 0.0003 0.0082 Runx2 -1.29 5.82 12.35 0.0004 0.0109 Runx3 -1.52 7.50 12.44 0.0004 0.0106 Rusc1 -1.46 4.77 12.94 0.0003 0.0087 Rxra 1.13 6.58 8.96 0.0028 0.0408 Ryk 1.94 3.37 11.42 0.0007 0.0157 S100a10 -1.59 7.56 13.17 0.0003 0.0081 S100a4 -2.44 7.44 15.79 0.0001 0.0028 S1pr2 1.52 6.73 16.05 0.0001 0.0026 S1pr3 -2.72 3.03 18.47 0.0000 0.0009 Saa3 2.16 11.04 10.74 0.0010 0.0204 Samsn1 -1.80 8.00 8.89 0.0029 0.0418 Sash1 2.14 6.39 18.68 0.0000 0.0009 Satb1 -2.76 2.81 17.96 0.0000 0.0012 Scara3 -4.91 3.04 14.05 0.0002 0.0057 Scin -2.96 5.72 10.66 0.0011 0.0212 Scn4b -2.77 5.29 25.49 0.0000 0.0001 Scube1 -6.44 2.80 14.61 0.0001 0.0046 Sec16b -6.63 1.35 13.13 0.0003 0.0081 Selenbp1 2.52 3.76 14.29 0.0002 0.0053 Sema6d -3.33 6.01 15.34 0.0001 0.0034 Sema7a -4.06 8.18 58.81 0.0000 0.0000 Sepp1 2.08 8.42 18.79 0.0000 0.0008 sep-04 -2.59 4.19 17.55 0.0000 0.0014 Serinc5 -1.32 5.37 8.75 0.0031 0.0442 Serpinb6b -2.63 7.27 32.86 0.0000 0.0000 Sesn3 -2.23 4.08 17.47 0.0000 0.0014 Sgsm1 -2.57 2.42 10.13 0.0015 0.0260 Sh2d1b1 -3.05 3.71 19.40 0.0000 0.0007 Sh3bp4 -1.59 6.58 10.93 0.0009 0.0189

13 Gene Name logFC logCPM LR P Value FDR

Sh3d21 -2.30 3.43 13.84 0.0002 0.0063 Sh3rf1 -2.46 3.12 19.25 0.0000 0.0007 Shmt1 2.71 3.41 21.42 0.0000 0.0003 Siae 1.21 5.54 8.53 0.0035 0.0476 Siglecg -2.56 3.54 21.76 0.0000 0.0002 Sik3 -1.26 7.29 9.58 0.0020 0.0321 Slain1 -2.41 1.68 10.86 0.0010 0.0194 Slamf1 -3.87 4.16 40.59 0.0000 0.0000 Slc11a1 1.38 8.26 8.71 0.0032 0.0446 Slc16a10 1.54 5.76 16.04 0.0001 0.0026 Slc16a14 -3.24 0.16 11.53 0.0007 0.0150 Slc16a7 2.32 2.95 12.32 0.0004 0.0110 Slc25a13 -1.75 4.02 10.66 0.0011 0.0211 Slc27a3 -3.54 6.75 14.15 0.0002 0.0055 Slc36a2 3.21 4.50 16.86 0.0000 0.0018 Slc40a1 2.08 5.92 14.57 0.0001 0.0047 Slc43a2 1.58 8.51 11.87 0.0006 0.0132 Slc6a13 1.85 5.30 14.92 0.0001 0.0040 Slc6a15 -3.76 2.05 28.03 0.0000 0.0000 Slc7a7 -1.50 5.31 13.36 0.0003 0.0074 Slc9a4 2.46 0.69 9.76 0.0018 0.0300 Slc9a9 2.49 4.73 15.24 0.0001 0.0035 Slco2b1 -3.48 5.65 12.01 0.0005 0.0125 Slco5a1 -4.12 5.55 21.48 0.0000 0.0003 Smap2 -1.51 8.39 11.78 0.0006 0.0137 Smarce1 -1.88 5.79 21.60 0.0000 0.0003 Smox -2.02 8.10 17.56 0.0000 0.0013 Smpdl3a 1.52 7.62 13.90 0.0002 0.0061 Snd1 -1.39 7.73 8.99 0.0027 0.0404 Sned1 -3.20 3.52 12.19 0.0005 0.0116 Snhg12 -1.52 3.92 10.27 0.0014 0.0247 Snn -2.74 6.59 21.20 0.0000 0.0003 Snph -2.95 2.51 19.82 0.0000 0.0005 Snta1 1.86 2.50 10.50 0.0012 0.0226 Snx7 1.39 4.96 10.17 0.0014 0.0254 Socs2 -2.47 7.73 17.73 0.0000 0.0013 Sod3 -5.72 0.91 9.27 0.0023 0.0360 Sord 1.61 4.37 9.43 0.0021 0.0343 Sort1 1.76 7.40 14.47 0.0001 0.0049 Sp140 -1.45 6.40 16.62 0.0000 0.0020 Sp6 -2.72 1.85 12.26 0.0005 0.0112 Specc1l -1.87 7.53 20.35 0.0000 0.0004 Spint1 -1.39 7.05 11.69 0.0006 0.0141 Spint2 -2.01 6.49 25.50 0.0000 0.0001 Spns3 -4.24 3.21 16.87 0.0000 0.0018 Spo11 -3.90 1.99 9.17 0.0025 0.0376 Srxn1 1.41 7.67 9.12 0.0025 0.0383 Ssbp3 -2.50 4.70 27.21 0.0000 0.0000 St18 1.66 3.34 11.18 0.0008 0.0171 St3gal3 -1.30 6.47 9.34 0.0022 0.0351 Stard5 1.30 5.36 11.15 0.0008 0.0173 Stard8 1.31 4.66 8.89 0.0029 0.0418 Stat4 -2.85 8.12 22.19 0.0000 0.0002 Stat5a -1.93 6.92 21.55 0.0000 0.0003 Stil -5.79 0.37 10.12 0.0015 0.0261 Stk38l -2.17 3.53 12.39 0.0004 0.0108

14 Gene Name logFC logCPM LR P Value FDR

Stk39 -3.14 5.76 54.26 0.0000 0.0000 Ston2 -1.25 4.68 8.46 0.0036 0.0490 Strbp -1.47 5.02 13.17 0.0003 0.0080 Stxbp6 -3.30 4.48 30.74 0.0000 0.0000 Susd2 1.49 6.74 13.05 0.0003 0.0084 Sycp1 5.22 0.30 21.87 0.0000 0.0002 Syn3 -3.93 4.71 19.67 0.0000 0.0006 Syne2 -1.69 4.88 10.58 0.0011 0.0219 Syngr1 1.89 4.91 15.48 0.0001 0.0032 Synpo2 -4.27 3.49 12.06 0.0005 0.0123 Sypl 1.13 5.80 9.39 0.0022 0.0345 Syt9 -4.51 1.49 17.87 0.0000 0.0012 Taf1d -1.74 5.17 8.75 0.0031 0.0442 Tanc2 1.33 4.82 10.86 0.0010 0.0194 Tbc1d10c -3.17 4.64 13.66 0.0002 0.0068 Tbc1d4 -3.36 7.08 26.17 0.0000 0.0000 Tbxas1 1.28 7.68 9.41 0.0022 0.0344 Tceal8 1.33 3.75 8.66 0.0033 0.0452 Tcf4 -1.62 5.46 14.46 0.0001 0.0049 Tcf7 -3.09 4.11 10.20 0.0014 0.0253 Tes -1.56 7.95 13.54 0.0002 0.0071 Tex14 -2.30 2.03 10.41 0.0013 0.0233 Tex30 -2.28 3.68 19.39 0.0000 0.0007 Tfdp2 -1.45 4.33 8.96 0.0028 0.0408 Tfeb 1.31 5.56 9.56 0.0020 0.0324 Tfpi 1.75 3.32 11.45 0.0007 0.0156 Tg -2.75 3.61 19.33 0.0000 0.0007 Tgfb2 -3.11 2.52 12.20 0.0005 0.0115 Tgfb3 -4.72 0.21 13.41 0.0003 0.0074 Tgfbr2 1.89 7.27 18.59 0.0000 0.0009 Tiam1 -1.23 5.72 9.03 0.0027 0.0398 Ticam1 -1.18 5.61 9.41 0.0022 0.0344 Ticam2 1.09 6.34 8.71 0.0032 0.0446 Tifa 1.45 6.17 15.78 0.0001 0.0028 Tifab 2.20 7.19 12.27 0.0005 0.0112 Timp3 -3.22 1.99 9.96 0.0016 0.0276 Tinagl1 -5.35 1.16 27.06 0.0000 0.0000 Tjp2 -1.57 5.52 15.35 0.0001 0.0034 Tlcd1 -2.69 1.90 11.64 0.0006 0.0144 Tlr12 -2.82 3.97 11.00 0.0009 0.0183 Tlr13 1.62 7.84 12.38 0.0004 0.0108 Tlr2 -1.10 6.85 8.57 0.0034 0.0468 Tlr8 2.95 6.28 13.15 0.0003 0.0081 Tm4sf5 2.58 2.72 17.54 0.0000 0.0014 Tmed5 1.23 6.33 11.09 0.0009 0.0176 Tmem123 -2.04 11.09 10.21 0.0014 0.0252 Tmem131 -2.04 8.00 17.75 0.0000 0.0013 Tmem150c -4.37 4.64 20.51 0.0000 0.0004 Tmem151b -6.56 2.94 13.57 0.0002 0.0070 Tmem176a -2.21 7.67 8.87 0.0029 0.0420 Tmem176b -2.20 8.69 9.54 0.0020 0.0326 Tmem39a -1.28 6.85 8.87 0.0029 0.0420 Tmem40 4.30 1.78 30.90 0.0000 0.0000 Tmem86a 1.14 6.28 8.51 0.0035 0.0479 Tmod2 -3.74 4.79 12.53 0.0004 0.0103 Tmtc2 -2.72 5.58 28.27 0.0000 0.0000

15 Gene Name logFC logCPM LR P Value FDR

Tnfaip8l2 1.32 5.81 11.01 0.0009 0.0183 Tnfrsf11a -1.97 6.74 13.15 0.0003 0.0081 Tnfrsf13b -1.82 2.92 9.78 0.0018 0.0298 Tnfrsf13c -3.85 1.21 15.18 0.0001 0.0036 Tnfrsf18 -2.06 3.88 16.33 0.0001 0.0023 Tnfsf15 -2.89 7.34 25.17 0.0000 0.0001 Tnfsf4 -1.95 5.32 11.36 0.0008 0.0160 Tnfsf8 -3.30 6.41 25.51 0.0000 0.0001 Tnk2 -1.88 3.28 8.73 0.0031 0.0443 Top2a -2.13 4.96 14.26 0.0002 0.0053 Traf1 -1.69 8.74 11.99 0.0005 0.0126 Traf4 -2.83 4.79 26.40 0.0000 0.0000 Trem1 -1.85 3.71 11.89 0.0006 0.0131 Trim29 2.11 3.89 12.97 0.0003 0.0086 Trim30b -3.44 1.28 14.83 0.0001 0.0042 Trim43b -2.70 2.43 14.33 0.0002 0.0052 Trp53i11 -1.70 4.89 12.94 0.0003 0.0087 Trpc2 -1.30 4.13 8.60 0.0034 0.0463 Trpm2 1.80 5.51 12.19 0.0005 0.0116 Tsku 1.43 4.30 9.38 0.0022 0.0346 Tspan13 -3.69 6.43 82.42 0.0000 0.0000 Tspan2 -2.97 2.90 14.59 0.0001 0.0047 Tspan33 -2.54 4.80 27.42 0.0000 0.0000 Tspan4 2.12 3.96 18.14 0.0000 0.0011 Ttc12 1.45 3.87 9.25 0.0024 0.0364 Ttc39a -2.75 4.44 19.30 0.0000 0.0007 Ttc39c -2.69 8.06 27.71 0.0000 0.0000 Ttc9 -2.62 1.35 13.36 0.0003 0.0074 Tuba1a -2.18 5.19 17.54 0.0000 0.0014 Tuba8 -2.15 4.08 9.37 0.0022 0.0347 Tubb2a -1.41 5.90 9.03 0.0027 0.0398 Tubb6 -1.41 7.10 11.15 0.0008 0.0173 Txlnb -4.01 2.22 22.24 0.0000 0.0002 Txndc17 -1.65 7.96 16.23 0.0001 0.0024 Tyms -1.86 3.14 11.66 0.0006 0.0143 Uck2 -1.49 5.32 12.90 0.0003 0.0088 Ugdh 1.24 5.87 11.27 0.0008 0.0165 Uhrf1 -2.03 3.14 10.09 0.0015 0.0262 Ust -4.30 1.40 14.68 0.0001 0.0045 Vangl2 3.10 0.17 11.59 0.0007 0.0147 Vash2 2.54 1.55 10.56 0.0012 0.0220 Vcam1 -2.82 2.75 13.50 0.0002 0.0072 Vdr -3.11 6.88 24.53 0.0000 0.0001 Vil1 -3.60 2.63 31.61 0.0000 0.0000 Vopp1 -1.70 8.68 15.40 0.0001 0.0033 Whrn -2.15 3.69 19.89 0.0000 0.0005 Wnt11 -1.85 4.79 13.49 0.0002 0.0072 Zadh2 1.34 5.47 8.78 0.0030 0.0436 Zbtb10 -1.68 4.29 11.73 0.0006 0.0139 Zbtb42 -1.51 4.64 11.81 0.0006 0.0135 Zbtb46 -2.47 5.56 26.72 0.0000 0.0000 Zcchc11 -1.35 5.83 13.11 0.0003 0.0082 Zcchc24 2.35 3.41 10.20 0.0014 0.0253 Zeb1 -2.49 5.67 17.17 0.0000 0.0016 Zfp296 -3.03 3.28 26.09 0.0000 0.0000 Zfp362 -1.09 5.64 8.58 0.0034 0.0467

16 Gene Name logFC logCPM LR P Value FDR

Zfp366 -3.09 4.84 9.26 0.0023 0.0362 Zfp503 1.96 3.37 13.70 0.0002 0.0066 Zfp524 -1.13 4.97 8.70 0.0032 0.0447 Zfp541 3.25 0.60 9.95 0.0016 0.0278 Zfp791 -2.65 2.69 11.37 0.0007 0.0159 Zfp819 -1.62 2.64 8.61 0.0033 0.0461 Zfp827 -2.27 3.16 13.91 0.0002 0.0061 Zkscan17 -1.28 6.07 12.75 0.0004 0.0094 Zmynd10 3.24 0.44 13.13 0.0003 0.0081

17 Supplemental Table II: GO Term enrichment LPS KO vs WT GO Term Enrichment analysis performed separately on Upregulated genes (n =289) and Downregulated genes (n =609).

GO, gene ontology; DE, differentially expressed.

Up / down regulated GO Term Description Adjusted DE Total P value genes in genes in category category Upregulated genes oxidation-reduction process 3.06E-08 41 900 Upregulated genes oxidoreductase activity 2.34E-07 35 723 Upregulated genes single-organism metabolic process 2.03E-06 105 4309 Upregulated genes membrane 4.33E-06 160 8326 Upregulated genes intrinsic component of membrane 1.04E-05 122 5898 Upregulated genes integral component of membrane 1.09E-05 120 5766 Upregulated genes membrane part 1.37E-05 133 6630 Upregulated genes immune system process 7.09E-05 50 1586 Upregulated genes single-organism process 0.000126 209 12481 Upregulated genes oxoacid metabolic process 0.001231 31 769 Upregulated genes lipid metabolic process 0.001772 36 995 Upregulated genes organic acid metabolic process 0.001889 31 783 Upregulated genes defense response 0.002294 32 918 Upregulated genes immune response 0.00247 30 781 Upregulated genes carbohydrate binding 0.004935 15 223 Downregulated genes immune system process 2.90E-19 119 1586 Downregulated genes immune response 1.09E-11 66 781 Downregulated genes leukocyte activation 3.26E-11 56 596 Downregulated genes regulation of immune system process 4.09E-11 68 822 Downregulated genes lymphocyte activation 4.41E-11 51 511 Downregulated genes positive regulation of biological process 8.38E-11 191 3744 Downregulated genes regulation of response to stimulus 1.98E-10 145 2524 Downregulated genes cell activation 2.49E-10 59 678 Downregulated genes positive regulation of cellular process 7.93E-10 173 3319 Downregulated genes external side of plasma membrane 8.82E-10 35 266 Downregulated genes leukocyte differentiation 1.06E-09 44 421 Downregulated genes T cell activation 1.45E-09 40 359 Downregulated genes side of membrane 1.77E-09 39 324 Downregulated genes protein binding 3.85E-09 292 6885 Downregulated genes regulation of lymphocyte activation 4.25E-09 35 289 Downregulated genes cell surface 8.20E-09 54 600 Downregulated genes regulation of cell proliferation 2.78E-08 81 1201 Downregulated genes cytokine production 4.94E-08 44 462 Downregulated genes regulation of T cell activation 5.14E-08 28 204 Downregulated genes regulation of cytokine production 1.22E-07 40 405 Downregulated genes alpha-beta T cell activation 2.30E-07 20 101 Downregulated genes regulation of lymphocyte proliferation 3.28E-07 24 161 Downregulated genes regulation of leukocyte activation 3.74E-07 35 335 Downregulated genes locomotion 3.81E-07 79 1162 Downregulated genes regulation of mononuclear cell proliferation 3.92E-07 24 162 Downregulated genes regulation of leukocyte proliferation 6.54E-07 24 167 Downregulated genes regulation of cell activation 8.99E-07 36 361 Downregulated genes positive regulation of T cell activation 1.60E-06 21 131 Up / down regulated GO Term Description Adjusted DE Total P value genes in genes in category category

Downregulated genes lymphocyte proliferation 2.14E-06 27 234 Downregulated genes mononuclear cell proliferation 2.46E-06 27 235 Downregulated genes cellular component movement 2.86E-06 81 1243 Downregulated genes cell proliferation 4.69E-06 88 1503 Downregulated genes leukocyte proliferation 5.12E-06 27 243 Downregulated genes positive regulation of cytokine production 6.14E-06 26 211 Downregulated genes regulation of T cell proliferation 7.00E-06 19 116 Downregulated genes positive regulation of lymphocyte activation 8.18E-06 24 183 Downregulated genes T cell proliferation 8.24E-06 21 144 Downregulated genes positive regulation of response to stimulus 9.32E-06 78 1255 Downregulated genes positive regulation of lymphocyte proliferation 1.27E-05 18 104 Downregulated genes plasma membrane part 1.44E-05 99 1735 Downregulated genes positive regulation of mononuclear cell proliferation 1.59E-05 18 105 Downregulated genes regulation of cellular process 1.77E-05 323 8999 Downregulated genes positive regulation of T cell proliferation 1.92E-05 15 72 Downregulated genes regulation of leukocyte differentiation 1.99E-05 25 210 Downregulated genes response to external stimulus 2.11E-05 79 1425 Downregulated genes positive regulation of cell differentiation 2.14E-05 47 586 Downregulated genes cell migration 2.53E-05 63 898 Downregulated genes positive regulation of leukocyte proliferation 2.96E-05 18 109 Downregulated genes regulation of developmental process 2.98E-05 96 1715 Downregulated genes regulation of signal transduction 3.17E-05 109 1984 Downregulated genes regulation of multicellular organismal process 3.43E-05 108 2045 Downregulated genes positive regulation of immune system process 4.15E-05 41 508 Downregulated genes biological regulation 5.31E-05 347 9972 Downregulated genes regulation of alpha-beta T cell activation 6.32E-05 14 63 Downregulated genes T cell differentiation 6.99E-05 24 191 Downregulated genes regulation of signaling 7.18E-05 118 2244 Downregulated genes lymphocyte differentiation 7.31E-05 29 291 Downregulated genes positive regulation of leukocyte activation 7.61E-05 24 203 Downregulated genes regulation of cell communication 8.14E-05 118 2247 Downregulated genes regulation of biological process 9.40E-05 334 9568 Downregulated genes cell motility 0.000138 64 973 Downregulated genes single-organism cellular process 0.000174 380 11164 Downregulated genes regulation of intracellular signal transduction 0.000207 75 1221 Downregulated genes positive regulation of metabolic process 0.000216 109 2110 Downregulated genes positive regulation of cell activation 0.000231 24 213 Downregulated genes response to stimulus 0.000325 261 7461 Downregulated genes defense response 0.000608 53 918 Downregulated genes regulation of multicellular organismal development 0.000725 77 1351

2 Up / down regulated GO Term Description Adjusted DE Total P value genes in genes in category category

Downregulated genes CD4-positive, alpha-beta T cell activation 0.000857 12 54 Downregulated genes positive regulation of multicellular organismal process 0.000977 41 543 Downregulated genes hemopoiesis 0.001002 36 457 Downregulated genes regulation of metabolic process 0.001018 208 5068 Downregulated genes positive regulation of CD4-positive, alpha-beta T cell activation 0.001109 8 21 Downregulated genes phosphate-containing compound metabolic process 0.001186 138 2917 Downregulated genes chemotaxis 0.001199 34 409 Downregulated genes taxis 0.001294 34 410 Downregulated genes hematopoietic or lymphoid organ development 0.001517 38 507 Downregulated genes phosphorus metabolic process 0.001568 139 2962 Downregulated genes positive regulation of alpha-beta T cell activation 0.001785 11 48 Downregulated genes negative regulation of cellular process 0.001888 138 3034 Downregulated genes cytokine activity 0.001967 18 196 Downregulated genes binding 0.001998 398 11356 Downregulated genes cellular response to chemical stimulus 0.002029 78 1565 Downregulated genes immune system development 0.002166 39 533 Downregulated genes positive regulation of developmental process 0.002309 53 820 Downregulated genes negative regulation of cell proliferation 0.002362 39 514 Downregulated genes actin filament-based process 0.002364 39 475 Downregulated genes regulation of phosphate metabolic process 0.002404 82 1487 Downregulated genes plasma membrane 0.002532 184 4846 Downregulated genes positive regulation of macromolecule metabolic process 0.002566 97 1894 Downregulated genes protein phosphorylation 0.002743 73 1247 Downregulated genes regulation of phosphorus metabolic process 0.002767 82 1492 Downregulated genes regulation of protein modification process 0.002771 61 1003 Downregulated genes positive regulation of phosphorus metabolic process 0.002784 49 737 Downregulated genes positive regulation of phosphate metabolic process 0.002784 49 737 Downregulated genes developmental process 0.002967 186 4478 Downregulated genes positive regulation of cellular metabolic process 0.002976 100 1976 Downregulated genes phosphorylation 0.003084 89 1661 Downregulated genes negative regulation of biological process 0.003124 148 3382 Downregulated genes regulation of immune response 0.003388 34 440 Downregulated genes single-organism developmental process 0.003614 185 4461 Downregulated genes positive regulation of cell proliferation 0.003614 46 692 Downregulated genes multicellular organismal development 0.003758 168 3948 Downregulated genes CD4-positive, alpha-beta T cell differentiation 0.003897 11 50

3 Up / down regulated GO Term Description Adjusted DE Total P value genes in genes in category category

Downregulated genes regulation of protein metabolic process 0.004124 79 1482 Downregulated genes cytokine receptor binding 0.00434 21 231 Downregulated genes immune effector process 0.004694 34 469 Downregulated genes cell periphery 0.004863 186 4944

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