SUPPLEMENTAL MATERIAL FOR:

Pax5 loss imposes a reversible differentiation block in B-progenitor acute lymphoblastic leukemia

Grace J. Liu, Luisa Cimmino, Julian G. Jude, Yifang Hu, Matthew T. Witkowski, Mark D. McKenzie, Mutlu Kartal-Kaess, Sarah A. Best, Laura Tuohey, Yang Liao, Wei Shi, Charles G. Mullighan, Michael A. Farrar, Stephen L. Nutt, Gordon K. Smyth, Johannes Zuber, and Ross A. Dickins

SUPPLEMENTAL FIGURE LEGENDS Figure S1. Restricted expression of Igh variable segments in STAT5-CA;Vav-tTA;TRE- GFP-shPax5 B-ALL. Expression (RNA-seq RPKM) of immunoglobulin heavy chain variable (Ighv) segments in leukemic cells sorted from untreated Rag1-/- mice (black) compared with normal pre-B cells (grey), showing dominant expression of Ighv2-5 in leukemia. Segments are arranged from 5’ to 3’. Mean ± SEM, n=3 mice for each group.

Figure S2. Characterisation of the Pax5 restoration response of independent Stat5-CA; Vav-tTA; TRE-GFP-shPax5 leukemia A008. (A) Peripheral white blood cell (WBC) counts in Rag1–/– mice transplanted with leukemia cells from STAT5-CA;Vav-tTA;TRE-GFP-shPax5 mouse A008. Mean ± SEM, n=4 for each group prior to Dox treatment and following 14 days of Dox treatment as indicated. P < 0.0005, Student’s t test. (B) Flow cytometry of CD19 and IgM expression on mononuclear cells from the peripheral blood of a representative Rag1–/– mouse that was transplanted with leukemia A008 and subsequently Dox treated as indicated. (C) Flow cytometry of CD19 and IgD expression as shown in (B). (D) Leukemia burden (proportion of CD19+ cells in the blood) upon Dox treatment (mean ± SEM, n=4 mice). (E) Proportion of CD19+ cells co-expressing IgM upon Dox treatment (mean ± SEM, n=4 mice). (F) Proportion of IgM+ cells co-expressing IgD upon Dox treatment (mean ± SEM, n=4 mice). (G) Kaplan-Meier survival curve for Rag1–/– mice transplanted with the leukemia A008. Dox treatment of leukemic mice was initiated at day zero. n=3 untreated mice and 5 Dox treated mice, logrank test P < 0.005. (H) Immunophenotype of bone marrow (upper panels), lymph nodes (middle panels) and peripheral blood (lower panels) of representative Rag1–/– recipient mice when moribund following prolonged Dox treatment. Flow cytometry of CD45.1 and CD19 expression is shown on left, and IgM and IgD expression on CD45.1–CD19+ cells is shown on right. (I)

1 profiles of CD45.1–CD19+ leukemia cells freshly isolated from representative untreated and Dox-treated leukemic mice. Percentage of cells in G0/G1 and S/G2/M phases are indicated. (J) Proportion of CD45.1–CD19+ cells in S/G2/M phases in untreated and Dox-treated leukemic mice (mean ± SEM, n=3 mice). Bone marrow P = NS, Blood P < 0.05, Spleen P < 0.005, Lymph node P < 0.05. (K) Quantitative RT-PCR analysis of changes in Pax5, and Rag1 expression in A008 leukemia cells harvested from a Dox-treated leukemic mouse. Results were normalized to housekeeping gene Gapdh and shown relative to levels in leukemia cells from an untreated mouse (mean ± SEM from 3 technical replicates).

Figure S3. Moribund phenotype following long-term Dox treatment of mice transplanted with Stat5-CA; Vav-tTA; TRE-GFP-shPax5 leukemia A024. Immunophenotype of bone marrow (upper panels), blood (middle panels) and spleen (lower panels) of representative Rag1– /– mice bearing triple transgenic leukemia A024, which then became moribund following prolonged Dox treatment. Flow cytometry of CD45.1 (host cell marker) and CD19 expression is shown on left, and CD45.1 and Mac1 is shown on right.

Figure S4. changes upon Pax5 restoration specifically correlate with the large cycling to small resting pre-B transition. Gene set analysis barcode plots (left panels) comparing differential gene expression upon Pax5 restoration in STAT5-CA;Vav-tTA;TRE-GFP- shPax5 leukemia cells in vivo with sets of previously described that are induced (red bars) or repressed (blue bars) upon the transition from: (A) pre-BI to large pre-BII (pro-B to large cycling pre-B); (B) large pre-BII to small pre-BII (large cycling pre-B to small resting pre-B); (C) small resting pre-B to immature B; (D) immature to mature B (Hoffmann et al. 2002). Red/blue traces above/below the bars represent relative enrichment. Scatter plots (right panels) comparing the log2 fold changes upon Pax5 restoration with the log2 fold changes during consecutive stages of normal B lymphocyte development from (Hoffmann et al. 2002). Regression lines are shown in red.

Figure S5. Coordinate upregulation of pre-BCR complex and signaling components following Pax5 restoration. (A) Schematic of the pre-BCR complex and associated signaling molecules. (B-D) Expression (RNA-seq RPKM) of Pax5 (B), selected pre-BCR complex components (C), and critical downstream pre-BCR signaling components (D) in B-ALL cells from untreated and Dox treated mice, compared with normal pre-B cells (mean ± SEM, n=3 mice for each group). (E) Expression (RNA-seq RPKM) of Stat5a and Stat5b as described above.

2 Figure S6. Pax5 restoration induces transcriptional changes associated with loss of Myc activity. Gene set analysis barcode plots comparing differential gene expression upon Pax5 restoration in STAT5-CA;Vav-tTA;TRE-GFP-shPax5 leukemia cells in vivo with sets of previously described genes that are induced (red bars) or repressed (blue bars) upon (A) activation of Myc (Zeller et al., 2003) or (B) or inactivation of Myc (Shachaf et al., 2004). Red/blue traces above/below the bar represent relative enrichment.

Figure S7. Cell cycle analysis and additional control data for B-ALL cell lines. (A) Representative cell cycle flow cytometry profiles of 697 cells, with BrdU and DAPI staining indicating the proportion of cells in S phase 3 days after PAX5-IRES-GFP induction relative to matched IRES-GFP control cells. Cells with less than 2N DNA content were excluded from analysis. (B) Quantitation of S phase cells (%) based on analysis shown in (A). For each cell line, the proportion GFP– (left) and GFP+ (right) cells (gated from within the same population) in S phase following Dox-mediated induction of PAX5-IRES-GFP (red) or control IRES-GFP (blue) is indicated. (C, D) Flow cytometric analysis of cell size/FSC (C) and cell surface markers (D) in GFP– (red line) and GFP+ (green line) cells in B-ALL cell lines showing no changes 3 days after Dox-dependent induction of the control IRES-GFP cassette. (E) Scatter plot of gene expression fold changes upon inducible PAX5 expression in the human B-ALL cell line REH versus Pax5 restoration in STAT5-CA;Vav-tTA;TRE-GFP-shPax5 leukemia A024. Dotted lines indicate 2- fold differential expression, and genes with > 2-fold upregulation in both experiments are shown in red. (F) Gene set analysis barcode plot. The RNA-seq differential gene expression dataset upon Pax5 restoration in STAT5-CA;Vav-tTA;TRE-GFP-shPax5 leukemia cells in vivo is shown as a horizontal bar as described in Figure 5F. Vertical lines indicate the expressed mouse homologs (106 genes) of genes upregulated > 2-fold upon inducible PAX5 expression in REH cells (203 genes). The curved line indicates relative enrichment. A significant positive correlation is observed with genes upregulated upon Pax5 restoration in mouse B-ALL (P < 0.0005, roast test).

3 SUPPLEMENTAL MATERIALS AND METHODS Transgenic mice TRE-GFP-shRNA transgenes were detected by PCR using forward primers specific for each shRNA (Pax5.437: TGTATTTGTCCGAATGATCCTGTTG; Ren.713: GTATAGATAAGCATTATAATTCC) and a common reverse primer (GAAAGAACAATCAAGGGTCC) yielding a 210 bp product. The Stat5b-CA transgene was detected using Stat5b-CA specific forward (TAGGAAGAAGCCTATATCCCAAAGG) and reverse (ACAGTCTCTCAAAGTCAGTGGGG) primers, yielding a 275 bp product. The CAGS-rtTA3 transgene was detected by CAGS specific forward (CTGCTGTCCATTCCTTATTC) and reverse (CGAAACTCTGGTTGACATG) primers, yielding a 200 bp product. The Vav-tTA transgene (Kim et al. 2007) was detected tTA specific forward (CCATACTCACTTTTGCCCTTTAG) and reverse (CAGCGCTGAGTGCATATAATGCA) primers, yielding a 221 bp product. All mice were on an inbred C57BL6/J background except for Vav-tTA mice, which were on an FVB/N background.

Blood and flow cytometry analysis recognising mouse CD19 (eBio1D3), IgM (II/41), IgD (11-26c) and CD93 (AA4.1) were from Affymetrix eBioscience (San Diego, CA). Anti-mouse CD25 (PC61), TCRβ (H57- 597) and Mac1 (M1/70) was from BD Pharmingen (San Jose, CA), while anti-cKit (2B8) was from BioLegend (San Diego, CA). Antibodies against mouse B220 (RA36B2), CD45.1 (A20.1), CD45.2 (S450) and cKit (ACK-4) were generated in-house. Cell preparations were co-stained with Fluoro-Gold to exclude dead cells (Sigma-Aldrich, St Louis, MO). qPCR Total RNA was extracted using RNAeasy Plus Mini Kit (QIAGEN, Valencia, CA) and cDNA was prepared using SuperScript III First-Strand Synthesis System (Life Technologies). qPCR was performed using SYBR Green-based detection in a LightCycler 480 (Roche) using the following primers: Pax5-F, 5'-CCACAGTCCTACCCTATTGTCA-3'; Pax5-R, 5'- GTAATAGTATGGGGAGCCAAGC-3'; Myc-F, 5'-AGAGCTCCTCGAGCTGTTTG -3'; Myc- R, 5'-AGGGCTGTACGGAGTCGTAG-3'; Rag1-F, 5'- CTGGGTTTACCATGAACTCAAA-3'; Rag1-R, 5'-GGTGCTAGGAGAAGACCTCACT-3'; Gapdh-F, 5'- ACCCAGAAGACTGTGGATGG-3'; Gapdh-R, 5'-CCCTGTTGCTGTAGCCGTAT-3'.

4 Human leukemia cell lines The human B-ALL cell lines BV173 (Pegoraro et al. 1983), NALM-6 (Hurwitz et al. 1979), REH (Rosenfeld et al. 1977), and 697 (Findley et al. 1982) were obtained from the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ, Braunschweig, Germany) and cultured as previously described (Drexler 2010). PAX5 copy number data for these cell lines was derived from our previous Affymetrix Mapping 250k SNP array data available in the NCBI Gene Expression Omnibus under GEO series accession number GSE9112 (Mullighan et al. 2008). The NALM-6 cell PAX5 promoter deletion coordinates are 37.025-37.067 Mb (build hg17). Point mutations in PAX5 in REH cells (c.1411insC [numbered according to position in mRNA reference sequence NM_016734]; p.Pro321fs) and 697 cells (c.1122delG; p.Arg225fs) were previously described (Dorfler and Busslinger 1996; Barretina et al. 2012). All cell lines were initially rendered ‘tet-on competent’ by transduction with a lentiviral vector (pRRL-SFFV- rtTA3-IRES-EcoR-PGK-Puro, or RIEP) encoding the ecotropic receptor and the rtTA3 (tet-on) transactivator. Following puromycin selection, cell lines were transduced with an ecotropically packaged retroviral vector (T3-PAX5-IRES-GFP-PGK-Neo) containing a human PAX5-IRES- GFP cassette under control of a third generation TRE promoter (TRE3G, Clontech, Mountain View, CA). Following G418 selection to establish stable cell lines, the PAX5-IRES-GFP (or negative control IRES-GFP) cassette was acutely induced with 1 mg/mL Dox, allowing visualisation of PAX5-expressing cells by flow cytometry. Changes in the proportion of GFP+ cells in PAX5-IRES-GFP cultures relative to negative control IRES-GFP cultures at each time point was calculated relative to levels 4 days following Dox treatment when maximum GFP induction was observed. Flow cytometry of cell surface markers was performed using APC- coupled anti-human CD10 or CD19 (Affymetrix eBioscience), or BV-coupled anti-human CD38 (Biolegend). Pelleted cells were resuspended in 1:20 TruStain Fc Receptor Blocking solution (Biolegend) in 5% FBS/PBS, incubated for 5 minutes at room temperature, and stained with antibodies (1:400) for 15 minutes. Cells were washed twice with 200 µl 5% FBS-BSA prior to FACS analysis. Cell cycle analysis was performed after three (697 cells) or four (REH, NALM-6, BV173 cells) days of Dox treatment using the BrdU Flow Kit (BD Pharmingen), detecting BrdU with an APC-coupled anti-BrdU and DNA with DAPI. Western blotting was performed using rabbit anti-PAX5 antibody D19F8 (Cell Signaling Technology, Danvers, MA). RNA-seq analysis of REH cells was performed after two days of Dox treatment.

Bioinformatics analysis of Pax5 restoration RNA-seq data Total RNA from three untreated and three Dox treated mice was extracted and profiled on an Illumina HiSeq 2000, producing 18.9 million or more 100 bp single end reads per sample. Reads

5 were mapped to the mm9 mouse genome (NCBI build 37.2) using the subread aligner (Liao et al. 2013). Read counts were summarized at the gene level using featureCounts (Liao et al. 2014) using NCBI RefSeq gene annotation. Sequence reads and genewise counts are available from the Gene Expression Omnibus (GEO) series GSE52870. Differential expression analysis used the edgeR (Robinson et al. 2010) and limma software packages. Genes were filtered as not expressed if they failed to achieve at least 0.5 counts per million reads in at least 3 of the 6 samples. All gene IDs without an official symbol were removed from further analysis, as were Y genes, Xist, “GmXXXX” and predicted genes, and ribosomal RNAs Rn18S, Rn28s1, and Rn4.5s, leaving 11,459 genes for downstream analysis. Library sizes were normalized using the TMM method (Robinson and Oshlack 2010) . The voom function of the limma package was used to convert read counts to log2 counts per million with associated precision weights (Law et al. 2014). Differential expression was assessed using empirical Bayes moderated t-statistics (Smyth 2004), controlling the false discovery rate at 5%. RPKM values (reads per million reads per kilobase) were computed using the total exon length for each Entrez gene. Predictive (shrunk) fold changes were computed using the predFC function of the edgeR package with prior.count equal to 5 (McCarthy et al. 2012).

Bioinformatics analysis of pre-B RNA-seq data Total RNA was extracted from pre-B cells of three wild-type mice. RNA-seq reads were generated, mapped and summarized as for the Pax5 restoration experiment. Sequence reads and genewise counts are available as GEO series GSE52868. A customized version of the Subjunc aligner (Liao et al. 2013) was used to map reads Igh segments. The Igh segments don’t contain exons, so the aligner was modified to remove the requirement for splice donor/acceptor sites. Insertions and deletions were allowed in the mapping to accommodate variations in the segment sequences. The number of reads overlapping each segment was counted using featureCounts (Liao et al. 2014) and NCBI RefSeq gene annotation.

Bioinformatics analysis of human leukemia cell line RNA-seq data PAX5 sample and control sample from the REH cell line and additional cell lines (data not shown) were profiled on an Illumina HiSeq 2000 sequencer, producing between 15 million to 18 million 50bp single-end reads for each sample. Reads were mapped to the (GRCh37, hg19) using the subread (Liao et al. 2013) and read were counted for each gene using

6 featureCounts (Liao et al. 2014) and NCBI RefSeq annotation. Sequence reads and genewise counts are available from the Gene Expression Omnibus (GEO) series GSE57480. Entrez genes IDs were removed if they did not have a current gene symbol in the NCBI gene information, and were filtered as not expressed if they failed to show at least one count per million reads in at least 4 samples. Library sizes were normalized using the TMM method (Robinson and Oshlack 2010). Predictive fold changes were computed as described above. To facilitate comparison with the mouse RNA-seq data, human Entrez Gene IDs were converted to mouse orthologs using the human and mouse homology report (downloaded on 12 August 2013) and orthology report (downloaded on 12 December 2012) from the Mouse Genome Informatics website (Blake et al. 2014).

Pathway analysis Gene expression signatures were tested used ROAST rotation gene set testing (Smyth 2004; Wu et al. 2010). ROAST is a hypothesis driven test that takes into account the directionality (up or down) and strength (log2 fold change) of the genes in the gene set. Gene set barcode plots were generated using the barcodeplot function of the limma package as described previously (Lim et al. 2009). analysis used the GOstats package (Falcon and Gentleman 2007).

7 SUPPLEMENTAL REFERENCES

Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, Wilson CJ, Lehar J, Kryukov GV, Sonkin D et al. 2012. The Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483: 603-607. Blake JA, Bult CJ, Eppig JT, Kadin JA, Richardson JE, Mouse Genome Database G. 2014. The Mouse Genome Database: integration of and access to knowledge about the . Nucleic Acids Res 42: D810-817. Dorfler P, Busslinger M. 1996. C-terminal activating and inhibitory domains determine the transactivation potential of BSAP (Pax-5), Pax-2 and Pax-8. EMBO J 15: 1971-1982. Drexler HG. 2010. Guide to leukemia-lymphoma cell lines. DSMZ, Braunschweig. Falcon S, Gentleman R. 2007. Using GOstats to test gene lists for GO term association. Bioinformatics 23: 257-258. Findley HW, Jr., Cooper MD, Kim TH, Alvarado C, Ragab AH. 1982. Two new acute lymphoblastic leukemia cell lines with early B-cell phenotypes. Blood 60: 1305-1309. Hoffmann R, Seidl T, Neeb M, Rolink A, Melchers F. 2002. Changes in gene expression profiles in developing B cells of murine bone marrow. Genome research 12: 98-111. Hurwitz R, Hozier J, LeBien T, Minowada J, Gajl-Peczalska K, Kubonishi I, Kersey J. 1979. Characterization of a leukemic cell line of the pre-B phenotype. Int J Cancer 23: 174-180. Kim WI, Wiesner SM, Largaespada DA. 2007. Vav promoter-tTA conditional transgene expression system for hematopoietic cells drives high level expression in developing B and T cells. Exp Hematol 35: 1231-1239. Law CW, Chen Y, Shi W, Smyth GK. 2014. Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15: R29. Liao Y, Smyth GK, Shi W. 2013. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res 41: e108. Liao Y, Smyth GK, Shi W. 2014. FeatureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30: 923-930. Lim E, Vaillant F, Wu D, Forrest NC, Pal B, Hart AH, Asselin-Labat M-L, Gyorki DE, Ward T, Partanen A et al. 2009. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nature Medicine 15: 907-913. McCarthy DJ, Chen Y, Smyth GK. 2012. Differential expression analysis of multifactor RNA- Seq experiments with respect to biological variation. Nucleic Acids Res 40: 4288-4297. Mullighan CG, Miller CB, Radtke I, Phillips LA, Dalton J, Ma J, White D, Hughes TP, Le Beau MM, Pui C-H et al. 2008. BCR-ABL1 lymphoblastic leukaemia is characterized by the deletion of Ikaros. Nature 453: 110-114. Pegoraro L, Matera L, Ritz J, Levis A, Palumbo A, Biagini G. 1983. Establishment of a Ph1- positive human cell line (BV173). Journal of the National Cancer Institute 70: 447-453. Robinson MD, McCarthy DJ, Smyth GK. 2010. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26: 139-140. Robinson MD, Oshlack A. 2010. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol 11: R25. Rosenfeld C, Goutner A, Choquet C, Venuat AM, Kayibanda B, Pico JL, Greaves MF. 1977. Phenotypic characterisation of a unique non-T, non-B acute lymphoblastic leukaemia cell line. Nature 267: 841-843. Smyth GK. 2004. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3: Article3. Wu D, Lim E, Vaillant F, Asselin-Labat M-L, Visvader JE, Smyth GK. 2010. ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics 26: 2176-2182.

8 GENESDEV/2014/240416 Figure S1 Liu et al normal pre-B cells untreated leukemia A 256 GENESDEV/2014/240416 128 Figure S2

/μl) 64 3 Liu et al 32 untreated 16 14d Dox 8 4 Cell count (x10 2 1 untreated 3d Dox 7d Dox 10d Dox 13d Dox 17d Dox B 105 0.1 0.1 1.5 17.3 28.1 42.4

104

103

102 0

IgM 38.3 61.7 4.5 95.4 5.8 92.6 7.8 74.8 26.4 44.8 27.2 29.8 0 102 103 104 105

C 105 0.1 0.0 0.3 6.0 16.4 31.2

104

103

102 0

IgD 38.3 61.1 4.5 95.5 5.9 93.8 7.9 86.1 27.0 56.5 27.5 41.0 0 102 103 104 105 CD19 D E F 100 100 100 + + 80 80 80 cells

+ 60 60 60 cells also IgM +

40 40 cells also IgD 40 + %CD19 20 20 20 %IgM %CD19 0 0 0 0 3 6 9 12 15 18 0 3 6 9 12 15 18 0 3 6 9 12 15 18 Days of Dox Days of Dox Days of Dox G 100 I Bone marrow Peripheral blood Spleen Lymph node Dox treated 80 untreated

60 untreated 74.1 25.6 80.9 18.9 73.4 26.1 70.1 29.1 40 Survival (%) 20

0 0 5 10 15 20 25 Days CD45.1–CD19+ 3d Dox 78.1 21.5 86.7 13.1 81.5 17.8 75.0 24.3 29.2 H 105 105

4 4 10 10 Cell number 45.6 Bone DNA content 3 3 marrow 10 10 40 102 102 J 43.6 1.7 0 0

4.0 65.7 /M 2 0 102 103 104 105 0 102 103 104 105 30

90.9 20 untreated cells in S/G + 3d Dox 95.0 Lymph 10

nodes %CD19

2.3 0.2 0 1.2 4.9 Bone Peripheral Spleen Lymph marrow blood node 59.9 K 2.5 2.0 95.4 Peripheral 1.5 blood 1.0 after 3d Dox 2.7 0.6 0.5 Relative expression

CD19 2.9 35.9 IgD CD45.1 IgM 0 Pax5 Myc Rag1 GENESDEV/2014/240416 Figure S3 Liu et al

0.7 0.3 79.3 105 105

104 104 Bone 103 103 marrow

102 102 0 0 6.6 92.5 7.2 13.4 0 102 103 104 105 1.6 0.2 84.1

Peripheral blood

9.1 89.1 10.6 5.2

5.5 0.6 25.8

Spleen

CD19 63.5 30.4 Mac1 68.8 5.2

CD45.1 GENESDEV/2014/240416 Figure S4 Liu et al

Pre-BI to large pre-BII transition (Hoffmann) A Pre-BI to large pre-BII transition (Hoffmann): Negative correlatioin, P=0.0285 4 2.4 2 0 Enrichment

increased decreased 0 upon Pax5 upon Pax5 restoration restoration -2 0 logFC 3d Dox vs. untreated -4 1.7 Enrichment -6 -4 -2 0 2 4 logFC in Hoffman table

Large pre-BII to small pre-BII transition (Hoffmann) B Large pre-BII to small pre-BII transition (Hoffmann): Positive correlation, P < 0.0001 4 3.0 2 0 Enrichment increased decreased upon Pax5 upon Pax5 0 restoration restoration -2 0 logFC 3d Dox vs. untreated -4 4.9 Enrichment -6 -4 -2 0 2 4 logFC in Hoffman table

Small pre-BII to immature B transition (Hoffmann) C Small pre-BII to immature B transition (Hoffmann): No significant correlation 4 2.5 2 0 Enrichment

increased decreased 0 upon Pax5 upon Pax5 restoration restoration -2 0 logFC 3d Dox vs. untreated -4 1.9 Enrichment -4 -2 0 2 4 6 logFC in Hoffman table

Immature B to mature B transition (Hoffmann) D Immature B to mature B transition (Hoffmann): No significant correlation 4 2.0 2 0 Enrichment increased decreased upon Pax5 upon Pax5 0 restoration restoration -2 0 logFC 3d Dox vs. untreated -4 2.1 Enrichment -4 -2 0 2 4 logFC in Hoffman table GENESDEV/2014/240416 Figure S5 Liu et al

A B Pax5 VpreB μ chain 300

200

λ5 100

Igα Igβ Expression (RPKM) 0

untreated leukemic 3d Dox normal pre-B P LYN SYK P BTK BLNK

Igll1 Ighm Cd79a Cd79b C Vpreb1 (λ5) (μ chain) (Igα) (Igβ) 2500 1500 8000 1500 1500

2000 6000 1000 1000 1000 1500 4000 1000 500 500 500 2000 500 Expression (RPKM) 0 0 0 0 0

D Syk Blnk Lyn Blk Btk Plcg1 800 400 150 200 150 60

600 300 150 100 100 40 400 200 100 50 50 20 200 100 50 Expression (RPKM) 0 0 0 0 0 0

E Stat5a Stat5b 300

200

100 Expression (RPKM) 0 GENESDEV/2014/240416 Figure S6 Liu et al

‘Myc activation’ (Zeller): A Negative correlation, P=0.0001

2.9 red bars: upregulated upon Myc activation 0 Enrichment

increased decreased upon Pax5 upon Pax5 restoration restoration 0

blue bars: downregulated 2.5 Enrichment upon Myc activation

B ‘Myc withdrawal’ (Shachaf): Positive correlation, P=0.0003 red bars: upregulated

1.7 upon Myc withdrawal 0 Enrichment

increased decreased upon Pax5 upon Pax5 restoration restoration 0

blue bars: downregulated 3.3 Enrichment upon Myc withdrawal GENESDEV/2014/240416 Figure S7 Liu et al A 697 cells GFP– GFP+

105 50.0 57.2 B IRES-GFP 104 PAX5-IRES-GFP 70 IRES-GFP 103 60

50

3 -10 40 0 50K 100K 150K 200K 250K 30 49.8 20.4

%cells in S phase 20

10 PAX5- IRES-GFP 0 GFP– GFP+ GFP– GFP+ GFP– GFP+ GFP– GFP+

BV173 697 REH NALM-6 BrdU

DAPI

100 100 C GFP– D 80 GFP+ 80 60 60 BV173 40 40

20 20

0 0 0 50 100 150 200 250 0 102 103 104 105 0 102 103 104 105 0 102 103 104 105

697

REH

NALM-6 %Max %Max FSC CD19 CD38 CD10

E 6 F PAX5 PAX5-upregulated genes in REH cells: BACH2 Positive correlation, P < 0.0005 3 4 TNFRSF13C (BAFF-R)

2 IGLC7 (Iglc3) Enrichment 0

increased decreased 0 (fold change) in REH:

2 upon Pax5 upon Pax5

log restoration restoration PAX5-IRES-GFP vs. IRES-GFP -2

-2 0 2 4

log2(fold change) in mouse: 3d Dox vs. untreated Table S1. Summary of leukemias arising in STAT5b-CA; Vav-tTA; TRE-GFP-shPax5 mice PRIMARY LEUKEMIA DOX RESPONSE OF TRANSPLANTED LEUKEMIA + Immunophenotypic Cell cycle Acute leukemia Mouse Age %Blasts %GFP differentiation arrest regression A008 172 10 93 Upregulation of IgM and IgD YES YES A018 172 18 53 A024 98 64 94 Upregulation of IgM YES YES A030 135 A036 145 A039 147 B001 131 60 95 NO YES B010 134 66 99 Downregulation of CD25 NO B015 142 58 91 B018 167 B025 229 76 94 B027 141 B028 125 77 90 B030 190 B044 212 48 87 B046 247 40 78

Age: age of mouse at moribund disease stage %Blasts: percentage of CD19+IgM–CD25+ leukemic blasts in peripheral blood + %GFP : percentage of leukemic blasts in peripheral blood expressing GFP Shaded box indicates parameter was not tested Table S2. Genes upregulated upon Pax5 restoration in B-ALL cells in vivo, ranked by fold change. GENES UPREGULATED upon Pax5 restoration, ranked by fold change Rank Symbol logFC AveExpr t P.Value FDR 1 Col5a3 8.12 1.01 9.38 3.80E-06 4.43E-05 2 Tmc5 7.81 -0.14 14.36 8.18E-08 4.56E-06 3 Cdhr2 6.18 1.91 7.53 2.50E-05 1.68E-04 4 Serpina3f 6.03 0.93 14.47 7.61E-08 4.46E-06 5 Rapgef4 5.69 -1.38 11.38 6.80E-07 1.45E-05 6 Iglv2 5.52 -0.56 3.40 7.17E-03 1.54E-02 7 Rag2 5.27 2.62 11.65 5.52E-07 1.30E-05 8 Ltbp2 5.21 2.57 9.50 3.41E-06 4.12E-05 9 Plb1 5.12 0.35 6.96 4.75E-05 2.71E-04 10 Evi5 5.09 -1.38 5.96 1.64E-04 7.00E-04 11 2310033E01Rik 5.04 -1.72 9.71 2.81E-06 3.55E-05 12 Aicda 4.95 -1.07 8.36 1.03E-05 8.87E-05 13 Iglj1 4.93 0.89 3.13 1.12E-02 2.23E-02 14 Prg3 4.91 -1.05 8.60 8.11E-06 7.51E-05 15 Cd40 4.91 0.40 6.00 1.54E-04 6.65E-04 16 A430084P05Rik 4.88 -0.27 11.63 5.59E-07 1.30E-05 17 Igkv2-112 4.81 1.19 4.16 2.13E-03 5.54E-03 18 Hdac11 4.71 1.53 12.92 2.17E-07 7.70E-06 19 Igkv3-12 4.69 2.97 3.83 3.57E-03 8.58E-03 20 Gas2l1 4.67 -2.46 11.03 9.05E-07 1.70E-05 21 Ighg2b 4.62 -1.22 6.87 5.32E-05 2.94E-04 22 Iglv1 4.55 4.65 3.28 8.77E-03 1.82E-02 23 Klhl14 4.52 1.09 11.60 5.73E-07 1.31E-05 24 Rasl10a 4.51 -0.78 10.78 1.11E-06 1.95E-05 25 Mybpc1 4.51 -0.99 6.83 5.57E-05 3.04E-04 26 Pgm5 4.49 -1.60 8.62 7.89E-06 7.35E-05 27 B230118H07Rik 4.47 0.87 5.84 1.90E-04 7.83E-04 28 Polm 4.45 3.76 12.72 2.49E-07 8.35E-06 29 Igkv8-23-1 4.43 -2.16 8.93 5.81E-06 6.00E-05 30 Faim3 4.41 -0.75 5.62 2.55E-04 9.94E-04 31 Pde4c 4.33 2.46 12.49 2.95E-07 9.09E-06 32 Abcb4 4.32 3.32 25.80 3.37E-10 3.21E-07 33 Cnr2 4.27 1.64 7.10 4.05E-05 2.41E-04 34 Igkv17-121 4.25 -2.13 6.83 5.53E-05 3.03E-04 35 BE692007 4.22 -0.30 4.86 7.37E-04 2.32E-03 36 4833411C07Rik 4.19 -2.67 10.11 1.97E-06 2.82E-05 37 Ifi30 4.17 6.18 27.71 1.71E-10 2.79E-07 38 Igkv1-117 4.12 0.06 8.71 7.27E-06 6.93E-05 39 Iglc1 4.10 5.00 3.02 1.36E-02 2.64E-02 40 Adam19 4.09 4.71 8.23 1.17E-05 9.77E-05 41 Sorcs2 4.07 5.10 27.87 1.62E-10 2.79E-07 42 Igkv6-25 4.06 -1.16 5.20 4.59E-04 1.58E-03 43 Rbm44 4.06 -1.57 7.71 2.05E-05 1.46E-04 44 Slc22a12 4.05 -1.33 6.74 6.19E-05 3.31E-04 45 Slc47a1 4.04 -0.98 6.05 1.45E-04 6.33E-04 46 Gjc2 4.04 0.96 9.43 3.63E-06 4.28E-05 47 Ms4a1 4.00 4.73 16.41 2.38E-08 2.62E-06 48 4933413J09Rik 3.99 0.05 9.52 3.35E-06 4.07E-05 49 Cdh17 3.97 0.98 7.03 4.41E-05 2.57E-04 50 Ildr1 3.96 -0.04 10.07 2.04E-06 2.87E-05 51 Igkv6-17 3.92 -0.67 6.49 8.33E-05 4.16E-04 52 Rag1 3.91 8.72 10.72 1.17E-06 2.01E-05 53 Tnfsf14 3.90 -1.10 8.10 1.35E-05 1.09E-04 54 Dnahc5 3.89 -0.98 5.35 3.71E-04 1.33E-03 55 Aldh1b1 3.85 -0.78 7.56 2.41E-05 1.64E-04 56 Gpr84 3.84 0.46 9.68 2.89E-06 3.62E-05 57 Igkv1-122 3.82 -1.33 4.92 6.81E-04 2.18E-03 58 Tlr13 3.81 -1.36 5.61 2.58E-04 1.00E-03 59 Igkv6-32 3.78 -2.08 5.79 2.05E-04 8.32E-04 60 Speer2 3.77 0.67 7.81 1.83E-05 1.35E-04 61 Mertk 3.75 -1.62 6.43 8.99E-05 4.41E-04 62 Igf1 3.73 -1.55 5.85 1.88E-04 7.76E-04 63 Tmem163 3.72 2.00 8.06 1.40E-05 1.12E-04 64 Igkv17-127 3.68 -1.22 5.85 1.89E-04 7.80E-04 65 Emr1 3.67 -0.76 6.92 4.97E-05 2.81E-04 66 Ffar1 3.67 -0.50 8.73 7.09E-06 6.82E-05 67 Tmc7 3.66 2.87 21.79 1.66E-09 8.17E-07 68 Ltb 3.61 2.66 5.06 5.53E-04 1.84E-03 69 Slco2b1 3.61 -1.71 5.78 2.08E-04 8.41E-04 70 Slco1b2 3.60 2.74 7.66 2.16E-05 1.52E-04 71 Svopl 3.56 -0.77 8.72 7.16E-06 6.87E-05 72 March1 3.55 1.00 11.54 6.02E-07 1.34E-05 73 Slc7a8 3.55 -1.53 5.96 1.64E-04 6.97E-04 74 4632428N05Rik 3.54 5.27 29.88 8.33E-11 2.65E-07 75 Rap1gap2 3.52 1.91 9.17 4.61E-06 5.07E-05 Table S3. Genes downregulated upon Pax5 restoration in B-ALL cells in vivo, ranked by t statistic GENES DOWNREGULATED upon Pax5 restoration, ranked by t statistic Rank Symbol logFC AveExpr t P.Value FDR 1 Wapal -3.23 4.99 -21.55 1.85E-09 8.17E-07 2 Emp1 -2.11 5.56 -21.01 2.35E-09 9.23E-07 3 Cdca7 -1.56 8.03 -19.73 4.24E-09 1.19E-06 4 Exo1 -1.47 5.70 -19.62 4.48E-09 1.22E-06 5 Mcm2 -1.22 8.43 -19.38 5.01E-09 1.30E-06 6 Chek1 -1.51 5.82 -19.15 5.61E-09 1.40E-06 7 Cdc6 -1.45 5.92 -18.88 6.41E-09 1.50E-06 8 Dut -1.38 7.44 -18.83 6.59E-09 1.51E-06 9 Mcm5 -1.29 8.61 -18.55 7.58E-09 1.62E-06 10 Shmt1 -1.44 6.29 -18.50 7.77E-09 1.62E-06 11 Rad51 -1.40 6.15 -18.48 7.84E-09 1.62E-06 12 Mcm3 -1.35 8.62 -18.28 8.70E-09 1.69E-06 13 Mcm6 -1.30 9.06 -18.22 8.95E-09 1.71E-06 14 Gspt1 -1.13 8.02 -18.15 9.28E-09 1.74E-06 15 Car2 -1.76 9.37 -18.11 9.48E-09 1.75E-06 16 Rpa2 -1.31 6.68 -17.86 1.08E-08 1.93E-06 17 Fignl1 -1.35 7.01 -17.81 1.10E-08 1.94E-06 18 Fen1 -1.14 7.29 -17.79 1.12E-08 1.94E-06 19 Ung -1.49 5.47 -17.63 1.22E-08 2.06E-06 20 Mcm10 -1.67 6.50 -17.58 1.25E-08 2.07E-06 21 Mcm4 -1.31 8.29 -17.48 1.32E-08 2.13E-06 22 Mcm7 -1.27 7.94 -17.44 1.35E-08 2.14E-06 23 E2f1 -1.44 5.55 -17.23 1.51E-08 2.22E-06 24 Lsm2 -1.07 6.16 -17.20 1.53E-08 2.23E-06 25 Slc25a10 -1.31 4.93 -17.05 1.66E-08 2.33E-06 26 Cdc7 -1.32 5.83 -17.02 1.69E-08 2.33E-06 27 Tk1 -1.27 6.02 -17.01 1.70E-08 2.33E-06 28 Ifrd2 -1.27 5.61 -16.97 1.74E-08 2.33E-06 29 Tyms -1.23 5.98 -16.83 1.88E-08 2.40E-06 30 Dnajc9 -1.05 7.87 -16.77 1.95E-08 2.44E-06 31 Uhrf1 -1.20 9.99 -16.74 1.98E-08 2.44E-06 32 Chaf1a -1.25 7.02 -16.72 2.00E-08 2.44E-06 33 Prim1 -1.24 6.53 -16.67 2.05E-08 2.47E-06 34 Spc24 -1.26 5.71 -16.58 2.16E-08 2.50E-06 35 2010317E24Rik -1.28 5.89 -16.42 2.37E-08 2.62E-06 36 Ranbp1 -1.09 7.57 -16.40 2.39E-08 2.62E-06 37 Tspan2 -1.27 6.29 -16.37 2.43E-08 2.62E-06 38 Cdc25a -1.06 6.29 -16.35 2.45E-08 2.62E-06 39 Myc -1.64 7.50 -16.32 2.50E-08 2.62E-06 40 Rrm2 -1.23 8.49 -16.29 2.54E-08 2.62E-06 41 Tipin -1.03 6.72 -16.26 2.59E-08 2.62E-06 42 Ccdc34 -1.34 5.00 -16.23 2.64E-08 2.62E-06 43 Zfp367 -1.21 5.76 -16.21 2.66E-08 2.62E-06 44 Cdc45 -1.32 6.24 -16.21 2.66E-08 2.62E-06 45 Arvcf -1.17 7.01 -16.15 2.76E-08 2.62E-06 46 Cdt1 -1.44 6.23 -16.12 2.81E-08 2.64E-06 47 Lig1 -1.26 8.11 -16.08 2.87E-08 2.67E-06 48 Polr1b -1.07 6.05 -16.03 2.97E-08 2.72E-06 49 Bard1 -1.40 5.84 -15.96 3.09E-08 2.79E-06 50 Nasp -1.21 7.58 -15.87 3.24E-08 2.85E-06 51 Hspd1 -1.07 7.52 -15.78 3.43E-08 3.00E-06 52 Pola1 -1.32 7.43 -15.68 3.63E-08 3.11E-06 53 Pold1 -1.07 8.36 -15.67 3.66E-08 3.11E-06 54 Cenpn -1.41 6.13 -15.57 3.87E-08 3.19E-06 55 Timeless -1.62 6.69 -15.51 4.02E-08 3.23E-06 56 Hn1l -1.18 6.31 -15.50 4.04E-08 3.23E-06 57 Tubb5 -1.23 9.53 -15.26 4.67E-08 3.57E-06 58 Dtl -1.51 7.13 -15.25 4.70E-08 3.57E-06 59 Pcna -1.18 7.93 -15.21 4.83E-08 3.59E-06 60 Wee1 -1.15 6.50 -15.18 4.90E-08 3.62E-06 61 Umps -1.21 6.63 -15.15 4.98E-08 3.64E-06 62 Ppat -1.12 6.66 -15.10 5.14E-08 3.71E-06 63 Gins1 -1.37 5.05 -15.01 5.45E-08 3.84E-06 64 Rfc3 -0.95 6.43 -15.00 5.47E-08 3.84E-06 65 Gnl3 -1.25 7.12 -14.97 5.58E-08 3.90E-06 66 Tcf19 -1.26 6.37 -14.96 5.61E-08 3.90E-06 67 Gins2 -1.18 5.49 -14.91 5.79E-08 3.97E-06 68 Chtf18 -1.47 5.53 -14.88 5.91E-08 4.01E-06 69 Odc1 -1.02 7.04 -14.86 5.97E-08 4.02E-06 70 Snrpa1 -0.90 6.52 -14.84 6.05E-08 4.03E-06 71 Kntc1 -1.39 6.28 -14.82 6.11E-08 4.03E-06 72 Gmnn -1.34 6.14 -14.79 6.25E-08 4.05E-06 73 Pole -1.53 7.44 -14.74 6.45E-08 4.13E-06 74 Grwd1 -1.08 5.31 -14.73 6.49E-08 4.13E-06 75 Oaf -1.11 5.89 -14.71 6.54E-08 4.14E-06 Table S4. Gene ontology (Biological Process) of downregulated genes (RNA-seq) upon Pax5 restoration in B-ALL. Rank GOBPID Pvalue OddsRatio ExpCount Count Size Term 1 GO:0006259 5.18E-39 5.75 28 111 621 DNA metabolic process 2 GO:0007049 6.31E-39 4.79 41 136 917 cell cycle 3 GO:0022403 5.31E-38 6.41 22 97 487 cell cycle phase 4 GO:0006260 1.60E-36 11.21 9 62 196 DNA replication 5 GO:0022402 1.55E-34 5.19 29 107 644 cell cycle process 6 GO:0000279 2.37E-32 6.67 16 78 368 M phase 7 GO:0000278 6.54E-31 5.80 20 84 446 mitotic cell cycle 8 GO:0000280 7.27E-28 7.20 12 62 269 nuclear division 9 GO:0007067 7.27E-28 7.20 12 62 269 10 GO:0000087 2.69E-27 7.00 12 62 275 M phase of mitotic cell cycle 11 GO:0051301 3.78E-26 5.75 16 70 366 cell division 12 GO:0048285 4.94E-26 6.56 13 62 289 organelle fission 13 GO:0006261 1.61E-23 18.94 3 30 66 DNA-dependent DNA replication 14 GO:0006974 4.32E-22 4.63 20 72 449 response to DNA damage stimulus 15 GO:0007059 1.30E-19 8.96 6 36 128 chromosome segregation 16 GO:0006281 4.88E-19 4.98 14 56 321 DNA repair 17 GO:0006725 3.83E-18 2.27 146 235 3275 cellular aromatic compound metabolic process 18 GO:1901360 6.17E-18 2.26 150 239 3367 organic cyclic compound metabolic process 19 GO:0034641 6.96E-18 2.25 151 239 3370 cellular nitrogen compound metabolic process 20 GO:0046483 2.05E-17 2.23 146 233 3276 heterocycle metabolic process 21 GO:0006139 2.50E-17 2.23 143 229 3201 nucleobase-containing compound metabolic process 22 GO:0006807 2.30E-16 2.16 157 242 3520 nitrogen compound metabolic process 23 GO:0010564 6.65E-16 4.93 12 46 262 regulation of cell cycle process 24 GO:0051325 1.87E-15 6.43 7 35 159 interphase 25 GO:0033554 4.73E-15 2.98 34 84 766 cellular response to stress 26 GO:0051329 2.79E-14 6.19 7 33 154 interphase of mitotic cell cycle 27 GO:0051726 5.58E-14 3.52 20 59 452 regulation of cell cycle 28 GO:0090304 6.45E-14 2.09 119 192 2674 nucleic acid metabolic process 29 GO:0000086 4.76E-13 15.67 2 17 41 G2/M transition of mitotic cell cycle 30 GO:0000226 1.02E-12 4.61 10 38 226 microtubule organization 31 GO:0006996 1.70E-12 2.22 70 127 1557 organelle organization 32 GO:0006270 4.50E-12 48.13 1 11 16 DNA replication initiation 33 GO:0006310 4.87E-12 5.50 7 30 153 DNA recombination 34 GO:0007017 2.18E-11 3.64 14 44 321 microtubule-based process 35 GO:0051320 2.71E-11 14.37 2 15 38 S phase 36 GO:0006302 2.33E-10 6.44 4 22 98 double-strand break repair 37 GO:0007051 4.48E-10 8.12 3 18 67 spindle organization 38 GO:0071840 4.51E-10 1.87 113 172 2535 cellular component organization or biogenesis 39 GO:0044249 7.08E-10 1.82 128 188 2865 cellular biosynthetic process 40 GO:0051276 8.94E-10 2.70 25 58 555 chromosome organization 41 GO:0006730 9.13E-10 27.28 1 10 18 one-carbon metabolic process 42 GO:0051052 1.28E-09 4.65 7 27 157 regulation of DNA metabolic process 43 GO:0071156 1.48E-09 4.98 6 25 137 regulation of cell cycle arrest 44 GO:0016043 1.57E-09 1.84 108 164 2418 cellular component organization 45 GO:0007346 1.98E-09 4.25 8 29 182 regulation of mitotic cell cycle 46 GO:2000602 2.26E-09 6.67 4 19 82 regulation of interphase of mitotic cell cycle 47 GO:0010948 2.80E-09 7.66 3 17 66 negative regulation of cell cycle process 48 GO:1901576 3.45E-09 1.77 130 188 2918 organic substance biosynthetic process 49 GO:0009058 6.47E-09 1.75 132 189 2960 biosynthetic process 50 GO:0071103 6.88E-09 5.20 5 22 116 DNA conformation change 51 GO:0033261 1.36E-08 14.14 1 11 28 regulation of S phase 52 GO:0009987 1.57E-08 1.86 337 390 7546 cellular process 53 GO:0044238 1.58E-08 1.69 238 298 5336 primary metabolic process 54 GO:0071704 1.71E-08 1.70 246 305 5499 organic substance metabolic process 55 GO:0000084 3.18E-08 12.65 1 11 30 S phase of mitotic cell cycle 56 GO:0000724 4.71E-08 8.90 2 13 45 double-strand break repair via homologous recombination 57 GO:0000725 6.30E-08 8.63 2 13 46 recombinational repair 58 GO:0045786 6.42E-08 3.46 10 30 224 negative regulation of cell cycle 59 GO:0007050 9.59E-08 3.79 8 26 179 cell cycle arrest 60 GO:0051297 1.07E-07 7.31 3 14 56 centrosome organization 61 GO:0000819 2.38E-07 8.47 2 12 43 sister chromatid segregation 62 GO:0044237 2.55E-07 1.61 240 294 5368 cellular metabolic process 63 GO:0031023 2.72E-07 6.67 3 14 60 microtubule organizing center organization 64 GO:0006950 2.93E-07 1.86 61 100 1373 response to stress 65 GO:0000075 3.58E-07 4.38 5 20 121 cell cycle checkpoint 66 GO:0009059 3.65E-07 1.67 110 157 2466 macromolecule biosynthetic process 67 GO:0051225 3.74E-07 9.24 2 11 37 spindle assembly 68 GO:0034645 6.96E-07 1.66 108 153 2411 cellular macromolecule biosynthetic process 69 GO:0071897 7.07E-07 12.24 1 9 25 DNA biosynthetic process 70 GO:0006323 8.88E-07 5.10 4 16 85 DNA packaging 71 GO:0000070 8.96E-07 8.28 2 11 40 mitotic sister chromatid segregation 72 GO:0031570 1.39E-06 5.68 3 14 68 DNA integrity checkpoint 73 GO:0007062 1.50E-06 10.88 1 9 27 sister chromatid cohesion 74 GO:0010389 1.82E-06 13.37 1 8 21 regulation of G2/M transition of mitotic cell cycle 75 GO:0008152 1.93E-06 1.57 269 318 6017 metabolic process Table S5. Genes with highest expression in B-ALL cells (RNA-seq RPKM). Pre-BCR components are highlighted. Rank Symbol AveExpr 1 LOC100503946 5100.45 2 Mir682 2388.69 3 Rpl39-ps 1797.61 4 Ubb 1765.43 5 Eef1a1 1723.59 6 B2m 1609.34 7 Rpl8 1571.29 8 Rpl41 1441.51 9 Rps6-ps4 1425.18 10 Rps19-ps6 1418.07 11 Hsp90ab1 1417.47 12 Ighm 1321.23 13 Rpl4 1226.62 14 Actb 1155.99 15 Rpl32 1143.24 16 Cd24a 1140.77 17 Rplp1 1116.77 18 Vpreb1 1108.91 19 Vpreb3 1091.88 20 Igkc 1086.92 21 Rpl31-ps8 1069.88 22 Plac8 1068.71 23 Rps15 1050.97 24 Rps9 928.24 25 Cfl1 905.61 26 Eef2 888.63 27 Pfn1 869.41 28 Rps11 850.14 29 Serinc3 838.41 30 Coro1a 835.59 31 Rplp0 831.24 32 Atp5b 821.77 33 Rps23-ps 776.74 34 H2-D1 774.30 35 Ppia 762.38 36 Ucp2 744.54 37 Vpreb2 744.23 38 Pou2af1 727.65 39 Igll1 709.46 40 Myl4 707.58 41 Rps15a-ps7 700.53 42 Arhgdib 690.63 43 Ly6e 677.03 44 Gnb2l1 675.13 45 Myl10 673.99 46 Car2 663.77 47 Rps3 656.07 48 Rps23 649.29 49 Rps26 638.43 50 Rpl26 637.14 51 Ighj1 635.69 52 H2-K1 619.08 53 Ptma 592.81 54 Pabpc1 567.41 55 Cd79b 567.21 56 Hnrnpa2b1 563.26 57 Hnrnpu 560.36 58 Rpl7 559.79 59 Cd79a 554.09 60 Igkv14-111 549.27 61 Ighd4-1 526.42 62 Eif5a 518.84 63 Rpl31-ps13 516.08 64 Atp5g3 510.30 65 Ifi27l2a 508.33 66 Anp32b 508.23 67 H2afy 503.50 68 Lrmp 498.21 69 2010001M09Rik 494.50 70 Pgls 487.76 71 Slc25a5 485.69 72 Rpl19 484.29 73 Rps14 484.01 74 Rps18 478.14 75 Ywhae 475.89 Table S6. Genes with >2-fold induction in both human cell line REH following PAX5 induction and mouse B-ALL upon Pax5 restoration Human gene REH logFC Mouse gene Mouse logFC HTRA3 3.595 Htra3 1.014 PARVB 2.626 Parvb 1.448 KLHL14 2.104 Klhl14 3.703 SPNS2 1.845 Spns2 1.018 WDR66 1.845 Wdr66 1.111 CNR2 1.739 Cnr2 3.746 IRAK2 1.657 Irak2 1.903 RAPGEF3 1.580 Rapgef3 1.281 PAX5 1.552 Pax5 1.062 SDC3 1.551 Sdc3 2.31 AHNAK 1.520 Ahnak 1.42 TNFRSF13C 1.495 Tnfrsf13c 2.196 ADCY7 1.422 Adcy7 2.122 TLE6 1.357 Tle6 1.568 CD37 1.342 Cd37 1.207 IGLC7 1.259 Iglc3 2.009 SAMHD1 1.255 Samhd1 1.323 THEMIS2 1.251 Themis2 1.074 SMAD7 1.246 Smad7 1.177 DOK4 1.211 Dok4 1.031 KDM7A 1.146 Kdm7a 1.675 BTG2 1.131 Btg2 2.055 ABCA1 1.127 Abca1 2.781 IGFBP4 1.118 Igfbp4 1.084 TMC8 1.114 Tmc8 1.221 BACH2 1.104 Bach2 1.073 CD52 1.073 Cd52 1.188 PMEPA1 1.069 Pmepa1 1.213 ABLIM1 1.064 Ablim1 1.441 SKI 1.057 Ski 1.191 OSTM1 1.052 Ostm1 1.181