PDF Output of CLIC (Clustering by Inferred Co-Expression)

PDF Output of CLIC (clustering by inferred co-expression)

Dataset: Num of genes in input gene set: 5 Total number of genes: 16493

CLIC PDF output has three sections:

1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set.

Red lines shows the partition of input genes into CEMs, ordered by CEM strength.

Each row shows one gene, and the brightness of squares indicates its correlations with other genes.

Gene symbols are shown at left side and on the top of the heatmap.

2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets.

Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows).

Each column is one GEO series dataset, sorted by their posterior probability of being selected.

The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset.

CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score.

3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset.

Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Srp54b Srp72 Srp68 Srp19 Num ofGenesinQueryGeneset:5.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Srp9

Srp9 Srp19 Srp68 Srp72 Srp54b CEM 1(59datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 D17Wsu104e Symbol Num ofCEMGenes:5.Predicted248.SelectedDatasets:59.Strength:0.4 CEM 1,Geneset"[G]signalrecognitionparticle,endoplasmicreticulumtargeting",Page1 Ppapdc1b Tmem248 Tmem39a Cdk5rap3 Gorasp2 Slc35b1 Slc39a7 Fam98a Krtcap2 Clptm1l Morf4l2 Sec61b Sec23b Mrps12 Gmppb Sec11a Srp54b Dpagt1 Zfp330 Tmed9 Copg1 Lrrc59 Tram1 Eif2s2 Spcs3 Spcs2 Sec13 Tssc4 Hdlbp Ddost Srp72 Srp68 Srp19 Serp1 Trabd Nme6 Srprb Surf4 Ufm1 Cope Uba5 Yipf5 Manf Nars Srp9 Ssr2 Ssr1 Ssr3 Srm 0.0 1.0

GSE39916 [6] GSE48935 [12]

GSE4142 [14] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE48932 [12] GSE29929 [14] GSE12693 [6] GSE21041 [6] GSE38031 [8] GSE27038 [12] GSE17509 [57] GSE35825 [9] GSE54678 [6] GSE17184 [12] GSE31638 [15] GSE8682 [8] GSE30861 [35] GSE51108 [6] GSE12881 [6] GSE24031 [18] GSE21491 [9] GSE31313 [22] GSE15871 [18] GSE13443 [27] GSE38138 [20] GSE14753 [6] GSE42473 [15] GSE13948 [21] GSE9249 [28] GSE24813 [10] GSE38136 [24] GSE43899 [12] GSE25088 [24] GSE22125 [6] GSE13693 [9] GSE13692 [8] GSE45051 [18] GSE28621 [21] GSE21272 [44] GSE3313 [24] GSE25140 [16] GSE18135 [18] GSE34423 [40] GSE44356 [18] GSE16691 [12] GSE27019 [6] GSE29241 [6] GSE9954 [70] GSE20391 [11] GSE31086 [6] GSE17925 [12] GSE12389 [8] GSE7348 [6] GSE11494 [16] GSE57425 [6] GSE20954 [14] GSE46150 [8] GSE22418 [8] GSE28895 [6] GSE5861 [6] GSE4734 [61] GSE38880 [12] GSE9013 [12] GSE19732 [20] GSE29262 [12] GSE35593 [6] GSE24207 [73] GSE34729 [6] GSE24078 [6] GSE46869 [6] GSE29048 [8] GSE33726 [48] GSE11680 [10] GSE9717 [6] GSE53951 [10] GSE28333 [6] GSE22774 [6] GSE30160 [6] GSE3889 [20] GSE7275 [8] GSE18858 [242] GSE7050 [18] GSE18500 [35] GSE3501 [6] GSE13963 [15] GSE45618 [6] GSE53590 [8] GSE2197 [6] GSE19517 [6] GSE27972 [6] GSE48204 [6] GSE35226 [12] GSE34552 [10] GSE38141 [18] GSE26695 [20] GSE34126 [19] GSE34961 [9] GSE8322 [12] GSE25645 [17] GSE4288 [36] GSE44101 [6] GSE11684 [16] GSE9913 [9] GSE34959 [10] GSE13590 [12] GSE17649 [36] GSE10525 [18] GSE2019 [12] GSE23040 [6] GSE5959 [6] GSE55809 [8] GSE38574 [32] GSE1435 [27] GSE12073 [12] GSE18745 [6] GSE37431 [6] GSE56492 [12] GSE32986 [18] GSE56162 [18] GSE25636 [8] GSE40230 [15] GSE46871 [6] GSE45820 [6] GSE9878 [6] GSE17373 [24] GSE18907 [12] GSE24437 [6] GSE51483 [45] GSE39355 [7] GSE7685 [12] GSE3583 [9] GSE52597 [7] GSE39375 [10] GSE32103 [6] GSE17322 [6] GSE13874 [14] GSE6837 [8] GSE14344 [6] GSE40655 [6] GSE55607 [18] GSE42238 [9] GSE6675 [8] GSE35805 [8] GSE9711 [6] GSE43620 [8] GSE39897 [36] GSE36437 [6] GSE55028 [6] GSE32624 [6] GSE10202 [8] GSE28887 [12] GSE36378 [20] GSE36665 [6] GSE9566 [38] GSE14007 [8] CEM+ CEM GSE55003 [12] GSE7759 [112] GSE4718 [6] GSE34839 [6] GSE19272 [30] GSE31150 [6] 0.0 GSE18115 [8] GSE24789 [9]

GSE20426 [35] Scale ofaveragePearsoncorrelations GSE35436 [6] GSE11147 [6] GSE5425 [6] GSE7838 [9] GSE35543 [6] GSE47196 [6] 0.2 GSE12748 [7] GSE13033 [6] GSE18771 [6] GSE30863 [20] GSE10478 [6] GSE56777 [8] GSE7503 [6] GSE30488 [52] GSE35332 [12] 0.4 GSE55733 [24] GSE40773 [10] GSE32681 [61] GSE9804 [9] GSE38304 [8] GSE11572 [12] GSE30957 [16] GSE10162 [6] GSE47719 [6] 0.6 GSE18148 [6] GSE20944 [18] GSE21836 [8] GSE7430 [12] GSE30012 [6] GSE15580 [14] GSE33156 [18] GSE37546 [20] GSE37676 [6] 0.8 GSE8312 [6] GSE50603 [12] GSE32277 [33] GSE28408 [6] Score 37.95 39.24 39.57 40.40 40.42 40.96 42.44 43.89 44.57 45.47 45.73 46.03 46.59 47.65 47.94 50.01 50.60 51.42 51.81 51.93 52.42 52.81 52.95 53.38 56.64 56.79 58.05 58.07 58.29 59.00 60.74 62.39 66.25 67.10 68.23 68.29 69.44 69.46 70.01 70.93 70.96 71.10 72.15 73.07 79.29 1.0 Notes Symbol Num ofCEMGenes:5.Predicted248.SelectedDatasets:59.Strength:0.4 CEM 1,Geneset"[G]signalrecognitionparticle,endoplasmicreticulumtargeting",Page2 Mrps18b Txndc11 Sec61a1 Nr2c2ap Dnajb11 Armcx3 Nudcd1 Hspa13 Sec22b Sec24d Magoh Creld2 Copb2 Hspa5 Sdf2l1 Cks1b Eif2b4 Ddx49 Sec63 Tasp1 Jagn1 Mettl1 Abcf3 Sar1a Pycr2 Pgm3 Pdia6 Txnl1 Mogs Prrc1 Copa P4hb Deb1 Dad1 Eif3b Nans Vimp Nfxl1 Uso1 Eif3g Yrdc Bet1 Elp5 Elp3 Lars Tars Ift20 Arf4 Ufl1 Tfg 0.0 1.0

GSE39916 [6] GSE48935 [12]

GSE20426 [35] Scale ofaveragePearsoncorrelations GSE35436 [6] GSE11147 [6] GSE5425 [6] GSE7838 [9] GSE35543 [6] GSE47196 [6] 0.2 GSE12748 [7] GSE13033 [6] GSE18771 [6] GSE30863 [20] GSE10478 [6] GSE56777 [8] GSE7503 [6] GSE30488 [52] GSE35332 [12] 0.4 GSE55733 [24] GSE40773 [10] GSE32681 [61] GSE9804 [9] GSE38304 [8] GSE11572 [12] GSE30957 [16] GSE10162 [6] GSE47719 [6] 0.6 GSE18148 [6] GSE20944 [18] GSE21836 [8] GSE7430 [12] GSE30012 [6] GSE15580 [14] GSE33156 [18] GSE37546 [20] GSE37676 [6] 0.8 GSE8312 [6] GSE50603 [12] GSE32277 [33] GSE28408 [6] Score 25.21 25.21 25.26 25.51 26.95 27.04 27.13 27.56 27.72 27.73 27.80 27.84 28.01 28.12 28.21 28.31 28.76 29.27 29.58 29.59 30.41 30.71 30.71 30.74 31.16 31.46 31.74 32.88 32.95 32.99 33.02 33.25 33.33 33.42 33.67 34.04 34.21 34.55 34.92 35.02 35.11 35.34 35.42 35.84 35.84 36.70 36.97 37.55 37.55 37.63 1.0 Notes Symbol Num ofCEMGenes:5.Predicted248.SelectedDatasets:59.Strength:0.4 CEM 1,Geneset"[G]signalrecognitionparticle,endoplasmicreticulumtargeting",Page3 Hnrnpab Mmadhc Sec23ip Arfgap1 Slc35e1 Slc30a5 Ube2g2 Exosc4 Txndc5 Cnot11 Tmed3 Copb1 Polr2c Hook1 Wdr74 Aimp1 Rexo2 Ddx56 Dtwd1 Gosr2 Arfip2 Magt1 Gmps Arcn1 Phf5a Hcfc2 Pold2 Dus1l Stx18 Osbp Atf6b Stt3a Pno1 Snd1 Ddx1 Eif3d Hax1 Drg2 Rars Gale Ssr4 Yars Calu Ppib Bysl Zfp9 Lig3 Nifk H13 Vcp 0.0 1.0

GSE39916 [6] GSE48935 [12]

GSE20426 [35] Scale ofaveragePearsoncorrelations GSE35436 [6] GSE11147 [6] GSE5425 [6] GSE7838 [9] GSE35543 [6] GSE47196 [6] 0.2 GSE12748 [7] GSE13033 [6] GSE18771 [6] GSE30863 [20] GSE10478 [6] GSE56777 [8] GSE7503 [6] GSE30488 [52] GSE35332 [12] 0.4 GSE55733 [24] GSE40773 [10] GSE32681 [61] GSE9804 [9] GSE38304 [8] GSE11572 [12] GSE30957 [16] GSE10162 [6] GSE47719 [6] 0.6 GSE18148 [6] GSE20944 [18] GSE21836 [8] GSE7430 [12] GSE30012 [6] GSE15580 [14] GSE33156 [18] GSE37546 [20] GSE37676 [6] 0.8 GSE8312 [6] GSE50603 [12] GSE32277 [33] GSE28408 [6] Score 11.09 11.29 11.84 12.10 12.15 12.67 12.71 12.81 13.30 13.42 13.68 13.70 13.80 14.58 14.75 14.99 15.37 15.99 16.03 16.03 16.21 16.31 16.39 16.47 16.70 17.05 17.19 18.07 18.22 18.93 19.50 20.08 21.12 21.19 21.28 21.52 21.60 21.61 21.61 22.23 22.45 22.66 23.35 23.56 23.90 23.96 24.20 24.66 24.70 24.72 1.0 Notes 1110004F10Rik Mphosph10 Symbol Num ofCEMGenes:5.Predicted248.SelectedDatasets:59.Strength:0.4 CEM 1,Geneset"[G]signalrecognitionparticle,endoplasmicreticulumtargeting",Page4 Rps19bp1 Tmem167 Ccdc115 Rwdd4a Timm21 Timm23 Exosc3 Sec31a Nploc4 Dnajc3 Edem2 Psmc2 Mmgt1 Kdelr2 Pcbp1 Abce1 Ddx50 Rab2a Eif2b1 Mrp63 Gpr89 Tsen2 Mcfd2 Gtf2f2 Gspt1 Tbrg1 Dpm2 Ufsp2 Rabl6 Nol12 Nif3l1 Nme1 Rabl3 Stx5a Ttc37 Ero1l Rpn2 Kti12 Pigm Eif3a Hars Gnl3 Ostc Abt1 Sars Ufc1 Selk Iars 0.0 1.0

GSE39916 [6] GSE48935 [12]

GSE20426 [35] Scale ofaveragePearsoncorrelations GSE35436 [6] GSE11147 [6] GSE5425 [6] GSE7838 [9] GSE35543 [6] GSE47196 [6] 0.2 GSE12748 [7] GSE13033 [6] GSE18771 [6] GSE30863 [20] GSE10478 [6] GSE56777 [8] GSE7503 [6] GSE30488 [52] GSE35332 [12] 0.4 GSE55733 [24] GSE40773 [10] GSE32681 [61] GSE9804 [9] GSE38304 [8] GSE11572 [12] GSE30957 [16] GSE10162 [6] GSE47719 [6] 0.6 GSE18148 [6] GSE20944 [18] GSE21836 [8] GSE7430 [12] GSE30012 [6] GSE15580 [14] GSE33156 [18] GSE37546 [20] GSE37676 [6] 0.8 GSE8312 [6] GSE50603 [12] GSE32277 [33] GSE28408 [6] Score 5.45 5.59 5.72 5.84 5.86 5.86 5.99 6.11 6.17 6.18 6.22 6.22 6.36 6.42 6.63 6.91 6.96 7.13 7.19 7.20 7.26 7.52 7.69 7.69 7.84 7.90 7.91 7.99 8.18 8.22 8.28 8.37 8.82 8.95 8.97 8.98 9.05 9.50 9.69 9.82 9.83 10.05 10.08 10.44 10.49 10.64 10.64 10.71 10.88 10.99 1.0 Notes Symbol Num ofCEMGenes:5.Predicted248.SelectedDatasets:59.Strength:0.4 CEM 1,Geneset"[G]signalrecognitionparticle,endoplasmicreticulumtargeting",Page5 AW209491 Tmem258 Hsp90b1 Slc35a4 Zswim1 Cdc25a Zc3h15 Golga5 Alkbh2 Paip2b Grpel1 Ythdf1 Cops3 Aimp2 Nop16 Eif2b3 Ube2k Cdc34 Pbdc1 Tfb1m Eif4a1 Mgat2 Mettl9 Erp29 Clint1 Abcf2 Trmt6 Riok1 Nme2 Txlna Gtf2b Crls1 Nmt1 Cdk7 Yif1a Blzf1 Zfpl1 Ece2 Gars Mlec Clpp Ubl4 Cct7 Hn1l Lyar Ykt6 Calr Ung Itpa Ik 0.0 1.0

GSE39916 [6] GSE48935 [12]

GSE20426 [35] Scale ofaveragePearsoncorrelations GSE35436 [6] GSE11147 [6] GSE5425 [6] GSE7838 [9] GSE35543 [6] GSE47196 [6] 0.2 GSE12748 [7] GSE13033 [6] GSE18771 [6] GSE30863 [20] GSE10478 [6] GSE56777 [8] GSE7503 [6] GSE30488 [52] GSE35332 [12] 0.4 GSE55733 [24] GSE40773 [10] GSE32681 [61] GSE9804 [9] GSE38304 [8] GSE11572 [12] GSE30957 [16] GSE10162 [6] GSE47719 [6] 0.6 GSE18148 [6] GSE20944 [18] GSE21836 [8] GSE7430 [12] GSE30012 [6] GSE15580 [14] GSE33156 [18] GSE37546 [20] GSE37676 [6] 0.8 GSE8312 [6] GSE50603 [12] GSE32277 [33] GSE28408 [6] Score 0.47 0.48 0.52 0.54 0.94 0.96 0.99 1.16 1.16 1.26 1.28 1.31 1.54 1.61 1.64 1.67 1.86 1.93 1.93 2.08 2.09 2.09 2.19 2.33 2.48 2.50 2.52 2.80 2.87 3.08 3.15 3.19 3.27 3.46 3.57 3.65 3.79 3.82 3.93 3.97 4.03 4.17 4.52 4.54 4.58 4.76 4.90 4.94 5.32 5.42 1.0 Notes Symbol Num ofCEMGenes:5.Predicted248. Num ofSelectedDatasets:59.CEMStrength:0.4 CEM 1,Geneset"[G]signalrecognitionparticle, endoplasmicreticulumtargeting",Page6 Ruvbl1 Syvn1 Alg12 0.0 1.0

GSE39916 [6] GSE48935 [12]

GSE4142 [14] Only showingfirst200datasets-Seetxtoutputforfulldetails . GSE48932 [12] GSE29929 [14] GSE12693 [6] GSE21041 [6] GSE38031 [8] GSE27038 [12] GSE17509 [57] GSE35825 [9] GSE54678 [6] GSE17184 [12] GSE31638 [15] GSE8682 [8] GSE30861 [35] GSE51108 [6] GSE12881 [6] GSE24031 [18] GSE21491 [9] GSE31313 [22] GSE15871 [18] GSE13443 [27] GSE38138 [20] GSE14753 [6] GSE42473 [15] GSE13948 [21] GSE9249 [28] GSE24813 [10] GSE38136 [24] GSE43899 [12] GSE25088 [24] GSE22125 [6] GSE13693 [9] GSE13692 [8] GSE45051 [18] GSE28621 [21] GSE21272 [44] GSE3313 [24] GSE25140 [16] GSE18135 [18] GSE34423 [40] GSE44356 [18] GSE16691 [12] GSE27019 [6] GSE29241 [6] GSE9954 [70] GSE20391 [11] GSE31086 [6] GSE17925 [12] GSE12389 [8] GSE7348 [6] GSE11494 [16] GSE57425 [6] GSE20954 [14] GSE46150 [8] GSE22418 [8] GSE28895 [6] GSE5861 [6] GSE4734 [61] GSE38880 [12] GSE9013 [12] GSE19732 [20] GSE29262 [12] GSE35593 [6] GSE24207 [73] GSE34729 [6] GSE24078 [6] GSE46869 [6] GSE29048 [8] GSE33726 [48] GSE11680 [10] GSE9717 [6] GSE53951 [10] GSE28333 [6] GSE22774 [6] GSE30160 [6] GSE3889 [20] GSE7275 [8] GSE18858 [242] GSE7050 [18] GSE18500 [35] GSE3501 [6] GSE13963 [15] GSE45618 [6] GSE53590 [8] GSE2197 [6] GSE19517 [6] GSE27972 [6] GSE48204 [6] GSE35226 [12] GSE34552 [10] GSE38141 [18] GSE26695 [20] GSE34126 [19] GSE34961 [9] GSE8322 [12] GSE25645 [17] GSE4288 [36] GSE44101 [6] GSE11684 [16] GSE9913 [9] GSE34959 [10] GSE13590 [12] GSE17649 [36] GSE10525 [18] GSE2019 [12] GSE23040 [6] GSE5959 [6] GSE55809 [8] GSE38574 [32] GSE1435 [27] GSE12073 [12] GSE18745 [6] GSE37431 [6] GSE56492 [12] GSE32986 [18] GSE56162 [18] GSE25636 [8] GSE40230 [15] GSE46871 [6] GSE45820 [6] GSE9878 [6] GSE17373 [24] GSE18907 [12] GSE24437 [6] GSE51483 [45] GSE39355 [7] GSE7685 [12] GSE3583 [9] GSE52597 [7] GSE39375 [10] GSE32103 [6] GSE17322 [6] GSE13874 [14] GSE6837 [8] GSE14344 [6] GSE40655 [6] GSE55607 [18] GSE42238 [9] GSE6675 [8] GSE35805 [8] GSE9711 [6] GSE43620 [8] GSE39897 [36] GSE36437 [6] GSE55028 [6] GSE32624 [6] GSE10202 [8] GSE28887 [12] GSE36378 [20] GSE36665 [6] GSE9566 [38] GSE14007 [8] CEM+ CEM GSE55003 [12] GSE7759 [112] GSE4718 [6] GSE34839 [6] GSE19272 [30] GSE31150 [6] 0.0 GSE18115 [8] GSE24789 [9]

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39916 Status: Public on Aug 07 2012 Title: Expression data from murine bone marrow-resident plasma cells and spleen mature follicular B cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22991471 Summary & Design: Summary: CD138+ B220- plasma cells were sorted from bone marrow and B220+ CD23+ mature follicular B cells were sorted from the spleens. Plasma cells were sorted from C57BL/6 mice 7 days after boosting with antigen, with mice first primed with an i.p. injection of KLH/IFA followed by boost at day 21 with KLH/PBS i.p. Mature B cells were sorted from antigen-naÃ¯ve C57BL/6 mice.

We compared expression profiles of plasma cells and mature B cells to identify differentially expressed transcripts.

Overall design: Seven days after boosting with KLH, plasma cells were enriched by CD138-PE/anti-PE magnetic bead enrichment and then sorted to purity. Affymetrix microarrays were performed on 50,000-70,000 plasma cells and 2,000,000-3,000,000 naÃ¯ve B cells.

Background corr dist: KL-Divergence = 0.0176, L1-Distance = 0.0538, L2-Distance = 0.0034, Normal std = 0.9040

0.480 Kernel fit Pairwise Correlations Normal fit

Density 0.240

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

B cells spleenB cells 1spleenB (0.209136) cells 2spleenPlasma (0.15302) 3 Plasmacells (0.13976) bone Plasmacells marrow bone cells marrow 1 bone (0.164229) marrow 2 (0.21281) 3 (0.121045)[ min ] [ medium ] [ max ] CEM 1 Srp9 2341.8 6681.2 6987.0 P ( S | Z, I ) = 1.00 Srp19 2454.6 5141.8 5799.7 Mean Corr = 0.97861 Srp68 990.2 3133.7 3439.4 Srp72 1205.8 2573.3 3006.0 Srp54b 108.0 433.6 447.8 Spcs2 1294.5 6317.0 6843.8 Sec23b 1273.4 2936.3 3410.4 Lrrc59 833.8 4090.0 5012.8 Hdlbp 580.5 4172.3 4472.3 Sec11a 2870.0 3782.3 4223.0 CEM 1 + Ssr3 3050.4 8299.0 8727.2 Top 10 Genes Tmem39a 659.1 2686.0 3044.6 Spcs3 1533.8 7274.8 8372.1 Ssr1 2881.3 7398.8 8110.6 Gorasp2 1886.9 4077.5 4618.6

Null module GEO Series "GSE48935" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48935 Status: Public on Sep 04 2013 Title: Analysis of gene expression changes induced in wild-type or Atf6a-/- mice by treatment with tunicamycin for 34h Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24069029 Summary & Design: Summary: Protein misfolding stress in the endoplasmic reticulum (ER) leads to dysregulation of lipid metabolism in the liver, and ER stress is associated with human diseases that are accompanied by hepatic lipid accumulation, including obesity, alcoholism, and viral hepatitis; yet the pathways leading from ER stress to the regulation of lipid metabolism are poorly understood. Working exclusively in vivo, we used a bottom-up approach to infer pathways in the genetic regulation of lipid metabolism by the UPR.

We used a functional genomics to link gene expression patterns taken from microarray data to the severity and persistence of ER stress, using mice lacking the UPR signaling molecule ATF6Î±. This approach revealed that functionally related genes clustered into a small number of distinct expression profiles, and that lipid oxidation and efflux were targets for coordinated transcriptional suppression during ER stress.Our results establish a framework for hepatic gene regulation during ER stress.

Overall design: Atf6a-/- or +/+ mice of variable age and gender were injected intraperitoneally with 1 mg/kg tunicamycin or vehicle. 3 separate mice were used in each group. 34h after injection, mice were sacrificed and total RNA was prepared from resected livers.

Background corr dist: KL-Divergence = 0.0722, L1-Distance = 0.0377, L2-Distance = 0.0019, Normal std = 0.5191

0.806 Kernel fit Pairwise Correlations Normal fit

Density 0.403

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

wild-typewild-type vehiclewild-type vehicleanimalAtf6a-/- vehicle1animal (34h) Atf6a-/-vehicle (0.0574061)2animal (34h) Atf6a-/-vehicleanimal (0.0661005)3 (34h) wild-typevehicle1animal (34h)(0.0629383) wild-type(0.0520154)2animal (34h)TM animal wild-type(0.0574415)3 (34h)TM 1animal Atf6a-/-(34h)(0.0614546) TM (0.0147156)2animal Atf6a-/-(34h)TM animal (0.012044)3 Atf6a-/-(34h)TM 1animal (34h)(0.00680427) TM (0.150221)2animal (34h) (0.228492)3 (34h) (0.230367)[ min ] [ medium ] [ max ] CEM 1 Srp9 2451.1 3987.1 7301.9 P ( S | Z, I ) = 1.00 Srp19 2070.3 3277.7 9798.9 Mean Corr = 0.94527 Srp68 1735.8 2943.8 6756.3 Srp72 2604.7 4401.7 6546.1 Srp54b 100.1 168.3 348.6 Spcs2 2172.5 5821.8 8845.7 Sec23b 1449.2 3026.5 10053.6 Lrrc59 2442.0 5610.0 21916.6 Hdlbp 4277.4 10170.3 16707.6 Sec11a 3912.4 8291.7 16343.0 CEM 1 + Ssr3 4999.7 13383.3 20030.4 Top 10 Genes Tmem39a 470.3 1040.9 1996.0 Spcs3 1633.4 4526.8 8120.6 Ssr1 3141.2 7096.7 15406.3 Gorasp2 3035.7 6029.4 8421.1

Null module GEO Series "GSE4142" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4142 Status: Public on Feb 02 2006 Title: Molecular Analysis of antigen-specific B cell responses Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 16492737 Summary & Design: Summary: In order to better understand the factors that regulate B cell differentiation upon exposure to antigen, we compares global gene expression profiles from naive B cells with antigen-specific plasma, germinal center, and memory B cells after immunization with the T-dependent antigen, NP-CGG. The memory B cell-enriched transcripts were then compared with memory T cell-enriched and hematopoietic stem cell-enriched transcripts in order to generate a transcriptional profile of self-renewal within the hematopoietic system.

Keywords: Cell Type Comparison

Overall design: Naive B cells were FACS sorted from unimmunized mice, while plasma, germinal center, and memory B cells were sorted from NP-CGG-immunized mice at 1, 2, or 10 weeks after immunization, respectively, using a combination of cell surface markers. RNA was extracted, amplified, and hybridized to Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0855, L1-Distance = 0.0388, L2-Distance = 0.0032, Normal std = 0.4621

0.863 Kernel fit Pairwise Correlations Normal fit

Density 0.432

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Naive BNaive cell replicate BNaive cell replicate B1Plasma cell(0.0209318) replicate 2 Plasma replicate(0.0187652) 3 Plasma replicate(0.0257464) 1 (0.191176) Plasmareplicate 2 (0.120764) Germinalreplicate 3 (0.167778)Germinal Center4 (0.234846)Germinal replicateCenterMemory replicateCenter 1 (0.0174662)Memory B replicate cell2 (0.0225915) replicateMemory B cell3 (0.0304099) replicateMemory B1 cell(0.0486769) replicate B2 cell(0.0390114) replicate 3 (0.0285647) 4 (0.0332734)[ min ] [ medium ] [ max ] CEM 1 Srp9 869.8 2328.8 9497.4 P ( S | Z, I ) = 1.00 Srp19 1904.6 2792.3 16047.1 Mean Corr = 0.91296 Srp68 775.4 1160.2 7144.5 Srp72 3176.7 5014.7 12377.2 Srp54b 47.5 73.4 561.0 Spcs2 831.5 2079.2 20532.6 Sec23b 662.3 1466.0 6194.1 Lrrc59 1122.3 2269.6 30426.9 Hdlbp 1623.9 2689.0 29898.7 Sec11a 2241.7 6618.8 14452.5 CEM 1 + Ssr3 1304.6 3245.5 27487.0 Top 10 Genes Tmem39a 208.1 386.5 4452.8 Spcs3 1709.2 2215.1 20059.2 Ssr1 1849.4 4243.7 24139.5 Gorasp2 378.2 761.3 1971.3

Null module GEO Series "GSE48932" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48932 Status: Public on Sep 04 2013 Title: Analysis of gene expression changes induced in wild-type or Atf6a-/- mice by treatment with tunicamycin for 8h Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24069029 Summary & Design: Summary: Protein misfolding stress in the endoplasmic reticulum (ER) leads to dysregulation of lipid metabolism in the liver, and ER stress is associated with human diseases that are accompanied by hepatic lipid accumulation, including obesity, alcoholism, and viral hepatitis; yet the pathways leading from ER stress to the regulation of lipid metabolism are poorly understood. Working exclusively in vivo, we used a bottom-up approach to infer pathways in the genetic regulation of lipid metabolism by the UPR.

Overall design: Atf6a-/- or +/+ mice of variable age and gender were injected intraperitoneally with 2 mg/kg tunicamycin or vehicle. 3 separate mice were used in each group. 8h after injection, mice were sacrificed and total RNA was prepared from resected livers.

Background corr dist: KL-Divergence = 0.0464, L1-Distance = 0.0564, L2-Distance = 0.0064, Normal std = 0.5923

0.674 Kernel fit Pairwise Correlations Normal fit

Density 0.337

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

wild-typeAtf6a-/- vehicle Atf6a-/-vehicle animal wild-typeTManimal 1 animal(8h) wild-type1 (0.112763) (8h)TM 1 (8h)animal (0.0415221)Atf6a-/- vehicle(0.130107) 1 wild-type(8h)TM animal animal(0.0273978)Atf6a-/- TM2 2(8h) (8h)animal Atf6a-/-vehicle (0.0498231) (0.109979) 2 wild-type(8h)vehicleanimal (0.0899621) wild-type2animal (8h)TM animal (0.0667711) Atf6a-/-3 (8h)vehicle 3 (0.0441653) (8h)TM animal a(0.0147884) animal 3 (8h) 3 (8h) (0.108486) (0.204235)[ min ] [ medium ] [ max ] CEM 1 Srp9 2100.3 6516.9 8086.8 P ( S | Z, I ) = 1.00 Srp19 1651.8 4989.9 9080.9 Mean Corr = 0.88016 Srp68 1315.0 3605.9 5963.4 Srp72 3581.2 5478.3 7193.5 Srp54b 82.6 137.7 300.0 Spcs2 2895.4 8386.7 11214.3 Sec23b 1358.5 6728.9 9219.9 Lrrc59 2604.0 9807.4 13603.0 Hdlbp 4555.6 7857.2 10959.1 Sec11a 5160.6 11078.7 21008.9 CEM 1 + Ssr3 6763.5 11702.9 18105.0 Top 10 Genes Tmem39a 478.3 1987.0 3130.8 Spcs3 2533.9 3689.4 5741.7 Ssr1 5173.3 8596.3 11545.1 Gorasp2 2744.7 7529.6 9186.5

Null module GEO Series "GSE29929" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29929 Status: Public on Jan 20 2012 Title: The eIF2 kinase PERK and the integrated stress response facilitate activation of ATF6 during endoplasmic reticulum stress Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21917591 Summary & Design: Summary: Disruptions of the endoplasmic reticulum (ER) that perturb protein folding cause ER stress and elicit an unfolded protein response (UPR) that involves translational and transcriptional changes in gene expression aimed at expanding the ER processing capacity and alleviating cellular injury. Three ER stress sensors PERK, ATF6, and IRE1 implement the UPR. PERK phosphorylation of eIF2 during ER stress represses protein synthesis, which prevents further influx of ER client proteins, along with preferential translation of ATF4, a transcription activator of the integrated stress response. In this study we show that the PERK/eIF2Î±~P/ATF4 pathway is required not only for translational control, but also activation of ATF6 and its target genes. The PERK pathway facilitates both the synthesis of ATF6 and trafficking of ATF6 from the ER to the Golgi for intramembrane proteolysis and activation of ATF6. As a consequence, liver-specific depletion of PERK significantly reduces both the translational and transcriptional phases of the UPR, leading to reduced protein chaperone expression, disruptions of lipid metabolism, and enhanced apoptosis. These findings show that the regulatory networks of the UPR are fully integrated, and helps explain the diverse pathologies associated with loss of PERK.

Overall design: Comparison of gene expression profiles for treated vs control in wildtype and knock-out.

Background corr dist: KL-Divergence = 0.1228, L1-Distance = 0.0299, L2-Distance = 0.0013, Normal std = 0.4159

0.968 Kernel fit Pairwise Correlations Normal fit

Density 0.484

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WT_6hTUN-rep1WT_6hTUN-rep2WT_6hTUN-rep3 (0.086176)WT_6hTUN-rep4 (0.0692599)WT_Control_DMSO-rep1 (0.0552951)WT_Control_DMSO-rep2 (0.0488351)WT_Control_DMSO-rep3lsPERK_6hTUN-rep1 (0.0956149)lsPERK_6hTUN-rep2 (0.0586835)lsPERK_6hTUN-rep3 (0.103827) (0.0452005)lsPERK_6hTUN-rep4 (0.0683177)lsPERK_Control_DMSO-rep1 (0.0570072)lsPERK_Control_DMSO-rep2 (0.0440493)lsPERK_Control_DMSO-rep3 (0.107783) (0.0911508) (0.0688)[ min ] [ medium ] [ max ] CEM 1 Srp9 2632.8 6197.1 7513.3 P ( S | Z, I ) = 1.00 Srp19 2346.2 6246.9 7171.4 Mean Corr = 0.87523 Srp68 1768.2 3806.1 4871.9 Srp72 2886.4 4737.0 6304.1 Srp54b 92.7 242.1 387.8 Spcs2 3566.2 8827.4 10879.6 Sec23b 1915.7 7702.9 9151.6 Lrrc59 2275.8 7603.8 8707.3 Hdlbp 4307.8 8021.7 9043.1 Sec11a 4489.8 9044.5 13380.8 CEM 1 + Ssr3 8466.3 15394.3 18080.3 Top 10 Genes Tmem39a 372.8 2108.6 3159.4 Spcs3 2659.0 5719.5 6419.3 Ssr1 4039.1 8896.4 11259.9 Gorasp2 3429.1 6783.2 10483.6

Null module GEO Series "GSE12693" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12693 Status: Public on Apr 09 2009 Title: Hepatic gene expression profile of mice exposed to social stress Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19106182 Summary & Design: Summary: Social stress is well known to be involved in the occurrence and exacerbation of mental illness, and also various life-style related diseases such as hyperinsulinemia, hyperglycemia, cardiovascular diseases and cancer. However, there is little information on tissue-specific gene expression in response to social stress, which reflects our daily life. Liver is one of the most important organs, owing to its biological functions such as energy metabolic homeostasis, metabolization and detoxification of endo- and exogenous substances. In order to elucidate the mechanism underlying response to social stress in the liver, we investigated hepatic gene expression in mice exposed to isolation stress using DNA microarray. Male BALB/c mice (4 weeks old) were housed 5 per cage for 10 days acclimatization. Then mice were exposed to isolation stress for 30 days. After stress treatment, the mouse liver RNA was subjected to DNA microarray analysis. Taking the false discovery rate into account, isolation stress altered expression of 420 genes. Moreover, Gene Ontology analysis of these differentially expressed genes indicated that isolation stress remarkably down-regulated lipid metabolism-related pathway through peroxisome proliferator-activated receptor-alpha (PPARalpha), while lipid biosynthesis pathway regulated by sterol regulatory element binding factor-1 (SREBF-1), Golgi vesicle transport and secretory pathway-related genes were significantly up-regulated. These results suggested that isolation for 30 days, mild and consecutive social stress, not only regulate the systems for lipid metabolism but also cause the endoplasmic reticulum stress in mouse liver.

Overall design: Male BALB/c mice (4 weeks old, Japan SLC, Shizuoka, Japan) weighing 14-18 g were housed 5 per cage. After acclimatization for 10 days, the mice were exposed to isolation (1 mouse per cage). All cages were placed in a foam plastic box in order to avoid social contact. To enhance the feeling of isolation, the bed volume in each cage for the isolated mice was reduced to one-tenth of that in the control group. The weight of bedding chips was about 2 g. All mice were housed in an air-conditioned room ( room temperature: 23 ´– 1´C, humidity: 55 Â± 5 %) under 12 h dark/12 h light cycles, with free access to tap water and MF diet (Oriental Yeast Co., Tokyo, Japan).

Background corr dist: KL-Divergence = 0.0484, L1-Distance = 0.0220, L2-Distance = 0.0006, Normal std = 0.5821

0.694 Kernel fit Pairwise Correlations Normal fit

Density 0.347

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Liver, ControlLiver, Control #2Liver, (0.108972) Control #1Liver, (0.143719) exposed #3Liver, (0.172904) exposed Liver,isolation exposed isolation stress isolation for stress 30 days for stress 30 #1 [days (0.0239152)for min 30 #2 days (0.439521) ] #3 (0.110968)[ medium ] [ max ] CEM 1 Srp9 1713.4 2211.4 3255.1 P ( S | Z, I ) = 1.00 Srp19 1791.5 2355.6 3470.7 Mean Corr = 0.84169 Srp68 1848.0 2290.7 3888.9 Srp72 2230.4 2771.7 3155.8 Srp54b 18.4 143.6 189.3 Spcs2 2846.2 4356.8 5899.1 Sec23b 1839.0 3060.9 5524.6 Lrrc59 2593.2 3479.1 5055.9 Hdlbp 5304.7 6209.9 7549.7 Sec11a 4789.8 5929.1 7400.8 CEM 1 + Ssr3 6554.0 7434.6 8816.6 Top 10 Genes Tmem39a 230.1 611.7 816.5 Spcs3 3518.5 4004.4 4807.8 Ssr1 4578.0 5381.0 6222.6 Gorasp2 3716.7 3939.9 5670.6

Null module GEO Series "GSE21041" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21041 Status: Public on Jul 15 2010 Title: Transcriptome analysis of miR-144/451-null bone marrow erythroid cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20679398 Summary & Design: Summary: microRNA miR-144/451 is highly expressed during erythropoiesis. We deleted the miR-144/451 gene locus in mice and compared the transcriptomes of miR-144/451-null bone marrow erythroid precursors to stage-matched wild-type control cells.

Overall design: Ter119+/CD71+/FSC-high bone marrow erythroblasts were sorted directly into Trizol LS reagent. Total RNAs extracted from three miR-144/451 knock-out and three wide type mice were analyzed using Affymetrix Mouse Genome 430 2.0 Arrays.

Background corr dist: KL-Divergence = 0.0360, L1-Distance = 0.0159, L2-Distance = 0.0003, Normal std = 0.6337

0.634 Kernel fit Pairwise Correlations Normal fit

Density 0.317

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WT_497WT_504 (0.208664)WT_550 (0.0396781)KO_493 (0.287444)KO_548 (0.0962199)KO_551 (0.16445) (0.203545) [ min ] [ medium ] [ max ] CEM 1 Srp9 2765.1 3287.6 3511.2 P ( S | Z, I ) = 1.00 Srp19 3992.5 4938.6 5351.5 Mean Corr = 0.83769 Srp68 1547.5 2313.3 2628.3 Srp72 1602.0 2109.7 2610.1 Srp54b 104.9 158.2 174.6 Spcs2 2597.8 2922.1 3363.5 Sec23b 1777.5 2010.1 2241.0 Lrrc59 1156.6 1587.8 1950.9 Hdlbp 1986.1 2087.8 2256.5 Sec11a 2509.3 2962.9 3208.6 CEM 1 + Ssr3 4112.1 4522.2 4626.6 Top 10 Genes Tmem39a 546.0 773.8 808.9 Spcs3 2024.1 2469.3 2679.5 Ssr1 4112.1 4554.5 5158.8 Gorasp2 440.4 830.5 879.1

Null module GEO Series "GSE38031" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38031 Status: Public on Jul 25 2013 Title: DNA damage-induced differentiation of NSC Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24052948 Summary & Design: Summary: Murine ES-derived neural stem cells (NSC) were not irradiated (ctrl) or irradiated with 10Gy and cultured for 7 days (irr).

The goal was to study the gene expression changes in NSC at d7 after irradiation.

Overall design: Total RNA was extracted from 4 ctrl and 4 irr samples (biological quadruplicates).

Background corr dist: KL-Divergence = 0.0114, L1-Distance = 0.0339, L2-Distance = 0.0011, Normal std = 0.9128

0.456 Kernel fit Pairwise Correlations Normal fit

Density 0.228

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ctrl_rep1ctrl_rep2 (0.146911)ctrl_rep3 (0.121033)ctrl_rep4 (0.140757)irr_rep1 (0.0938855)irr_rep2 (0.1025)irr_rep3 (0.102969)irr_rep4 (0.146143) (0.145801) [ min ] [ medium ] [ max ] CEM 1 Srp9 2811.5 3296.0 3428.8 P ( S | Z, I ) = 1.00 Srp19 3268.5 4411.0 4964.3 Mean Corr = 0.85909 Srp68 2001.9 2753.0 3008.4 Srp72 2712.1 3261.8 3401.5 Srp54b 59.4 77.7 104.1 Spcs2 6948.3 7536.0 7901.2 Sec23b 1911.9 2048.6 2359.8 Lrrc59 2660.4 5339.4 5514.8 Hdlbp 1303.5 1526.1 1632.4 Sec11a 5936.1 6863.0 7330.6 CEM 1 + Ssr3 6086.9 6463.2 6664.7 Top 10 Genes Tmem39a 741.1 900.7 964.4 Spcs3 1774.5 2217.0 2445.9 Ssr1 4817.1 5922.9 6379.8 Gorasp2 3805.6 3961.9 4391.3

Null module GEO Series "GSE27038" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27038 Status: Public on Feb 03 2011 Title: Expression data from the Ire1Î± null and control murine livers in the absence or presence of ER stress Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21407177 Summary & Design: Summary: Ire1Î± conditional null or control mice of 3-months old were injected intraperitoneally with TM or vehicle.

At 8 hours after the injection, total RNA was isolated from murine liver tissue and subjected to Affymetrix microarray analysis.

Overall design: We used microarrays to profile the global programme of gene expression in the livers of Ire1Î± null and control mice in the absence or presence of ER stress.

Background corr dist: KL-Divergence = 0.1000, L1-Distance = 0.0233, L2-Distance = 0.0009, Normal std = 0.4442

0.898 Kernel fit Pairwise Correlations Normal fit

Density 0.449

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Fe+CRE+Tm,Fe+CRE+Tm, BiologicalFe+CRE+Tm, BiologicalFe-CRE+Tm, Rep Biological1Fe-CRE+Tm, (0.156321) Rep Biological 2Fe-CRE+Tm, (0.304902) Rep Biological 3Fe+CRE+, (0.231073) Rep Biological1 Fe+CRE+,(0.0398648) Rep Biological 2 Fe+CRE+,(0.00489632) Rep Biological 3Rep Fe-CRE+,(0.0199712) Biological1 (0.0308771) RepFe-CRE+, Biological 2 (0.0397702) RepFe-CRE+, Biological 3 (0.0370558) Rep Biological1 (0.0468514) Rep 2 (0.0522844) Rep 3 (0.0361315)[ min ] [ medium ] [ max ] CEM 1 Srp9 3687.7 4787.4 10555.3 P ( S | Z, I ) = 1.00 Srp19 1691.8 2162.2 5461.4 Mean Corr = 0.82465 Srp68 1390.4 1746.9 4361.4 Srp72 2698.9 3671.8 7189.1 Srp54b 123.7 144.7 180.8 Spcs2 2560.3 4121.1 10570.9 Sec23b 1879.4 2365.3 8368.9 Lrrc59 2004.6 2401.6 9539.8 Hdlbp 4578.9 6322.4 11331.0 Sec11a 3469.9 7848.4 12573.9 CEM 1 + Ssr3 4171.0 5902.7 14759.7 Top 10 Genes Tmem39a 324.1 477.1 1912.5 Spcs3 2172.9 2938.9 6587.9 Ssr1 3024.8 4375.6 10406.9 Gorasp2 2553.9 3623.6 8336.5

Null module GEO Series "GSE17509" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 57 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17509 Status: Public on Aug 20 2009 Title: Reduced levels of protein tyrosine phosphatase CD45 protect mice from the lethal effects of Ebola virus infection Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19683682 Summary & Design: Summary: To gain insight into the changes in gene expression pattern upon Ebola infection, CD45+/+ (100% protein level) and CD45+/- (62% protein level) mice were challenged with mouse adapted Ebola virus. At time-points day 0, 1, 3, 5, 7, 9, 11 and 13, spleen tissue was harvested and splenocytes isolated. Total RNA was isolated for mRNA expression analysis. The mouse genome 430 2.0 array (Affymetrix, Inc.), which consists of over 39,000 genes in a single array, was used. Based on gene expression patterns, the variable genes were grouped into sixteen clusters. Each cluster contained genes associated with cellular immune processes, signaling, cell-cycle, complement coagulation cascade, biosynthesis/metabolism, ubiquitous genes involved in several cascades, and genes of unknown function. Interestingly, gene expression in clusters 2 and 3 were significantly downregulated by day 1 following EBOV challenge in CD45100% mice. In contrast, at day 1 following EBOV infection, the CD45 62% mice maintained gene expression patterns similar to day 0. The differences in gene expression patterns between the CD45 100% and CD45 62% splenocytes were less apparent at day 3 following infection and by days 5 and 7 they became very similar. At day 9, when wild-type mice had succumbed to the disease, the pattern in CD45 62% mice remained similar to the day 7 patterns of CD45 100% and CD45 62% mice. The pattern at days 11 and 13 in the CD45 62% mice had returned to that of day 0 CD45 100% or CD45 62% mice. These results suggested that in CD45 100% mice, subversion of the cell transcriptional machinery during the early stages of EBOV infection (day 1) might represent a major factor leading to death of the mice. In CD45 62% mice, early control of gene regulation likely provided the appropriate antiviral responses leading to regulated inflammation, immune co-stimulation, and survival.

Overall design: RNA expression in CD45 100% and 62% mice were compared at each time point: days 0, 1, 3, 5, and 7, using an empirical Bayes procedure. From 3 to 8 biological replicates were in each group. Samples for days 9, 11, and 13 (4 biological replicates each) were also available for only CD45 62%. Median expression values for highly variable genes within each group were clustered using agglomerative nesting over all available time points.

Background corr dist: KL-Divergence = 0.2878, L1-Distance = 0.0465, L2-Distance = 0.0049, Normal std = 0.2883

1.384 Kernel fit Pairwise Correlations Normal fit

Density 0.692

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

splenocytes_100%_d0_1splenocytes_100%_d0_2splenocytes_100%_d0_3splenocytes_100%_d1_1 (0.00435727)splenocytes_100%_d1_2 (0.0164125)splenocytes_100%_d1_3 (0.00727893)splenocytes_100%_d1_4 (0.00852165)splenocytes_100%_d3_1 (0.0071871)splenocytes_100%_d3_2 (0.00440348)splenocytes_100%_d3_3 (0.0184885)splenocytes_100%_d3_4 (0.00481318)splenocytes_100%_d5_1 (0.00847162)splenocytes_100%_d5_2 (0.0147528)splenocytes_100%_d5_3 (0.00396535)splenocytes_62%_d0_1 (0.00261043)splenocytes_62%_d0_2 (0.00173163)splenocytes_62%_d0_3 (0.00748062)splenocytes_62%_d0_4 (0.00126634)splenocytes_62%_d1_1 (0.00329237)splenocytes_62%_d1_2 (0.00642718)splenocytes_62%_d1_3 (0.00824097)splenocytes_62%_d1_4 (0.00617468)splenocytes_62%_d3_1 (0.00733531)splenocytes_62%_d3_2 (0.00709801)splenocytes_62%_d3_3 (0.0252599)splenocytes_62%_d3_4 (0.00221399)splenocytes_62%_d5_1 (0.00552178)splenocytes_62%_d5_2 (0.0146261)splenocytes_62%_d5_3 (0.0168728)splenocytes_62%_d5_4 (0.000750562)splenocytes_100%_d5_4 (0.00193347)splenocytes_100%_d7_1 (0.00364029)splenocytes_62%_d5_5 (0.00224371)splenocytes_62%_d9_1 (0.00457658)splenocytes_62%_d11_1 (0.350617)splenocytes_62%_d13_1 (0.00405912)splenocytes_100%_d5_5 (0.0445266)splenocytes_100%_d7_2 (0.00240074)splenocytes_62%_d5_6 (0.00110135)splenocytes_62%_d7_1 (0.00457361)splenocytes_62%_d9_2 (0.00481185)splenocytes_62%_d11_2 (0.00388768)splenocytes_62%_d13_2 (0.00437736)splenocytes_100%_d5_6 (0.0133824)splenocytes_100%_d7_3 (0.00405261)splenocytes_62%_d5_7 (0.0042984)splenocytes_62%_d7_2 (0.00672121)splenocytes_62%_d9_3 (0.0723152)splenocytes_62%_d11_3 (0.00434858)splenocytes_62%_d13_3 (0.0977709)splenocytes_100%_d5_7 (0.00449209)splenocytes_100%_d7_4 (0.00410884)splenocytes_62%_d5_8 (0.00431177)splenocytes_62%_d7_3 (0.00424556)splenocytes_62%_d9_4 (0.086706)splenocytes_62%_d11_4 (0.00565966)splenocytes_62%_d13_4 (0.0100318) (0.0238654) (0.00362737) (0.00175757)[ min ] [ medium ] [ max ] CEM 1 Srp9 1063.6 1471.6 3492.0 P ( S | Z, I ) = 1.00 Srp19 2368.8 4846.5 11306.2 Mean Corr = 0.79515 Srp68 1912.1 2582.0 4672.0 Srp72 1686.2 2500.0 4830.1 Srp54b 27.3 59.8 429.9 Spcs2 6009.1 7879.3 16212.7 Sec23b 1370.9 1975.9 3233.4 Lrrc59 1531.7 3152.5 10126.4 Hdlbp 1367.8 1878.2 6538.9 Sec11a 2939.5 3931.4 6021.2 CEM 1 + Ssr3 3197.1 4388.3 11819.1 Top 10 Genes Tmem39a 104.4 268.8 1088.3 Spcs3 1731.2 2864.7 6807.1 Ssr1 3186.3 5549.7 13967.9 Gorasp2 2040.3 3397.9 8932.4

Null module GEO Series "GSE35825" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE35825 Status: Public on Feb 15 2012 Title: Type I and II Interferon-Stimulated Genes in Murine Primary Bone Marrow Macrophages Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22371602 Summary & Design: Summary: We used microarrays to compare interferon-alpha (IFNa)- and interferon-gamma (IFNg)-stimulated genes under an equivalent biological input. The goal was to compare IFNa- and IFNg-stimulated genes, as well as to identify common and distinct sets of type I and II ISGs.

Overall design: Bone marrow macrophages derived from mouse bone marrow in M-CSF for 7 days. The cells were stimulated with 62U/mL IFNa and 1U/mL of IFNg for 2.5 hrs in culture. These concentrations induced equivalent STAT1 phosphorylation in BMMs.

Background corr dist: KL-Divergence = 0.0865, L1-Distance = 0.0224, L2-Distance = 0.0007, Normal std = 0.4706

0.848 Kernel fit Pairwise Correlations Normal fit

Density 0.424

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Media rep1Media (0.0880167) rep2Media (0.256209) rep3IFNa (0.0397293) rep1IFNa (0.135718) rep2IFNa (0.170384) rep3IFNg (0.18396) rep1IFNg (0.0333416) rep2IFNg (0.0233829) rep3 (0.0692574) [ min ] [ medium ] [ max ] CEM 1 Srp9 1219.6 1557.1 2115.1 P ( S | Z, I ) = 1.00 Srp19 1174.7 1773.8 2038.9 Mean Corr = 0.76651 Srp68 1630.8 1841.4 2044.0 Srp72 1568.9 1919.0 2204.8 Srp54b 2.9 71.1 154.7 Spcs2 6844.8 7125.8 7911.0 Sec23b 2717.9 2901.4 3306.0 Lrrc59 3750.7 4193.9 4717.5 Hdlbp 1875.0 2060.8 2506.4 Sec11a 3976.9 4464.4 4785.0 CEM 1 + Ssr3 6541.9 7077.2 7521.7 Top 10 Genes Tmem39a 218.4 298.5 396.5 Spcs3 3165.7 3566.8 3813.8 Ssr1 5195.1 5699.0 6326.5 Gorasp2 3395.3 3795.3 4595.9

Null module GEO Series "GSE54678" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE54678 Status: Public on Jun 30 2014 Title: A pivotal role of SRC-2 in Metastatic and Castration Resistant Prostate Cancer Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: SRC-2 is frequently amplified or overexpressed in metastatic prostate cancer patients. In this study, we used genetically engineered mice, overexpressing SRC-2 specifically in the prostate epithelium as a mouse model to examine the role of SRC-2 in prostate tumorigenesis. Over-expression of SRC-2 in PTEN heterozygous mice accelerates PTEN mutation induced tumor progression and develops a metastasis-prone cancer.

We used microarrays to examine the molecular profile of prostate-specific SRC-2 overexpression adult dorsal-lateral prostate in comparison with that of control PTENF/+ heterozygous deletion mice.

Overall design: total RNA was extracted from dorsal-lateral prostate of 7 months old-PTEN flox/+ control and PTEN flox/+; Rosa26-SRC-2 OE/+ adult mice, followed by gene expression profiling using Affymetrix microarrays. Each sample contains pooled prostate RNA from 3 mice.

Background corr dist: KL-Divergence = 0.0300, L1-Distance = 0.0202, L2-Distance = 0.0004, Normal std = 0.6761

0.600 Kernel fit Pairwise Correlations Normal fit

Density 0.300

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Control,Control, biologicalControl, biological replicateSRC-2OE, biological replicate 1 SRC-2OE,(0.056422) biological replicate 2 SRC-2OE,(0.08169) biological 3replicate (0.362467) biological replicate 1 (0.0608422) replicate 2 (0.251421) [3 (0.187158)min ] [ medium ] [ max ] CEM 1 Srp9 2012.9 2848.6 4043.2 P ( S | Z, I ) = 1.00 Srp19 3005.3 3713.3 4301.8 Mean Corr = 0.76701 Srp68 1716.7 2659.4 2694.3 Srp72 2995.4 3525.2 4390.1 Srp54b 122.9 229.6 265.6 Spcs2 6810.6 9165.9 11498.8 Sec23b 3810.1 4829.3 5515.7 Lrrc59 3057.4 3740.7 4119.3 Hdlbp 3445.6 5449.7 6841.1 Sec11a 5583.8 5988.5 6372.0 CEM 1 + Ssr3 7997.2 9877.9 11782.8 Top 10 Genes Tmem39a 605.8 936.9 1127.0 Spcs3 2870.0 5608.4 7003.2 Ssr1 5445.2 5969.8 6475.7 Gorasp2 3881.1 5820.1 7191.8

Null module GEO Series "GSE17184" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17184 Status: Public on Jul 21 2009 Title: ConA-induced fulminant hepatitis in a mouse model Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20398290 Summary & Design: Summary: The goal of this experiment was to investigate the early mechanisms of human fulminant hepatitis through ConA-induced hepatitis model.Early diagnosis and interventions are important for patients with fulminant hepatitis and gene expression may be pivotal in the early diagnosis.

Keyword :ConA-induced hepatitis model

Overall design: ConA was injected through the mouse caudal vein at one of 4 time points (0 hr, 1 hr, 3 hr, 6 hr). The effects of ConA treatment on hepatic gene expression at these time points were analyzed .There are 3 replicates at each timepoint then 4*3=12 samples in all.

Background corr dist: KL-Divergence = 0.1011, L1-Distance = 0.0314, L2-Distance = 0.0014, Normal std = 0.4480

0.910 Kernel fit Pairwise Correlations Normal fit

Density 0.455

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

hepatic hepaticgene expression hepaticgene expression hepaticgene at ""0 expression hepaticgene hr"", at ""0 expression rep1 hepaticgene hr"", at (0.0759138) ""0 expression rep2 hepaticgene hr"", at (0.0462166) ""1 expression rep3 hepaticgene hr"", at (0.0206988) ""1 expression rep1 hepaticgene hr"", at (0.0439674) ""1 expression rep2 hepaticgene hr"", at (0.0340895) ""3 expression rep3 hepaticgene hr"" at (0.0510517) ""3 expression(rep1) hepaticgene hr"" at (0.0442405)""6 expression(rep3) gene hr"" at (0.0622119)""3 expression(rep1) hr"" at (0.17163)""6 (rep2) hr"" at (0.0739106)""6 (rep2)[ hr"" min (0.167332) (rep3) ] (0.208737) [ medium ] [ max ] CEM 1 Srp9 2407.8 2774.1 4071.0 P ( S | Z, I ) = 1.00 Srp19 2883.3 3959.3 7852.1 Mean Corr = 0.75406 Srp68 2231.0 2513.7 4241.7 Srp72 2623.7 2962.4 3958.8 Srp54b 7.4 83.9 173.8 Spcs2 3060.8 4401.5 8716.7 Sec23b 3047.9 4613.8 9507.0 Lrrc59 3054.1 4680.9 11416.1 Hdlbp 5694.2 6831.3 7977.1 Sec11a 3724.2 4230.7 6451.4 CEM 1 + Ssr3 8943.4 12087.0 14919.9 Top 10 Genes Tmem39a 462.1 1367.1 1997.9 Spcs3 3101.2 3782.1 5165.7 Ssr1 5818.2 6963.8 10311.4 Gorasp2 4547.9 5375.0 7823.3

Null module GEO Series "GSE31638" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31638 Status: Public on Aug 31 2011 Title: Expression data from primary hepatocytes knocking down or overexpressing IRE1a Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21911379 Summary & Design: Summary: The ER-resident protein kinase/endoribonuclease IRE1 is activated through trans-autophosphorylation in response to protein folding overload in the ER lumen and maintains ER homeostasis by triggering a key branch of the unfolded protein response. Here we show that mammalian IRE1a in liver cells is also phosphorylated by a kinase other than itself in response to metabolic stimuli. Glucagon stimulated protein kinase PKA, which in turn phosphorylated IRE1a at Ser724, a highly conserved site within the kinase activation domain. Blocking Ser724 phosphorylation impaired the ability of IRE1a to augment the upregulation by glucagon signaling of the expression of gluconeogenic genes. Moreover, hepatic IRE1a was highly phosphorylated at Ser724 by PKA in mice with obesity, and silencing hepatic IRE1a markedly reduced hyperglycemia and glucose intolerance. Hence, these results suggest that IRE1a integrates signals from both the ER lumen and the cytoplasm in the liver and is coupled to the glucagon signaling in the regulation of glucose metabolism.

We used DNA microarray to analyze the transcriptomic change upon IRE1a overexpression or IRE1a depletion in primary hepatocytes, to study the changes related to IRE1a

Overall design: Primary hepatocytes were infected with the desired adenoviruses (Ad-EGFP, Ad-WT, Ad-S724A, Ad-shCON, Ad-shIRE1a#2) or treated with glucagon. Total cellular RNA was isolated with TRIzol (Invitrogen) and subjected to analysis by Affymetrix Mouse Genome 430 2.0 Arrays. Three experiments were independently conducted.

Background corr dist: KL-Divergence = 0.1161, L1-Distance = 0.0361, L2-Distance = 0.0027, Normal std = 0.4128

0.966 Kernel fit Pairwise Correlations Normal fit

Density 0.483

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

EGFP-1EGFP-2 (0.0350633)EGFP-3 (0.0300616)WT-1 (0.0464464) (0.0922723)WT-2 (0.0914352)WT-3 (0.226715)724-1 (0.059311)724-2 (0.0936022)724-3 (0.0395821)SG-1 (0.043375)SG-2 (0.0488825)SG-3 (0.0282792)I2G-1 (0.0462296)I2G-2 (0.0668206)I2G-3 (0.0519242) [ min ] [ medium ] [ max ] CEM 1 Srp9 1605.5 2182.2 4109.4 P ( S | Z, I ) = 1.00 Srp19 2949.3 3365.0 5673.2 Mean Corr = 0.74725 Srp68 2450.7 3082.7 4947.4 Srp72 2305.2 3364.6 4637.2 Srp54b 92.2 133.1 260.4 Spcs2 3194.2 4747.3 8890.5 Sec23b 4445.6 5035.1 8604.1 Lrrc59 9034.0 11294.9 14840.4 Hdlbp 3056.5 4151.6 6484.0 Sec11a 7910.1 9627.7 14128.4 CEM 1 + Ssr3 7782.1 10039.7 18898.1 Top 10 Genes Tmem39a 483.7 844.1 1297.2 Spcs3 1862.3 2537.1 6789.8 Ssr1 2592.9 3130.7 8866.5 Gorasp2 4947.2 5714.4 6201.8

Null module GEO Series "GSE8682" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8682 Status: Public on Jan 11 2008 Title: Gene expression in mouse 3T3-L1 adipocyte tissue culture treated with tunicamycin Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17878318 Summary & Design: Summary: Tunycamcin induces UPR/ISR and Inflammation in mouse 3T3-L1 adipocyte tissue culture. The early transcriptome changes were analyzed using high-density microarrays to better characterize the signaling pathways responding to tunicamycin, to be compared with similar experiments with CLA as the treatment. Their gene expression responses between 4 to 12 hr after treatment showed a common set of early gene expression changes indicative of a UPR/Inflammation stress response.

Keywords: control/treatment time course

Overall design: Mouse 3T3-L1 RNA for each time point was isolated from control and treatment samples for analysis on microarrays with two biological reps.

Background corr dist: KL-Divergence = 0.0724, L1-Distance = 0.0702, L2-Distance = 0.0125, Normal std = 0.5281

0.951 Kernel fit Pairwise Correlations Normal fit

Density 0.476

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

3T3-L1 adipocyte3T3-L1 adipocyte3T3-L1 tissue adipocyte3T3-L1 culture, tissue adipocyte3T3-L1 culture, control,tissue adipocyte3T3-L1 culture, tunicamycintissue T1, biologicaladipocyte3T3-L1 culture, control,tissue adipocyte3T3-L1 exposed, culture, control,rep1tissue T2, biologicaladipocyte(0.0836123) culture, tunicamycintissueT1, T2, biological biological culture, control,rep1tissue (0.0617941)exposed, culture,rep1 tunicamycinrep2 T3, (0.0313926) biological[(0.128824) tunicamycinminT2, biological exposed, rep1 ] (0.114108)exposed, rep1 T3, biological(0.352636) [T3, medium biological rep1 (0.0996946) rep2 (0.127938) ] [ max ] CEM 1 Srp9 1609.5 2597.5 4115.0 P ( S | Z, I ) = 1.00 Srp19 3873.4 4448.9 6088.5 Mean Corr = 0.74022 Srp68 1810.8 2586.7 3772.5 Srp72 3412.1 4497.6 5582.0 Srp54b 5.4 35.7 71.9 Spcs2 2864.8 3781.4 10008.7 Sec23b 1920.7 3005.3 7883.8 Lrrc59 7237.7 9007.7 13453.0 Hdlbp 5706.6 6528.0 11391.8 Sec11a 3572.9 4476.1 10594.9 CEM 1 + Ssr3 7656.9 8960.1 16641.5 Top 10 Genes Tmem39a 1289.3 1796.9 3315.7 Spcs3 2181.0 2995.3 7302.6 Ssr1 6287.2 7594.6 11807.2 Gorasp2 4068.5 4476.4 9216.0

Null module GEO Series "GSE30861" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 35 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30861 Status: Public on Aug 01 2011 Title: Pathways identified by toxicogenomics analysis reveal the size and dose independency of silica particles-induced toxicity in mice. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Understanding the interactions of nanostructures with biological systems is essential to nanotoxicological research.

Using a microarray-based toxicogenomics approach at early stage, this study investigated the relationship between particle size and toxicity of silica particles (SP) with diameters of 30, 70, and 300 nm (SP30, SP70, and SP300) as well as the mechanism of injury in mice.

Overall design: Two experiments with SiO2 particles of different sizes were considered in mice. One was aimed to investigate the dose-response relationship of SP70 toxicity at a dose of 10, 20, or 40 mg/kg (experiment 1), and the other set to study the size-response relationship of SP-induced toxicity using SP30, SP70, or SP300 (experiment 2). In experiment 2, two dosages each of SP30, SP70, and SP300 were performed. One was 10 mg/kg at three particle sizes, and the other was toxic doses of the three particle sizes, i.e., 10 mg/kg for SP30, 40 mg/kg for SP70, and 200 mg/kg for SP300. The toxic doses of the three particle sizes of SP were decided on the basis of the results of histopathological examinations and serum biochemical analysis in our previous study.n = 5

Background corr dist: KL-Divergence = 0.3288, L1-Distance = 0.0438, L2-Distance = 0.0037, Normal std = 0.2739

1.456 Kernel fit Pairwise Correlations Normal fit

Density 0.728

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

liver_control_6h_biologicalliver_control_6h_biologicalliver_control_6h_biologicalliver_control_6h_biological rep1liver_control_6h_biological (0.049449) rep2liver_10 (0.0422472) rep3liver_10 mg/kg (0.0344969) rep4 liver_10SP70_6h_biological mg/kg (0.0508822) rep5 liver_10SP70_6h_biological mg/kg (0.0414512) liver_10SP70_6h_biological mg/kg rep1 liver_20SP70_6h_biological mg/kg (0.00401382) rep2 liver_20SP70_6h_biological mg/kg (0.00817196) rep3 liver_20SP70_6h_biological mg/kg (0.017183) rep4 liver_20SP70_6h_biological mg/kg (0.013224) rep5 liver_20SP70_6h_biological mg/kg (0.00284623) rep1 liver_40SP70_6h_biological mg/kg (0.00900507) rep2 liver_40SP70_6h_biological mg/kg (0.0252318) rep3 liver_40SP70_6h_biological mg/kg (0.0356116) rep4 liver_40SP70_6h_biological mg/kg (0.0536219) rep5 liver_40SP70_6h_biological mg/kg (0.0536183) rep1 liver_10SP70_6h_biological mg/kg (0.00822682) rep2 liver_10SP70_6h_biological mg/kg (0.0208566) rep3 liver_10SP30_6h_biological mg/kg (0.00769768) rep4 liver_10SP30_6h_biological mg/kg (0.00388787) rep5 liver_10SP30_6h_biological mg/kg (0.028378) rep1 liver_10SP30_6h_biological mg/kg (0.011158) rep2 liver_10SP30_6h_biological mg/kg (0.00941848) rep3 liver_10SP300_6h_biological mg/kg (0.0250851) rep4 liver_10SP300_6h_biological mg/kg (0.0430337) rep5 liver_10SP300_6h_biological mg/kg (0.0212223) rep1 liver_200SP300_6h_biological mg/kg (0.016036) rep2 liver_200SP300_6h_biological mg/kg (0.0542312) rep3liver_200 SP300_6h_biological mg/kg (0.0353987) rep4liver_200 SP300_6h_biological mg/kg (0.0332426) rep5liver_200 SP300_6h_biological mg/kg (0.0697308) rep1 SP300_6h_biological mg/kg (0.0118628) rep2 SP300_6h_biological (0.0534218) rep3 (0.00260285) [rep4 min (0.0233146) rep5 ] (0.0801398) [ medium ] [ max ] CEM 1 Srp9 2754.6 4243.6 6481.2 P ( S | Z, I ) = 1.00 Srp19 2736.3 4557.5 6603.5 Mean Corr = 0.73521 Srp68 1166.9 2160.3 2799.8 Srp72 3016.9 3914.5 5098.3 Srp54b 117.3 248.3 409.4 Spcs2 3727.1 7063.3 10269.4 Sec23b 1966.2 4923.9 7225.2 Lrrc59 2096.8 5916.1 9020.3 Hdlbp 3789.4 5166.3 6562.4 Sec11a 4487.0 6036.3 7822.2 CEM 1 + Ssr3 6118.5 9721.5 12322.3 Top 10 Genes Tmem39a 332.2 1249.3 1965.7 Spcs3 2023.2 2957.0 3864.1 Ssr1 3862.5 5659.1 7711.8 Gorasp2 2850.1 4190.8 5534.7

Null module GEO Series "GSE51108" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51108 Status: Public on Nov 18 2013 Title: Gene expression in liver tissue from Ghrh-KO and normal (wild-type) mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24175087 Summary & Design: Summary: The hypothalamus has recently emerged as a key regulator of metabolism and aging in mammals. We have examined the impact of targeted disruption of hypothalamic hypophysiotropic peptide: Growth Hormone-releasing Hormone (GHRH) in mice on longevity, and the putative mechanisms of delayed aging. GHRH knockout (KO) mice are remarkably long-lived and in comparison to genetically normal (wild type) animals exhibiting major shifts in the expression of genes related to xenobiotic detoxification, stress resistance, and insulin signaling. These mutant mice also have increased adiponectin levels and alterations in glucose homeostasis consistent with the removal of the counter-insulin effects of GH. While these effects overlap with those of caloric restriction (CR), we show that effects of CR and the GHRH mutation are additive, with lifespan of GHRH-KO mutants further increased by CR. We conclude that GHRH-KO mice feature perturbations in a network of signaling pathways related to stress resistance, metabolic control and inflammation, and therefore provide a new model that can be used to explore links between GHRH repression, downregulation of the somatotropic axis, and extended longevity.

Overall design: Hepatic tissue was obtained from 3 Ghrh-KO mice and 3 control (wild-type) mice (males). Expression in each sample was profiled using Affymetrix Mouse Genome 430 2.0 arrays.

Background corr dist: KL-Divergence = 0.0371, L1-Distance = 0.0160, L2-Distance = 0.0002, Normal std = 0.6267

0.642 Kernel fit Pairwise Correlations Normal fit

Density 0.321

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Normal_001Normal_002 (0.128671)Normal_003 (0.272678)GhrhKO_004 (0.120807)GhrhKO_005 (0.193249)GhrhKO_006 (0.175124) (0.109471) [ min ] [ medium ] [ max ] CEM 1 Srp9 2991.7 3834.1 4476.2 P ( S | Z, I ) = 1.00 Srp19 1548.5 2362.6 2529.9 Mean Corr = 0.70977 Srp68 1140.7 1777.6 2613.9 Srp72 3197.8 3652.8 3870.2 Srp54b 102.0 137.7 157.2 Spcs2 4141.8 5858.3 6060.4 Sec23b 3219.3 5101.4 6433.9 Lrrc59 3733.5 4279.0 5623.9 Hdlbp 3795.3 4527.7 6402.2 Sec11a 5202.0 7128.7 8044.0 CEM 1 + Ssr3 5955.1 7246.7 7578.4 Top 10 Genes Tmem39a 533.3 1081.7 1205.0 Spcs3 2883.4 3661.7 4118.2 Ssr1 4743.4 5647.9 6575.5 Gorasp2 2304.3 4412.8 5645.8

Null module GEO Series "GSE12881" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12881 Status: Public on Jan 26 2009 Title: Loss of Caveolin-3 Induces the Development of a Lactogenic Microenvironment Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19164602 Summary & Design: Summary: Here, we show that functional loss of a single gene is sufficient to confer constitutive milk protein production and protection against mammary tumor formation. Caveolin-3 (Cav-3), a muscle-specific caveolin-related gene, is highly expressed in striated and smooth muscle cells. We demonstrate that Cav-3 is also expressed in myoepithelial cells within the mammary gland. To determine if genetic ablation of Cav-3 expression affects adult mammary gland development, we next studied the phenotype(s) of Cav-3 (-/-) null mice. Interestingly, detailed analysis of Cav-3 (-/-) virgin mammary glands shows dramatic increases in ductal thickness, side-branching, and the development of extensive lobulo-alveolar hyperplasia, akin to the changes normally observed during pregnancy and lactation. Analysis by genome-wide expression profiling reveals the upregulation of gene transcripts associated with pregnancy/lactation, mammary stem cells, and human breast cancers, consistent with a constitutive lactogenic phenotype. The expression levels of three key transcriptional regulators of lactation, namely Elf5, Stat5a, and c-Myc are also significantly elevated. Experiments with pregnant mice directly show that Cav-3 (-/-) mice undergo precocious lactation. Finally, using orthotopic implantation of a transformed mammary cell line (known as Met-1), we demonstrate that virgin Cav-3 (-/-) mice are dramatically protected against mammary tumor formation. Interestingly, Cav-3 (+/-) mice also show similar protection, indicating that even reductions in Cav-3 levels are sufficient to render these mice resistant to tumorigenesis. Thus, Cav-3 (-/-) mice are a novel preclinical model to study the protective effects of a constitutive lactogenic microenviroment on mammary tumor onset and progression. Our current studies have broad implications for using the lactogenic micro-environment as a paradigm to discover new therapies for the prevention and/or treatment of human breast cancers. Most importantly, a lactation-based therapeutic strategy would provide a more natural and nontoxic approach to the development of novel anti-cancer therapies.

Overall design: All WT and Cav-3 knockout (KO) mice used in this study were in the FVB/N genetic background. 4-month old virgin female mice were utilized in a micro array study between 3 wildtype and 3 Caveolin-3 knock-out mammary glands.

Background corr dist: KL-Divergence = 0.0260, L1-Distance = 0.0141, L2-Distance = 0.0002, Normal std = 0.6931

0.576 Kernel fit Pairwise Correlations Normal fit

Density 0.288

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

MammaryMammary Gland_WT_rep1Mammary Gland_WT_rep3Mammary Gland_WT_rep2 (0.145992)Mammary Gland_Cav-3KO_rep1 (0.0866312)Mammary Gland_Cav-3KO_rep2 (0.116587) Gland_Cav-3KO_rep3 (0.031089) (0.278576)[ (0.341126)min ] [ medium ] [ max ] CEM 1 Srp9 1557.9 1602.7 1681.5 P ( S | Z, I ) = 1.00 Srp19 3181.3 3750.3 4983.4 Mean Corr = 0.66468 Srp68 1250.7 1418.2 1690.4 Srp72 2602.3 3312.6 3889.0 Srp54b 146.2 149.3 167.4 Spcs2 4171.0 5614.7 6242.7 Sec23b 1864.9 2335.9 4058.3 Lrrc59 4970.3 6734.9 8897.5 Hdlbp 3749.6 4895.4 6764.0 Sec11a 2001.2 2990.4 3439.6 CEM 1 + Ssr3 5797.4 7102.5 7935.5 Top 10 Genes Tmem39a 815.7 1075.6 1283.3 Spcs3 1948.7 2317.6 4013.6 Ssr1 4953.8 5837.2 7989.4 Gorasp2 2425.1 2730.4 3398.4

Null module GEO Series "GSE24031" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24031 Status: Public on Sep 09 2010 Title: Adipose tissue dysfunction signals progression of hepatic steatosis towards nonalcoholic steatohepatitis in C57Bl/6 mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20858684 Summary & Design: Summary: Objective: Nonalcoholic fatty liver disease (NAFLD) is linked to obesity and diabetes, suggesting an important role of adipose tissue in the pathogenesis of NAFLD. Here we aim to investigate the interaction between adipose tissue and liver in NAFLD, and identify potential early plasma markers that predict NASH. Research Design and Methods: C57Bl/6 mice were chronically fed a high fat diet to induce NAFLD and compared with mice fed low fat diet. Extensive histological and phenotypical analyses coupled with a time-course study of plasma proteins using multiplex assay was performed. Results: Mice exhibited pronounced heterogeneity in liver histological scoring, leading to classification into 4 subgroups: LF-low (LFL) responders displaying normal liver morphology, LF-high (LFH) responders showing benign hepatic steatosis, HF-low (HFL) responders displaying pre-NASH with macrovesicular lipid droplets, and HF-high (HFH) responders exhibiting overt NASH characterized by ballooning of hepatocytes, presence of Mallory bodies, and activated inflammatory cells. Compared to HFL responders, HFH mice gained weight more rapidly and exhibited adipose tissue dysfunction characterized by decreased final fat mass, enhanced macrophage infiltration and inflammation, and adipose tissue remodelling. Plasma haptoglobin, IL-1Î², TIMP-1, adiponectin and leptin were significantly changed in HFH mice. Multivariate analysis indicated that in addition to leptin, plasma CRP, haptoglobin, eotaxin and MIP-1Î± early in the intervention were positively associated with liver triglycerides. Intermediate prognostic markers of liver triglycerides included IL-18, IL-1Î², MIP-1Î³ and MIP-2, whereas insulin, TIMP-1, GCP-2 and MPO emerged as late markers. Conclusions: Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis and point to several novel potential predictive biomarkers for NASH.

Keywords: Expression profiling by array

Overall design: Male wildtype C57Bl/6 mice were fed LFD or HFD for 21 weeks. Mice were divided into 4 groups based on liver histology.

Background corr dist: KL-Divergence = 0.2859, L1-Distance = 0.0624, L2-Distance = 0.0104, Normal std = 0.2854

1.398 Kernel fit Pairwise Correlations Normal fit

Density 0.699

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

liver_WT_LFL_rep1liver_WT_LFH_rep1liver_WT_LFL_rep2 (0.0242818)liver_WT_LFH_rep2 (0.0412821)liver_WT_LFL_rep3 (0.143842)liver_WT_LFH_rep3 (0.0204308)liver_WT_LFH_rep4 (0.0561798)liver_WT_LFL_rep4 (0.0251381)liver_WT_LFH_rep5 (0.0359483)liver_WT_LFH_rep6 (0.202997)liver_WT_HFL_rep1 (0.0640372)liver_WT_HFL_rep2 (0.0660297)liver_WT_HFL_rep3 (0.0396018)liver_WT_HFH_rep1 (0.0286188)liver_WT_HFL_rep4 (0.051975)liver_WT_HFH_rep2 (0.0318498)liver_WT_HFH_rep3 (0.0464664)liver_WT_HFH_rep4 (0.064226) (0.00885766) (0.0482373)[ min ] [ medium ] [ max ] CEM 1 Srp9 2635.8 2913.7 3329.7 P ( S | Z, I ) = 1.00 Srp19 1947.5 2359.3 2911.5 Mean Corr = 0.59077 Srp68 1474.4 1763.3 2327.1 Srp72 2297.4 2802.9 3148.0 Srp54b 27.0 31.3 49.8 Spcs2 4215.5 6535.2 8966.3 Sec23b 1519.2 2726.9 3539.8 Lrrc59 2584.2 4286.5 4755.5 Hdlbp 5111.0 5782.9 6686.4 Sec11a 3742.7 4325.0 5307.8 CEM 1 + Ssr3 10701.3 12090.0 15334.4 Top 10 Genes Tmem39a 127.3 266.8 579.6 Spcs3 2785.0 3222.2 4028.1 Ssr1 2439.6 3131.6 4048.0 Gorasp2 5913.7 6927.3 8588.1

Null module GEO Series "GSE21491" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21491 Status: Public on Oct 17 2012 Title: Analysis of early dendritic cell, natural killer cell and B lymphocyte responses to murine cytomegalovirus (MCMV) infection by genome-wide expression profiling Organism: Mus musculus Experiment type: Third-party reanalysis Platform: GPL1261 Pubmed ID: 23084923 Summary & Design: Summary: Dendritic cells (DCs) are a complex group of cells which play a critical role in vertebrate immunity. They are subdivided into conventional DC (cDC) subsets (CD11b and CD8alpha in mouse) and plasmacytoid DCs (pDCs). Natural killer cells are innate lymphocytes involved in the recognition and killing of abnormal self cells, including virally infected cells or tumor cells. DCs and NK cells are activated very early upon viral infections and regulate one another. However, the global responses of DC and NK cells early after viral infection in vivo and their molecular regulation are not entirely characterized. The goal of this experiment was to use global gene expression profiling to assess the global genetic reprogramming of DC and NK cells during a viral infection in vivo, as compared to B lymphocytes, and to investigate the underlying molecular mechanisms

This study includes data from cell sort purified DCs, NK cells and B cells isolated from the spleen of MCMV-infected mice. 2 independent replicates were made for each cell type except B cells. The control dataset for cells isolated from uninfected control animals has been previously published and is available in the GEO database as GSE9810.

The complete dataset representing: (1) the infected Samples and (2) the uninfected control Samples from Series GSE9810 (re-processed using RMA), is linked below as a supplementary file.

Overall design: Comparison of the gene expression programs of wild-type spleen leukocyte subsets, including plasmacytoid DCs, CD8alpha conventional DCs, CD11b conventional DCs and NK cells, isolated from MCMV-infected versus control animals.

Background corr dist: KL-Divergence = 0.0690, L1-Distance = 0.0366, L2-Distance = 0.0024, Normal std = 0.5156

0.774 Kernel fit Pairwise Correlations Normal fit

Density 0.387

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

activatedactivated CD8alphaactivated CD8alpha cDCs,activated CD11b replicate cDCs,activated cDCs,CD11b replicate 1 activated(0.112066) replicate cDCs,pDCs, 2 activated(0.156006) replicatereplicate pDCs, 1 (0.0451206)activated replicate NK 21 (0.08771)(0.0443915) cells,activated NK 2 replicate (0.0211986) cells, B replicatelymphocytes, 1 (0.253989) 2 (0.264598) replicate[ min 1 (0.0149205) ] [ medium ] [ max ] CEM 1 Srp9 1563.3 2380.7 3483.9 P ( S | Z, I ) = 1.00 Srp19 1561.7 2440.1 4154.0 Mean Corr = 0.57512 Srp68 1148.2 1589.3 2955.2 Srp72 1908.2 2645.0 3879.4 Srp54b 125.0 163.7 197.2 Spcs2 4931.2 6765.3 13532.9 Sec23b 2769.9 5496.8 8003.1 Lrrc59 2117.6 3702.0 5967.8 Hdlbp 2247.4 2932.2 5198.3 Sec11a 7888.3 9152.6 13335.9 CEM 1 + Ssr3 4510.8 5207.1 6487.2 Top 10 Genes Tmem39a 970.4 3357.3 8881.3 Spcs3 1803.8 3643.7 9056.2 Ssr1 2859.4 5671.0 9909.7 Gorasp2 960.1 1213.2 1659.9

Null module GEO Series "GSE31313" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 22 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31313 Status: Public on Aug 08 2012 Title: Expression data from anti-EpCAM treated and untreated SP cells compared to lung tissue Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Targeted therapies against cancer stem cells which are enriched in side populations (SP) involves interruption of Wnt-signalling. Furthermore, EpCAM is a SP marker and modulator of Wnt-signalling. Therefore, the effects of an anti-EpCAM treatment on SP-cells and WNT/Î²-catenin signalling was studied.

SP of the murine lung adenocarcinoma cell line A2C12 was obtained by fluorescence activated cell sorting and whole genome scans helped to define their molecular phenotype after anti-EpCAM antibody treatment.

Overall design: Anti-EpCAM treated and untreated A2C12 cells were subjected to Hoechst 33342 dye exclusion assay and sorted to SP fractions by FACS. Gene expression of SP cells was compared to non-transgenic lung tissue.

Background corr dist: KL-Divergence = 0.0208, L1-Distance = 0.0491, L2-Distance = 0.0029, Normal std = 0.7902

0.505 Kernel fit Pairwise Correlations Normal fit

Density 0.252

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

A2C12 SPA2C12 cells SPA2C12 biological cells SPA2C12 biological cells replicate anti-EpCAMA2C12 biological replicate 1 anti-EpCAM(0.0958531)A2C12 replicate treated 2 anti-EpCAM(0.111856)Male treatedSP lung,3 (0.167086)Male cells biological treatedSPlung, biologicalMale cells biological SPlung, biologicalreplicateMale cells replicate biological lung, biologicalreplicateMale 1 replicate (0.0194951) biological1 (0.0557352)lung, replicateMale 2 replicate (0.0284657) biological2 (0.0816154)lung, replicateMale 3 (0.0165384) biological3 (0.114237)lung, replicateMale 4 (0.0114366) biological lung, replicateFemale 5 (0.00718491) biological replicate Female lung,6 (0.015426) biologicalreplicate Female lung,7 (0.0155714) biological Female lung,8 replicate (0.0244085) biological Femalelung, replicate 1 (0.0420017) biological Femalelung, replicate 2 (0.0369904) biological Femalelung, replicate 3 (0.0486548) biological Femalelung, replicate 4 (0.0320534) biological lung, replicate 5 (0.0132062) biological replicate 6 (0.0248252) replicate 7 (0.0177369)[ min8 (0.0196211) ] [ medium ] [ max ] CEM 1 Srp9 1719.9 2075.0 4599.1 P ( S | Z, I ) = 0.99 Srp19 1356.0 2401.1 3269.9 Mean Corr = 0.79508 Srp68 1653.7 1868.2 2528.8 Srp72 1790.3 2106.9 3334.3 Srp54b 27.8 59.9 230.8 Spcs2 4341.4 5195.1 7614.1 Sec23b 1922.7 2551.5 3083.8 Lrrc59 2400.5 2729.1 7939.9 Hdlbp 1999.9 2376.7 4139.1 Sec11a 2848.6 3785.4 5444.8 CEM 1 + Ssr3 3850.1 4586.2 8750.5 Top 10 Genes Tmem39a 589.6 744.7 1130.5 Spcs3 1848.6 2586.5 4805.1 Ssr1 3737.6 4565.8 9569.1 Gorasp2 2551.9 3045.6 3682.1

Null module GEO Series "GSE15871" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15871 Status: Public on Nov 05 2009 Title: Expression data from NFI-C knock out embryonic fibroblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23402308 Summary & Design: Summary: The Nuclear Factor I C (NFI-C) transcription factor has been implicated in TGF-Î² signaling, extracellular matrix deposition and skin appendage pathologies.

We performed a global gene expression analysis in NFI-C-/- and wild-type embryonic primary murine fibroblasts. This indicated that NFI-C acts mostly to repress gene expression in response to TGF-Î²1. Misregulated genes featured a prominent over-representation of regulators of connective tissue inflammation and repair.

Overall design: mRNAs were isolated from embryonic fibroblasts obtained from 3 wild-type and 3 NFI-C knock-out mice, and their levels were probed using microarrays. Prior to RNA extraction, fibroblast cultures were treated or not with TGF-Î²1 for 1 hour to examine the immediate response to the growth factor, or treated for 10 hours to assess the delayed response.

Background corr dist: KL-Divergence = 0.1186, L1-Distance = 0.0278, L2-Distance = 0.0011, Normal std = 0.4192

0.964 Kernel fit Pairwise Correlations Normal fit

Density 0.482

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

MEF, noMEF, treatment, noMEF, treatment, wild noMEF, treatment,type wild no 1MEF, (0.0369626) treatment,type wild no 2MEF, (0.0490847) treatment,type knock no 3MEF, (0.0200126)treatment, out knock 1h MEF,1 TGF-Î²1 (0.0452069) out knock 1h MEF,2 TGF-Î²1 (0.0138326)treatment, out 1h MEF,3 TGF-Î²1 (0.0299115)treatment, 1hwildMEF, TGF-Î²1 treatment,type 1hwild MEF,1 TGF-Î²1 (0.0460712) treatment,type 1hwild MEF,2 TGF-Î²1 (0.0186925) treatment,type 10hknock MEF,3 (0.01629)treatment,TGF-Î²1 out 10hknockMEF, 1 TGF-Î²1 (0.0252166)treatment, out 10hknockMEF, 2 TGF-Î²1 (0.0335322)treatment, out 10h wildMEF, 3 TGF-Î²1 (0.0188451) treatment,type 10h wildMEF, 1 TGF-Î²1 (0.0413278) treatment,type 10h wild 2 TGF-Î²1 (0.269826) treatment,type knock 3 (0.0792547)treatment, out knock 1 (0.135174) out knock[ 2min (0.0364463) out 3 (0.0843128)] [ medium ] [ max ] CEM 1 Srp9 1924.2 2264.1 3212.8 P ( S | Z, I ) = 1.00 Srp19 3480.2 3912.3 5951.6 Mean Corr = 0.52174 Srp68 2602.6 2902.4 4274.4 Srp72 3381.7 3679.4 4161.1 Srp54b 66.2 81.5 128.0 Spcs2 3549.8 4666.7 6897.0 Sec23b 1648.5 2186.4 4431.0 Lrrc59 6990.2 7751.7 14148.4 Hdlbp 7809.8 8981.6 12060.6 Sec11a 3826.2 6756.2 9543.7 CEM 1 + Ssr3 8368.2 10676.0 12110.5 Top 10 Genes Tmem39a 1369.3 1649.3 2973.8 Spcs3 2795.4 3290.8 4555.1 Ssr1 9227.2 10584.1 13631.1 Gorasp2 4901.3 5768.3 9311.1

Null module GEO Series "GSE13443" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 27 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13443 Status: Public on Nov 11 2008 Title: Induction of systemic disease-specific salivary biomarker profiles in mouse cancer models Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19517020 Summary & Design: Summary: Saliva (oral fluids) is an emerging biofluid poised for clinical diseases detection. Although the rationale for oral diseases applications (e.g. oral cancer) is clear, the rationale and relationship between systemic diseases and saliva biomarkers are unknown. In this study, we used mouse models of melanoma and non-small cell lung cancer and compared the transcriptome biomarker profiles of tumor-bearing mice to those of control mice. Microarray analysis showed that salivary transcriptomes were significantly altered in tumor-bearing mice vs. controls. Analysis of the transcriptomes in the mouse tumors, serum, salivary glands and saliva revealed that salivary biomarkers have multiple origins. Furthermore, we identified that the expression of two groups of significantly altered transcription factors Runx1, Mlxipl, Trim30 and Egr1, Tbx1, Nr1d1 in melanoma-bearing mice that can potentially be responsible for 82.6% of the up-regulated genes expression and 62.5% of the down-regulated gene expression in the mice saliva, respectively. We also confirmed that the ectopic production of nerve growth factor (NGF) in the melanoma tumor tissue as a tumor-released mediator that can induce expression of the transcription factor Egr-1 in the salivary gland. Taken together, our data support the conclusion that upon systemic disease development, a disease-specific change occurs in the salivary biomarker profile. Although the origins of the disease-specific salivary biomarkers are both systemic and local, stimulation of salivary gland by mediators released from remote tumors play an important role in regulating the salivary surrogate biomarker profiles.

Overall design: Salivary,salivary gland, serum or tumor RNA was isolated using the RNeasy Mini Kit (Qiagen) as described previously. There are 15 mice in the control group or tumor group (totally 30 C57BL/6 mice for melanoma mouse model, another 30 DBA/2 mice for lung cancer mouse model). Samples derived from 5 mice in each group were pooled and RNA extracted. The pooling is necessary to ensure sufficient salivary mRNA can be obtained for microarray analyses. Isolated total RNA was treated with recombinant DNase (Ambion, Austin, TX). For microarray analysis, mRNA from mouse saliva, gland or tumor was linearly amplified using the RiboAmp RNA Amplification kit (Molecular Devices, Sunnyvale, CA). After purification, cDNA were in vitro transcribed and biotinylated using GeneChip Expression 3-Amplification Reagents for in vitro transcription labeling (Affymetrix, Santa Clara, CA). The labeled RNAs was subsequently fragmented, hybridization and scanning.

Background corr dist: KL-Divergence = 0.1726, L1-Distance = 0.0919, L2-Distance = 0.0202, Normal std = 0.3872

1.043 Kernel fit Pairwise Correlations Normal fit

Density 0.522

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

melanomamelanoma micemelanoma model micemelanoma saliva model mice controlmelanoma saliva model mice controlmelanoma1 saliva model(0.0334517) mice controlmelanoma2 saliva model(0.0261352) mice inmelanoma3 saliva model (0.0291956)tumor mice inmelanoma salivamicemodel tumor mice 1inmelanoma gland(0.104689)micemodel tumor mice 2tissuemelanoma gland(0.0309286)micemodel mice in3tissuemelanoma gland(0.0305173)controlmodel mice in tissuemelanoma glandcontrolmodelmice mice in 1tissuemelanoma gland (0.0978739)controlmodelmice mice in 2tissuemelanoma gland (0.101484)tumormodelmice mice in 3tissue melanoma mice serum(0.136763)tumormodel mice 1in melanoma(0.0518602) inmice serumtumormodel control mice 2 melanoma(0.0422898) inmiceserum model control micemice 3 melanoma(0.0541355) inserum 1model (0.0132404)control micemice melanoma inserum 2model (0.0127247)tumor micemice melanoma inserum 3 modelmice (0.0224482)tumor mice 1non intumor model(0.0184826)mice tumor mice small 2tissuenon tumor model(0.0126988)mice cell small (0.019313) lung3tissuenon tumor (0.0103246) cell smallcancer 2 lungtissuenon (0.0206131) cell smallmodelcancer 3lungnon (0.0175082) cell salivasmallmodelcancer lungnon incell salivasmallmodelcancer control lung incell saliva modelcancer controlmice lung in 1saliva modelcancer (0.0135227)controlmice in 2saliva model (0.00989449)tumormice[ minin 3 salivamice (0.0223017)tumor 1in (0.0253349)mice] tumor 2 (0.0198759)mice 3[ (0.0223935) medium ] [ max ] CEM 1 Srp9 14.2 500.2 6837.7 P ( S | Z, I ) = 1.00 Srp19 367.5 1222.8 7647.3 Mean Corr = 0.52691 Srp68 59.9 1293.0 6305.2 Srp72 34.0 3076.6 5174.2 Srp54b 73.3 284.6 1112.4 Spcs2 51.8 10007.5 51794.2 Sec23b 61.4 658.1 15059.9 Lrrc59 80.1 854.0 13493.3 Hdlbp 490.0 4712.3 34494.3 Sec11a 148.4 802.4 8133.7 CEM 1 + Ssr3 50.8 278.0 13562.0 Top 10 Genes Tmem39a 56.6 334.6 1201.6 Spcs3 52.1 457.1 4357.6 Ssr1 101.1 1656.4 13289.2 Gorasp2 32.0 3216.7 14650.4

Null module GEO Series "GSE38138" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 20 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38138 Status: Public on May 30 2012 Title: Hepatic gene expression in streptozotocin-induced diabetic mice fed a phloridzin diet Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19413312 Summary & Design: Summary: Phloridzin is a dihydrochalcone typically contained in apples. A diet containing 0.5 % phloridzin significantly improves hyperglycemia but not hypoinsulinemia and tissue lipid peroxidation in streptozotocin (STZ)-induced diabetic mice after 14 days. The phloridzin diet has no effect on the alteration of hepatic gene expression in STZ-induced diabetic mice.

A quantitative RT-PCR analysis showed a reversal of the STZ induction of the sodium/glucose cotransporter gene Sglt1 and the drug-metabolizing enzyme genes Cyp2b10 and Ephx1 in the small intestine of mice fed a 0.5% phloridzin diet. These mice also showed a reversal of the STZ-mediated renal induction of the glucose-regulated facilitated glucose transporter gene Glut2. Dietary phloridzin improved the abnormal elevations in blood glucose level and the overexpression of Sglt1, Cyp2b10 and Ephx1 in the small intestine of STZ-induced diabetic mice.

Overall design: Six-week-old male mice were divided into 4 groups of 6 mice each, housed in groups of 3 per cage. After 1 week mice were intraperitoneally injected with STZ. Mice (n=6) in the untreated control group did not receive any treatment. After 1 week, 18 mice showing non-fasting blood glucose levels of 330-590 mg/dL were divided into 3 groups: one group was fed with AIN93G only (control group), the others with an AIN93G diet containing 0.1% or 0.5% phloridzin (Funakoshi, Tokyo, Japan) for 2 weeks.

Background corr dist: KL-Divergence = 0.2564, L1-Distance = 0.0474, L2-Distance = 0.0051, Normal std = 0.3007

1.327 Kernel fit Pairwise Correlations Normal fit

Density 0.663

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

non STZnon liver STZ controlnon liver STZ controldietnon liver rep1 STZ controldietnon (0.0761197)liver rep2 STZ controldietliver (0.0434273)liver rep3 STZ controldietliver (0.0435404) treated rep4 STZ dietliver (0.0592616) treateddiabetic rep5 STZliver (0.130223) treateddiabetic rep1 STZliver (0.0663481) treateddiabetic rep2 STZliver (0.0383868) treateddiabetic rep3 STZliver (0.0185854) 0.1%diabetic rep4 STZ phloridzinliver (0.0425256) 0.1% rep5 STZ phloridzinliver (0.0275385) 0.1% diet STZ phloridzinliverrep1 0.1% diet STZ(0.0285739) phloridzinliverrep2 0.1% diet STZ(0.00101188) phloridzinliverrep3 0.5% diet STZ(0.0658922) phloridzinliverrep4 0.5% diet STZ(0.0854721) phloridzinliverrep5 0.5% diet STZ(0.0918077) phloridzinliverrep1 0.5% diet STZ(0.058204) phloridzinrep2 0.5% diet (0.0273476) phloridzinrep3 diet (0.0263527) rep4 diet (0.00382404) rep5[ min (0.0655572) ] [ medium ] [ max ] CEM 1 Srp9 1648.4 2671.5 3887.1 P ( S | Z, I ) = 1.00 Srp19 1990.5 2538.9 3357.4 Mean Corr = 0.50059 Srp68 1841.6 2437.5 3176.9 Srp72 2793.0 3378.5 3814.3 Srp54b 9.1 81.7 124.6 Spcs2 2488.3 3717.7 6680.6 Sec23b 1443.8 2093.1 3282.4 Lrrc59 2106.1 3640.1 5192.3 Hdlbp 5947.7 6648.6 7988.0 Sec11a 3566.4 4384.2 6487.3 CEM 1 + Ssr3 6823.4 7999.7 12256.6 Top 10 Genes Tmem39a 274.2 464.3 1225.4 Spcs3 2219.9 3009.2 4369.1 Ssr1 3196.3 4502.9 6550.9 Gorasp2 3820.1 4734.8 5635.5

Null module GEO Series "GSE14753" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14753 Status: Public on Feb 10 2009 Title: Mammary tumors from K14-cre; ApcCKO/+ mice vs control mammary glands Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19197353 Summary & Design: Summary: Many components of Wnt/Î²-catenin signaling pathway also play critical roles in mammary tumor development. To study the role of Apc in mammary tumorigensis, we introduced conditional Apc mutations specifically into two different mammary epithelial populations using K14-Cre (progenitor) and WAP-cre (lactaing luminal) transgenic mice. Only the K14-cre mediated Apc heterozygosity developed mammary adenocarcinomas demonstrating histological and molecular heterogeneity, suggesting the progenitor cell origin of these tumors. These tumors harbored truncation mutation in a very defined region in the remaining wild-type allele of Apc that would retain some down-regulating activity of Î²-catenin signaling. Our results suggest that not only the epithelial origin but also a certain Apc mutations are selected to achieve a specific level of Î²-catenin signaling optimal for mammary tumor development.

Overall design: We have compared 3 mammary tumors from K14-cre; ApcCKO/+ mice with 3 control mammary glands.

Background corr dist: KL-Divergence = 0.0282, L1-Distance = 0.0235, L2-Distance = 0.0007, Normal std = 0.6907

0.582 Kernel fit Pairwise Correlations Normal fit

Density 0.291

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

control controlmammary controlmammary gland, mammary biological gland,mammary biological tumor,gland, replicatemammary biologicaltumor, replicate 1 (0.222906) biologicaltumor, replicate 2 (0.0662091) biological replicate 31 (0.178601)(0.041917) replicate 2[ (0.196493)min 3 (0.293873) ] [ medium ] [ max ] CEM 1 Srp9 1018.0 1583.7 1710.4 P ( S | Z, I ) = 0.99 Srp19 2400.5 3375.6 4820.6 Mean Corr = 0.75832 Srp68 1990.1 2930.1 3931.0 Srp72 1862.9 3004.2 3433.4 Srp54b 69.4 144.4 256.2 Spcs2 2487.6 6723.3 8266.2 Sec23b 1245.7 1875.0 2033.2 Lrrc59 1620.4 2616.2 3725.5 Hdlbp 2188.4 3852.8 6386.9 Sec11a 2627.7 4683.1 5777.0 CEM 1 + Ssr3 4406.9 5058.7 7200.7 Top 10 Genes Tmem39a 339.1 659.9 797.1 Spcs3 1386.5 2344.9 4829.8 Ssr1 3163.3 5572.7 8533.0 Gorasp2 1845.8 3055.9 3251.7

Null module GEO Series "GSE42473" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42473 Status: Public on Dec 04 2012 Title: PGC-1 alpha isoforms and muscle hypertrophy Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23217713 Summary & Design: Summary: An alternative promoter of the PGC-1alpha gene gives rise to three new PGC-1alpha isoforms refered to as PGC-1a2 (A2), PGC-1a3 (A3) and PGC-1a4 (A4). The proximal PGC-1 alpha promotor transcribes the canonical PGC-1 alpha which is refered to as PGC-1a1 (A1).G1/G2/G3 samples refer to the Green fluorescent protein (GFP) control samples used in this experiment. Forced expression of the PGC-1a4 isoform results in muslce hypertrophy associated with increased IGF-1 signaling and repression of myostatin signaling.

Overall design: Mouse primary myoblasts isolated from C57BL/6 mice were differentiated in vitro. Fully differentiated myotubes were transduced with adenoviral vectors expressing GFP (as control) or each of the PGC-1alpha isoforms originating from the proximal or alternative promotor.

Background corr dist: KL-Divergence = 0.1210, L1-Distance = 0.0285, L2-Distance = 0.0011, Normal std = 0.4209

0.965 Kernel fit Pairwise Correlations Normal fit

Density 0.482

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WtPMC_A1_1WtPMC_A1_2 (0.0648238)WtPMC_A1_3 (0.0795992)WtPMC_A2_1 (0.0639914)WtPMC_A2_2 (0.0364926)WtPMC_A2_3 (0.0194668)WtPMC_A3_1 (0.0535646)WtPMC_A3_2 (0.0193079)WtPMC_A3_3 (0.0459597)WtPMC_A4_1 (0.056044)WtPMC_A4_2 (0.165609)WtPMC_A4_3 (0.171452)WtPMC_G1 (0.143745)WtPMC_G2 (0.0328001)WtPMC_G3 (0.021751) (0.025393) [ min ] [ medium ] [ max ] CEM 1 Srp9 1311.7 1619.6 2586.1 P ( S | Z, I ) = 1.00 Srp19 2748.9 3082.0 4205.4 Mean Corr = 0.48377 Srp68 1281.7 1774.1 3482.7 Srp72 1225.8 1390.2 1612.1 Srp54b 314.6 379.9 437.4 Spcs2 1804.0 2736.9 3172.1 Sec23b 1343.5 1470.6 1628.7 Lrrc59 2422.0 2911.6 3699.2 Hdlbp 3184.3 3417.4 3687.3 Sec11a 1120.6 1305.1 1964.7 CEM 1 + Ssr3 3205.8 3615.6 4898.0 Top 10 Genes Tmem39a 547.5 621.8 850.5 Spcs3 1590.4 1834.6 2250.3 Ssr1 2149.0 2697.8 3334.8 Gorasp2 2172.2 2449.0 3561.7

Null module GEO Series "GSE13948" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 21 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13948 Status: Public on Dec 16 2008 Title: Antagonism of microRNA-122 in mice by systemically administered LNA-antimiR Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18158304 Summary & Design: Summary: Antagonism of microRNA-122 in mice by systemically administered LNA-antimiR leads to up-regulation of a large set of predicted target mRNAs in the liver

MicroRNA-122 (miR-122) is an abundant liver-specific miRNA, implicated in fatty acid and cholesterol metabolism as well as hepatitis C viral replication. Here, we report that a systemically administered 16-nt, unconjugated LNA (locked nucleic acid)-antimiR oligonucleotide complementary to the 5' end of miR-122 leads to specific, dose-dependent silencing of miR-122 and shows no hepatotoxicity in mice. Antagonism of miR-122 is due to formation of stable heteroduplexes between the LNA-antimiR and miR-122 as detected by northern analysis. Fluorescence in situ hybridization demonstrated uptake of the LNA-antimiR in mouse liver cells, which was accompanied by markedly reduced hybridization signals for mature miR-122 in treated mice. Functional antagonism of miR-122 was inferred from a low cholesterol phenotype and de-repression within 24 h of 199 liver mRNAs showing significant enrichment for miR-122 seed matches in their 3' UTRs. Expression profiling extended to 3 weeks after the last LNA-antimiR dose revealed that most of the changes in liver gene expression were normalized to saline control levels coinciding with normalized miR-122 and plasma cholesterol levels. Combined, these data suggest that miRNA antagonists comprised of LNA are valuable tools for identifying miRNA targets in vivo and for studying the biological role of miRNAs and miRNA-associated gene-regulatory networks in a physiological context.

Keywords: compound treatment

Overall design: Female NMRI mice were treated at day 2 with either 25mg/kg antimiR-122 (SPC3372) or vehicle (saline). Mice were sacrificied at day 3, 9 and 23 and liver RNA assayed. Three biological replicates for each of the six groups.

Background corr dist: KL-Divergence = 0.2960, L1-Distance = 0.0653, L2-Distance = 0.0117, Normal std = 0.2812

1.419 Kernel fit Pairwise Correlations Normal fit

Density 0.709

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

p0617_treated_day_23_rep1p0617_treated_day_23_rep2p0617_treated_day_23_rep3p0617_treated_day_3_rep1 (0.0196151)p0617_treated_day_3_rep2 (0.0229993)p0617_treated_day_3_rep3 (0.0384915)p0617_treated_day_9_rep1 (0.0255602)p0617_treated_day_9_rep2 (0.0276921)p0617_treated_day_9_rep3 (0.0234333)p0617_control_day_3_rep1 (0.116586)p0617_control_day_3_rep2 (0.0736627)p0617_control_day_3_rep3 (0.067955)p0617_control_day_9_rep1 (0.0270487)p0617_control_day_9_rep2 (0.0388048)p0617_control_day_9_rep3 (0.0404818)p0621_treated_day_23_rep1 (0.0300137)p0621_treated_day_23_rep2 (0.0878332)p0621_treated_day_23_rep3 (0.0163925)p0621_control_day_23_rep1 (0.0191877)p0621_control_day_23_rep2 (0.0239184)p0621_control_day_23_rep3 (0.0216518) (0.0260926) (0.155606) (0.0969734)[ min ] [ medium ] [ max ] CEM 1 Srp9 2360.1 2935.4 3877.6 P ( S | Z, I ) = 1.00 Srp19 2175.9 2851.9 3695.8 Mean Corr = 0.47017 Srp68 1513.0 1862.7 2652.0 Srp72 3009.4 3388.9 4147.2 Srp54b 32.8 43.4 49.5 Spcs2 4440.6 7341.4 8732.0 Sec23b 1608.6 2992.4 4799.7 Lrrc59 2623.2 3724.9 4620.9 Hdlbp 2767.5 3360.3 3892.2 Sec11a 5136.7 5957.5 7207.2 CEM 1 + Ssr3 5134.8 5977.9 7514.3 Top 10 Genes Tmem39a 497.3 720.9 1329.5 Spcs3 2410.9 3464.3 4581.7 Ssr1 3109.0 4479.6 5625.2 Gorasp2 2749.8 3237.5 3589.8

Null module GEO Series "GSE9249" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 28 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9249 Status: Public on Nov 01 2007 Title: Gene expression analysis of B-NHL from ˛»MYC, ˛»MYC/I´HABCL6, ˛»MYC/AIDKO and ˛»MYC/I´HABCL6/AIDKO mouse models Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18066064 Summary & Design: Summary: Most human B cell lymphomas (B-NHL) are derived from germinal centers (GCs), the structure where B-cells undergo class switch recombination (CSR) and somatic hypermutation (SHM) and are selected for high-affinity antibody production. The pathogenesis of B-NHL is associated with distinct genetic lesions, including chromosomal translocations and aberrant somatic hypermutation, which appear to arise from mistakes occurring during CSR and SHM. To ascertain the role of CSR and SHM in lymphomagenesis, we crossed three oncogene-driven (MYC, BCL6, MYC/BCL6) mouse models of B cell lymphoma with mice lacking activation-induced cytidine deaminase (AID), the enzyme required for both processes.

We show that AID deficiency prevents BCL6-dependent, GC-derived B-NHL, while it has no impact on the formation of MYC-driven, pre-GC lymphomas. Accordingly, abrogation of AID is associated with the disappearance of both CSR- and SHM-mediated structural alterations, including cMYC-IgH chromosomal translocations and aberrant SHM. These results demonstrate that AID is required for GC-derived lymphomagenesis, providing direct support to the notion that errors in AID-mediated antigen-receptor gene modification events represent major contributors to the pathogenesis of human B-NHL.

Keywords: Phenotypic characterization of tumors developing in oncogene-driven mouse models of lymphomas

Overall design: Nodal B-NHL from 5 MYC, 7 MYC/AIDKO, 12 MYC/HABCL6 and 6 MYC/HABCL6/AIDKO mice were analyzed in this study. Total RNA was extracted from frozen tumor biopsies and processed according to Affymetrix standard protocols

Background corr dist: KL-Divergence = 0.3116, L1-Distance = 0.0597, L2-Distance = 0.0098, Normal std = 0.2778

1.436 Kernel fit Pairwise Correlations Normal fit

Density 0.718

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

LymphomaLymphoma lambdaLymphoma lambdaMYCtgLymphoma lambda1MYCtg (0.0352857)Lymphoma lambda2MYCtg (0.0469782)Lymphoma lambda3MYCtg (0.0185851)Lymphoma lambda4MYCtg (0.01546)Lymphoma lambda5MYCtg/AIDKO (0.0708564)Lymphoma lambdaMYCtg/AIDKOLymphoma lambda1MYCtg/AIDKO (0.0343619)Lymphoma lambda2MYCtg/AIDKO (0.0103217)Lymphoma lambda3MYCtg/AIDKO (0.10712)Lymphoma lambda4MYCtg/I´HABCL6KI (0.0153893)Lymphoma lambda5MYCtg/I´HABCL6KI (0.0120201)Lymphoma lambdaMYCtg/I´HABCL6KILymphoma 1 lambda(0.0724322)MYCtg/I´HABCL6KILymphoma 2 lambda(0.0298416)MYCtg/I´HABCL6KILymphoma 3 lambda(0.0870327)MYCtg/I´HABCL6KILymphoma 4 lambda(0.107679)MYCtg/I´HABCL6KILymphoma 5 lambda(0.04512)MYCtg/I´HABCL6KILymphoma 6 lambda(0.0528822)MYCtg/I´HABCL6KILymphoma 7 lambda(0.00684563)MYCtg/I´HABCL6KILymphoma 8 lambda(0.0179419)MYCtg/I´HABCL6KILymphoma 9 lambda(0.0243867)MYCtg/I´HABCL6KILymphoma 10 lambdaMYCtg/I´HABCL6KI/AIDKO (0.0242754)Lymphoma 11 lambdaMYCtg/I´HABCL6KI/AIDKO (0.0185533)Lymphoma 12 lambdaMYCtg/I´HABCL6KI/AIDKO (0.024643)Lymphoma lambdaMYCtg/I´HABCL6KI/AIDKO 1 lambda(0.0240076)MYCtg/I´HABCL6KI/AIDKO 2 (0.0167501)MYCtg/I´HABCL6KI/AIDKO 3 (0.0268841)[ 4min (0.0145044) 5 (0.00610129)] 6 (0.0337403)[ medium ] [ max ] CEM 1 Srp9 1601.1 2189.7 4632.2 P ( S | Z, I ) = 1.00 Srp19 3937.6 8125.2 15106.2 Mean Corr = 0.39651 Srp68 2621.4 4535.0 11409.8 Srp72 2598.9 3607.9 5022.9 Srp54b 42.2 213.2 1474.0 Spcs2 4234.0 10104.7 21023.4 Sec23b 1584.6 3054.3 5645.3 Lrrc59 3040.0 6060.1 16007.4 Hdlbp 1637.3 4323.2 11400.7 Sec11a 5515.2 7069.6 12319.0 CEM 1 + Ssr3 3538.4 6306.7 21330.4 Top 10 Genes Tmem39a 339.1 1134.7 3299.5 Spcs3 2487.9 6512.5 15244.6 Ssr1 3284.1 7237.7 17010.5 Gorasp2 1921.4 4017.5 8876.3

Null module GEO Series "GSE24813" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 10 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24813 Status: Public on Aug 24 2011 Title: Gene expression data of BCR-ABL1 transformed myeloid cells from BCL6 wild-type and BCL6 knockout mice treated with and without Imatinib and RI-BPI Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21911423 Summary & Design: Summary: To identify differences in the gene regulation between BCL6+/+ and BCL6-/- CML cells a gene expression analysis has been performed. We investigated the gene expression pattern in BCL6+/+ cells in the presence or absence of Imatinib and a combination of Imatinib and RI-BPI (a novel retro-inverso BCL6 peptide inhibitor). In BCL6-/- CML cells, we investigated the gene expression pattern in the presence or absence of Imatinib.

Overall design: BCR-ABL1 transformed myeloid cells from BCL6+/+ mice were cultured in the presence or absence of 10´M Imatinib or 10´M Imatinib and 20´M RI-BPI for 16 hours. BCR-ABL1 transformed myeloid cells from BCL6-/- mice were cultured in the presence or absence of 10´M Imatinib. Two samples for each condition were processed.

Background corr dist: KL-Divergence = 0.0654, L1-Distance = 0.0414, L2-Distance = 0.0023, Normal std = 0.5423

0.785 Kernel fit Pairwise Correlations Normal fit

Density 0.393

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

BCL6 WTBCL6 chip WT 1BCL6 untreated chip WT 2BCL6 untreated chip (0.287526) WT 1BCL6 Imatinib chip (0.232291) WT 2BCL6 Imatinib chiptreated WT 1BCL6 Imatinib/RI-BPI chiptreated(0.0141738) KO 2BCL6 Imatinib/RI-BPI chip (0.0332623) KO 1BCL6 untreated chiptreated KO 2BCL6 untreated chiptreated(0.0636486) (0.0411885) KO 1 Imatinib chip(0.0627393) (0.0545799) 2 Imatinib treated treated(0.0847669)[ min(0.125824) ] [ medium ] [ max ] CEM 1 Srp9 1996.3 2177.1 2746.1 P ( S | Z, I ) = 0.99 Srp19 2974.3 3797.3 5668.1 Mean Corr = 0.68003 Srp68 2071.3 2244.4 2571.4 Srp72 1273.8 1949.4 2355.7 Srp54b 90.3 128.4 169.5 Spcs2 9074.2 11124.3 11887.1 Sec23b 1329.3 1988.1 2763.9 Lrrc59 1300.4 1451.6 3598.6 Hdlbp 1479.0 2174.6 3716.1 Sec11a 5794.9 6916.4 8114.2 CEM 1 + Ssr3 6072.5 6824.8 8022.8 Top 10 Genes Tmem39a 639.1 742.4 1302.7 Spcs3 11472.6 13043.2 21501.2 Ssr1 6238.6 8921.0 11208.8 Gorasp2 1726.8 1974.5 3132.6

Null module GEO Series "GSE38136" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38136 Status: Public on May 30 2012 Title: Hepatic gene expression in BALB/c mice fed a quercetin diet Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19496084 Summary & Design: Summary: We showed that diets containing 0.1% or 0.5% quercetin lowered the STZ-induced increase in blood glucose levels and improved plasma insulin levels. A cluster analysis of the hepatic gene expressions showed that 0.5% quercetin diet suppressed STZ-induced alteration of gene expression. Gene set enrichment analysis (GSEA) and quantitative RT-PCR analysis showed that the quercetin diets had their greatest suppressive effect on the STZ-induced elevation of expression of cyclin dependent kinase inhibitor p21(WAF1/Cip1) (Cdkn1a).

In this experiment, we determined the effect of quercetin on healthy control BALB/c mice that were fed the AIN93G diet containing 0, 0.1, 0.5 or 1% quercetin for 2 weeks. GSEA and one-way ANOVA did not detect any significant changes in hepatic gene expression in normal mice as a result of a quercetin diet. Using a linear modeling approach and the empirical Bayes statistics, we found that Ubc were significantly reduced by both the 0.5% and 1% quercetin.

Overall design: Six-week-old male mice were divided into 4 groups of 6 mice each, housed in groups of 3 per cage, and fed a standard purified AIN-93G diet containing 0% (Control), 0.1% (0.1), 0.5% (0.5), or 1% quercertin (1.0) for 2 weeks.

Background corr dist: KL-Divergence = 0.4062, L1-Distance = 0.0793, L2-Distance = 0.0196, Normal std = 0.2460

1.622 Kernel fit Pairwise Correlations Normal fit

Density 0.811

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

liver controlliver controldietliver rep1 controldiet (0.0134773)liver rep2 controldiet (0.0252141)liver rep3 controldiet (0.0160642)liver rep4 controldiet (0.0175774)liver rep5 0.1%diet (0.0323477)liver rep6 quercetin 0.1% (0.0225488)liver quercetin 0.1%dietliver rep1quercetin 0.1%diet (0.0239287)liver rep2quercetin 0.1%diet (0.024786)liver rep3quercetin 0.1%diet (0.0527268)liver rep4quercetin 0.5%diet (0.0342561)liver rep5quercetin 0.5%diet (0.0474741)liver rep6quercetin 0.5%diet (0.0338228)liver rep1quercetin 0.5%diet (0.029071)liver rep2quercetin 0.5%diet (0.031465)liver rep3quercetin 0.5%diet (0.0224882)liver rep4quercetin 1.0%diet (0.053391)liver rep5quercetin 1.0%diet (0.0240539)liver rep6quercetin 1.0%diet (0.244032)liver rep1quercetin 1.0%diet (0.0165972)liver rep2quercetin 1.0%diet (0.0207541)liver rep3quercetin 1.0%diet (0.0240323) rep4quercetin diet (0.0411505) rep5 diet (0.0886274) rep6 (0.060114)[ min ] [ medium ] [ max ] CEM 1 Srp9 3082.8 3587.9 4335.0 P ( S | Z, I ) = 1.00 Srp19 2786.8 3338.0 4981.5 Mean Corr = 0.43830 Srp68 2279.5 2631.8 3599.1 Srp72 2993.4 3456.4 4136.6 Srp54b 12.7 59.5 159.8 Spcs2 4155.3 5715.9 7163.5 Sec23b 2029.9 2712.9 5365.4 Lrrc59 3037.8 3733.4 5756.4 Hdlbp 5833.4 6968.6 8114.7 Sec11a 5522.4 6356.2 7837.5 CEM 1 + Ssr3 7454.5 10126.3 12764.4 Top 10 Genes Tmem39a 234.8 545.8 1139.1 Spcs3 3231.5 3768.0 4630.2 Ssr1 4628.3 6032.9 8224.7 Gorasp2 4025.0 4734.7 6588.8

Null module GEO Series "GSE43899" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43899 Status: Public on Aug 30 2013 Title: Co-ordinate inhibiton of autism candidate genes by topoisomerase inhibitors [array] Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23995680 Summary & Design: Summary: Topoisomerases are necessary for the expression of neurodevelopmental genes, and are mutated in some patients with autism spectrum disorder (ASD). We have studied the effects of inhibitors of Topoisomerase 1 (Top1) and Topoisomerase 2 (Top2) enzymes on mouse cortical neurons. We find that topoisomerases selectively inhibit long genes (>100kb), with little effect on all other gene expression. Using ChIPseq against RNA Polymerase II (Pol2) we show that the Top1 inhibitor topotecan blocks transcriptional elongation of long genes specifically. Many of the genes inhibited by topotecan are candidate ASD genes, leading us to propose that topoisomerase inhibition might contribute to ASD pathology.

Overall design: 9) cultured mouse cortical neurons treated with topotecan with or without subsequent drug washout, vs vehicle-treated controls.

Background corr dist: KL-Divergence = 0.0306, L1-Distance = 0.0234, L2-Distance = 0.0007, Normal std = 0.6443

0.619 Kernel fit Pairwise Correlations Normal fit

Density 0.310

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ICRF193_3´M_1ICRF193_3´M_2ICRF193_3´M_3 (0.0321838)ICRF193_3´M_vehicle_1 (0.0278368)ICRF193_3´M_vehicle_2 (0.0262863)ICRF193_3´M_vehicle_3Topotecan_300nM_1 (0.0766812)Topotecan_300nM_2 (0.0688305)Topotecan_300nM_3 (0.0804745) (0.205418)Topotecan_300nM_vehicle_1 (0.0872461)Topotecan_300nM_vehicle_2 (0.222505)Topotecan_300nM_vehicle_3 (0.0547771) (0.0420867) (0.0756744)[ min ] [ medium ] [ max ] CEM 1 Srp9 1656.7 2010.5 2814.1 P ( S | Z, I ) = 0.99 Srp19 3754.7 4281.9 5259.4 Mean Corr = 0.75253 Srp68 1029.1 1166.7 1835.2 Srp72 1952.5 2276.9 3347.0 Srp54b 109.9 141.8 167.6 Spcs2 3437.1 4062.2 5014.0 Sec23b 1407.6 1865.4 2313.5 Lrrc59 2796.6 3131.3 4315.4 Hdlbp 596.8 673.5 1126.4 Sec11a 3972.6 4269.4 5442.1 CEM 1 + Ssr3 3244.4 4824.0 6457.1 Top 10 Genes Tmem39a 396.3 453.0 763.7 Spcs3 1174.1 1260.0 1823.1 Ssr1 3622.3 3810.5 4952.6 Gorasp2 1919.6 2226.4 2673.3

Null module GEO Series "GSE25088" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25088 Status: Public on Nov 18 2010 Title: PPARg and IL-4-induced gene expression data from wild-type and STAT6 knockout mouse bone marrow-derived macrophages Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21093321 Summary & Design: Summary: C57Bl/6 wild-type and STAT6 KO mice were used to study PPARg and IL-4 signaling. Bone marrow of 3 mice per group was isolated and differentiated to macrophages with M-CSF (20 ng/ml). 20 ng/ml IL-4 was used to induce alternative macrophage activation and 1 uM Rosiglitazone (RSG) was used to activate PPARg. From each mouse 4 samples were generated: 1. M-CSF, 2. M-CSF+RSG, 3. IL-4 and 4. IL-4+RSG. All compounds were added throughout the whole differentiation process, and frech media was added every other day. Control cells were treated with vehicle (DMSO:ethanol). After 10 days, RNA was isolated and gene expression profiles were analyzed using Mouse Genome 430 2.0 microarrays from Affymetrix.

Overall design: 3 C57Bl/6 wild-type and 3 STAT6 KO mice were used to isolate bone marrow and from each macrophages were differentiated with or without IL-4 and simultaneously treated with vehicle or RSG. Altogether we analyzed 24 samples with 3 biological replicates as below.

Background corr dist: KL-Divergence = 0.2287, L1-Distance = 0.0913, L2-Distance = 0.0220, Normal std = 0.3531

1.233 Kernel fit Pairwise Correlations Normal fit

Density 0.616

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

1 Wild-type1 Wild-type control1 Wild-type controlmacrophage1 Wild-type IL-4macrophage+RSG2 macrophageWild-type (0.0614974) IL-42 macrophage+RSGWild-type control (0.131924)2 (0.00919217)Wild-type controlmacrophage2 Wild-type IL-4macrophage+RSG (0.0570231)3 macrophageWild-type (0.0151893) IL-43 macrophage+RSGWild-type control (0.125675)3 (0.00925141)Wild-type controlmacrophage3 Wild-type IL-4macrophage+RSG (0.0426253)4 macrophageSTAT6KO (0.00578537) IL-44 macrophage+RSGSTAT6KO control (0.115096)4 (0.0291475)STAT6KO controlmacrophage4 STAT6KO IL-4macrophage+RSG(0.0889976)5 macrophageSTAT6KO (0.0700603) IL-45 macrophage+RSGSTAT6KO control (0.020973)5 (0.0130712)STAT6KO controlmacrophage5 STAT6KO IL-4macrophage+RSG (0.0612192)6 macrophageSTAT6KO (0.0118324) IL-46 macrophage+RSGSTAT6KO control (0.0191308)6 (0.025898)STAT6KO controlmacrophage6 STAT6KO IL-4macrophage+RSG (0.0261172) macrophage (0.00915743) IL-4 macrophage+RSG (0.01817) (0.0136911)[ min (0.0192754) ] [ medium ] [ max ] CEM 1 Srp9 422.0 440.2 632.7 P ( S | Z, I ) = 1.00 Srp19 422.0 439.3 568.5 Mean Corr = 0.11252 Srp68 391.7 435.9 492.0 Srp72 422.0 440.2 680.2 Srp54b 391.7 435.3 629.1 Spcs2 422.0 440.2 624.6 Sec23b 422.0 438.5 610.0 Lrrc59 422.0 440.1 696.3 Hdlbp 422.0 443.5 548.0 Sec11a 422.0 438.5 519.9 CEM 1 + Ssr3 422.0 440.1 656.8 Top 10 Genes Tmem39a 391.7 435.9 571.3 Spcs3 422.0 440.1 579.9 Ssr1 422.0 439.3 534.7 Gorasp2 422.0 440.2 675.0

Null module GEO Series "GSE22125" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22125 Status: Public on Jun 04 2010 Title: Mouse pancreatic islets during pregnancy Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20581837 Summary & Design: Summary: During pregnancy, pancreatic islets undergo structural and functional changes that lead to enhance insulin release in response to increased insulin demand, which is rapidly reversed at parturition. One of the most important changes is expansion of pancreatic Î²-cell mass mainly by increased proliferation of Î² cells.

We used microarrays to detail the global programme of gene expression and identified distinct up- or down-regulated genes during pregnancy.

Overall design: Maternal islet were isolated from mice at dpc 0 and 12.5 dpc of pregnancy for RNA extraction and hybridization on Affymetrix microarrays. We sought to identify the responsible factors for the proliferation of islets during pregnancy.

Background corr dist: KL-Divergence = 0.0435, L1-Distance = 0.0196, L2-Distance = 0.0004, Normal std = 0.6024

0.670 Kernel fit Pairwise Correlations Normal fit

Density 0.335

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

islet of non-pregnantislet of non-pregnantislet of mice non-pregnantislet 1of (0.209206)mice 12.5islet 2dpcof (0.207107)mice 12.5islet pregnant 3dpcof (0.134585) 12.5 pregnant mice dpc pregnant1 (0.141108)mice 2 (0.175099)mice[ 3 min(0.132895) ] [ medium ] [ max ] CEM 1 Srp9 2645.6 4085.7 4411.1 P ( S | Z, I ) = 0.99 Srp19 3745.3 5653.7 5829.8 Mean Corr = 0.43412 Srp68 4126.0 4586.5 5001.6 Srp72 6303.7 7203.5 7291.9 Srp54b 325.4 453.5 535.1 Spcs2 15113.8 17942.1 18401.8 Sec23b 5723.3 7957.3 9257.1 Lrrc59 3263.1 4943.9 5395.5 Hdlbp 3847.4 5828.6 6464.9 Sec11a 6491.2 9059.2 9170.5 CEM 1 + Ssr3 5273.0 7186.9 8015.9 Top 10 Genes Tmem39a 1604.3 2331.2 2451.5 Spcs3 8391.2 10821.3 11447.3 Ssr1 7448.7 10579.1 11098.5 Gorasp2 7281.5 8412.2 9481.3

Null module GEO Series "GSE13693" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13693 Status: Public on Feb 06 2009 Title: Gene expression profiling of normal mouse myeloid cell populations Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19200802 Summary & Design: Summary: Normal myeloid lineage cell populations (C57BL/6 mice, aged 4-10 weeks, male or female) with three distinct immunophenotypes were prospectively isolated and characterized. In preparation for FACS sorting, bone marrow cells were separated into c-kit+ and c-kit- fractions using an AutoMACS device. C-kit+ cells were further fractionated based on Gr1 and Mac1 expression, and absence of lineage antigen expression (B220, TER119, CD3, CD4, CD8 and IL7RÎ±), by cell sorting. C-kit+ Gr1+ Mac1lo/- and c-kit+ Gr1+ Mac1+ displayed cytologic features of undifferentiated hematopoietic cells or myeloblasts, whereas c-kit- Gr1+ Mac1+ cells were mature neutrophils.

Overall design: See summary.

Background corr dist: KL-Divergence = 0.0176, L1-Distance = 0.0380, L2-Distance = 0.0018, Normal std = 0.8108

0.500 Kernel fit Pairwise Correlations Normal fit

Density 0.250

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

NORMALNORMAL BM NEUTROPHILS_2NORMAL BM NEUTROPHILS_1NORMAL BM NEUTROPHILS_3NORMAL (0.242158)MYELOBLASTS_CD117POS_GR1+_MAC1-_1NORMAL (0.221123)MYELOBLASTS_CD117POS_GR1+_MAC1-_2NORMAL (0.170813)MYELOBLASTS_CD117POS_GR1+_MAC1-_3NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_2NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_1 MYELOBLASTS_CD117POS_GR1+_MAC1+_3 (0.0992332) (0.0724037)[ min(0.0687905) (0.0699751)] (0.0185264)[ (0.0369765) medium ] [ max ] CEM 1 Srp9 2418.0 5386.9 5656.0 P ( S | Z, I ) = 0.99 Srp19 876.6 1672.0 2152.4 Mean Corr = 0.30454 Srp68 648.0 4362.5 5473.7 Srp72 590.5 4243.6 5106.8 Srp54b 74.1 97.5 136.8 Spcs2 1695.9 9393.5 10367.7 Sec23b 688.5 4642.6 5056.8 Lrrc59 721.4 5566.6 7653.2 Hdlbp 2301.9 4346.8 5367.8 Sec11a 2151.2 7077.3 8203.6 CEM 1 + Ssr3 2409.1 8933.4 9912.3 Top 10 Genes Tmem39a 227.7 1580.9 1790.0 Spcs3 2748.6 10360.6 11201.0 Ssr1 2453.7 8078.2 9226.1 Gorasp2 918.9 4256.9 5268.5

Null module GEO Series "GSE13692" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13692 Status: Public on Feb 06 2009 Title: Expression profiling of MLL-AF10 myeloid leukemia cellular subsets Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19200802 Summary & Design: Summary: Leukemia cells from mice with MLL-AF10 AML were fractionated into separate sub-populations on the basis of c-kit expression, which correlates with MLL LSC frequency (Somervaille and Cleary, 2006). The sorted AML sub-populations exhibited substantial differences in their frequencies of AML CFCs/LSCs (mean 14-fold) and morphologic features, consistent with a leukemia cell hierarchy with maturation through to terminally differentiated neutrophils.

Overall design: Leukemic splenocytes from four mice with MLL-AF10 AML were sub-fractionated in to c-kit high and c-kit negative sub-populations by FACS.

Background corr dist: KL-Divergence = 0.0464, L1-Distance = 0.0346, L2-Distance = 0.0017, Normal std = 0.6099

0.681 Kernel fit Pairwise Correlations Normal fit

Density 0.341

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

MLL-AF10MLL-AF10 LEUKEMICMLL-AF10 LEUKEMIC MLL-AF10SPLENOCYTES_CD117NEG_948 LEUKEMIC MLL-AF10SPLENOCYTES_CD117POS_948 LEUKEMIC MLL-AF10SPLENOCYTES_CD117NEG_951 LEUKEMIC MLL-AF10SPLENOCYTES_CD117POS_951 LEUKEMIC MLL-AF10SPLENOCYTES_CD117NEG_952 LEUKEMIC(0.0731304) SPLENOCYTES_CD117POS_952 LEUKEMIC(0.152017) SPLENOCYTES_CD117NEG_953 (0.141204) SPLENOCYTES_CD117POS_953 (0.207905)[ min(0.0915941) (0.0833431) ] (0.172229) [(0.078578) medium ] [ max ] CEM 1 Srp9 3503.0 5399.0 5852.7 P ( S | Z, I ) = 0.97 Srp19 1915.2 2500.8 3201.3 Mean Corr = 0.63356 Srp68 2269.3 3981.2 5181.3 Srp72 4293.3 5409.5 6494.2 Srp54b 64.4 87.4 111.6 Spcs2 5789.1 8309.9 9203.8 Sec23b 2495.4 3016.4 3710.7 Lrrc59 3280.6 4213.5 5802.7 Hdlbp 2602.3 2983.3 3441.0 Sec11a 3357.9 5468.2 7536.0 CEM 1 + Ssr3 4379.2 6508.8 7620.2 Top 10 Genes Tmem39a 627.5 1086.4 1215.3 Spcs3 7699.1 10847.7 12383.7 Ssr1 5854.8 6954.9 8178.2 Gorasp2 2475.0 3217.7 3907.6

Null module GEO Series "GSE45051" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE45051 Status: Public on Jun 01 2013 Title: Gene expression profile of liver from adult and neonatal Balb/c mice after listeriosis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Expression profiling by microarray was used with a murine listeriosis model to better understand increased susceptibility of preterm neonates to infection.

We used DNA microarray to identify genes that were differentially expressed in liver of adult and neonatal Balb/c mice after listeriosis infection.

Overall design: A murine listeriosis model was established. The methods for culturing and counting the Listeria monocytogenes (strain CNL 85/163) had been described in previous publications. The Listeria was injected intraperitoneally using a 1-mL U-100 insulin syringe with a 30 gauge needle. Doses of Listeria monocytogenes used were based on work by our laboratory showing that similar bacterial colony counts were obtained with 4.2 x 10^5 total Listeria per adult mouse and 150 Listeria per gram for 3 to 5 day old neonatal mice. In neonatal mice, great care was taken to void deep intraperitoneal injection towards the viscera, or across the central abdominal vessels. At specified time points, liver was removed upon animal sacrifice and immediately flash frozen in liquid nitrogen and stored at -80 degrees Centigrade. Three adult mice and three neonatal mice were used at each time point.

Background corr dist: KL-Divergence = 0.1508, L1-Distance = 0.0278, L2-Distance = 0.0014, Normal std = 0.3783

1.054 Kernel fit Pairwise Correlations Normal fit

Density 0.527

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

A1-0hourA2-0hour (0.0222783)A3-0hour (0.0756708)P1-0hour (0.0354806)P2-0hour (0.0468439)P3-0hour (0.0190458)A1-24hour (0.0168561)A3-24hour (0.235227)A4-24hour (0.1395)P1-24hour (0.137153)P2-24hour (0.0180145)P5-24hour (0.0223884)A1-48hour (0.0409835)A2-48hour (0.0337351)A3-48hour (0.00937831)P2-48hour (0.0302767)P3-48hour (0.0731481)P6-48hour (0.0170174) (0.0270023) [ min ] [ medium ] [ max ] CEM 1 Srp9 1351.1 1700.8 3562.2 P ( S | Z, I ) = 0.97 Srp19 1981.8 3358.1 4814.6 Mean Corr = 0.47116 Srp68 1612.0 2061.8 3321.4 Srp72 2644.5 3073.1 4781.3 Srp54b 9.0 107.8 257.6 Spcs2 4150.8 6571.4 9265.6 Sec23b 1878.4 2684.6 5015.5 Lrrc59 2600.3 5064.0 8945.2 Hdlbp 3620.9 5518.6 8394.2 Sec11a 4083.7 5321.8 8533.6 CEM 1 + Ssr3 5246.8 8330.8 15033.8 Top 10 Genes Tmem39a 416.4 697.2 1115.5 Spcs3 1901.2 2786.8 4397.6 Ssr1 3128.7 4881.6 8140.8 Gorasp2 1152.2 2913.8 3858.9

Null module GEO Series "GSE28621" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 21 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28621 Status: Public on May 09 2014 Title: Transcriptional profiles of macrophages in resolving inflammation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24762537 Summary & Design: Summary: We have performed a comprehensive transcriptional analysis of specific monocyte and macrophage (Mˆ) subsets during an acute self-resolving inflammatory insult. Following initial induction of acute inflammation, tissue resident (Resident) Mˆ are rapidly cleared from the inflammatory foci, only becoming recoverable as inflammation resolves. Monocytes are recruited to the inflammatory lesion where they differentiate into Mˆ. We term these monocyte-derived Mˆ inflammation-associated to distinguish them from Resident Mˆ which are present throughout the inflammatory response and can renew during the resolution of inflammation by proliferation. Comparative analysis of the Mo and Mˆ populations (both inflammation-associated and Resident Mˆ) identifies select genes expressed in subsets of inflammation-associated and Resident Mˆ that play important roles in the resolution of inflammation and/or for immunity, including molecules involved in antigen presentation, cell cycle and others associated with immaturity and Mˆ activation.

Overall design: We purified monocyte and macrophage populations from the peritoneal cavity of C57BL/6 mice 4, 18, 72 and 168 hours after the induction of inflammation with intraperitoneal administration of zymosan (2x10^7 particles). We also purified tissue resident macrophages and Ly-6B+ bone marrow monocytes from naive mice as reference populations.

Background corr dist: KL-Divergence = 0.1827, L1-Distance = 0.0365, L2-Distance = 0.0024, Normal std = 0.3564

1.131 Kernel fit Pairwise Correlations Normal fit

Density 0.565

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

F4/80(med-high),F4/80(med-high),F4/80(med-high), Ly-6B+F4/80(high), Ly-6B+inflammation-associatedF4/80(high), Ly-6B+inflammation-associated Ly-6B-F4/80(high), inflammation-associated inflammation-associatedLy-6B-Ly-6B+, inflammation-associatedLy-6B- macrophages_168Ly-6B+, Ly-6G- inflammation-associated macrophages_168Ly-6B+, inflammation-associatedLy-6G- macrophages_168 F4/80+, macrophages_168inflammation-associatedLy-6G- hours_biological F4/80+, macrophages_168CD11b+inflammation-associated hours_biological F4/80+,macrophages_168CD11b+ inflammation-associated hours_biological monocyte_4 hours_biological rep Ly-6B+/low,CD11b+ 1inflammation-associated (0.020377)monocyte_4 hours_biological repLy-6B+/low, 2inflammation-associatedhours_biological (0.00361963)monocyte_4 hours_biological repLy-6G- repLy-6B+/low, 3hours_biological (0.00446398)1 macrophages_72inflammation-associatedLy-6G-(0.0633553) repF4/80(high), hours_biological 2 rep macrophages_72inflammation-associatedLy-6G-(0.0175374) rep F4/80(high),1 (0.19211) 3 rep macrophages_72inflammation-associated(0.00517385)CD11b(high) hours_biological F4/80(high),2 (0.170873) rep CD11b(high) hours_biological Ly-6B+Ly-6G-monocyte/macrophage_183 (0.166028) peritoneal CD11b(high) hours_biologicalLy-6B+Ly-6G-monocyte/macrophage_18 rep peritoneal 1 residentbone Ly-6B+Ly-6G-monocyte/macrophage_18(0.0302344) rep peritoneal marrow 2 residentbone macrophages_naive_biological(0.0307983) rep hours_biologicalmarrow monocyte_biological3 residentbone macrophages_naive_biological(0.0504124) hours_biologicalmarrow monocyte_biological macrophages_naive_biological hours_biological monocyte_biological rep[ min 1 rep (0.0166793) rep 1 rep (0.043111) 2 ]rep (0.00407977)1 rep(0.0331833) 2 rep (0.0120614) 3 rep (0.0601338)2 (0.0346191) 3 rep [(0.0249639) medium3 (0.0161857) ] [ max ] CEM 1 Srp9 2187.1 3417.2 4266.5 P ( S | Z, I ) = 0.96 Srp19 1248.5 1822.4 2652.1 Mean Corr = 0.54751 Srp68 2190.9 2706.3 3946.5 Srp72 2475.1 3263.9 5342.9 Srp54b 219.8 433.9 1360.5 Spcs2 4873.1 7053.6 10081.9 Sec23b 2306.1 2849.3 7573.2 Lrrc59 2783.7 3722.3 8659.1 Hdlbp 2506.3 3706.1 6094.6 Sec11a 6239.1 8543.0 11421.0 CEM 1 + Ssr3 10747.7 14972.9 19490.7 Top 10 Genes Tmem39a 733.1 979.2 2665.4 Spcs3 6466.2 7527.8 8667.8 Ssr1 4395.4 6951.4 10940.6 Gorasp2 1924.4 2453.1 4600.6

Null module GEO Series "GSE21272" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 44 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21272 Status: Public on Oct 21 2010 Title: Time Course Gene Expression Microarray Analysis of a Mouse B-cell Line (CH12.LX) Activated with Lipopolysaccharide and Treated with 2,3,7,8-Tetrachlorodibenzo-p-dioxin Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20819909 Summary & Design: Summary: The objective of the study was to characterize gene expression cascade involved in the suppression of B-cell activation and differentiation by 2,3,7,8-tetrachlorodibenzo-p-dixoxin (TCDD). The underlying hypothesis was that multiple nodes in the B-cell differentiation network are directly or indirectly regulated by TCDD through its receptor, the AHR.

Overall design: The mouse B-cell line (CH12.LX) was plated at 1X10^5 cells/ml at time 0 and activated with lipopolysaccharide (LPS, Salmonella typhosa). The cells were then treated with either dimethyl sulfoxide (DMSO, 0.01%) or 10 nM 2,3,7,8-tetrachlorodibenzo-p-dixoxin (TCDD). The cells were harvested at 0, 8, 12, 24, 36, and 48 hrs post-treatment. At the 0 hr time point, cells were untreated. A total of 4 experimental replicates per time point per treatment group were included with the cells for each replicate treated and harvested on separate days. Single color Affymetrix Mouse 430 2.0 arrays were used.

Background corr dist: KL-Divergence = 0.2971, L1-Distance = 0.0472, L2-Distance = 0.0048, Normal std = 0.2838

1.406 Kernel fit Pairwise Correlations Normal fit

Density 0.703

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

LX_ND_0_0_12_CH12LX_UN_2_120408_Mouse430_2_RSTMSU601_9LX_ND_0_0_1_CH12LX_UN_1_111908_Mouse430_2_RSTMSU601_9LX_ND_0_0_23_CH12LX_UN_3_121508_Mouse430_2_RSTMSU601_9LX_ND_0_0_34_CH12LX_UN_4_013009_Mouse430_2_RSTMSU601_9LX_ND_0_12_15_CH12LX_D_2_120408_Mouse430_2_RSTMSU601_9LX_ND_0_12_26_CH12LX_D_3_121508_Mouse430_2_RSTMSU601_9LX_ND_0_12_37_CH12LX_D_4_013009_Mouse430_2_RSTMSU601_9LX_ND_0_12_4_CH12LX_D_1_111908_Mouse430_2_RSTMSU601_9LX_ND_0_24_17_CH12LX_D_2_120408_Mouse430_2_RSTMSU601_9LX_ND_0_24_28_CH12LX_D_3_121508_Mouse430_2_RSTMSU601_9 (0.00490644)LX_ND_0_24_39_CH12LX_D_4_013009_Mouse430_2_RSTMSU601_9 (0.023721)LX_ND_0_24_6_CH12LX_D_1_111908_Mouse430_2_RSTMSU601_9 (0.00678882)LX_ND_0_36_19_CH12LX_D_2_120408_Mouse430_2_RSTMSU601_9 (0.0160819)LX_ND_0_36_30_CH12LX_D_3_121508_Mouse430_2_RSTMSU601_9 (0.0156433)LX_ND_0_36_41_CH12LX_D_4_013009_Mouse430_2_RSTMSU601_9 (0.0177752)LX_ND_0_36_8_CH12LX_D_1_111908_Mouse430_2_RSTMSU601_9 (0.0112565)LX_ND_0_48_10_CH12LX_D_1_111908_Mouse430_2_RSTMSU601_9 (0.010636)LX_ND_0_48_21_CH12LX_D_2_120408_Mouse430_2_RSTMSU601_9 (0.0196877)LX_ND_0_48_32_CH12LX_D_3_121508_Mouse430_2_RSTMSU601_9 (0.00851248)LX_ND_0_48_43_CH12LX_D_4_013009_Mouse430_2_RSTMSU601_9 (0.015699)LX_ND_0_8_13_CH12LX_D_2_120408_Mouse430_2_RSTMSU601_9 (0.0300397)LX_ND_0_8_24_CH12LX_D_3_121508_Mouse430_2_RSTMSU601_9 (0.0318187)LX_ND_0_8_2_CH12LX_D_1_111908_Mouse430_2_RSTMSU601_9 (0.0363196)LX_ND_0_8_35_CH12LX_D_4_013009_Mouse430_2_RSTMSU601_9 (0.0712099)LX_ND_10_12_16_CH12LX_T_2_120408_Mouse430_2_RSTMSU601_9 (0.04476)LX_ND_10_12_27_CH12LX_T_3_121508_Mouse430_2_RSTMSU601_9 (0.0208936)LX_ND_10_12_38_CH12LX_T_4_013009_Mouse430_2_RSTMSU601_9 (0.0705782)LX_ND_10_12_5_CH12LX_T_1_111908_Mouse430_2_RSTMSU601_9 (0.0446999)LX_ND_10_24_18_CH12LX_T_2_120408_Mouse430_2_RSTMSU601_9 (0.0610501)LX_ND_10_24_29_CH12LX_T_3_121508_Mouse430_2_RSTMSU601_9 (0.0344833)LX_ND_10_24_40_CH12LX_T_4_013009_Mouse430_2_RSTMSU601_9 (0.0109679) (0.0301725)LX_ND_10_24_7_CH12LX_T_1_111908_Mouse430_2_RSTMSU601_9LX_ND_10_36_20_CH12LX_T_2_120408_Mouse430_2_RSTMSU601_9 (0.0355523)LX_ND_10_36_31_CH12LX_T_3_121508_Mouse430_2_RSTMSU601_9 (0.00992859)LX_ND_10_36_42_CH12LX_T_4_013009_Mouse430_2_RSTMSU601_9 (0.0397072)LX_ND_10_36_9_CH12LX_T_1_111908_Mouse430_2_RSTMSU601_9 (0.0201936)LX_ND_10_48_11_CH12LX_T_1_111908_Mouse430_2_RSTMSU601_9 (0.0187966)LX_ND_10_48_22_CH12LX_T_2_120408_Mouse430_2_RSTMSU601_9 (0.00200179)LX_ND_10_48_33_CH12LX_T_3_121508_Mouse430_2_RSTMSU601_9 (0.00592856)LX_ND_10_48_44_CH12LX_T_4_013009_Mouse430_2_RSTMSU601_9 (0.0159483)LX_ND_10_8_14_CH12LX_T_2_120408_Mouse430_2_RSTMSU601_9 (0.0143299)LX_ND_10_8_25_CH12LX_T_3_121508_Mouse430_2_RSTMSU601_9 (0.00646506)LX_ND_10_8_36_CH12LX_T_4_013009_Mouse430_2_RSTMSU601_9 (0.00370206)LX_ND_10_8_3_CH12LX_T_1_111908_Mouse430_2_RSTMSU601_9 (0.00572652) (0.0208307) (0.0140396) (0.0260424)[ (0.0126654)min (0.0266956) ] (0.0101724) (0.0214182)[ medium (0.0380908) (0.0140627) ] [ max ] CEM 1 Srp9 1824.9 3001.2 4403.8 P ( S | Z, I ) = 0.95 Srp19 5265.6 6392.4 8157.1 Mean Corr = 0.50128 Srp68 5310.1 6443.7 9048.4 Srp72 2091.4 3368.1 4821.1 Srp54b 140.1 259.1 530.1 Spcs2 7179.9 11096.5 15819.6 Sec23b 2955.8 4029.2 5302.7 Lrrc59 10901.1 12721.4 15721.9 Hdlbp 3471.5 4637.2 8169.7 Sec11a 4245.2 5465.9 7013.0 CEM 1 + Ssr3 6743.8 9949.2 13540.3 Top 10 Genes Tmem39a 1741.1 2739.4 4287.0 Spcs3 3437.9 4388.9 6176.8 Ssr1 6126.6 7679.3 9706.0 Gorasp2 3803.8 5390.7 7243.3

Null module GEO Series "GSE3313" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE3313 Status: Public on Jun 30 2014 Title: Impaired revascularization in a mouse model of diabetes associated with dysregulation of angiogenic-regulatory network. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 15920034 Summary & Design: Summary: Diabetes is a risk factor for the development of cardiovascular diseases that are associated with impaired angiogenesis or increased endothelial cell apoptosis. Here is it shown that angiogenic repair of ischemic hind limbs was impaired in Lepr db/db mice, a leptin receptor deficient model of diabetes, compared to wild-type C57BL/6 (WT) mice as evaluated by laser Doppler flow and capillary density analyses. To identify molecular targets associated with this disease process, hind limb cDNA expression profiles were created from adductor muscle of Lepr db/db and WT mice before and after hind limb ischemia using Affymetrix GeneChipÂ® Mouse Expression Set microarrays. The expression patterns of numerous angiogenesis related proteins were altered in Lepr db/db versus WT mice following ischemic injury. These transcripts included neuropilin-1, VEGF-A, placental growth factor, elastin and matrix metalloproteinases that are implicated in blood vessel growth and maintenance of vessel wall integrity. These data illustrate that impaired ischemia-induced neovascularization in type 2 diabetes is associated with the dysregulation of a complex angiogenesis-regulatory network.

Keywords: Diabetes, ischemia, angiogenesis, microarrays

Overall design: Gene expression data for adductor muscle in the ischemic limb from wild type mice and Lepr db/db mice of 4 time points (before hind limb ischemia, 1 day, 7 days and 14 days after hind limb ischemia surgery). Three independent experimental replicates of each condition for each time point.

Background corr dist: KL-Divergence = 0.1724, L1-Distance = 0.0358, L2-Distance = 0.0026, Normal std = 0.3616

1.106 Kernel fit Pairwise Correlations Normal fit

Density 0.553

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WT1_hindlimb_d0_rep1WT2_hindlimb_d0_rep2WT3_hindlimb_d0_rep3WT4_hindlimb_d1_rep1 (0.0242986)WT5_hindlimb_d1_rep2 (0.0141429)WT6_hindlimb_d1_rep3 (0.0383006)WT7_hindlimb_d7_rep1 (0.0609109)WT8_hindlimb_d7_rep2 (0.0680806)WT9_hindlimb_d7_rep3 (0.0366115)WT10_hindlimb_d14_rep1 (0.0183701)WT11_hindlimb_d14_rep2 (0.0268887)WT12_hindlimb_d14_rep3 (0.0168467)LEPRDB/DB1_hindlimb_d0_rep1 (0.035687)LEPRDB/DB2_hindlimb_d0_rep2 (0.0227424)LEPRDB/DB3_hindlimb_d0_rep3 (0.0118194)LEPRDB/DB4_hindlimb_d1_rep1LEPRDB/DB5_hindlimb_d1_rep2 (0.00798851)LEPRDB/DB6_hindlimb_d1_rep3 (0.0109352)LEPRDB/DB7_hindlimb_d7_rep1 (0.0200078)LEPRDB/DB8_hindlimb_d7_rep2 (0.0680513)LEPRDB/DB9_hindlimb_d7_rep3 (0.124966)LEPRDB/DB10_hindlimb_d14_rep1 (0.0628551)LEPRDB/DB11_hindlimb_d14_rep2 (0.0381533)LEPRDB/DB12_hindlimb_d14_rep3 (0.05638) (0.0446931) (0.088783) (0.0320765)[ min (0.0704108) ] [ medium ] [ max ] CEM 1 Srp9 1725.5 3095.0 4331.9 P ( S | Z, I ) = 0.93 Srp19 2001.1 3261.2 5163.1 Mean Corr = 0.44800 Srp68 2166.4 4430.9 5570.5 Srp72 1238.1 1869.8 2400.3 Srp54b 54.8 119.8 230.4 Spcs2 997.0 2129.8 3378.9 Sec23b 415.9 939.3 1821.7 Lrrc59 1513.5 2233.7 6647.1 Hdlbp 3252.1 4264.0 6384.5 Sec11a 1622.5 2906.5 5515.2 CEM 1 + Ssr3 4934.2 7286.8 9764.5 Top 10 Genes Tmem39a 260.2 631.8 1527.1 Spcs3 944.5 1651.6 5275.4 Ssr1 646.5 2498.4 4761.8 Gorasp2 2200.1 4143.3 7445.4

Null module GEO Series "GSE25140" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25140 Status: Public on Nov 05 2010 Title: Prostate specific Pten deletion, Pten-Smad4 deletion, and Pten-p53 deletion Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21289624 Summary & Design: Summary: We used microarrays to detail the global gene expression and identified differentially expressed gene list between wild-type anterior prostates and Ptenpc-/- anterior prostates, Ptenpc-/-Smad4pc-/- and Ptenpc-/- anterior prostates, Ptenpc-/-p53pc-/- and Ptenpc-/- anterior prostates at 15 weeks of age.

Overall design: Prostate-specific Pten deletion (Ptenpc-/-) results in prostate intraepithelial neoplasia (PIN) which, following a long latency, can progress to high-grade adenocarcinoma, albeit with minimally invasive and metastatic features. To understand this feeble progression phenotype, we conducted transcriptome comparison of five Ptenpc-/- PIN relative to three wild-type anterior prostate. Moreover, Ptenpc-/-Smad4pc-/- progress to metastasis, while Ptenpc-/-p53pc-/- not progress to metastasis. To understand this phenotype difference, we conducted transcriptome comparison of five Ptenpc-/-Smad4pc-/-to five Ptenpc-/- prostate tumor, and three Ptenpc-/-p53pc-/- to five Ptenpc-/- tumor.

Background corr dist: KL-Divergence = 0.1614, L1-Distance = 0.0335, L2-Distance = 0.0022, Normal std = 0.3647

1.094 Kernel fit Pairwise Correlations Normal fit

Density 0.547

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

wild-typewild-type anteriorwild-type anterior prostateProstate-specific anterior prostate Q6515APProstate-specific prostate Q6516AP (0.227545)Prostate-specific Pten Q6424AP_redo (0.095002) Prostate-specificdeletion Pten Prostate-specificdeletion anterior Pten (0.168165) Prostate-specificdeletion anterior prostatePten Prostate-specificdeletion anterior prostatePten tumor Prostate-specificdeletion anterior prostatePtenM5852 tumor Prostate-specificand anterior prostatePten(0.0164768)M5853 tumor Smad4 Prostate-specificand prostatePten(0.0257828)M6167 tumor Smad4deletion Prostate-specificand Pten(0.0278971)M7802 tumor Smad4deletion anterior Prostate-specificand Pten(0.0396142)M7805 Smad4deletion anterior prostate Prostate-specificand Pten(0.0668265) Smad4deletion anterior prostate andtumor Pten p53deletion anterior prostate A6291 and tumordeletion Pten p53 anterior (0.0219465) prostate A6295 and tumordeletion anterior p53 (0.0282533) prostateA6296[ tumordeletion anteriormin prostate (0.0421477) A5755 tumor anterior prostate ]tumor (0.0870229) A7907 prostate11452A0 tumor (0.034716)[ 11526A0-REDO tumor medium(0.032646) 11527A0-REDO (0.0324463) ] (0.0535119)[ max ] CEM 1 Srp9 1381.3 1853.7 3905.4 P ( S | Z, I ) = 0.92 Srp19 2159.0 2734.6 4662.7 Mean Corr = 0.43416 Srp68 1588.2 2632.5 9075.7 Srp72 2619.7 3631.3 5515.2 Srp54b 13.2 115.8 344.2 Spcs2 3442.9 4835.6 8186.7 Sec23b 2501.0 3483.8 4592.5 Lrrc59 2534.0 4049.6 5804.4 Hdlbp 3110.8 6124.9 19697.3 Sec11a 3658.9 4743.1 8693.7 CEM 1 + Ssr3 3888.6 4982.0 10660.5 Top 10 Genes Tmem39a 556.2 889.0 2549.9 Spcs3 1779.3 2262.1 6865.8 Ssr1 2858.6 3797.1 4707.0 Gorasp2 2267.9 3808.8 6778.8

Null module GEO Series "GSE18135" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18135 Status: Public on Jan 15 2010 Title: Gene Expression Profile of Androgen Modulated Genes in the Murine Fetal Developing Lung Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20064212 Summary & Design: Summary: Accumulating evidences suggest that sex affects lung development. During the fetal period, male lung maturation is delayed compared with female and surfactant production appears earlier in female than in male fetal lungs.

We analyzed by microarrays the expression of genes showing a sexual difference and those modulated by endogenous androgens (flutamide).

Overall design: Following flutamide or vehicle administration to pregnant mothers, fetal mouse lungs were studied at gestational day 17 (GD17) and GD18. RNA was extracted and hybridized on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0822, L1-Distance = 0.0567, L2-Distance = 0.0049, Normal std = 0.5081

0.862 Kernel fit Pairwise Correlations Normal fit

Density 0.431

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

FlutamideFlutamide treatedFlutamide treatedmaleVehicule at treatedmaleGD 17,Vehicule at (control) malebiologicalGD 17,Vehicule at (control) biologicalfemaleGD rep1 17,Vehicule (control) at biologicalfemale(0.0131393) GD rep2Vehicule (control)17, at female(0.00636583) biologicalGD rep3Vehicule (control)17, at male(0.0291167) biologicalGDFlutamide rep1 at(control)17, maleGD biological(0.0789824) Flutamide17, rep2at treated malebiologicalGD (0.129076) Flutamide17, rep3at treated malebiologicalGD (0.080263)rep1 Vehicule17, at treatedmaleGD biological(0.0743207) rep2 18,Vehicule at (control) malebiologicalGD (0.0220712) rep3 18,Vehicule at (control) biologicalfemaleGD (0.0340866) rep1 18,Vehicule (control) at biologicalfemale(0.0991815) GD rep2Vehicule (control)18, at female(0.0669449) biologicalGD rep3Vehicule (control)18, at male(0.0972352) biologicalGD rep1 at(control)18, maleGD biological(0.0967921) 18, rep2at malebiologicalGD (0.029257) 18, rep3at biologicalGD (0.0367447)rep1 [18, min biological(0.0276046) rep2 (0.0256374)] rep3 (0.0531805)[ medium ] [ max ] CEM 1 Srp9 1282.7 1750.8 2061.6 P ( S | Z, I ) = 0.91 Srp19 2636.0 3428.6 3875.1 Mean Corr = 0.61883 Srp68 1962.6 2372.4 2635.2 Srp72 2337.1 2592.7 2893.6 Srp54b 102.4 173.1 219.0 Spcs2 4642.8 5453.4 6016.4 Sec23b 1769.8 2176.1 2400.1 Lrrc59 2138.6 3937.6 4835.7 Hdlbp 2133.1 2238.4 2426.9 Sec11a 3585.8 4230.8 4673.9 CEM 1 + Ssr3 6061.8 6602.0 7224.0 Top 10 Genes Tmem39a 877.9 1108.3 1262.7 Spcs3 1944.5 2510.5 2952.6 Ssr1 5247.7 6681.5 7303.8 Gorasp2 2315.8 2990.9 3374.1

Null module GEO Series "GSE34423" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 40 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE34423 Status: Public on Dec 14 2011 Title: Phenobarbital mediates an epigenetic switch at the constitutive androstane receptor (CAR) target gene Cyp2b10 in the liver of B6C3F1 mice [Expression array]. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21455306 Summary & Design: Summary: Evidence suggests that epigenetic perturbations are involved in the adverse effects associated with some drugs and toxicants, including certain classes of non-genotoxic carcinogens. Such epigenetic changes (altered DNA methylation and covalent histone modifications) may take place at the earliest stages of carcinogenesis and their identification holds great promise for biomedical research. Here, we evaluate the sensitivity and specificity of genome-wide epigenomic and transcriptomic profiling in phenobarbital (PB)-treated B6C3F1 mice, a well-characterized rodent model of non-genotoxic liver carcinogenesis. Methylated DNA Immunoprecipitation (MeDIP)-coupled microarray profiling of 17,967 promoter regions and 4,566 intergenic CpG islands was combined with genome-wide mRNA expression profiling to identify liver tissue-specific PB-mediated DNA methylation and transcriptional alterations. Only a limited number of significant anti-correlations were observed between PB-induced transcriptional and promoter-based DNA methylation perturbations. However, the constitutive androstane receptor (CAR) target gene Cyp2b10 was found to be concomitantly hypomethylated and transcriptionally activated in a liver tissue-specific manner following PB treatment. Furthermore, analysis of active and repressive histone modifications using chromatin immunoprecipitation revealed a strong PB-mediated epigenetic switch at the Cyp2b10 promoter. Our data reveal that PB-induced transcriptional perturbations are not generally associated with broad changes in the DNA methylation status at proximal promoters and suggest that the drug-inducible CAR pathway regulates an epigenetic switch from repressive to active chromatin at the target gene Cyp2b10. This study demonstrates the utility of integrated epigenomic and transcriptomic profiling for elucidating early mechanisms and biomarkers of non-genotoxic carcinogenesis.

Overall design: 2932 days old male B6C3F1/Crl (C57BL/6 x C3H/He ) mice were obtained from Charles River Laboratories (Germany). Animals were allowed to acclimatise for 5 days prior to being randomly divided into two treatment groups (n = 10) and phenobarbital (Sigma 04710, 0.05% (w/v) in drinking water) was administered to one group through ad libitum access to drinking water for 28 days. Mice were checked daily for activity and behavior and sacrificed on the last day of dosing (day 28). Blood was withdrawn for PK analysis and target (liver) and non-target (kidney) tissues removed, split into several sections, frozen in liquid nitrogen and stored at 80´C for subsequent analyses. Total RNA from liver and kidney was purified and processed for Affymetrix gene expression profiling while genomic DNA was prepared for promoter array based methylome analysis using the Methylated DNA immunoprecipitation (MeDIP) procedure. Remaining tissue material was used for chromatin immunoprecipitation (ChIP) to analyze histone modifications at individual promoters. Plasma samples were also collected to evaluate phenobarbital exposure in individual animals by LC-MS.

Background corr dist: KL-Divergence = 0.0734, L1-Distance = 0.0729, L2-Distance = 0.0087, Normal std = 0.5583

0.829 Kernel fit Pairwise Correlations Normal fit

Density 0.415

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

PB_Kidney_Control_5PB_Kidney_Control_1PB_Kidney_Control_9 PB_Kidney_Control_4(0.0269884) PB_Kidney_Control_10(0.0300365) PB_Kidney_Control_8(0.0222973) PB_Kidney_Control_3(0.0255115)PB_Kidney_Control_7 (0.0134516) PB_Kidney_Control_2(0.0271706) PB_Kidney_Control_6(0.0301829) PB_Liver_Control_10(0.0224313) PB_Liver_Control_9(0.00994237) PB_Liver_Control_2(0.0270398) (0.0351756)PB_Liver_Control_3 (0.0382709)PB_Liver_Control_6 (0.0818686)PB_Liver_Control_5 (0.0512451)PB_Liver_Control_4 (0.0177604)PB_Liver_Control_8 (0.0121834)PB_Liver_Control_1 (0.0277083)PB_Liver_Control_7 (0.0286489)PB_Kidney_treated_20 (0.0273177)PB_Kidney_treated_18 (0.00383636)PB_Kidney_treated_12PB_Kidney_treated_11 (0.0311328)PB_Kidney_treated_17 (0.0189041)PB_Kidney_treated_16 (0.0251282)PB_Kidney_treated_14 (0.033283)PB_Kidney_treated_15 (0.021026)PB_Kidney_treated_13 (0.0259356)PB_Kidney_treated_19 (0.00688275)PB_Liver_treated_12 (0.014949)PB_Liver_treated_13 (0.0129383)PB_Liver_treated_14 (0.0228391) (0.0134833)PB_Liver_treated_15 (0.022308)PB_Liver_treated_11 (0.0334739)PB_Liver_treated_16 (0.0323729)PB_Liver_treated_18 (0.0147923)PB_Liver_treated_19 (0.0418254)PB_Liver_treated_20 (0.0233317)PB_Liver_treated_17 (0.0235313) (0.0164545) (0.00634036)[ min ] [ medium ] [ max ] CEM 1 Srp9 1265.3 2528.3 3422.9 P ( S | Z, I ) = 0.92 Srp19 2161.3 2637.3 4023.6 Mean Corr = 0.42000 Srp68 1642.1 2104.7 2738.6 Srp72 1717.0 3063.2 3693.1 Srp54b 13.8 96.3 148.0 Spcs2 1753.5 4876.3 6502.8 Sec23b 3051.4 3770.1 5121.4 Lrrc59 1345.3 3015.1 5886.4 Hdlbp 2617.5 5339.5 6921.3 Sec11a 5341.9 6136.2 10177.6 CEM 1 + Ssr3 4688.6 7833.7 9657.5 Top 10 Genes Tmem39a 146.7 428.8 1010.5 Spcs3 1692.6 2937.1 3693.1 Ssr1 3203.8 4766.6 7069.3 Gorasp2 2142.5 3612.3 5801.9

Null module GEO Series "GSE44356" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44356 Status: Public on Aug 24 2013 Title: Expression data from wild-type and HMGN1 knockout mice injected with N-nitrosodiethylamine Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24296759 Summary & Design: Summary: HMGN1 contributes to the shortened latency of liver tumorigenesis by changing a chromatin structure and expression of relevant genes

To assess the molecular mechanisms underlying accelerated tumor development in Hmgn1-/- mice, we performed the gene expression profiling of liver cells at early stages

Overall design: Expression profiles has been compared between Hmgn1+/+ and Hmgn1-/- mice livers at 4 weeks after birth and at 12 weeks after DEN or saline (control) injection at 4 weeks

Background corr dist: KL-Divergence = 0.2569, L1-Distance = 0.0562, L2-Distance = 0.0079, Normal std = 0.2990

1.334 Kernel fit Pairwise Correlations Normal fit

Density 0.667

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WildtypeWildtype liver non-injectedWildtype liver non-injectedKnockout liver 4weeks non-injectedKnockout liver 4weeks rep1 Knockoutnon-injected liver(0.0261828) 4weeks rep2 Wildtypenon-injected liver(0.0403064) rep34weeks Wildtypenon-injected liver (0.0474275) 4weeks rep1DEN-injectedWildtype liver (0.0999891) 4weeks rep2DEN-injectedKnockout liver (0.0170897) 12weeks rep3DEN-injectedKnockout liver (0.02994) 12weeks repl1KnockoutDEN-injected liver (0.0335173)12weeks repl2WildtypeDEN-injected liver (0.212237) 12weeks repl3WildtypeDEN-injected liver_saline-injected (0.0893092) 12weeksWildtype repl1 liver_saline-injected (0.0242)12weeksKnockout repl2 liver_saline-injected (0.0368634) Knockout12weeks repl3 liver_saline-injected (0.0418465) Knockout12weeks repl1 liver_saline-injected (0.0330704)12weeks repl2 liver_saline-injected (0.0223386) 12weeks repl3 (0.0154701) 12weeks repl1[ (0.0265316)12weeks minrepl2 (0.113746) repl3 ] (0.0899346)[ medium ] [ max ] CEM 1 Srp9 2360.0 2801.3 3594.9 P ( S | Z, I ) = 0.92 Srp19 2060.2 2732.4 3414.6 Mean Corr = 0.38187 Srp68 1419.2 1708.9 2159.7 Srp72 3350.2 3777.3 4540.3 Srp54b 52.6 119.3 177.5 Spcs2 3826.1 5176.2 6003.7 Sec23b 1838.8 2804.4 4207.4 Lrrc59 2035.3 2573.7 3545.5 Hdlbp 3806.8 4287.8 5373.9 Sec11a 4355.8 4970.4 5629.7 CEM 1 + Ssr3 8162.8 9960.3 12771.8 Top 10 Genes Tmem39a 213.6 364.9 528.9 Spcs3 2372.0 2903.7 3231.3 Ssr1 3943.9 5240.2 6168.0 Gorasp2 2391.1 2872.2 3463.2

Null module GEO Series "GSE16691" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE16691 Status: Public on Oct 01 2009 Title: Transcriptional regulation by Norrin-Frizzled4 signaling in the embryonic yolk sac Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19837032 Summary & Design: Summary: Transcriptional profiles of the embryonic yolk sac from embryos with ectopic Norrin expression were compared to their wild type littermate controls. The goal is to identify the transcriptional response to Norrin-Frizzled 4 signaling during embryonic angiogenesis.

Overall design: Ectopic Norrin expression was achieved using a conditional over-expression strategy. Yolk sacs from 3-5 embryos were pooled for each sample and 3 replicates of both control and experimental groups were analyzed.

Background corr dist: KL-Divergence = 0.0423, L1-Distance = 0.0287, L2-Distance = 0.0014, Normal std = 0.5865

0.680 Kernel fit Pairwise Correlations Normal fit

Density 0.340

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

wild typewild mouse typewild yolkmouse type sacZ/Norrin yolkmouse E8.5 sacZ/Norrin replicatemouse yolk E8.5 sacZ/Norrin replicateyolkmouse 1 E8.5 (0.0216901) sacwild replicateyolkmouse E8.52 (0.0879119)type sac wildreplicate yolk mouseE8.53 (0.0343299)type sac wildreplicate 1yolk mouseE8.5 (0.0485384) type sac Z/Norrinreplicate 2yolkmouse E10.5(0.334138) sacZ/Norrin mouse 3yolkreplicate E10.5(0.0549043) sacZ/Norrin yolkmouse replicate E10.51 (0.0256009)sac yolkmouse replicateE10.5 2 (0.0908939)sac yolkreplicate E10.5 3 (0.0872912)sac replicate E10.51 (0.0277779)[ replicate min2 (0.107558) 3 ](0.0793653) [ medium ] [ max ] CEM 1 Srp9 1435.7 2113.9 2658.6 P ( S | Z, I ) = 0.86 Srp19 2573.0 4165.7 6466.1 Mean Corr = 0.67565 Srp68 2276.4 3015.3 3371.6 Srp72 2657.5 3077.3 3619.1 Srp54b 63.5 71.6 111.2 Spcs2 4845.9 5690.3 6305.6 Sec23b 2303.3 3379.0 3945.3 Lrrc59 4468.5 7334.7 9074.3 Hdlbp 3123.8 3940.0 5495.1 Sec11a 4473.4 5534.0 7053.9 CEM 1 + Ssr3 6955.4 9131.3 10983.7 Top 10 Genes Tmem39a 1414.9 2073.5 2576.6 Spcs3 1901.1 3153.4 4354.2 Ssr1 6361.1 7756.0 9964.6 Gorasp2 3743.9 4731.0 5548.4

Null module GEO Series "GSE27019" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27019 Status: Public on Aug 01 2012 Title: Role of transcriptional regulators IFRD1 and IFRD2 in intestinal lipid absorption and obesity Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Because of the epidemic rise of obesity worldwide, the identification of novel target genes for pharmacological treatment of obesity and related disorders is becoming of high importance. IFRD1 and IFRD2 are members of a novel transcriptional regulators family. Intestinal over-expression of mouse homologue of IFRD1 promoted intestinal triglyceride uptake and induced whole body adiposity in mice. To further elucidate the role of IFRD1 and IFRD2 in vivo, we generated mice lacking both mouse homologues of IFRD1 (TIS7) and IFRD2 (SKMc15) genes. Here, we report that mice deficient in TIS7 and SKMc15 genes, despite normal calorie intake had severely reduced amount of adipose tissue, were resistant to diet-induced obesity and displayed high glucose tolerance. Lower dietary fat entry into the circulation suggested that this phenotype resulted from impaired intestinal lipid transport. We identified down-regulation of CD36, a fatty acid transporter, both on RNA and protein levels. Reporter assays indicated that TIS7 and SKMc15 transcriptionally regulated CD36 expression and CD36 overexpression partially restored fatty acid uptake in vitro. Hence, our study suggested that TIS7 and SKMc15 play an important role in the regulation of the lipid metabolism and might represent a novel strategy for treatment of disorders caused by excess fat intake.

To determine whether decreased intestinal lipid absorption might be caused by changes in expression of lipid processing and transport molecules, we performed Affymetrix microarray analyses of total RNA samples isolated from the jejunum of HFD-fed WT type and dKO animals. The moderated t-test was used to calculate p-values for significance of differential gene expression between 3 dKO and 3 wild type mice. These raw p-values were adjusted for multiple hypothesis testing using the method from Benjamini and Hochberg for a strong control of the false discovery rate (FDR) and genes with thus adjusted p-values < 0.05 were considered significant.

Overall design: Age-matched (7-10 week old) male wild type and TIS7 (Ifrd1) SKMc15 (Ifrd2) double knock out mice (C57Bl6 background) were caged individually and maintained from 3 weeks up to 8 weeks on a synthetic high saturated fat (HFD) diet (Ssniff). Small intestines (jejunum) were harvested for total RNA isolation. RNAs from 3 WT and 3 dKO mice were subjected to Affymetrix based whole genome gene expression analysis (Mouse 430.2 GeneChip).

Background corr dist: KL-Divergence = 0.0401, L1-Distance = 0.0172, L2-Distance = 0.0003, Normal std = 0.6130

0.656 Kernel fit Pairwise Correlations Normal fit

Density 0.328

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

HFD fedHFD wild fed typeHFD wild mouse fed typeHFD wild 1mouse fed(0.152134) typeHFD TIS7 3mouse fed(0.123084) SKMc15HFD TIS7 4 fed(0.209311) SKMc15 double TIS7 SKMc15 doubleknock out doubleknock mouse out [knock min1mouse (0.100162) out 2mouse ](0.15242) 3 (0.26289)[ medium ] [ max ] CEM 1 Srp9 1690.3 2129.0 2327.9 P ( S | Z, I ) = 0.85 Srp19 1874.8 2278.8 2473.1 Mean Corr = 0.62084 Srp68 2568.9 2904.3 3614.2 Srp72 1150.8 1397.7 1728.5 Srp54b 59.9 89.6 104.7 Spcs2 3499.0 4414.0 4542.8 Sec23b 3236.4 3727.6 4459.6 Lrrc59 8023.8 9250.6 10457.4 Hdlbp 4432.9 4630.7 5306.0 Sec11a 3594.0 3697.0 4328.5 CEM 1 + Ssr3 6151.0 7229.5 7487.0 Top 10 Genes Tmem39a 184.3 276.6 287.6 Spcs3 3117.7 3427.9 4095.2 Ssr1 4283.2 5699.8 6418.8 Gorasp2 6150.0 6857.5 7683.9

Null module GEO Series "GSE29241" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29241 Status: Public on Nov 13 2011 Title: Dendritic cell lineage commitment is instructed by distinct cytokine signals Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22078373 Summary & Design: Summary: Dendritic cells (DC) develop from hematopoietic stem cells, which is guided by instructive signals through cytokines. DC development progresses from multipotent progenitors (MPP) via common DC progenitors (CDP) into DC. Flt3 ligand (Flt3L) signaling via the Flt3/Stat3 pathway is of pivotal importance for DC development under steady state conditions. Additional factors produced during steady state or inflammation, such as TGF-beta1 or GM-CSF, also influence the differentiation potential of MPP and CDP. Here, we studied how gp130, GM-CSF and TGF-beta1 signaling influence DC lineage commitment from MPP to CDP and further into DC. We observed that activation of gp130 signaling promotes expansion of MPP. Additionally, gp130 signaling inhibited Flt3L-driven DC differentiation, but had little effect on GM-CSF-driven DC development. The inflammatory cytokine GM-CSF induces differentiation of MPP into inflammatory DC and blocks steady state DC development. Global transcriptome analysis revealed a GM-CSF-driven gene expression repertoire that primes MPP for differentiation into inflammatory DC. Finally, TGF-beta1 induces expression of DC-lineage affiliated genes in MPP, including Flt3, Irf-4 and Irf-8. Under inflammatory conditions, however, the effect of TGF- beta1 is altered: Flt3 is not upregulated, indicating that an inflammatory environment inhibits steady state DC development. Altogether, our data indicate that distinct cytokine signals produced during steady state or inflammation have a different outcome on DC lineage commitment and differentiation.

Overall design: - GM-TNFa-DC_2

Background corr dist: KL-Divergence = 0.0220, L1-Distance = 0.0160, L2-Distance = 0.0003, Normal std = 0.7247

0.550 Kernel fit Pairwise Correlations Normal fit

Density 0.275

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

MultipotentMultipotent progenitorDendritic progenitorDendritic sample cell sampleDendritic sample1 cell (GM-MPP_1) sample1Dendritic (GM-DC_1)2 cell (GM-MPP_2) plus2 (0.326968)(GM-DC_2) cell TNFa (0.0799547) plus (0.141415) sample TNFa (0.102331) sample1 (GM-TNFa-DC_1)[ 2min (GM-TNFa-DC_2) ] (0.231376) (0.117956)[ medium ] [ max ] CEM 1 Srp9 1415.1 2080.9 2358.8 P ( S | Z, I ) = 0.85 Srp19 2030.7 2897.1 4033.0 Mean Corr = 0.51391 Srp68 1994.7 2270.5 4398.0 Srp72 2290.9 2367.0 2548.2 Srp54b 84.6 102.8 265.0 Spcs2 5323.2 7715.0 9016.8 Sec23b 1525.6 1923.9 2884.3 Lrrc59 2373.8 3013.0 7331.1 Hdlbp 2235.8 2633.7 3421.8 Sec11a 4785.4 5514.5 8119.5 CEM 1 + Ssr3 3624.5 4939.0 5832.2 Top 10 Genes Tmem39a 483.9 1087.6 2417.6 Spcs3 2709.0 3435.6 4272.8 Ssr1 3268.8 3438.0 3954.1 Gorasp2 2146.9 2821.6 3577.0

Null module GEO Series "GSE9954" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 70 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9954 Status: Public on Dec 20 2007 Title: Large-scale analysis of the mouse transcriptome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18365009 Summary & Design: Summary: We used microarrays to compare gene expression across different murine tissues.

Keywords: Other

Overall design: Different tissues were dissected from 10-12 week old C57Bl6 mice for RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.3484, L1-Distance = 0.0923, L2-Distance = 0.0272, Normal std = 0.2989

1.449 Kernel fit Pairwise Correlations Normal fit

Density 0.724

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Mouse diaphragm,Mouse diaphragm,Mouse biological diaphragm,Mouse biological spleen,replicateMouse biological spleen,replicateMousebiological 1 (0.00887567) spleen,replicateMousebiological 2 replicate(0.00479781) muscle,Mousebiological 3 replicate(0.007511) 1 (0.0112675)muscle,Mouse biological replicate 2 (0.00263593)muscle,Mouse biological replicate 3 (0.00738332)muscle,Mouse biological replicate 1 liver,(0.00391507)Mouse biological replicate biological2 liver,(0.00389255)Mouse replicate biological3 liver,(0.00578668)Mouse replicate biological4 brain,(0.00498264)Mouse replicate 1 (0.0090027) biological brain,Mouse replicate 2 (0.00637038) biological brain,Mouse replicate 3 (0.00352075) biological lung,Mouse replicate 1 (0.0111505)biological lung,Mouse replicate 2 (0.00750103)biological lung,Mouse replicate 3 (0.0154169)biological kidney,Mouse replicate 1 (0.0140801) kidney,Mousebiological replicate 2 (0.0120581) kidney,Mousebiological 3replicate (0.0115772) adrenalMousebiological replicate 1 (0.00782919)adrenal Mousegland, replicate 2 (0.0106167)biologicaladrenal Mousegland, 3 (0.00886463)biologicalbone Mousegland, replicate marrow, biologicalboneMouse replicate 1 marrow, (0.00678367) biologicalboneMouse replicate 2 marrow, (0.00745953) biologicalboneMouse replicate 3 marrow, (0.00114889) biologicaladiposeMouse replicate 1 (0.00572722) biologicaladiposeMouse tissue, replicate 2 (0.00652239) adiposeMouse biologicaltissue, replicate 3 (0.00371036) pituitaryMouse biologicaltissue, replicate4 (0.00521435) pituitaryMouse biologicalgland, replicate 1 (0.0160058)pituitaryMouse biological gland, replicate 2 (0.011565)pituitaryMouse biological gland, replicate 3 (0.0158771)pituitaryMouse biological gland, replicate 1 (0.0161862)salivaryMouse biological gland, replicate 2 (0.0247307)salivaryMouse biologicalgland, replicate 3 (0.0218876)salivaryMousebiological gland, replicate 4 (0.0208002)seminalMousebiological gland, replicate 5 (0.0297415)seminalMousebiological vesicle, replicate 1 (0.0591052) seminalMouse vesicle, biological replicate 2 (0.0867085) thymus,Mouse vesicle, biological replicate3 (0.0824165) thymus,Mouse biologicalbiological replicate 1 thymus,Mouse (0.0674475)biological replicatereplicate 2 testis,Mouse (0.0549303)biological replicate 13biological testis,Mouse (0.00671904)(0.0578022) replicate 2 biological testis,Mouse(0.0070872) replicate 3 biological heart,Mouse(0.00548846) replicate 1 (0.0140245)biological heart,Mouse replicate 2 (0.00770941)biological heart,Mouse replicate 3 (0.00764422)biological smallMouse replicate 1 (0.0128137)intestine, smallMouse replicate 2 (0.0136814)intestine, smallMouse biological 3 (0.0128965)intestine, eye,Mouse biological replicate biological eye,Mouse biological replicate biological 1 (0.00627335)eye,Mousereplicate replicate biological 2 (0.00965315)ESMousereplicate 1 cells,(0.00838339) 3 (0.0179719)ESMousereplicate biological2 cells,(0.0096936) ESMouse biological3 cells,(0.00835713) replicate placenta,Mouse biological replicate 1 placenta,Mouse (0.00907223) biological replicate 2 placenta,Mouse (0.0142413) biological replicate 3 ovary,Mouse (0.012975) biological replicate biological 1ovary,Mouse (0.00218907) replicate biological 2ovary,Mouse (0.00402613) replicate biological 3fetus,Mouse (0.00179254) replicate 1 (0.0070759)biological fetus,Mouse replicate 2 (0.00566756)biological fetus, replicate 3 (0.005539)biological replicate 1 (0.00552766) replicate 2 (0.000843065)[ min3 (0.00184666) ] [ medium ] [ max ] CEM 1 Srp9 875.7 1620.7 3034.3 P ( S | Z, I ) = 0.84 Srp19 1245.4 2270.0 3818.7 Mean Corr = 0.52073 Srp68 932.5 1539.9 4131.8 Srp72 914.1 1503.1 3005.9 Srp54b 169.3 258.9 465.2 Spcs2 900.1 3461.6 14883.6 Sec23b 513.9 1653.9 6479.1 Lrrc59 774.5 1766.3 5147.3 Hdlbp 809.8 1695.3 9459.2 Sec11a 1360.5 3193.3 5968.8 CEM 1 + Ssr3 790.8 3487.9 15663.5 Top 10 Genes Tmem39a 315.6 695.6 2406.0 Spcs3 658.7 1554.1 9190.5 Ssr1 743.5 2611.6 7530.0 Gorasp2 1075.3 2328.5 11023.2

Null module GEO Series "GSE20391" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 11 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20391 Status: Public on Jun 16 2010 Title: Comprehensive expression profiling across primary fetal liver terminal erythroid differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20231426 Summary & Design: Summary: Primary murine fetal liver cells were freshly isolated from day e14.5 livers and then sorted for successive differentiation stages by Ter119 and CD71 surface expression (ranging from double-negative CFU-Es to Ter-119 positive enucleated erythrocytes) [Zhang, et al. Blood. 2003 Dec 1; 102(12):3938-46]. RNA isolated from each freshly isolated, stage-sorted population was reverse-transcribed, labelled, and then hybridized onto 3' oligo Affymetrix arrays. Important erythroid specific genes as well as the proteins that regulate them were elucidated through this profiling based on coexpression and differential expression patterns as well as by extracting specific GO categories of genes (such as DNA-binding proteins).

Overall design: Gene-targeting experiments report that the homeodomain-interacting protein kinases 1 and 2, Hipk1 and Hipk2, are essential but redundant in hematopoietic developmentbecause Hipk1/Hipk2 double-deficient animals exhibit severe defects in hematopoiesis and vasculogenesis while the single knockouts do not. These serine-threonine kinases phosphorylate, and consequently modify the functions of, several important hematopoietic transcription factors and cofactors. Here we show that Hipk2 knockdown alone plays a significant role in terminal fetal liver erythroid differentiation. Hipk1 and Hipk2 are highly induced during primary mouse fetal liver erythropoiesis. Specific knockdown of Hipk2 inhibits terminal erythroid cell proliferationexplained in part by impaired cell cycle progression as well as increased apoptosisand terminal enucleation as well as the accumulation of hemoglobin. Hipk2 knockdown also reduces the transcription of many genes involved in proliferation and apoptosis as well as important, erythroid-specific genes involved in hemoglobin biosynthesissuch as alpha-globin and mitoferrin 1demonstrating that Hipk2 plays an important role in some but not all aspects of normal terminal erythroid differentiation.

Background corr dist: KL-Divergence = 0.0629, L1-Distance = 0.0458, L2-Distance = 0.0040, Normal std = 0.5380

0.745 Kernel fit Pairwise Correlations Normal fit

Density 0.373

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

sorted-R1sorted-R2 cells,sorted-R3 repl cells, 1 sorted-R5(0.094603) repl cells, 1 sorted-R1(0.135096) repl cells, 1 sorted-R2(0.0285524) repl cells, 1 sorted-R3(0.0420873) repl cells, 2 sorted-R4(0.058392) repl cells, 2 sorted-R5(0.0575497) repl cells, 2 sorted-R2(0.131055) repl cells, 1 sorted-R3(0.0458209) repl cells, 2 (0.241144) repl cells, 3 (0.118724) repl 3 (0.0469753)[ min ] [ medium ] [ max ] CEM 1 Srp9 687.3 1582.2 2667.7 P ( S | Z, I ) = 0.83 Srp19 1375.4 4539.1 6278.4 Mean Corr = 0.34729 Srp68 711.5 2528.2 4981.7 Srp72 1604.9 2488.8 3317.6 Srp54b 120.8 234.7 465.8 Spcs2 2208.7 5588.1 7882.6 Sec23b 1393.4 2792.2 3246.5 Lrrc59 1124.8 3634.0 7115.0 Hdlbp 1768.8 2335.5 3465.8 Sec11a 1947.8 5073.6 7337.4 CEM 1 + Ssr3 2639.7 3871.8 5972.9 Top 10 Genes Tmem39a 126.9 461.8 1218.9 Spcs3 1007.5 2967.1 6731.7 Ssr1 4331.1 7458.2 8991.3 Gorasp2 707.5 1516.4 2977.2

Null module GEO Series "GSE31086" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31086 Status: Public on Feb 08 2012 Title: Expression data from Bmi1-null common myeloid progenitor (CMP) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22351929 Summary & Design: Summary: Bmi1 is a component of polycomb repressive complex 1 and its role in the inheritance of the stemness of adult somatic stem cells has been well characterized. Bmi1 maintains the self-renewal capacity of adult stem cells, at least partially, by repressing the Ink4a/Arf locus that encodes a cyclin-dependent kinase inhibitor, p16Ink4a, and a tumor suppressor, p19Arf 14. Deletion of both Ink4a and Arf in Bmi1-deficient mice substantially restored the defective self-renewal capacity of HSCs and neural stem cells.

Overall design: Purified CMP from BM of recipient mice repopulated with wild-type, Ink4a-/-Arf-/-, and Bmi1-/- Ink4a-/-Arf-/- BM cells were subjected to RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0491, L1-Distance = 0.0270, L2-Distance = 0.0010, Normal std = 0.5869

0.712 Kernel fit Pairwise Correlations Normal fit

Density 0.356

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WT CMP1WT (0.0979624) CMP2DKO (0.15141) CMP1DKO (0.0554037) CMP2TKO (0.200359) CMP1TKO (0.247912) CMP2 (0.246953) [ min ] [ medium ] [ max ] CEM 1 Srp9 4080.6 4681.4 5025.9 P ( S | Z, I ) = 0.82 Srp19 1552.8 2036.7 2236.0 Mean Corr = 0.32591 Srp68 4053.3 4634.5 4766.1 Srp72 4164.9 4803.2 4938.7 Srp54b 278.8 582.2 694.7 Spcs2 6762.7 7242.0 8451.3 Sec23b 3447.3 3627.8 3813.0 Lrrc59 4341.2 5070.7 5409.3 Hdlbp 2317.2 2590.1 2823.6 Sec11a 7409.6 8054.2 8912.5 CEM 1 + Ssr3 7902.5 8935.1 9360.5 Top 10 Genes Tmem39a 487.5 633.3 866.6 Spcs3 7726.0 8968.5 9328.7 Ssr1 5705.8 6609.5 7522.5 Gorasp2 1961.3 2303.0 2446.7

Null module GEO Series "GSE17925" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17925 Status: Public on Sep 03 2009 Title: Gene expression from TCDD treated C57BL6/J and human Aryl hydrocarbon Receptor expressing primary mouse hepatocytes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20044593 Summary & Design: Summary: The human and mouse aryl hydrocarbon receptor (hAHR and mAHRb) share limited (58%) transactivation domain sequence identity. Compared to the mAHRb allele, the hAHR displays 10-fold lower relative affinity for prototypical ligands such as 2,3,7,8 tetrachlorodibenzo-p-dioxin (TCDD). However, in previous studies we have demonstrated that the hAHR can display a higher relative ligand binding affinity than the mAHRb for specific AHR ligands such as indirubin. Each receptor has also been shown to differentially recruit LXXLL co-activator-motif proteins and to utilize different TAD subdomains in gene transactivation. Using hepatocytes isolated from C57BL6/J mice (Ahrb/b) and AHRTtr transgenic mice which express hAHR protein specifically in hepatocytes, we investigated whether the hAHR and mAHRb differentially regulate genes. Microarray and quantitative-PCR analysis of Ahrb/b and AHRTtr primary-mouse hepatocytes treated with 10 nM TCDD revealed that a number of established AHR target genes such as Cyp1a1 and Cyp1b1 are significantly induced by both receptors. Remarkably, of the 1752 genes induced by mAHRb and 1186 genes induced by hAHR, only 265 genes (<10%) were significantly activated by both receptors in response to TCDD. Conversely of the 1100 and 779 genes significantly repressed in mAHRb and hAHR hepatocytes respectively, only 462 (<25%) genes were significantly repressed by both receptors in response to TCDD treatment. Genes identified as differentially expressed are known to be involved in a number of biological pathways, including cell proliferation and inflammatory response which suggests that compared to the mAHRb, the hAHR may play contrasting roles in TCDD-induced toxicity and endogenous AHR-mediated gene regulation.

Overall design: Isolated mouse hepatocytes from wild type and treated with 10nM TCDD for 6h were analyzed. 1 array per mouse (3 mice per treatment group) was used.GeneChipÂ® Operating Software (Affymetrix) was utilized to preprocess CAB/CEL files generated from the 12 scanned microarrays which represented hepatocytes isolated from one mouse each. Data quality was initially assessed by checking the array image, B2 oligo performance, average background to noise ratios, poly-A controls, hybridization controls and the 3' to 5' probe-set ratios for control genes (e.g. ˆ-actin or GAPDH). Microarray data was normalized using Probe Logarithmic Intensity Error Approximation PLIER-MM algorithm (Affymetrix Expression Console¢ Software 1.1). Normalized microarray data outputs from TCDD and control treated Ahrb/band AHRTtr hepatocytes were compared for differential expression using Significance Analysis of Microarrays (SAM, version 2.23A (Pan 2002; Tusher et al. 2001)) with 100 permutations, KNN-10.

Background corr dist: KL-Divergence = 0.1387, L1-Distance = 0.0308, L2-Distance = 0.0018, Normal std = 0.3861

1.033 Kernel fit Pairwise Correlations Normal fit

Density 0.517

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

hAHR-mousehAHR-mouse hepatocyteshAHR-mouse hepatocyteshAHR-mouse DMSO hepatocyteshAHR-mouse treatedDMSO hepatocyteshAHR-mouse treatedbiologicalDMSO hepatocytesC57BL6/J-mouse treatedbiological10nM hepatocytesrepC57BL6/J-mouse TCDD1 biological10nM (0.0358097) repC57BL6/J-mouse treated hepatocytes TCDD2 10nM (0.0384155) repC57BL6/J-mouse treatedbiological hepatocytes TCDD3 (0.034999)C57BL6/J-mouse DMSO treatedbiological hepatocytes replicate C57BL6/J-mouse treatedDMSO biological hepatocytes replicate 1 treatedbiological DMSO(0.0309814) hepatocytes replicate 2 treatedbiological 10nM(0.0489734) hepatocytesrep1 TCDD3 biological 10nM(0.0806801)(0.0900143) rep2 treated TCDD[ 10nM(0.140262) minrep3 treatedbiological TCDD (0.0638604) ] treatedbiological rep1 biological(0.0550601) rep2[ medium (0.138957) rep3 (0.241987) ] [ max ] CEM 1 Srp9 1724.9 2289.3 2785.5 P ( S | Z, I ) = 0.82 Srp19 3916.3 4947.6 5412.4 Mean Corr = 0.11836 Srp68 2598.7 2911.6 3304.1 Srp72 1930.1 2459.5 3029.0 Srp54b 219.0 288.9 595.4 Spcs2 2381.5 2676.0 2849.7 Sec23b 3607.0 4339.0 4730.4 Lrrc59 6950.1 8987.8 9562.2 Hdlbp 5196.3 5774.1 7008.7 Sec11a 6649.7 7558.7 8228.9 CEM 1 + Ssr3 10198.0 13540.1 16197.1 Top 10 Genes Tmem39a 472.2 720.2 846.3 Spcs3 2430.5 2950.8 3207.1 Ssr1 4852.4 5563.3 6404.8 Gorasp2 4250.8 5421.3 7502.0

Null module