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: 7 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. Cdkn1b Ccne1 Cks1b Skp1a Num ofGenesinQueryGeneset:7.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Cdk2 Skp2 Cul1

Cks1b Skp2 Ccne1 Cul1 Skp1a Cdkn1b Cdk2 Singletons CEM 1(179datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page1 Rad51ap1 Ranbp1 Shcbp1 Wdhd1 Cenph Kpna2 Cenpk Ercc6l Ccna2 Cdc45 Trip13 Kif20a Rad51 Cdca5 Ccne1 Cks1b Spc24 Skp1a Fbxo5 Fignl1 Aurkb Mcm2 Mcm7 Mcm4 Mcm5 Gins1 Prim1 Asf1b Tfdp1 Uhrf1 Rrm1 Birc5 Bub1 Rpa2 Cdk1 Cdc6 Pcna Hells Exo1 Skp2 Tipin Fen1 Ezh2 Orc6 Melk Rfc4 Rfc5 Cul1 Lig1 Tk1 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE20954 [14] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE16679 [8] GSE12465 [14] GSE7705 [10] GSE6837 [8] GSE6998 [32] GSE7875 [16] GSE57543 [6] GSE16874 [12] GSE18135 [18] GSE28237 [6] GSE48790 [8] GSE13874 [14] GSE13873 [27] GSE46185 [6] GSE26616 [6] GSE12464 [23] GSE27605 [8] GSE10176 [6] GSE51483 [45] GSE46797 [6] GSE48204 [6] GSE11220 [44] GSE28389 [20] GSE7430 [12] GSE31598 [12] GSE39233 [40] GSE51628 [15] GSE22180 [60] GSE17316 [12] GSE38831 [7] GSE11356 [9] GSE6689 [12] GSE15541 [12] GSE12078 [8] GSE11222 [42] GSE51385 [8] GSE12498 [12] GSE15161 [26] GSE32078 [12] GSE32277 [33] GSE13692 [8] GSE46970 [15] GSE6933 [15] GSE21278 [48] GSE21841 [18] GSE7863 [16] GSE15872 [18] GSE22005 [23] GSE21606 [6] GSE45619 [6] GSE7897 [60] GSE24813 [10] GSE12454 [13] GSE24210 [16] GSE27786 [20] GSE20398 [30] GSE17509 [57] GSE33471 [12] GSE24789 [9] GSE44162 [6] GSE16925 [15] GSE10525 [18] GSE9763 [20] GSE7404 [144] GSE51243 [7] GSE32598 [11] GSE30962 [16] GSE15580 [14] GSE38693 [8] GSE42135 [42] GSE10344 [6] GSE14406 [54] GSE1479 [36] GSE21299 [12] GSE4739 [19] GSE24512 [29] GSE25637 [9] GSE29632 [42] GSE7784 [12] GSE8836 [56] GSE9287 [8] GSE9297 [27] GSE9146 [27] GSE15303 [11] GSE5976 [12] GSE30485 [15] GSE46090 [12] GSE9247 [15] GSE8960 [18] GSE15267 [8] GSE39034 [9] GSE51883 [30] GSE51804 [10] GSE52474 [154] GSE39449 [6] GSE19657 [21] GSE48382 [10] GSE28621 [21] GSE23040 [6] GSE15069 [15] GSE33308 [10] GSE15624 [12] GSE28457 [24] GSE6875 [8] GSE23845 [15] GSE21224 [16] GSE16110 [16] GSE21716 [28] GSE35106 [9] GSE32386 [13] GSE4818 [21] GSE46600 [44] GSE14769 [24] GSE35593 [6] GSE21063 [24] GSE46091 [8] GSE27848 [16] GSE35825 [9] GSE9804 [9] GSE51608 [6] GSE8025 [21] GSE15324 [8] GSE7020 [8] GSE7759 [112] GSE10913 [6] GSE25640 [12] GSE39469 [6] GSE6850 [10] GSE21905 [6] GSE27379 [6] GSE40513 [6] GSE13227 [6] GSE31028 [6] GSE18534 [15] GSE44260 [10] GSE12518 [6] GSE21379 [10] GSE7948 [13] GSE32963 [6] GSE38304 [8] GSE35998 [20] GSE43145 [12] GSE31313 [22] GSE5671 [18] GSE38257 [14] GSE24243 [6] GSE11870 [6] GSE6259 [21] GSE28417 [12] GSE13306 [17] GSE11186 [33] CEM+ CEM GSE11201 [18] GSE5334 [19] GSE35366 [78] GSE4260 [6] GSE34839 [6] GSE51075 [12] 0.0 GSE4230 [8] GSE35785 [10]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 142.90 143.03 143.58 143.62 144.14 144.49 144.75 145.41 146.56 146.57 146.94 147.13 147.15 147.22 148.34 148.43 148.69 148.79 148.80 149.25 149.41 149.49 149.82 150.25 150.26 152.06 152.91 153.33 153.33 153.43 153.92 154.46 155.29 155.62 157.27 159.44 159.65 161.39 161.68 161.80 162.39 164.08 165.09 165.09 165.47 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page2 Arhgap11a BC055324 Mis18bp1 Hnrnpab Ncapd2 Nup107 Topbp1 Chaf1b Dnajc9 Zwilch Bub1b Apitd1 Ncapg Ncaph Nup85 Ube2c Ccne2 Cdc20 Rfwd3 Gmnn Mcm6 Aurka Hirip3 Brca1 Gins2 Atad2 Atad5 Cenpi Phf5a Spdl1 Sgol1 Pola1 Eme1 Cse1l Lsm3 Rrm2 Rpa3 Kif11 Ppil1 Cks2 Tpx2 Orc1 Dbf4 Hat1 Rfc3 Pole Plk4 Plk1 Dhfr Pbk 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 128.75 128.95 129.02 129.06 129.08 129.20 129.41 129.81 130.08 130.30 130.35 131.59 132.02 132.94 133.55 133.58 133.77 133.96 134.26 134.35 134.40 134.66 134.85 135.26 135.50 135.62 136.08 136.40 136.57 136.64 137.50 137.51 137.62 137.76 137.95 138.25 138.27 138.76 139.55 139.59 140.18 140.37 140.50 140.69 140.72 141.95 141.99 142.30 142.35 142.72 1.0 Notes 4930579G24Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page3 Racgap1 Suv39h1 Suv39h2 Mms22l Rbmxl1 Nup133 Nup155 Snrpa1 Hmgb3 Nudt21 Ruvbl1 Cenpw Incenp Dnmt1 Chtf18 Cenpn Lrrc40 Ccnb2 Nup93 Cenpe Rqcd1 Pbdc1 Spag5 Actl6a Dpy30 Cdca7 Cdca8 Ddx39 Esco2 Mybl2 Alyref Sf3a3 Espl1 Pole2 Gsg2 Uba2 Kif22 Cdc7 Rcc1 Ska3 Oip5 Nuf2 Ccnf Ect2 E2f7 Dis3 Blm Ttf2 Stil 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 116.67 116.72 116.74 116.76 116.97 117.32 117.66 117.91 117.93 118.27 118.27 118.73 118.77 119.15 119.38 119.41 120.03 120.47 120.70 120.85 121.14 121.23 121.49 121.61 121.63 121.89 121.99 122.01 122.07 122.19 122.21 122.64 122.68 122.89 123.08 123.45 123.45 124.63 124.73 125.48 125.61 126.18 126.34 126.55 126.66 126.67 126.78 127.57 127.72 128.69 1.0 Notes 2700029M09Rik 2700094K13Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page4 Rnaseh2b Zmynd19 Timeless Snrnp40 Anp32b Nup160 Ncapg2 Rad54b Nucks1 Sephs1 Dctpp1 Dnaaf2 Rbm8a Rad54l Mrpl18 Magoh Polr2d Cenpu Cenpp Nup35 Dtymk Rpp30 Nup43 Haus1 Ndc80 Cdca2 Ckap2 Kif18a Tex30 Gspt1 Mcm8 Gmps Cenpf Prim2 Gins4 Ssrp1 Ube2t Kntc1 Sgol2 H2afx Lsm2 Nek2 Cdt1 Anln Nxt1 Hn1l Lyar Kif4 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 104.40 104.52 105.00 105.35 105.40 105.51 106.62 106.67 106.77 106.96 107.09 107.17 107.44 107.75 107.82 108.16 108.17 108.69 108.71 108.81 108.89 109.51 109.53 109.70 109.71 109.73 110.07 110.07 110.23 110.51 111.05 111.24 111.57 111.97 112.06 112.19 112.63 113.58 113.67 114.01 114.35 114.77 114.81 114.87 115.19 115.23 115.36 115.51 115.79 116.13 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page5 Depdc1a Psmc3ip Tamm41 Psmd14 Hnrnpm Nudcd2 Nusap1 Anp32e Cdc25c Ccdc34 Exosc2 Snrpd3 Stoml2 Lmnb1 Psma1 Whsc1 Polr2b C1qbp Kpnb1 Cenpq Nup54 Kif18b Apex1 Cep55 Cdca4 Poc1a Syce2 Snrpe Mki67 Cenpl Aspm Nme1 Clhc1 Larp7 Cct6a Asf1a Uchl5 Mastl Msh6 Gen1 Xpo1 Rpa1 Mtfr2 Dkc1 Mtbp Tcp1 Prc1 E2f8 Gart Ung 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 92.74 93.09 93.79 93.98 94.01 94.18 94.62 94.93 94.99 95.02 95.13 95.21 95.27 95.33 95.36 95.49 95.56 95.65 96.17 97.34 97.68 97.68 98.05 98.08 98.27 98.47 98.87 99.07 99.23 99.24 99.31 99.43 99.98 100.00 100.49 100.55 100.65 100.75 101.08 101.21 101.59 101.73 101.82 102.15 102.18 102.91 103.10 103.10 103.24 103.73 1.0 Notes 2810417H13Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page6 Ebna1bp2 Cdk2ap1 Prpf38a Cacybp Cdc25a Mrps22 Skiv2l2 Parpbp Cenpm Mis18a Dlgap5 Ruvbl2 Rbmx2 Ppm1g Recql4 Ckap2l Polr2h Prpf31 Rbbp7 Stmn1 Ncbp1 Usp14 Pdap1 Tubg1 Znhit3 Naa50 Pa2g4 Fancb Rrp15 Prmt1 Nudt1 Brca2 Gtse1 Gins3 Pfdn4 Pold2 U2af1 H2afz Siva1 Snrpf Nhp2 Dsn1 Ska2 Sfpq Ppat Rfc2 Pfas Itpa Set 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 85.83 85.87 85.97 86.11 86.19 86.25 86.35 86.51 86.60 86.67 86.70 86.71 87.27 87.35 87.51 87.77 88.37 88.39 88.40 88.77 88.81 88.99 89.07 89.18 89.40 89.76 89.76 89.79 89.83 89.98 90.10 90.10 90.40 90.57 91.01 91.06 91.12 91.20 91.23 91.32 91.32 91.34 91.42 91.50 91.81 91.83 92.23 92.57 92.62 92.64 1.0 Notes 3110082I17Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page7 Nsmce4a Smarcc1 Psmd12 Cdc123 Hnrnpu Mthfd1l Metap2 Ppp1r8 Psmg1 Lmnb2 Psmc4 G3bp1 Nop56 Nup62 Nop58 Haus5 Casc5 Naa15 Sass6 Snrpb Snrpc Polr2j Banf1 Xrcc6 Emg1 Pold3 Etaa1 Smc3 Fanci Txnl1 Msh2 Strap Brip1 Srsf9 Pno1 Ddx1 Pask Ints7 Dbr1 Utp6 Ctps Cct5 Rfc1 Eif3l Taf9 Eri1 Atic Fxn Ilf2 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 79.62 79.63 80.04 80.12 80.17 80.27 80.55 80.83 81.08 81.38 81.38 81.52 81.59 81.61 81.71 81.83 82.11 82.32 82.44 82.46 82.86 82.92 83.11 83.14 83.39 83.55 83.65 83.78 83.79 83.88 83.90 83.91 84.04 84.50 84.73 84.87 84.91 85.16 85.19 85.21 85.25 85.25 85.38 85.44 85.45 85.59 85.59 85.64 85.78 85.83 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page8 Depdc1b Smarca5 Anapc15 Snrnp25 Fam98b Exosc3 Tsen15 Ppp1r7 Rnf168 Psmd6 Tcerg1 Psmd1 Trim59 Rsl1d1 Eef1e1 Psma7 Gtf2e2 Aimp2 Cops3 Cops5 Dhx15 Ddx18 Ube2k Ddx20 Thoc3 Prmt5 Cfdp1 Pold1 Nol11 Pole3 Palb2 Psip1 Paics Pwp1 Lsm6 Mns1 Srsf1 Nudc Dhx9 Usp1 Hus1 Eif4e Hdgf Hars Dctd Api5 Cct7 Ipo5 Taf5 Ncl 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 72.49 72.66 72.83 72.87 72.91 73.18 73.44 73.65 73.78 73.80 73.82 74.14 74.28 74.38 74.58 74.69 75.26 75.42 76.17 76.53 76.55 76.58 76.64 76.64 76.68 76.75 76.80 76.84 76.94 77.13 77.14 77.21 77.29 77.34 77.66 77.79 77.81 77.92 78.06 78.23 78.28 78.45 78.56 78.98 78.98 79.07 79.20 79.35 79.53 79.61 1.0 Notes 4632434I11Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page9 Rnaseh2a Casp8ap2 Ppp2r1b Ankrd32 Gemin2 Nudcd1 Ccp110 Rbm12 Nap1l1 Trim37 Cmss1 Trim28 Mthfd1 Psmc1 Psmc3 Mcph1 Gtf2h2 Polr2c Kpna3 Nsun2 Nop16 Bend3 Haus3 Haus6 Ahsa1 Rad18 Naa10 Snrpg Myef2 Gstcd Cetn3 Rnf26 Yars2 Pms2 Mrpl3 Ipo11 Prpf3 Nop9 Nde1 Nelfe Orc2 Drg1 Nip7 Adsl Rbl1 Isy1 Srm Eri2 Nifk 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 66.76 66.89 66.90 66.91 67.17 67.18 67.19 67.24 67.29 67.35 67.39 67.45 67.51 67.66 67.68 67.85 68.06 68.08 68.14 68.14 68.28 68.47 68.64 68.85 69.04 69.06 69.07 69.41 69.77 69.91 69.95 70.01 70.25 70.29 70.38 70.48 70.53 70.82 71.39 71.51 71.62 71.67 71.69 71.80 71.87 72.16 72.19 72.20 72.41 72.42 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page10 Mphosph6 BC030867 Hsp90aa1 Fam133b Fam64a Fam72a Syncrip Prpf40a Anapc1 Tubb4b Ccdc58 Sapcd2 Exosc7 Supt16 Nt5dc2 Psmd5 Hnrnpf Psma4 Psma2 Cirh1a Dnph1 Srsf10 Nup88 Usp10 Usp39 Hspa4 Cep57 Lrwd1 Polr2f Mis12 Dars2 Trmt6 Sf3b5 Noc4l Diap3 Mnd1 Prr11 Prpf4 Bzw1 Plrg1 Rad1 Phb2 Stip1 Eif3b Aaas Tdp1 Gnl3 Rrs1 Cct2 Lin9 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 60.20 60.28 60.35 60.37 60.44 60.66 60.82 61.15 61.16 61.19 61.77 61.87 61.91 62.07 62.20 62.21 62.57 62.73 62.88 62.89 62.91 63.02 63.35 63.38 63.44 63.49 63.61 63.73 64.20 64.30 64.75 64.81 64.81 65.04 65.07 65.11 65.25 65.37 65.58 65.60 65.64 65.77 65.77 65.88 65.90 65.92 66.27 66.37 66.44 66.68 1.0 Notes D030056L22Rik 2610318N02Rik 1600002H07Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page11 Eif4enif1 Magohb Donson Prps1l3 Exosc9 Dazap1 Zmym1 Rprd1b Aarsd1 Hmgb2 Zbtbd6 Pgam5 Psmd2 Psmc2 Smc1a Psma6 Mrpl11 Mrpl28 Grwd1 Rbbp8 Cand1 Nup50 Ncbp2 Wdr18 Nelfcd Enkd1 Cep76 Haus4 Rpl7l1 Ddx11 Eif2b1 Abce1 Eif4a1 Fkbp3 Hmbs Ptcd3 Eef1d Smu1 Smc2 Vwa9 Myg1 Wdr3 Wdr4 Pes1 Tbl3 Ipo9 Ssb 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 54.32 54.43 54.50 54.56 54.58 54.87 55.05 55.09 55.11 55.20 55.21 55.24 55.25 55.36 55.44 55.56 55.57 55.80 55.91 56.44 56.73 57.05 57.14 57.31 57.51 57.65 57.77 57.78 58.00 58.04 58.09 58.12 58.20 58.31 58.34 58.43 58.43 58.69 58.69 58.81 58.83 58.96 58.96 59.20 59.23 59.46 59.52 59.76 59.94 60.12 1.0 Notes 1110004F10Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page12 Rps19bp1 Mybbp1a Wbscr22 Rsl24d1 Fastkd5 Fam83d Timm23 Caprin1 Chchd1 Pkmyt1 Cep192 Otud6b Sssca1 Zc3h15 Arl6ip6 Rps27l Psmg3 Psmb2 Iqgap3 Mak16 Rpap3 Cpsf3l Wdr90 Pcbp1 Ddx46 Ddx21 Eif2b3 Tsen2 Gtf2f2 Sarnp Amd1 Bccip Sf3b3 Rpl14 Wee1 Fancl Lsm4 Nanp Cstf2 Blmh Nop2 Pop1 Tfam Rrp8 Rtca Bysl Lrr1 Eed Srrt 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 48.87 48.93 49.15 49.35 49.66 49.84 49.93 50.03 50.34 50.37 50.58 50.61 50.70 50.71 50.87 50.91 50.93 51.18 51.25 51.34 51.35 51.46 51.53 51.64 51.68 51.83 52.07 52.08 52.18 52.20 52.23 52.30 52.35 52.54 52.66 52.73 52.77 52.81 52.89 52.91 52.93 53.50 53.60 53.60 53.64 53.78 53.83 53.88 54.04 54.23 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page13 Fam60a Ndufaf2 Cenpc1 Ddx19a Hmgn5 Rbm14 Psmb4 Cdca7l Psmb7 Wbp11 Mrpl42 Zfp367 Mrpl22 Gtf2h5 Prpf4b Pitrm1 Nubp1 Wdr55 Ccnb1 Cops4 Chek2 Ddx27 Pspc1 Fanca Nol10 Nif3l1 Recql Smn1 Gpn1 Med4 Srsf3 Bub3 Ccnh Wdr5 Shq1 Eif3g Dcps Ndc1 Ppa1 Pus7 Ints2 Ftsj1 Imp4 Ftsj3 Iws1 Cct4 Nkrf Pif1 Dut Cit 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 44.59 44.84 44.89 44.92 44.95 45.07 45.09 45.11 45.13 45.15 45.32 45.33 45.56 45.62 45.64 45.90 45.93 45.95 46.10 46.12 46.16 46.18 46.28 46.29 46.61 46.66 46.66 46.74 46.74 46.77 46.81 47.04 47.31 47.32 47.59 47.75 47.79 47.94 47.97 47.97 48.02 48.08 48.13 48.18 48.21 48.22 48.46 48.54 48.70 48.80 1.0 Notes 4930422G04Rik 0610009D07Rik 1810009A15Rik Mphosph10 Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page14 Tomm70a Tomm40 Mrps27 Mcmbp Tada2a Cnot11 Psmb6 Dcaf13 Psmb3 Spata5 Psmb5 Psmc5 Mrpl12 Mrpl40 Med14 Pacrgl Polr1e Nedd8 Nop10 Senp1 Eif2b5 Hdac1 Hspe1 Slmo2 Eif2s2 Thoc6 Gtf2f1 Tex10 Parp1 Prps1 Cpsf2 Dimt1 Phf10 Nme7 Defa3 Pms1 Gtf3a Bzw2 Srsf4 Pycrl Xpo5 Leo1 Urb2 Rars Naf1 E2f1 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 40.03 40.07 40.09 40.20 40.23 40.30 40.35 40.37 40.38 40.67 40.68 40.74 40.82 40.83 41.26 41.26 41.35 41.49 41.55 41.56 41.57 41.85 41.85 41.92 41.96 41.98 42.00 42.14 42.15 42.26 42.34 42.40 42.43 42.62 42.75 42.89 43.00 43.12 43.18 43.20 43.25 43.26 43.27 43.35 43.47 43.58 43.71 43.79 43.86 44.35 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page15 Hsp90ab1 Gemin5 Chchd4 Enoph1 Ncaph2 Mrps17 H2-Ke2 Isg20l2 Ankle1 Ppwd1 Mrpl49 Mrpl13 Rangrf Polr3h Wdr74 Wdr43 Ssbp1 Cdc26 Znhit6 Rrp12 Parp2 Cpsf4 Abcf2 Pycr2 Dus1l l7Rn6 Noc2l Noc3l Pinx1 Smc4 Tonsl Tcf19 Ttc27 Mbd3 Gps1 Tyw3 Coq7 Bop1 G2e3 Eif3d Slirp Rcl1 Tsr2 Tsr1 Ltv1 Taf2 Me2 Nbn Lbr Mif 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 35.26 35.26 35.37 35.40 35.43 35.50 35.53 35.59 35.63 35.66 35.76 36.06 36.32 36.34 36.41 36.42 36.54 36.87 36.94 36.99 37.02 37.02 37.06 37.37 37.67 37.72 37.74 37.75 37.87 37.92 38.00 38.04 38.37 38.44 38.71 38.87 38.96 39.38 39.42 39.53 39.57 39.62 39.66 39.68 39.76 39.80 39.83 39.96 40.00 40.00 1.0 Notes A430005L14Rik 2410127L17Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page16 Rnaseh2c Arhgef39 Tubgcp2 Mrps18c Tmem97 Hnrnpa0 Dnajc11 Timm13 Ndufaf6 Wrap53 Nup188 Zc3hc1 Arl6ip4 Trmt11 Rnf219 Mthfd2 Mrpl46 Polr1b Heatr1 G3bp2 Wdr36 Rpp40 Cep78 Eif1ad Mrps7 Jade3 Prmt3 Pomp Utp15 Clspn Utp20 Pcgf6 Tmpo Tcof1 Ttll12 Srsf7 Vbp1 Elof1 Xpo7 Kti12 Pop4 Noa1 Xpo4 Eif3a Ybx1 Mlh1 Ifrd2 Ctcf 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 31.45 31.49 31.53 31.70 31.70 31.71 31.84 31.91 31.98 32.09 32.15 32.28 32.34 32.37 32.37 32.41 32.52 32.62 32.82 32.84 32.85 32.86 32.96 33.12 33.27 33.44 33.45 33.50 33.55 33.57 33.61 33.63 33.69 33.71 33.74 34.10 34.11 34.18 34.22 34.38 34.53 34.60 34.66 34.68 34.74 34.74 34.75 34.86 35.13 35.25 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page17 Tmem209 Thumpd1 Timm17a Tomm22 Rabggtb Hmgxb4 Klhdc10 Smchd1 Timm22 Mrps10 Hnrnpc Prkrip1 Arpp19 Serbp1 Rnf126 Rbm19 Psme3 Ywhah Mrpl47 Gtf2e1 Knop1 Polr1c Nedd1 Cdkn3 Cactin Dhx29 Ppp4c Alms1 Apex2 Ddx56 Tnpo3 Pus10 Bard1 Pprc1 Xrcc2 Galk1 Sart3 Cdk8 Pmf1 Rcc2 Tdp2 Lap3 Mars Toe1 Gars Rrn3 Npat Ppie Parl Coil 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 25.52 25.54 25.56 25.63 25.68 25.79 26.11 26.53 26.68 26.76 26.84 26.89 27.04 27.14 27.31 27.33 27.40 27.49 27.59 27.68 27.69 27.96 28.00 28.15 28.20 28.30 28.33 28.42 28.54 28.58 28.78 29.05 29.12 29.13 29.25 29.33 29.71 29.94 29.98 30.32 30.64 30.66 30.70 30.75 30.76 30.79 30.84 30.95 31.00 31.18 1.0 Notes 1200014J11Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page18 Khdrbs1 Trmt10a Efcab11 Pom121 Fam98a Katnbl1 Pdcd11 Rad51c Pabpc4 Mrps28 Hnrnpll Dhrs13 Rbm34 Txnrd1 Sumo1 Nap1l4 Mrpl50 Heatr3 Polr2g Med30 Cenpo Ythdf2 Ubap2 Aimp1 Hsph1 Cops2 Hddc2 Ddx51 Rad21 Haus8 Rrp1b Metrn Taf11 Mogs Glrx3 Cnbp Nmt2 Fmr1 Ppan Eif5a Mtx1 Ubr7 Drg2 Mtx2 Esf1 Krr1 Ak2 Dck Iars 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 20.78 20.90 21.07 21.09 21.11 21.18 21.23 21.30 21.31 21.39 21.45 21.58 21.70 21.72 21.84 21.96 22.03 22.17 22.18 22.57 22.60 22.62 22.67 22.97 23.04 23.05 23.11 23.12 23.36 23.37 23.37 23.43 23.46 23.66 23.78 23.80 23.91 24.27 24.51 24.54 24.57 24.71 24.71 24.74 24.88 25.01 25.12 25.17 25.31 25.33 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page19 BC027231 Mrps18b Hnrnph1 Fam96a Ctnnbl1 Exosc1 Mrps33 Mrps30 Mrps25 Gtpbp4 Kbtbd8 Dnttip2 Gas2l3 Psmd3 Pmpca Psmd9 Mrpl44 Mrpl37 Mrpl16 Nubp2 Nufip1 Rad50 Dynll2 Ewsr1 Mbnl3 Prmt6 Ccar1 Srp19 Pfdn1 Xrcc1 Nme6 Alg13 Lin54 Coa7 Nelfa Cbx5 Adss Eif5b Pus1 Pdk3 Ppil3 Hax1 Top1 Dars Utp3 Vars Tars Rdx Tfrc Fus 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 17.63 17.66 17.87 17.90 17.91 17.92 18.10 18.12 18.22 18.23 18.24 18.26 18.37 18.43 18.46 18.49 18.52 18.64 18.71 18.78 18.81 18.83 18.85 18.88 18.92 18.95 19.12 19.12 19.26 19.47 19.48 19.65 19.66 19.67 19.70 19.74 19.75 19.81 20.07 20.12 20.12 20.14 20.15 20.24 20.32 20.42 20.52 20.53 20.70 20.77 1.0 Notes 9130401M01Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page20 BC052040 Commd2 Commd1 Ube2cbp Smarce1 Tomm20 Nsmce2 Anapc5 Morf4l2 Sac3d1 Fbxo45 Mapre1 Gpsm2 Smyd5 Mrpl39 Lrpprc Gtf3c5 Carm1 Gtf3c4 Eif4g2 Foxk2 Hmmr Trmt5 Rbmx Bms1 Hbs1l U2af2 Acat2 Riok2 Eif3m Nat10 Pus7l Lsm1 Brix1 Odc1 Hint1 Terf1 Neil3 Rae1 Ece2 Sae1 Orc5 Abt1 Alg6 Elp5 Eif3i Gtl3 Aatf Dtl 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 13.40 13.40 13.42 13.47 13.50 13.50 13.50 13.61 13.64 13.75 13.81 13.85 14.03 14.06 14.07 14.18 14.35 14.35 14.55 14.61 14.62 14.92 15.04 15.22 15.24 15.29 15.30 15.39 15.52 15.52 15.61 15.63 15.74 15.95 16.01 16.25 16.30 16.40 16.45 16.46 16.48 16.53 16.53 16.72 16.86 16.88 17.07 17.16 17.22 17.31 1.0 Notes 1110004E09Rik Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page21 Smarcad1 Xrcc6bp1 Slc25a13 Fam111a Tubgcp3 Mmachc Cep128 Kdm2b Trmt2a Pphln1 Atad3a Kdelc1 Kansl2 Mrpl20 Hnrnpl Srfbp1 Polr3g Med21 Ahctf1 Polr1a Lrrc59 Wdr77 Cdc73 Pds5b Qtrtd1 Sap30 Ssna1 Sec13 Mettl1 Mettl5 Msto1 Tacc3 Cenpt Adat2 Trub1 Chd1l Sfxn1 Zfp41 Nob1 Txn1 Orc3 Nfyb Rnf4 Rnf8 Emd Hprt Rif1 Hn1 Nvl 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 9.52 9.53 9.54 9.66 9.68 9.82 9.86 9.99 10.00 10.02 10.04 10.08 10.12 10.14 10.37 10.44 10.94 11.11 11.17 11.27 11.35 11.42 11.48 11.51 11.61 11.74 11.77 11.92 11.94 11.95 12.10 12.17 12.18 12.23 12.39 12.43 12.51 12.54 12.56 12.57 12.82 12.91 12.94 12.97 13.00 13.14 13.23 13.27 13.28 13.36 1.0 Notes 4930427A07Rik 9430016H08Rik D19Bwg1357e Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page22 Tmem194 Wbscr16 Ccdc124 Ankrd26 Dnajc24 L3mbtl2 Ndufaf4 Ranbp3 N6amt2 Mrps12 Hnrnpk Polr2m Cbwd1 Ywhae Grpel1 Dhodh Wdr46 Shmt2 Caap1 Eif2b4 Tubb5 Dtwd1 Khsrp Tssc4 Polr2i Prdx4 Aifm1 Pfdn2 Nupl1 Psrc1 Park7 Sf3b4 Pwp2 Gpn3 Aven Bag2 Nans Dna2 Dap3 Ccz1 Lsg1 Taf5l Bora Clpp Lrdd Nrm Pigf 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 5.78 5.88 6.00 6.09 6.09 6.17 6.36 6.58 6.63 6.65 6.73 6.84 6.94 6.96 7.00 7.06 7.06 7.11 7.15 7.24 7.25 7.25 7.30 7.33 7.38 7.42 7.43 7.54 7.57 7.64 7.75 7.94 7.97 8.01 8.27 8.28 8.32 8.39 8.39 8.44 8.44 8.48 8.51 8.67 8.87 8.97 9.07 9.24 9.32 9.50 1.0 Notes 2700097O09Rik Gadd45gip1 Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page23 Cdkn2aipnl Hnrnpa3 Gpatch4 Champ1 Nfatc2ip Fgfr1op Ctdspl2 Ube2e3 Ccdc14 Mrps26 Mrps35 Zc3h18 Mettl13 U2surp Bhlhb9 Atp5a1 Efcab7 Mrfap1 Zfp770 Mrpl34 Gtf2h3 Srsf11 Cops8 Sdad1 Vdac3 Lage3 Vprbp Tcea1 Gnb1l Prps2 Kdm8 Cnih4 Rabl3 Fancf Mrpl2 Txlna Mdc1 Dohh Crls1 Qtrt1 Rrp9 Prep Sfr1 Arl6 Fh1 Tsn Aqr Ttk 0.0 1.0

GSE13693 [9] GSE30160 [6]

GSE14012 [24] Scale ofaveragePearsoncorrelations GSE20302 [12] GSE25737 [6] GSE42601 [6] GSE38837 [6] GSE46209 [21] GSE25423 [10] 0.2 GSE40856 [8] GSE29681 [32] GSE15155 [12] GSE19885 [9] GSE8034 [17] GSE9725 [16] GSE45051 [18] GSE24628 [16] GSE30164 [23] 0.4 GSE46606 [30] GSE21309 [9] GSE14308 [12] GSE13493 [6] GSE54653 [6] GSE18281 [33] GSE23600 [10] GSE13149 [25] GSE49346 [6] 0.6 GSE40230 [15] GSE14698 [12] GSE39621 [51] GSE43197 [27] GSE8512 [207] GSE18136 [12] GSE4142 [14] GSE51932 [8] GSE3861 [6] 0.8 GSE6957 [12] GSE50813 [24] GSE14753 [6] GSE36530 [6] Score 2.20 2.27 2.33 2.48 2.49 2.90 2.93 2.94 3.04 3.06 3.08 3.17 3.21 3.22 3.37 3.37 3.40 3.57 3.62 3.74 3.77 3.92 3.97 4.03 4.07 4.15 4.23 4.38 4.39 4.40 4.47 4.53 4.77 4.91 4.93 4.97 5.00 5.03 5.10 5.12 5.27 5.28 5.30 5.32 5.34 5.36 5.47 5.59 5.68 5.77 1.0 Notes Symbol Num ofCEMGenes:5.Predicted1174.SelectedDatasets:179.Strength:0.9 CEM 1,Geneset"[C]p27-cyclinE-Cdk2-UbiquitinE3ligase",Page24 Aasdhppt Samm50 Zdhhc16 Ppp2r5c Trmt10c Ngfrap1 Tarbp2 Samd1 Armc6 Cops6 Dhx33 Cep72 Nsfl1c Vdac1 Thoc5 Larp1 Med6 Glmn Cyc1 Ybx3 Cycs Eif3c Xpot Rtcb Alg8 Fzr1 C1d Vcp Mtr 0.0 1.0

GSE13693 [9] GSE30160 [6]

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 (0.140816)MYELOBLASTS_CD117POS_GR1+_MAC1-_1NORMAL (0.171002)MYELOBLASTS_CD117POS_GR1+_MAC1-_2NORMAL (0.263307)MYELOBLASTS_CD117POS_GR1+_MAC1-_3NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_2NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_1 MYELOBLASTS_CD117POS_GR1+_MAC1+_3 (0.0953041) (0.0964118)[ min(0.0824689) (0.0235547)] (0.0426527)[ (0.0844827) medium ] [ max ] CEM 1 Cks1b 90.6 3751.3 4381.5 P ( S | Z, I ) = 1.00 Skp2 11.2 1026.7 1573.8 Mean Corr = 0.94906 Ccne1 9.8 614.4 893.4 Cul1 2272.2 3190.8 3843.1 Skp1a 1207.2 3742.5 4159.2 Ercc6l 74.9 1980.3 2539.9 Cdc6 36.0 2897.1 4104.8 Exo1 20.2 1120.3 1732.3 Fen1 44.6 2899.0 3730.9 Cdk1 467.4 5858.2 9393.7 CEM 1 + Cdca5 26.0 2451.4 3092.7 Top 10 Genes Gins1 62.2 1582.3 2878.6 Tipin 79.9 4956.8 5881.4 Mcm5 161.3 5570.7 6370.6 Rad51 3.6 2722.9 3084.5

Null module Cdkn1b Cdk2 GEO Series "GSE30160" 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=GSE30160 Status: Public on Jul 05 2011 Title: The RANK IVVY Motif-regulated Genes in Osteoclastogenesis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: By carrying out a systematic structure/function study of the RANK cytoplasmic domain, we previously identified a specific 4-a.a. RANK motif (IVVY535-538) which plays a critical role in osteoclastogenesis by mediating commitment of macrophages to the osteoclast lineage. We have recently validated the role of this IVVY motif in osteoclastogenesis in vivo by generating knockin (KI) mice bearing inactivating mutations in the RANK IVVY motif. This microarray experiment was performed to determine whether the IVVY motif is involved in regulating gene expression in osteoclastogenesis.

We used microarrays to detail the global programme of gene expression underlying cellularisation and identified distinct classes of up-regulated genes during this process.

Overall design: Bone marrow macrophages isolated from wild-type (WT) or knockin (KI) mice were plated in 60-mm tissue culture dishes and treated with M-CSF (44ng/ml) and RANKL (100ng/ml) for 24 hours. Each genotype has three triplicates. Total RNA was isolated for microarray analysis using mouse chips (type 430.2.0) at the Microarray Shared Facility at the University of Alabama at Birmingham.

Background corr dist: KL-Divergence = 0.0193, L1-Distance = 0.0421, L2-Distance = 0.0019, Normal std = 0.8277

0.522 Kernel fit Pairwise Correlations Normal fit

Density 0.261

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 replicate typewild replicate 1 type (0.446349)knockin replicate 2 (0.0451117)knockin replicate 3 (0.128658)knock replicate 1 (0.258317) in replicate 2 (0.0355928) 3 (0.0859713)[ min ] [ medium ] [ max ] CEM 1 Cks1b 1792.7 3953.2 5725.7 P ( S | Z, I ) = 1.00 Skp2 622.7 736.9 976.0 Mean Corr = 0.92513 Ccne1 126.6 363.0 472.9 Cul1 1471.4 1802.5 2027.9 Skp1a 6408.4 6728.5 7358.7 Ercc6l 552.9 1097.8 1582.3 Cdc6 209.7 534.5 796.6 Exo1 102.9 355.9 616.0 Fen1 1137.0 2390.5 3187.7 Cdk1 2128.5 4240.2 5976.7 CEM 1 + Cdca5 341.8 752.6 1257.5 Top 10 Genes Gins1 488.9 1040.2 1701.3 Tipin 1079.3 2944.8 4234.3 Mcm5 656.7 2033.9 2912.4 Rad51 341.6 1145.0 1946.7

Null module Cdkn1b Cdk2 GEO Series "GSE20954" 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=GSE20954 Status: Public on Aug 17 2010 Title: mRNA expression profile in mouse lung development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20520778 Summary & Design: Summary: We performed miRNA and mRNA profiling over a 7-point time course, encompassing all recognized stages of lung development and explore dynamically regulated miRNAs and potential miRNA-mRNA interaction networks specific to mouse lung development

Overall design: replicated time course of mouse lung development in 7 time points

Background corr dist: KL-Divergence = 0.0229, L1-Distance = 0.0372, L2-Distance = 0.0026, Normal std = 0.7245

0.551 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

Mouse lung-embryoMouse lung-embryoMouse day lung-embryoMouse 12-rep1 day lung-embryoMouse 12-rep2 (0.119107) day lung-embryoMouse 14-rep1 (0.14432) day lung-embryoMouse 14-rep2 (0.0677179) day lung-embryoMouse 16-rep1 (0.085627) day lung-embryoMouse 16-rep2 (0.0611571) day lung-postnatalMouse 18-rep1 (0.0545595) day lung-postnatalMouse 18-rep2 (0.0410163) lung-postnatalMouseday (0.127614) 2-rep1 lung-postnatalMouseday (0.0211091)2-rep2 lung-postnatalMouseday (0.0300744)10-rep1 lung-postnatalday 10-rep2 (0.0378378) day 30-rep1 (0.0371198) day 30-rep2 (0.0705684)[ min (0.102172) ] [ medium ] [ max ] CEM 1 Cks1b 406.1 1226.2 6866.9 P ( S | Z, I ) = 1.00 Skp2 211.2 724.0 5533.3 Mean Corr = 0.91032 Ccne1 158.8 218.9 1127.8 Cul1 1473.2 2174.3 2683.0 Skp1a 4268.7 5066.0 7703.7 Ercc6l 131.8 364.5 1840.0 Cdc6 72.0 242.3 1726.5 Exo1 37.0 110.4 1267.0 Fen1 264.7 608.1 2733.1 Cdk1 138.5 1288.7 5556.8 CEM 1 + Cdca5 68.6 192.9 1434.6 Top 10 Genes Gins1 85.3 272.1 1305.7 Tipin 817.7 1824.9 5003.6 Mcm5 189.8 586.8 3589.7 Rad51 80.1 359.5 2385.6

Null module Cdkn1b Cdk2 GEO Series "GSE16679" 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=GSE16679 Status: Public on Aug 01 2010 Title: Plag1 overexpression cooperates with Evi1 overexpression and Gata1s mutation in leading to M7 leukemia Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20679399 Summary & Design: Summary: The goal of this study is to develop a Plag1 signature and determine how its overexpression contributes to leukemogenesis.

To study this, we transduced an immortalized (but not transformed) cell line (derived from Gata1s mutant fetal liver progenitor through insertional mutagenesis) by Plag1-expressing retrovirus. This turned a non-transformed cell line to a leukemogenic cell line. To study whether Plag1 overexpression led to deregulation of signaling pathways that may contribute to leukemic transformation, we generated microarray gene expression profiles of this cell line transduced with either Plag1 or the empty vector.

Overall design: We generated gene expression profiles by microarray from stable cell lines transduced with either the empty vector or the Plag1-expressing vector.

Background corr dist: KL-Divergence = 0.0435, L1-Distance = 0.0264, L2-Distance = 0.0008, Normal std = 0.6089

0.677 Kernel fit Pairwise Correlations Normal fit

Density 0.338

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

cell line2_Plag1_KT_subline1_Acell line2_Plag1_KT_subline2_Acell line2_Vector_KT_subline1_Acell line2_Vector_KT_subline2_Acell (0.191886) line2_Plag1_KT_subline1_Bcell (0.121938) line2_Plag1_KT_subline2_Bcell (0.110298)line2_Vector_KT_subline1_Bcell (0.113449)line2_Vector_KT_subline2_B (0.167727) (0.102562) (0.0615693)[ min (0.13057) ] [ medium ] [ max ] CEM 1 Cks1b 1701.8 4970.5 5327.2 P ( S | Z, I ) = 1.00 Skp2 126.0 756.3 1192.9 Mean Corr = 0.90276 Ccne1 57.0 336.7 453.2 Cul1 1285.9 1761.4 2007.9 Skp1a 2808.9 3524.5 3988.0 Ercc6l 638.9 969.5 1125.0 Cdc6 134.2 760.1 813.0 Exo1 157.1 671.1 899.5 Fen1 424.5 2075.0 2391.0 Cdk1 3713.7 8116.3 9636.7 CEM 1 + Cdca5 323.2 819.1 942.2 Top 10 Genes Gins1 324.9 628.6 764.3 Tipin 690.9 2566.1 3068.8 Mcm5 884.2 5293.8 6381.0 Rad51 131.9 600.6 692.3

Null module Cdkn1b Cdk2 GEO Series "GSE12465" 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=GSE12465 Status: Public on May 20 2009 Title: Transcriptional signatures of Itk-deficiency using CD3+, CD4+ and CD8+ T-cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19450280 Summary & Design: Summary: The Tec-family kinase Itk plays an important role during T-cell activation and function, and controls also conventional versus innate-like T-cell development. We have characterized the transcriptome of Itk-deficient CD3+ T-cells, including CD4+ and CD8+ subsets, using Affymetrix microarrays. The largest difference between Itk-/- and Wt CD3+ T-cells was found in unstimulated cells, e.g. for killer cell lectin-like receptors. Compared to anti-CD3-stimulation, anti-CD3/CD28 significantly decreased the number of transcripts suggesting that the CD28 co-stimulatory pathway is mainly independent of Itk. The signatures of CD4+ and CD8+ T-cell subsets identified a greater differential expression than in total CD3+ cells. Cyclosporin (CsA)-treatment had a stronger effect on transcriptional regulation than Itk-deficiency, suggesting that only a fraction of TCR-mediated calcineurin/NFAT-activation is dependent on Itk. Bioinformatic analysis of NFAT-sites of the group of transcripts similarly regulated by Itk-deficiency and CsA-treatment, followed by chromatin-immunoprecipitation, revealed NFATc1-binding to the Bub1, IL7R, Ctla2a, Ctla2b, and Schlafen1 genes. Finally, to identify transcripts that are regulated by Tec-family kinases in general, we compared the expression profile of Itk-deficient T-cells with that of Btk-deficient B-cells and a common set of transcripts was found. Taken together, our study provides a general overview about the global transcriptional changes in the absence of Itk.

Overall design: CD3+ CD4+ and CD8+ T-cells from pooled suspensions of spleen and lymph nodes of Wt and Itk knockout mice on C57BL/6 background were isolated after negative depletion. Unstimulated as well as stimulated T-cells were studied. Stimulations were done with anti-CD3 (1 mg/ml) for 24 hrs. For the CD4+ T-cells we collected triplicates from the Itk knockout mice and duplicates from the Wt group. For the CD8+ T-cells, we got duplicates from Itk knockout , while we obtained a single sample from Wt owing to the low cell yield for resting Wt CD8+ T-cells. After CD3-stimulation we got a single sample from the CD8+ subset of both Wt and Itk knockout, while for the CD4+ subsets we collected duplicates.

Background corr dist: KL-Divergence = 0.0403, L1-Distance = 0.0459, L2-Distance = 0.0032, Normal std = 0.6284

0.635 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

Wild typeWild CD4+ typeItk unstimulated CD4+knockoutItk unstimulated knockout CD4+ 1Itk (0.0486707) knockout unstimulated CD4+ 2Wild (0.0278266) unstimulated typeCD4+Itk CD8+1knockout unstimulated(0.0421494)Itk unstimulated 2knockout (0.0666063) CD8+Wild 3 unstimulated (0.0926969) typeCD8+ (0.0261757)Wild CD4+ unstimulated typeItk CD3-stimulated CD4+1knockout (0.141573)Itk CD3-stimulated 2knockout (0.0472288) CD4+Wild 1 (0.136867)CD3-stimulated typeCD4+Itk 2 CD8+knockout (0.110171)CD3-stimulated CD3-stimulated 1CD8+ (0.0217763) CD3-stimulated 2 (0.0376428) (0.184535)[ min (0.0160813) ] [ medium ] [ max ] CEM 1 Cks1b 254.2 685.2 1957.7 P ( S | Z, I ) = 1.00 Skp2 134.4 341.9 939.7 Mean Corr = 0.89225 Ccne1 174.7 415.9 1185.5 Cul1 1460.6 2009.6 3116.4 Skp1a 3376.9 4593.7 6065.6 Ercc6l 120.6 603.0 2188.5 Cdc6 79.1 734.7 4145.2 Exo1 94.4 211.8 1595.0 Fen1 257.8 452.8 2102.1 Cdk1 125.0 995.0 4251.7 CEM 1 + Cdca5 71.0 309.9 2207.4 Top 10 Genes Gins1 151.3 288.4 2011.4 Tipin 710.5 1431.9 6243.1 Mcm5 230.2 453.7 2621.3 Rad51 65.6 578.8 4241.1

Null module Cdkn1b Cdk2 GEO Series "GSE7705" 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=GSE7705 Status: Public on May 01 2008 Title: Microarray analysis of CD4+T cells in murine arthritis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Although activated CD4+ T cell-driven overproduction of cytokines, especially TNF and IL1, is generally regarded as the major factor in the development of rheumatoid arthritis (RA), little is known about the precise role of CD4+ T cells in the initiation and progression of this disease. In this study, this issue was addressed using a time-course microarray analysis in a mouse model of RA, Il1rn deficient mice.No obvious cytokine gene expression changes reflecting T cell activation was observed in CD4+ T cells in the Il1rn deficient mice during the course of spontaneous arthritis. On the contrast, majority of dysregulated genes were those predominantly expressed in myeloid lineage cells, suggesting T cell reprogramming involvement in arthritis development. Distinct gene expression patterns were identified for different stages of disease, including downregulated expression of immunoglobulin heavy chain constant region genes and increased expression of inflammatory genes in the early phase, and downregulation of MHC class II genes in the late phase. The common changes occurred in both early and late phases included upregulation of Arl2bp and Mfap1, which are involved in the regulation of cytoskeletal dynamics.

Keywords: Time course

Overall design: Two KO mice and three WT mice for each time point (1 month and 4 month) were used for this study.

Background corr dist: KL-Divergence = 0.0808, L1-Distance = 0.0282, L2-Distance = 0.0010, Normal std = 0.4856

0.836 Kernel fit Pairwise Correlations Normal fit

Density 0.418

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

CD4+ cellsCD4+ IL1RN cellsCD4+ knockout IL1RN cellsCD4+ knockout IL1RN 1cells monthCD4+ knockout IL1RN 1cells rep1monthCD4+ knockout IL1RN (0.270161) 4cells rep2monthCD4+ wild IL1RN (0.19828) 4cells rep1 monthCD4+type wild IL1RN (0.0667678) 1 cells rep2month CD4+type wild IL1RN (0.0744472) 1 cells rep1month CD4+type wild IL1RN(0.0485367) 1 cells rep2month type wild IL1RN(0.057362) 4 rep3month type wild (0.0791738) 4 rep1month type (0.0932184) 4 rep2month[ min (0.0339295) rep3 (0.0781236)] [ medium ] [ max ] CEM 1 Cks1b 1630.9 3428.3 6001.5 P ( S | Z, I ) = 1.00 Skp2 404.2 811.8 1561.9 Mean Corr = 0.88946 Ccne1 456.6 1253.2 1804.7 Cul1 1374.1 1882.5 2600.1 Skp1a 8145.1 12143.8 16272.9 Ercc6l 383.7 825.4 1413.1 Cdc6 1246.9 3396.6 5358.6 Exo1 328.9 827.8 1657.6 Fen1 1888.6 4035.2 5489.0 Cdk1 1407.4 3144.5 4801.5 CEM 1 + Cdca5 291.7 717.1 1223.1 Top 10 Genes Gins1 567.3 1220.3 2486.2 Tipin 3334.0 6047.3 10255.8 Mcm5 2396.7 4188.0 5242.9 Rad51 558.1 1235.4 2637.2

Null module Cdkn1b Cdk2 GEO Series "GSE6837" 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=GSE6837 Status: Public on Jan 31 2007 Title: Expression data from wild type (wt) and Ikbke knockout (Ikke) embryonic fibroblasts (EF) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17332413 Summary & Design: Summary: WT and Ikbke-/- EF cells were stimulated with recombinant interferon beta for 6 hours. Cells lacking IKKe kinase show a defect in a subset of interferon stimulated gene transcription

Keywords: comparative study

Overall design: WT and Ikbke cells were either stimulated and left untreated to compare their response to interferon.

Background corr dist: KL-Divergence = 0.0231, L1-Distance = 0.0545, L2-Distance = 0.0038, Normal std = 0.8315

0.536 Kernel fit Pairwise Correlations Normal fit

Density 0.268

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

unstimulatedunstimulated embryonicstimulated embryonicstimulated fibroblasts embryonicstimulated fibroblasts embryonic WT, stimulatedfibroblasts biologicalembryonic KO, stimulatedfibroblasts biologicalembryonicWT, rep1 stimulatedfibroblasts biological embryonicWT,(0.0740298) rep1 fibroblasts biological embryonicrep1WT,(0.0593076) fibroblasts biological(0.0445131) rep2KO, fibroblasts biological (0.0478509) rep3KO,[ biological (0.0955204) min rep1KO, biological(0.318417) rep2] (0.119877) rep3 (0.240484)[ medium ] [ max ] CEM 1 Cks1b 373.9 6680.1 7336.1 P ( S | Z, I ) = 1.00 Skp2 5.3 1721.8 2100.1 Mean Corr = 0.88155 Ccne1 121.3 736.3 903.3 Cul1 1599.1 2507.4 2739.4 Skp1a 5985.8 8626.6 9153.2 Ercc6l 97.3 1669.8 2260.0 Cdc6 89.4 1504.5 1603.9 Exo1 25.0 832.7 1120.9 Fen1 214.2 3350.6 3855.0 Cdk1 218.2 9389.5 13256.5 CEM 1 + Cdca5 35.3 1055.5 1422.3 Top 10 Genes Gins1 85.8 1477.5 1705.2 Tipin 749.2 5325.5 6970.7 Mcm5 230.5 4139.4 5677.5 Rad51 11.3 2157.4 2847.4

Null module Cdkn1b Cdk2 GEO Series "GSE6998" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 32 -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=GSE6998 Status: Public on Feb 09 2007 Title: Expression profiling of developmental and regenerating liver in mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17227769 Summary & Design: Summary: Normal adult liver is uniquely capable of renewal

and repair after injury. Whether this response

represents simple hyperplasia of various liver elements

or requires recapitulation of the genetic program of

the developing liver is not known. To study these possibilities,

we examined transcriptional programs of

adult liver after partial hepatectomy and contrasted

these with developing embryonic liver. Principal component

analysis demonstrated that the time series of

gene expression during liver regeneration does not segregate

according to developmental transcription patterns.

Gene ontology analysis revealed that liver restoration

after hepatectomy and liver development differ

dramatically with regard to transcription factors

and chromatin structure modification. In contrast, the

tissues are similar with regard to proliferationassociated

genes. Consistent with these findings, realtime

polymerase chain reaction showed transcription

factors known to be important in liver development

are not induced during liver regeneration. These three

lines of evidence suggest that at a transcriptional level,

restoration of liver mass after injury is best described

as hepatocyte hyperplasia and not true regeneration.

We speculate this novel pattern of gene expression may

underlie the unique capacity of the liver to repair itself

after injury.

Keywords: time course

Overall design: Each experimental time point is represented by two separate samples, each consisting of at least 3 pooled tissues from different animals. For example, 6 hepatectomies were performed for the 1 hour post-hepatectomy time point. Time 0 is used as control.

Background corr dist: KL-Divergence = 0.0534, L1-Distance = 0.0220, L2-Distance = 0.0006, Normal std = 0.5487

0.727 Kernel fit Pairwise Correlations Normal fit

Density 0.364

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

baselinebaseline sampleregeneration sampleat T0,regeneration rep1 at T0, (0.0219683)sampleregeneration rep2 (0.0208194) sampleatregeneration T1, rep1 sampleatregeneration T1, (0.014714) rep2 sampleatregeneration T2, (0.00999608) rep1 sampleatregeneration T2, (0.0145306) rep2 sampleatregeneration T6, (0.0277155) rep1 sampleatregeneration T6, (0.0156078) rep2 sampleatregeneration T12, (0.0128433) samplerep1atregeneration T12, (0.0305352) samplerep2atregeneration T18, (0.0170546) samplerep1atregeneration T18, (0.0248511) samplerep2atregeneration T24, (0.0259566) samplerep1atregeneration T24, (0.0164316) samplerep2atregeneration T30, (0.0365523) samplerep1atregeneration T30, (0.0180799) samplerep2atregeneration T48, (0.019105) samplerep1atdevelopmental T48, (0.0218459) samplerep2atdevelopmental T72, (0.0254914) rep1at developmentalsample T72, (0.0124714) rep2 developmental sampleat T105,(0.0176213) developmental sampleat rep1 T105, (0.0770747) developmental sampleat rep2 T115, (0.102504) developmental sampleat rep1 T115, (0.0461767) developmental sampleat rep2 T125, (0.0827978) developmental sampleat rep1 T125, (0.0333591) developmental sampleat rep2 T135, (0.0393553) developmental sampleat rep1 T135, (0.0563166) developmental sampleat rep2 T145, (0.0390308) sampleat rep1 T145, (0.0545574) sampleat rep2 T165, (0.0291869) at rep1 T165, (0.0191979)[ rep2min (0.0162515) ] [ medium ] [ max ] CEM 1 Cks1b 138.8 591.4 5227.9 P ( S | Z, I ) = 1.00 Skp2 3.5 28.0 2059.3 Mean Corr = 0.86059 Ccne1 3.4 66.9 2049.1 Cul1 1105.6 1384.9 2429.0 Skp1a 1349.0 2539.0 5226.3 Ercc6l 33.1 108.4 765.0 Cdc6 3.3 3.9 2822.5 Exo1 119.9 223.9 1166.5 Fen1 4.7 107.0 4149.4 Cdk1 3.3 251.9 6343.5 CEM 1 + Cdca5 3.3 45.7 948.4 Top 10 Genes Gins1 24.5 165.9 1454.6 Tipin 42.9 254.1 4312.1 Mcm5 426.7 677.6 5708.9 Rad51 3.3 6.1 1413.0

Null module Cdkn1b Cdk2 GEO Series "GSE7875" 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=GSE7875 Status: Public on Oct 03 2007 Title: Deletion of PKBalpha/Akt1 affects thymic development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17912369 Summary & Design: Summary: The thymus constitutes the primary lymphoid organ for the majority of T cells. The phosphatidyl-inositol 3 kinase (PI3K) signaling pathway is involved in lymphoid development. Defects in single components of this pathway prevent thymocytes from progressing beyond early T cell developmental stages. Protein kinase B (PKB) is the main effector of the PI3K pathway. To determine whether PKB mediates PI3K signaling in early T cell development, we characterized PKB knockout thymi. Our results reveal a significant thymic hypocellularity in PKBalpha-/- neonates and an accumulation of early thymocyte subsets in PKBalpha-/- adult mice. The latter finding is specifically attributed to the lack of PKBalpha within the lymphoid component of the thymus. Microarray analyses show that the absence of PKBalpha in early thymocyte subsets modifies the expression of genes known to be involved in pre-TCR signaling, in T cell activation, and in the transduction of interferon-mediated signals. This report highlights the specific requirements of PKBalpha for thymic development.

Keywords: Genetic modification

Overall design: Early thymocyte subsets (DN3 and ISP8) were sorted by FACS from 4 PKBalpha-/- / PKBalpha+/+ mouse littermate pairs. The same number of DN3 or ISP8 cells was sorted (7 000 to 25 000 cells) within a PKBalpha-/- / PKBalpha+/+ pair. Four replicates per condition were then analysed (4xPKBalpha-/- DN3, 4xPKBalpha+/+ DN3, 4xPKBalpha-/- ISP8, 4xPKBalpha+/+ ISP8). Total RNA was extracted using PicoPureTM RNA isolation kit (Arcturus, Sunnyvale, CA, USA) and RNA quality was controlled using the 2100 Bioanalyser (Agilent Technologies, Santa Clara, CA, USA). Total RNA was amplified and labeled using the Affymetrix 2-cycle 3 labelling kit according to manufacturers instructions. After fragmentation, 10 ug cRNA was hybridised to mouse genome 430 2.0 GeneChips (Affymetrix, Santa Clara, CA). The supplementary file represents the expression values estimated using the GC-RMA function provided by Refiner 3.1 (Genedata, Basel, Switzerland) for each of the samples.

Background corr dist: KL-Divergence = 0.1420, L1-Distance = 0.0394, L2-Distance = 0.0024, Normal std = 0.3992

1.035 Kernel fit Pairwise Correlations Normal fit

Density 0.518

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

bh20061128m430v2_A_16_pTN3-PKBa-2435bh20061128m430v2_A_15_pTN3-PKBa-2432bh20061128m430v2_A_14_pTN3-PKBa-2425bh20061128m430v2_A_13_pTN3-PKBa-2424bh20061128m430v2_A_12_pTN3-PKBa-2420bh20061128m430v2_A_11_pTN3-PKBa-2416 (0.0652273)bh20061128m430v2_A_10_pTN3-PKBa-2402 (0.0755871)bh20061128m430v2_A_09_pTN3-PKBa-2401 (0.026359)bh20061128m430v2_A_08_preDP-PKBa-2435 (0.0341487)bh20061128m430v2_A_07_preDP-PKBa-2432 (0.0522867)bh20061128m430v2_A_06_preDP-PKBa-2425 (0.0394752)bh20061128m430v2_A_05_preDP-PKBa-2424 (0.106657)bh20061128m430v2_A_04_preDP-PKBa-2420 (0.0542883)bh20061128m430v2_A_03_preDP-PKBa-2416bh20061128m430v2_A_02_preDP-PKBa-2402 (0.0325443)bh20061128m430v2_A_01_preDP-PKBa-2401 (0.0579007) (0.0845044) (0.161811) (0.0599366)[ (0.0361105) min (0.0399298) ] (0.0732332)[ medium ] [ max ] CEM 1 Cks1b 843.8 2351.5 3274.9 P ( S | Z, I ) = 1.00 Skp2 988.5 2273.0 3385.4 Mean Corr = 0.84701 Ccne1 141.9 730.6 1140.9 Cul1 3215.2 4998.2 5883.5 Skp1a 6141.9 8050.5 11499.0 Ercc6l 483.0 1879.2 2340.7 Cdc6 1933.8 5475.1 7259.8 Exo1 448.0 1313.5 1631.1 Fen1 950.8 2150.3 2951.7 Cdk1 889.7 5042.3 6984.5 CEM 1 + Cdca5 411.3 2268.5 2854.2 Top 10 Genes Gins1 2164.7 4744.7 6006.8 Tipin 4921.0 10172.3 11944.1 Mcm5 1041.1 2945.6 4350.3 Rad51 834.1 2866.6 3713.4

Null module Cdkn1b Cdk2 GEO Series "GSE57543" 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=GSE57543 Status: Public on May 13 2014 Title: Expression data from B6 mouse miR-142 KO and WT T cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: T cells are critical for modulating immune responses. miRNAs are small, noncoding RNAs and play a significant role in T cell responses. miR-142 is a hematopoietic specific miRNA. To explore the potential role of miR-142 in regulating T cell responses, we generated mutant mice bearing a targeted deletion of the miR-142 gene.

We used microarrays to detail the global programme of gene expression underlying the profile changes between miR-142 KO and WT T cell and identified distinct classes of up-regulated genes during this process.

Overall design: miR-142 KO mice and WT littermates (biological triplicates) matched with age and sex were selected. T cells were purified from spleens by negative selection and processed for RNA isolation and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0094, L1-Distance = 0.0206, L2-Distance = 0.0006, Normal std = 0.8842

0.451 Kernel fit Pairwise Correlations Normal fit

Density 0.226

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 biologicalWT biological repWT 1 biological (0.181653) repKO 2biological (0.207905) repKO 3biological (0.0935213) repKO 1 biological (0.108896) rep 2 (0.243579) rep 3 (0.164446)[ min ] [ medium ] [ max ] CEM 1 Cks1b 1314.0 5717.3 6433.6 P ( S | Z, I ) = 1.00 Skp2 252.5 1331.6 2271.4 Mean Corr = 0.84800 Ccne1 445.0 961.9 1526.1 Cul1 2030.5 2192.5 2443.0 Skp1a 9635.1 10150.7 10744.7 Ercc6l 338.9 1022.8 1157.1 Cdc6 413.2 2541.8 3756.4 Exo1 95.1 562.0 867.8 Fen1 711.9 1862.3 2774.0 Cdk1 756.0 3521.6 4546.7 CEM 1 + Cdca5 230.6 1112.4 1505.2 Top 10 Genes Gins1 455.4 2097.7 3065.2 Tipin 2714.2 5973.8 7926.5 Mcm5 803.5 2997.0 4455.2 Rad51 406.6 1415.6 1848.0

Null module Cdkn1b Cdk2 GEO Series "GSE16874" 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=GSE16874 Status: Public on Dec 07 2010 Title: Expression in wild type and TgDREAM mouse B cells unstimulated or 2 days after LPS+IL4 stimulation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21059893 Summary & Design: Summary: DREAM/KChIP-3 is a calcium-dependent transcriptional repressor highly expressed in immune cells. Transgenic mice expressing a dominant active DREAM mutant show reduced serum immunoglobulin levels. In vitro assays show that reduced immunoglobulin secretion is an intrinsic defect of transgenic B cells that occurs without impairment in plasma cell differentiation but with an accelerated entry in cell division and an increase in class switch recombination. B cells from DREAM knockout mice did not show any phenotype, due to compensation by endogenous KChIP-2. Expression arrays revealed modified expression of Edem1 and Derlin3, two proteins related to the ER-associated degradation pathway and of Klf9, a cell-cycle regulator. Our results disclose a function of DREAM and KChIP-2 in Ig subclass production in B lymphocytes.

Overall design: We used Affymetrix microarrays (GeneChip Mouse Genome 430 2.0) to compare global gene expression in wild type (WT) versus transgenic B cells (Tg), unstimulated and 2 days after LPS + IL4 stimulation. For ech type of sample three hybridizations were carried-out (independent biological replicates).

Background corr dist: KL-Divergence = 0.0300, L1-Distance = 0.0974, L2-Distance = 0.0115, Normal std = 0.9421

0.423 Kernel fit Pairwise Correlations Normal fit

Density 0.212

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

BCells_WildType_day0_REP1BCells_WildType_day0_REP2BCells_WildType_day0_REP3BCells_Transgenic_day0_REP1 BCells_Transgenic_day0_REP2(0.100776) BCells_Transgenic_day0_REP3(0.0804453) BCells_WildType_day2_REP1(0.0692222)BCells_WildType_day2_REP2 (0.0716032)BCells_WildType_day2_REP3 (0.0740124)BCells_Transgenic_day2_REP1 (0.148326) BCells_Transgenic_day2_REP2(0.0782602) BCells_Transgenic_day2_REP3(0.0579213) (0.108604) (0.0761064) (0.052017)[ (0.0827059)min ] [ medium ] [ max ] CEM 1 Cks1b 562.6 4695.4 6061.0 P ( S | Z, I ) = 1.00 Skp2 101.5 455.4 611.6 Mean Corr = 0.84081 Ccne1 313.7 1039.0 1357.2 Cul1 1996.6 2481.6 2959.2 Skp1a 1918.1 3684.1 4375.9 Ercc6l 309.9 1203.6 1380.5 Cdc6 142.6 2788.6 3422.9 Exo1 52.1 1109.2 1569.8 Fen1 972.3 3745.6 5276.4 Cdk1 389.6 5943.4 6640.3 CEM 1 + Cdca5 209.9 1669.7 1959.6 Top 10 Genes Gins1 182.7 1148.4 1371.0 Tipin 1347.3 8289.2 9257.3 Mcm5 1047.5 6431.7 7571.6 Rad51 208.8 2731.3 3243.1

Null module Cdkn1b Cdk2 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(0.0327577) GD rep2Vehicule (control)17, at female(0.0305535) biologicalGD rep3Vehicule (control)17, at male(0.0468823) biologicalGDFlutamide rep1 at(control)17, maleGD biological(0.0635187) Flutamide17, rep2at treated malebiologicalGD (0.0583751) Flutamide17, rep3at treated malebiologicalGD (0.0668328)rep1 Vehicule17, at treatedmaleGD biological(0.0520679) rep2 18,Vehicule at (control) malebiologicalGD (0.10642) rep3 18,Vehicule at (control) biologicalfemaleGD (0.042216) rep1 18,Vehicule (control) at biologicalfemale(0.0502557) GD rep2Vehicule (control)18, at female(0.0740787) biologicalGD rep3Vehicule (control)18, at male(0.0900746) biologicalGD rep1 at(control)18, maleGD biological(0.0773279) 18, rep2at malebiologicalGD (0.0323996) 18, rep3at biologicalGD (0.0535379)rep1 [18, min biological(0.0494473) rep2 (0.029951)] rep3 (0.0433033)[ medium ] [ max ] CEM 1 Cks1b 2170.3 5211.3 5758.7 P ( S | Z, I ) = 1.00 Skp2 1586.6 3794.1 4600.3 Mean Corr = 0.83501 Ccne1 168.3 344.5 560.0 Cul1 1483.8 1668.5 1829.3 Skp1a 4596.0 6202.6 7358.3 Ercc6l 607.2 1349.2 1777.6 Cdc6 342.7 1366.2 1846.9 Exo1 237.4 801.1 1140.9 Fen1 742.8 1745.3 2520.2 Cdk1 2455.1 4678.0 4966.2 CEM 1 + Cdca5 293.9 668.9 763.5 Top 10 Genes Gins1 188.9 534.8 722.3 Tipin 1619.8 3418.7 4272.2 Mcm5 538.6 1679.3 2113.4 Rad51 390.8 1238.9 1497.5

Null module Cdkn1b Cdk2 GEO Series "GSE28237" 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=GSE28237 Status: Public on Mar 29 2011 Title: T cell dependent immune responses: B cell activation and differentiation Group1 Fo, Group2 GC1, Group3 GC2 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19265543 Summary & Design: Summary: Upon immunization with a T cell dependent antigen naive follicular B cells (Fo) are activated and a germinal center reaction is induced. Within the next 2 weeks large germinal centers develop where the process of affinity maturation takes place. To analyze the gene expression profile of resting and activated B cells, follicular B cells (Fo), B cells from early (GC1) and late germinal centers (GC2) were isolated and their gene expression profile compared.

Overall design: After total RNA extraction, reverse transcription, cDNA extraction, the biotinylated cRNA was transcribed, fragmented, and 15 ´g cRNA hybridized in duplicates for each of the three groups to the GeneChip arrays. Group1: Fo, Group2: GC1, Group3: GC2. Lists of differentially regulated genes were created using High Performance Chip Data Analysis (HPCDA) with Bioretis database (http://www.bioretis-analysis.de). Worldwide data sharing is possible via Bioretis, please ask the authors.

Background corr dist: KL-Divergence = 0.0482, L1-Distance = 0.0328, L2-Distance = 0.0015, Normal std = 0.5930

0.682 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

T cell dependentT cell dependentT cellimmune dependentT cellimmune responses: dependentT cellimmune responses: dependent TB cellimmunecell responses: dependent activation B immunecell responses: activation B andimmunecell responses: differentiationactivation B andcell responses: differentiationactivation [B andcellmin Group1differentiationactivation B andcell ] Group1 differentiationactivationfollicular and Group2 differentiationfollicular B and [cells medium Group2 differentiationearly (Fo),B cells germinal Group3 Chipearly (Fo), 2 germinal (0.174629)Group3 Chipcenterlate ] germinal 3 (0.209474) Bcellscenterlate germinal center(GC1) Bcells[ max Chip1 Bcenter(GC1) cell (0.334966)(GC2) Chip2B] cell Chip1 (0.0805204)(GC2) (0.0391217) Chip2 (0.161289) CEM 1 Cks1b 176.8 643.1 1648.8 P ( S | Z, I ) = 1.00 Skp2 118.1 367.8 681.3 Mean Corr = 0.83298 Ccne1 153.1 442.6 684.0 Cul1 3375.3 4394.5 4683.5 Skp1a 1561.5 2507.5 3254.3 Ercc6l 363.4 883.2 1702.7 Cdc6 159.2 1398.9 3777.0 Exo1 51.9 895.3 1276.9 Fen1 142.2 401.5 606.9 Cdk1 136.6 2169.3 3249.7 CEM 1 + Cdca5 27.0 711.8 968.0 Top 10 Genes Gins1 268.1 1111.4 1956.1 Tipin 973.8 3859.2 6925.3 Mcm5 79.0 424.3 590.2 Rad51 225.4 1032.2 2218.5

Null module Cdkn1b Cdk2 GEO Series "GSE48790" 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=GSE48790 Status: Public on Jul 12 2013 Title: Expression data from GTF2i mutated ES cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23831514 Summary & Design: Summary: Data present the expression analysis of different mouse ES cell line with altered expression of GTF2I.

Overall design: We used microarrays to detail the global programme of gene expression underlying altered expression of GTF2I and identified distinct classes of deregulated genes

Background corr dist: KL-Divergence = 0.0303, L1-Distance = 0.0391, L2-Distance = 0.0018, Normal std = 0.6989

0.613 Kernel fit Pairwise Correlations Normal fit

Density 0.307

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

HPRTKO,HPRTKO, biologicalGTF2iTrap biological rep1GTF2iTrap (0.218113)line, rep2Wild-type, biological (0.328214)line,Wild-type, biological biological rep Gtf2i1 (0.0911164) biological rep Mutant rep1 Gtf2i2 (0.0486788) (0.0547967) Mutantline, rep2 biological (0.160801) line, biological rep 1 (0.054883) rep[ 2min (0.0433965) ] [ medium ] [ max ] CEM 1 Cks1b 5358.5 5699.0 7191.2 P ( S | Z, I ) = 1.00 Skp2 1009.3 1153.8 1395.9 Mean Corr = 0.83263 Ccne1 1274.3 1605.5 2884.6 Cul1 1522.1 1622.2 1874.9 Skp1a 10930.1 11473.8 13021.1 Ercc6l 1003.8 1114.4 1646.5 Cdc6 699.9 1335.4 1420.1 Exo1 985.6 1216.8 2106.8 Fen1 1269.1 1952.3 2792.3 Cdk1 4427.5 5449.9 6114.1 CEM 1 + Cdca5 1329.2 1870.5 2262.1 Top 10 Genes Gins1 1482.0 2236.8 2423.3 Tipin 6875.7 7869.8 11096.2 Mcm5 1812.7 3084.8 3589.0 Rad51 2832.4 4939.4 5774.6

Null module Cdkn1b Cdk2 GEO Series "GSE13874" 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=GSE13874 Status: Public on Mar 05 2009 Title: microRNA-1 negatively regulates expression of the hypertrophy-associated genes calmodulin and Mef2a Organism: Mus musculus Experiment type: Non-coding RNA profiling by array Platform: GPL1261 Pubmed ID: 19188439 Summary & Design: Summary: Calcium signaling is a central regulator of cardiomyocyte growth and function. Calmodulin is a critical mediator of calcium signals. Because the amount of calmodulin within cardiomyocytes is limiting, precise regulation of calmodulin expression may be an important for regulation of calcium signaling. In this study, we show for the first time that calmodulin levels are regulated post-transcriptionally in heart failure. The cardiomyocyte-restricted microRNA miR-1 inhibited translation of calmodulin-encoding mRNAs via highly conserved target sites within their 3-untranslated regions. In keeping with its effect on calmodulin expression, miR-1 downregulated calcium-calmodulin signaling through the calcineurin to NFAT. miR-1 also negatively regulated expression of Mef2a and Gata4, key transcription factors that mediate calcium-dependent changes in gene expression. Consistent with downregulation of these hypertrophy-associated genes, miR-1 attenuated cardiomyocyte hypertrophy in cultured neonatal rat cardiomyocytes and in the intact adult heart. Our data indicate that miR-1 regulates cardiomyocyte growth responses by negatively regulating the calcium-signaling components calmodulin, Mef2a, and Gata4.

Overall design: We show that miR-1 is downregulated in a murine heart failure model. miRNAs expression changes were measured in calcineurin transgenic model of heart failure and control mice using a Luminex platform. Reduced miR-1 expression was associated with broad alteration in expression of predicted target genes. To test this, we measured miRs including miR-1 and genome wide transcriptome changes in vivo and in vitro system. Calcineurin transgenic heart was compared to nontransgenic heart (NTg vs. CNTg). We also investigated the gene expression changes during the course of cardiomyocytes differentiation using DMSO treated P19CL6 cell lines. Two time points (day 6 and day 10) were compared to identified the gene expression changes of predicted miR-1 targets (Day 6 vs. Day 10).

Background corr dist: KL-Divergence = 0.0212, L1-Distance = 0.0629, L2-Distance = 0.0054, Normal std = 0.8282

0.482 Kernel fit Pairwise Correlations Normal fit

Density 0.241

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

NTg, biologicalNTg, biologicalNTg, replicate biologicalNTg, replicate 1 (Affymetrix) biologicalCalcineurin replicate 2 (Affymetrix)Calcineurin replicate (0.0351745) 3 (Affymetrix)Tg,Calcineurin biological (0.0474812) 4 (Affymetrix)Tg,Calcineurin biological (0.0509705) replicate Tg,Differentiating biological (0.0872189) replicate Tg, 1 (Affymetrix)Differentiating biological replicate 2 P19CL6(Affymetrix)Differentiating replicate (0.0386328) 3 P19CL6(Affymetrix)Differentiating cells (0.0538258) 4at P19CL6(Affymetrix)Differentiating cellsday (0.0320845)6 at afterP19CL6Differentiating cellsday DMSO(0.0347481)6 at afterP19CL6 cellsday treatment, DMSO6 at afterP19CL6 cellsday treatment, DMSO10 at replicate aftercellsday treatment, 10 DMSOat replicate[ afterday 1min (Affymetrix) 10 treatment,DMSO replicate after 2 (Affymetrix)] treatment,DMSO (0.0867184)replicate 3 (Affymetrix) treatment, (0.153646)replicate [1 (Affymetrix)medium (0.109144)replicate 2 (Affymetrix) (0.142973) 3 (Affymetrix) ] (0.0918395) (0.0355431)[ max ] CEM 1 Cks1b 207.3 420.9 6848.9 P ( S | Z, I ) = 1.00 Skp2 5.2 39.7 1402.0 Mean Corr = 0.82530 Ccne1 83.3 127.5 332.6 Cul1 1288.2 1514.0 4218.9 Skp1a 4192.4 4949.2 11017.3 Ercc6l 115.4 207.7 719.8 Cdc6 18.1 40.4 1231.2 Exo1 44.1 75.3 1486.0 Fen1 84.2 142.7 1833.1 Cdk1 51.2 226.4 7170.4 CEM 1 + Cdca5 31.3 67.2 893.2 Top 10 Genes Gins1 146.0 237.3 1106.0 Tipin 192.1 328.8 3187.8 Mcm5 145.7 223.4 4067.2 Rad51 27.3 59.4 1409.6

Null module Cdkn1b Cdk2 GEO Series "GSE13873" 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=GSE13873 Status: Public on Mar 05 2009 Title: Expression data from murine gastric epithelium Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19454706 Summary & Design: Summary: Chronic infection with the bacterial pathogen Helicobacter pylori is a risk factor for the development of gastric cancer, yet remains asymptomatic in a majority of individuals. We report here that the C57Bl6 mouse model of experimental infection with the closely related H. felis recapitulates this wide range in host susceptibility. A majority of infected mice develop premalignant lesions such as gastric atrophy, compensatory epithelial hyperplasia and intestinal metaplasia, whereas a minority is completely protected from preneoplasia. Protection is associated with the failure to mount an IFN-gamma response to the infection and an associated high Helicobacter burden. We demonstrate that IFN-gamma is essential for clearance of Helicobacter, but also mediates the formation of preneoplastic lesions. We further provide evidence that IFN-gamma triggers a specific transcriptional program in murine gastric epithelial cells in vitro and in vivo, and induces their preferential transformation to the hyperplastic phenotype. In summary, our data suggest a dual role for IFN-gamma in Helicobacter pathogenesis that could provide an explanation for the differential susceptibility to H. pylori-induced gastric pathology in the human population.

Keywords: response to in vitro stimulus / comparison of histopathological states

Overall design: We chose mice for gene expression profiling that following Helicobacter infection had (a) symptoms of gastritis, but no epithelial changes, (b) atrophic gastritis accompanied by corpus gland hyperplasia or (c) atrophic gastritis accompanied by intestinal metaplasia. An uninfected control group was also included in the analysis, as were two groups of mice that lacked mature T- and B-cells due to a deletion mutation in the rag1 gene (Rag-1-/-) and that were either experimentally infected or served as Rag-1-/- uninfected controls. To see the effects of IFNg on murine gastric epithelial cells we analysed an immortalized murine primary gastric epithelial cell line treated with three different concentrations of IFNg in comparison to an untreated control.

Background corr dist: KL-Divergence = 0.0517, L1-Distance = 0.0400, L2-Distance = 0.0031, Normal std = 0.5764

0.692 Kernel fit Pairwise Correlations Normal fit

Density 0.346

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

IMPGE untreatedIMPGE IFNGIMPGE (0.150386) 1 (0.135978)IFNGIMPGE 2 (0.162399)IFNGstomach 3 (0.158724)stomach uninfectedstomach uninfected 1 (0.020261)stomach infected 2 (0.018282)stomach infected gastritisstomach infected gastritis 1 (0.0132482)stomach infected gastritis 2 (0.00368068)stomach infected gastritis 3 (0.0285123)stomach infected metaplasia 4 (0.00538515)stomach infected hyperplasia 1stomach (0.0113161)infected hyperplasia stomach1 infected(0.0179735) hyperplasia stomach2 infected(0.00949795) hyperplasia stomach3 infected(0.0111406) hyperplasia stomach4 infected(0.00993046) metaplasia stomach5 infected(0.013461) metaplasia 2stomach (0.0534379)infected metaplasia 3stomach (0.0234443)uninfected metaplasia 4stomach (0.0170747)uninfected Rg 5stomach (0.0170346) infected1 (0.0108387) Rgstomach infected2 Rg (0.0242809) 1stomach (0.00872702)infected Rg 2stomach (0.0101745)infected Rg 3 (0.00859968)infected Rg 4 (0.0396124) Rg 5 (0.0165996)[ min ] [ medium ] [ max ] CEM 1 Cks1b 437.4 761.9 4171.0 P ( S | Z, I ) = 1.00 Skp2 114.4 274.4 1310.3 Mean Corr = 0.80513 Ccne1 149.9 197.7 650.4 Cul1 780.2 1079.1 2129.6 Skp1a 3309.9 5043.0 6480.5 Ercc6l 208.2 365.9 2060.5 Cdc6 165.2 320.3 968.3 Exo1 34.8 90.5 573.8 Fen1 182.1 461.1 2175.6 Cdk1 642.4 1471.8 8807.3 CEM 1 + Cdca5 126.0 281.4 805.2 Top 10 Genes Gins1 197.1 396.4 1033.8 Tipin 389.8 620.9 4629.2 Mcm5 224.9 580.2 2473.2 Rad51 220.2 511.3 2808.7

Null module Cdkn1b Cdk2 GEO Series "GSE46185" 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=GSE46185 Status: Public on Apr 19 2013 Title: Genome-wide gene expression profiling revealed a critical role for GATA3 in the maintenance of the Th2 cell identity Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23824597 Summary & Design: Summary: Functionally polarized CD4+ T helper (Th) cells such as Th1, Th2 and Th17 cells are central to the regulation of acquired immunity. However, the molecular mechanisms governing the maintenance of the polarized functions of Th cells remain unclear. GATA3, a master regulator of Th2 cell differentiation, initiates the expressions of Th2 cytokine genes and other Th2-specific genes. GATA3 also plays important roles in maintaining Th2 cell function and in continuous chromatin remodeling of Th2 cytokine gene loci. However, it is unclear whether continuous expression of GATA3 is required to maintain the expression of various other Th2-specific genes. In this report, genome-wide DNA gene expression profiling revealed that GATA3 expression is critical for the expression of a certain set of Th2-specific genes. We demonstrated that GATA3 dependency is reduced for some Th2-specific genes in fully developed Th2 cells compared to that observed in effector Th2 cells, whereas it is unchanged for other genes. Moreover, effects of a loss of GATA3 expression in Th2 cells on the expression of cytokine and cytokine receptor genes were examined in detail. A critical role of GATA3 in the regulation of Th2-specific gene expression is confirmed in in vivo generated antigen-specific memory Th2 cells. Therefore, GATA3 is required for the continuous expression of the majority of Th2-specific genes involved in maintaining the Th2 cell identity.

Overall design: Mock-transfected and GATA3 siRNA-transfected Th2 and Th2-4th cells are profiled for mRNA expression

Background corr dist: KL-Divergence = 0.0332, L1-Distance = 0.0373, L2-Distance = 0.0018, Normal std = 0.6839

0.604 Kernel fit Pairwise Correlations Normal fit

Density 0.302

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

Th2 (controlTh2 (control siRNA)Th2 (Gata3 siRNA)(0.280715)Th2-4th siRNA) a-TCRTh2-4th (control a-TCR stimTh2-4th (control siRNA)(0.127612) stim (Gata3(0.146815) siRNA)(0.18369) siRNA) a-TCR a-TCR stim (0.138524) stim[ min (0.122644) ] [ medium ] [ max ] CEM 1 Cks1b 1489.7 5352.9 6960.3 P ( S | Z, I ) = 1.00 Skp2 328.7 849.0 1073.2 Mean Corr = 0.80377 Ccne1 306.3 703.1 1356.8 Cul1 1763.4 2081.0 2744.1 Skp1a 6411.2 8725.6 9319.7 Ercc6l 261.2 801.8 1360.8 Cdc6 368.6 1637.8 2986.7 Exo1 229.5 1338.3 1530.3 Fen1 691.4 2074.7 2745.4 Cdk1 1548.1 7696.7 8955.5 CEM 1 + Cdca5 283.0 1034.2 1955.4 Top 10 Genes Gins1 319.7 1531.7 2650.4 Tipin 2567.1 5503.2 7311.7 Mcm5 637.9 1676.2 2305.2 Rad51 709.6 2688.6 5567.0

Null module Cdkn1b Cdk2 GEO Series "GSE26616" 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=GSE26616 Status: Public on Jun 09 2011 Title: EZH1 and EZH2 Co-Govern Histone H3-K27 Trimethylation and Are Essential for Hair Follicle Homeostasis and Wound Repair Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21317239 Summary & Design: Summary: Polycomb protein group (PcG)-dependent trimethylation on H3-K27(H3K27me3) regulates identity of embryonic stem cells (SCs). How H3K27me3 governs adult SCs and tissue development is unclear. Here, we conditionally target H3-K27-methyltransferases Ezh2 and Ezh1 to address their roles in mouse skin homeostasis. Postnatal phenotypes appear only in doubly-targeted skin, where H3K27me3 is abolished, revealing functional redundancy in EZH1/2 proteins. Surprisingly, while Ezh1/2-null hair follicles (HFs) arrest morphogenesis and degenerate due to defective proliferation and increased apoptosis, epidermis hyperproliferates and survives engraftment. mRNA-microarray studies reveal that despite these striking phenotypic differences, similar genes are upregulated in HF and epidermal Ezh1/2-null progenitors. Featured prominently are a) PcG-controlled non-skin lineage genes, whose expression is still significantly lower than in native tissues, and b) the PcG-regulated Ink4a/Inkb/Arf locus. Interestingly, even though Ink4a/Arf/Ink4b genes are fully activated in HF cells, they only partially so in epidermal-progenitors. Importantly, transduction of Ink4b/Ink4a/Arf shRNAs restores proliferation/survival of Ezh1/2-null HF progenitors in vitro, pointing towards the relevance of this locus to the observed HF phenotypes. Our findings reveal new insights into Polycomb-dependent tissue control and provide a new twist to how different progenitors within one tissue respond to loss of H3K27me3.

Overall design: RNAs from FACS-purified WT and Ezh1/2 2KO ORS, matrix and epidermal cells (Rendl et al., 2005) were provided to the Genomics Core Facility, MSKCC for quality control, quantification, reverse transcription, labeling and hybridization to MOE430A 2.0 microarray chips (Affymetrix). Arrays were scanned per the manufacturers specifications for the Affymetrix MOE430v2 chip. Images were background-subtracted. Probesets were identified as differentially expressed when the absolute fold change was ¥2. Probesets selected for visualization were log2 transformed and were analyzed with hierarchical clustering (Pearson correlation, average linkage), and visualized with heatmaps to assist in interpretation.

Background corr dist: KL-Divergence = 0.0410, L1-Distance = 0.0331, L2-Distance = 0.0015, Normal std = 0.6238

0.652 Kernel fit Pairwise Correlations Normal fit

Density 0.326

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

Ezh1/2 2KOEzh1/2 FACS 2KOEzh1/2 purified FACS 2KOEzh1/2 purified basalFACS WTEzh1/2 epidermal purifiedFACS matrix WTEzh1/2 purified FACS cellsORS cells WT (0.100665) cellspurified basalFACS(0.102714) (0.121745) epidermal purified matrix cellsORS cells [ (0.407849)cells (0.104637)min (0.162389) ] [ medium ] [ max ] CEM 1 Cks1b 1921.2 3734.3 4917.3 P ( S | Z, I ) = 1.00 Skp2 202.5 289.4 865.5 Mean Corr = 0.80331 Ccne1 178.3 438.0 567.7 Cul1 1452.6 1830.6 2370.5 Skp1a 8093.5 11216.3 12681.8 Ercc6l 334.7 504.8 722.3 Cdc6 96.0 162.8 434.0 Exo1 121.7 254.3 495.1 Fen1 333.5 560.2 1365.4 Cdk1 1482.1 3379.4 4032.3 CEM 1 + Cdca5 252.1 375.7 865.0 Top 10 Genes Gins1 491.1 728.5 1572.8 Tipin 1773.5 2500.0 3596.3 Mcm5 1083.0 1362.4 2059.0 Rad51 754.0 1532.7 2017.7

Null module Cdkn1b Cdk2 GEO Series "GSE12464" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 23 -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=GSE12464 Status: Public on May 20 2009 Title: Transcriptional signatures of Itk-deficiency using CD3+ T-cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19450280 Summary & Design: Summary: The Tec-family kinase Itk plays an important role during T-cell activation and function, and controls also conventional versus innate-like T-cell development. We have characterized the transcriptome of Itk-deficient CD3+ T-cells, including CD4+ and CD8+ subsets, using Affymetrix microarrays. The largest difference between Itk-/- and Wt CD3+ T-cells was found in unstimulated cells, e.g. for killer cell lectin-like receptors. Compared to anti-CD3-stimulation, anti-CD3/CD28 significantly decreased the number of transcripts suggesting that the CD28 co-stimulatory pathway is mainly independent of Itk. The signatures of CD4+ and CD8+ T-cell subsets identified a greater differential expression than in total CD3+ cells. Cyclosporin (CsA)-treatment had a stronger effect on transcriptional regulation than Itk-deficiency, suggesting that only a fraction of TCR-mediated calcineurin/NFAT-activation is dependent on Itk. Bioinformatic analysis of NFAT-sites of the group of transcripts similarly regulated by Itk-deficiency and CsA-treatment, followed by chromatin-immunoprecipitation, revealed NFATc1-binding to the Bub1, IL7R, Ctla2a, Ctla2b, and Schlafen1 genes. Finally, to identify transcripts that are regulated by Tec-family kinases in general, we compared the expression profile of Itk-deficient T-cells with that of Btk-deficient B-cells and a common set of transcripts was found. Taken together, our study provides a general overview about the global transcriptional changes in the absence of Itk.

Overall design: CD3+ T-cells from pooled suspensions of spleen and lymph nodes of Wt and Itk knockout mice on C57BL/6 background were isolated after negative depletion. Unstimulated as well as stimulated T-cells were studied. Stimulations were done with anti-CD3 (1 mg/ml) with or without anti-CD28 (3 mg/ml) in the presence or absence of CsA (1 mg/ml) for 24 hrs. For each stimulus, at least duplicate samples were used.

Background corr dist: KL-Divergence = 0.1100, L1-Distance = 0.0376, L2-Distance = 0.0025, Normal std = 0.4333

0.938 Kernel fit Pairwise Correlations Normal fit

Density 0.469

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 unstimulated typeWild unstimulated typeItk 1 unstimulatedknockout(0.0486539)Itk 2 knockout(0.056134) unstimulatedWild 3 (0.0960179) typeunstimulatedWild CD3-stimulated 1 type (0.0504015)Wild CD3-stimulated 2 type (0.0348685)Wild CD3-stimulated 1 typedayWild 1CD3-stimulated 2(0.0249396) typedayItk 1 CD3-stimulatedknockout 3(0.0129863) dayItk 1 knockout 1(0.0706699) dayCD3-stimulatedWild 2 2(0.02254) typedayCD3-stimulatedWild 2CD3CD28-stimulated (0.0198252) type 1Wild (0.00602063) CD3CD28-stimulated type 2Wild (0.017138) CD3CD28-stimulated typeWild 1 CD3CD28-stimulated day type Itk1 2(0.053104) CD3CD28-stimulatedknockoutday Itk1 3(0.0297219) knockoutday CD3CD28-stimulated Wild1 1(0.0632981) day typeCD3CD28-stimulated Wild2 2(0.0156985) CD3-stimulated day type Wild2 (0.0127356) CD3-stimulated 1type (0.0466113)Wild CD3CD28-stimulated and 2type (0.0368798) CsA-treated CD3CD28-stimulated and CsA-treated 1 (0.0619508) and 2CsA-treated (0.096077)[ and min CsA-treated 1] (0.0351348) 2 (0.088593)[ medium ] [ max ] CEM 1 Cks1b 402.5 1647.1 2904.2 P ( S | Z, I ) = 1.00 Skp2 131.4 472.0 1008.1 Mean Corr = 0.79884 Ccne1 248.6 998.9 1853.6 Cul1 1700.8 2630.5 3811.3 Skp1a 3295.1 4452.9 5539.3 Ercc6l 194.1 1258.5 2443.6 Cdc6 165.5 2746.5 3895.9 Exo1 85.4 1434.1 1994.0 Fen1 331.5 1614.4 3129.6 Cdk1 326.9 2923.9 5248.4 CEM 1 + Cdca5 157.0 1207.3 2277.9 Top 10 Genes Gins1 142.1 1563.2 2684.4 Tipin 854.4 4626.6 7176.7 Mcm5 332.1 1927.1 4420.8 Rad51 231.4 2743.3 3972.0

Null module Cdkn1b Cdk2 GEO Series "GSE27605" 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=GSE27605 Status: Public on Mar 14 2011 Title: The intestinal stem cell signature identifies colorectal cancer stem cells and predicts disease relapse Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21419747 Summary & Design: Summary: Using EphB2 or the ISC marker Lgr5, we have FACS-purified and profiled intestinal stem cells (ISCs), crypt proliferative progenitors and late transient amplifying cells to define a gene expression program specific for normal ISCs.

A frequent complication in colorectal cancer (CRC) is regeneration of the tumor after therapy. The intestinal stem cell signature predicts disease relapse in CRC and identifies a stem cell-like population that displays robust tumor- initiating capacity in immunodeficient mice as well as long-term self-renewal potential.

Overall design: We FACS purified mouse intestinal crypt cells according to their EphB2 or Lgr5 contents. We used Affymetrix chips to hybridize 2 samples from EphB2 high, 2 samples from EphB2 medium and 2 samples from EphB2 low cells (one sample from each group in a first hybridization on February 2009 plus an additional sample from each group on March 2009). Additionally, we hybridized one sample from Lgr5-EGFP high and one sample from Lgr5-EGFP low cells, obtained from Lgr5-EGFP knock-in mice (Barker et al., 2007).

Background corr dist: KL-Divergence = 0.0298, L1-Distance = 0.0338, L2-Distance = 0.0014, Normal std = 0.6870

0.614 Kernel fit Pairwise Correlations Normal fit

Density 0.307

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

intestine-Lgr5High-R1intestine-Lgr5Low-R1intestine-EphB2High-R1 intestine-EphB2Medium-R1(0.204546) (0.0269838)intestine-EphB2Low-R1intestine-EphB2High-R2 (0.0663849)intestine-EphB2Medium-R2 (0.0493833)intestine-EphB2Low-R2 (0.283285) (0.100574) (0.0560888) (0.212753)[ min ] [ medium ] [ max ] CEM 1 Cks1b 396.0 1899.3 2640.5 P ( S | Z, I ) = 1.00 Skp2 94.3 232.7 259.4 Mean Corr = 0.78637 Ccne1 108.2 571.5 646.5 Cul1 2771.3 3138.8 3252.7 Skp1a 4951.5 5186.8 5371.0 Ercc6l 123.5 640.6 849.6 Cdc6 132.9 684.7 869.9 Exo1 87.1 731.0 973.7 Fen1 575.0 2217.4 2758.4 Cdk1 773.8 3314.4 4331.3 CEM 1 + Cdca5 177.2 800.9 1119.9 Top 10 Genes Gins1 291.8 1816.9 2267.2 Tipin 179.4 1125.4 1385.6 Mcm5 259.1 1561.4 2101.3 Rad51 180.4 885.6 1163.0

Null module Cdkn1b Cdk2 GEO Series "GSE10176" 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=GSE10176 Status: Public on Jan 16 2008 Title: Inducible repositioning of genes to the inner nuclear membrane Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18272965 Summary & Design: Summary: Nuclear compartmentalization appears to play an important role in regulating metazoan genes. While studies on immunoglobulin (Ig) and other loci have correlated positioning at the nuclear lamina with gene repression, the functional consequences of this compartmentalization remain untested. We devised an approach for inducible tethering of genes to the inner nuclear membrane (INM) and demonstrate with 3D DNA-ImmunoFISH, repositioning of chromosomal regions to the nuclear lamina. Relocalization requires mitotic nuclear envelope breakdown and reformation. Tethering leads to the accumulation of lamin and INM proteins but not to association with pericentromeric heterochromatin or nuclear pore complexes. Recruitment of genes to the INM can result in their transcriptional repression. Using DamID we show that as is the case for our model system, inactive Ig loci at the nuclear periphery are contacted by INM and lamina components. We propose that such molecular interactions are used to compartmentalize and limit the accessibility of Ig loci.

Keywords: Inducible

Overall design: We used microarray to analyze the transcription status of genomic regions are inducibly tethered to the INM

Background corr dist: KL-Divergence = 0.0247, L1-Distance = 0.0189, L2-Distance = 0.0005, Normal std = 0.7016

0.569 Kernel fit Pairwise Correlations Normal fit

Density 0.284

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

clone M,clone untethered, M,clone tethered, M,replicateclone untethered, replicate M, clone1 tethered, (0.239456) 1 M,replicate (0.232629)clone untethered, replicate M, 2 tethered, (0.140224) 2 replicate (0.0619162) replicate 3 (0.174593) 3 (0.15118)[ min ] [ medium ] [ max ] CEM 1 Cks1b 1472.1 2462.3 2974.3 P ( S | Z, I ) = 1.00 Skp2 234.1 750.2 950.1 Mean Corr = 0.76821 Ccne1 456.2 858.7 942.5 Cul1 1829.5 1894.0 2077.5 Skp1a 2570.4 3654.9 3950.6 Ercc6l 410.0 832.1 997.7 Cdc6 123.0 631.1 888.3 Exo1 198.3 443.2 535.1 Fen1 293.9 892.0 1262.6 Cdk1 1403.1 3873.3 4526.9 CEM 1 + Cdca5 326.2 484.8 586.0 Top 10 Genes Gins1 305.9 576.1 580.3 Tipin 675.2 1240.6 1355.2 Mcm5 778.7 2539.6 2921.4 Rad51 300.4 798.3 945.2

Null module Cdkn1b Cdk2 GEO Series "GSE51483" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 45 -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=GSE51483 Status: Public on May 19 2014 Title: Transcriptional Atlas of Cardiogenesis Maps Congenital Heart Disease Interactome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24803680 Summary & Design: Summary: Mammalian heart development is built on highly conserved molecular mechanisms with polygenetic perturbations resulting in a spectrum of congenital heart diseases (CHD). However, the transcriptional landscape of cardiogenic ontogeny that regulates proper cardiogenesis remains largely based on candidate-gene approaches. Herein, we designed a time-course transcriptome analysis to investigate the genome-wide expression profile of innate murine cardiogenesis ranging from embryonic stem cells to adult cardiac structures. This comprehensive analysis generated temporal and spatial expression profiles, prioritized stage-specific gene functions, and mapped the dynamic transcriptome of cardiogenesis to curated pathways. Reconciling the bioinformatics of the congenital heart disease interactome, we deconstructed disease-centric regulatory networks encoded within this cardiogenic atlas to reveal stage-specific developmental disturbances clustered on epithelial-to-mesenchymal transition (EMT), BMP regulation, NF-AT signaling, TGFb-dependent induction, and Notch signaling. Therefore, this cardiogenic transcriptional landscape defines the time-dependent expression of cardiac ontogeny and prioritizes regulatory networks at the interface between health and disease.

Overall design: To interrogate the temporal and spatial expression profiles across the entire genome during mammalian heart development, we designed a time-course microarray experiment using the mouse model at defined stages of cardiogenesis, starting with embryonic stem cells (ESC, R1 stem cell line), early embryonic developmental stages: E7.5 whole embryos, E8.5 heart tubes, left and right ventricle tissues at E9.5, E12.5, E14.5, E18.5 to 3 days after birth (D3) and adult heart (Figure 1A). At each time point, microarray experiments were performed on triplicate biological samples. Starting at E9.5, tissue samples from left ventricles (LV) and right ventricles (RV) were microdissected for RNA purification and microarray analysis to determine spatially differential gene expression between LV and RV during heart development.

Background corr dist: KL-Divergence = 0.0679, L1-Distance = 0.0271, L2-Distance = 0.0013, Normal std = 0.5057

0.789 Kernel fit Pairwise Correlations Normal fit

Density 0.394

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 R1Mouse Stem R1Mouse Cells Stem R1.1R1Mouse Cells Stem (0.0564228) R1.2E7.5Mouse Cells (0.0635908)whole R1.3E7.5Mouse embryo (0.0587934)whole E7.5Mouse embryo tissuewhole E8.5Mouse E7.1embryo tissuewhole E8.5Mouse (0.0420103) E7.2heart tissuewhole E8.5Mouse (0.0438899) tissue E7.3heart whole E9.5Mouse (0.0528879)(heart tissue heart left E9.5Mousetube) ventricle(heart tissue left E8.1 E9.5Mousetube) ventricle(heart tissue (0.0168637) left E8.2 E9.5Mousetube) ventricle E9L.1 tissue (0.0238107) right E8.3 E9.5Mouse (0.0114817) E9L.2ventricletissue (0.0268012) right E9.5Mouse (0.0139473) E9L.3ventricle tissueright E12.5Mouse (0.0212526) ventricle E9R.1 tissue left E12.5Mouse ventricle(0.0278755) E9R.2 tissue left E12.5Mouse ventricle(0.0160074) E9R.3tissue left E12.5Mouse ventricle(0.0126357) E12L.1 tissue right E12.5Mouse (0.00464797)E12L.2ventricletissue right E12.5Mouse (0.00302996)E12L.3ventricle tissueright E14.5Mouse (0.00216225)ventricle E12R.1 tissueleft E14.5Mouse ventricle E12R.2(0.0040888) tissueleft E14.5Mouse ventricle tissue E12R.3(0.00151824) left E14.5Mouse ventricle E14L.1 tissue (0.010628) right E14.5Mouse (0.00657654)E14L.2ventricletissue right E14.5Mouse (0.011475)E14L.3ventricle tissueright E18.5Mouse (0.00586514)ventricle E14R.1 tissueleft E18.5Mouse ventricle E14R.2(0.00676872) tissueleft E18.5Mouse ventricle tissue E14R.3(0.00409031) left E18.5Mouse ventricle E18L.1 tissue (0.0339199) right E18.5Mouse (0.0635957)E18L.2ventricletissue right E18.5Mouse (0.0202443)E18L.3ventricle tissueright leftMouse (0.0211219)ventricle E18R.1 tissue leftMouse ventricle E18R.2 (0.0177992)tissue leftMouse ventricle atE18R.3 (0.0260448)tissue 3rightMouse days at (0.0151429)ventricletissue after3rightMouse days birth atventricle aftertissue3rightAdult days D3L.1 birth ventricle mouseat aftertissueAdult 3(0.0164274) D3L.2 days birth leftmouseat tissueAdult after3(0.0171964) ventricleD3L.3 days leftbirthmouseatAdult after3(0.0144077) ventricle days D3R.1tissue leftbirthmouseAdult after ventricle (0.0187901) AdltL.1D3R.2tissue rightbirthmouseAdult (0.0145439) AdltL.2(0.0283502)ventricleD3R.3tissue rightmouse (0.0125169) AdltL.3(0.0267182)ventricle tissueright (0.0259871)ventricle AdltR.1 tissue AdltR.2(0.0296866)tissue[ min AdltR.3(0.0229133) ] (0.0254715) [ medium ] [ max ] CEM 1 Cks1b 316.7 6533.6 11091.4 P ( S | Z, I ) = 1.00 Skp2 37.3 1356.7 4599.1 Mean Corr = 0.75665 Ccne1 80.6 575.2 3834.8 Cul1 1162.9 1639.6 2764.0 Skp1a 10660.8 12844.2 20435.1 Ercc6l 60.2 524.3 1600.0 Cdc6 19.8 569.7 2106.4 Exo1 16.3 435.0 1782.4 Fen1 118.1 877.1 2618.6 Cdk1 95.3 4332.4 6361.5 CEM 1 + Cdca5 41.5 468.0 1389.0 Top 10 Genes Gins1 220.7 1700.2 2866.1 Tipin 315.8 2449.5 10062.9 Mcm5 45.4 956.2 3603.9 Rad51 37.6 994.7 4002.7

Null module Cdkn1b Cdk2 GEO Series "GSE46797" 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=GSE46797 Status: Public on May 10 2013 Title: Expression data from c-Myc+ Notch1 T-ALL initiating cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23791182 Summary & Design: Summary: Missense FBXW7 mutations are prevalent in various tumors, including T-cell acute lymphoblastic leukemia (T-ALL). To study the effects of such lesions, we generated animals carrying regulatable Fbxw7 mutant alleles. We show here that these mutations specifically bolster cancer-initiating cell activity in collaboration with Notch1 oncogenes, but spare normal hematopoietic stem cell function. We were also able to show that FBXW7 mutations specifically affect the ubiquitylation and half-life of c-Myc protein, a key T-ALL oncogene. Using animals carrying c-Myc fusion alleles, we connected Fbxw7 function to c-Myc abundance and correlated c-Myc expression to leukemia-initiating activity.

Overall design: Three independent Notch1 T-ALL were derived on c-Myc-GFP background and sorted from the spleen of leukemic mice on the basis of GFP expression for RNA extraction and hybridization on Affymetrix microarrays

Background corr dist: KL-Divergence = 0.0376, L1-Distance = 0.0289, L2-Distance = 0.0011, Normal std = 0.6371

0.637 Kernel fit Pairwise Correlations Normal fit

Density 0.318

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

Notch1 Notch1T-ALL MycGFP Notch1T-ALL MycGFP Notch1T-ALL negative MycGFP Notch1T-ALL negative replicate MycGFP Notch1T-ALL negative replicate 1 (0.0855944) MycGFP T-ALL positive replicate 2 (0.148885) MycGFP positive replicate 3 (0.209257) positive replicate 1 (0.363301)[ replicatemin 2 (0.121215) 3] (0.0717483) [ medium ] [ max ] CEM 1 Cks1b 910.3 3090.2 4880.9 P ( S | Z, I ) = 1.00 Skp2 103.3 358.0 450.4 Mean Corr = 0.77040 Ccne1 89.9 409.8 1067.1 Cul1 952.1 1706.2 2286.7 Skp1a 6371.3 7252.9 8056.8 Ercc6l 72.9 501.9 1003.3 Cdc6 22.6 649.0 1299.8 Exo1 237.4 1988.4 2420.0 Fen1 1173.5 4136.0 6917.5 Cdk1 698.1 5664.8 9993.5 CEM 1 + Cdca5 44.6 417.0 616.8 Top 10 Genes Gins1 162.7 2147.7 2608.1 Tipin 686.7 3385.1 6045.6 Mcm5 208.6 1568.7 2220.7 Rad51 124.5 841.4 1404.2

Null module Cdkn1b Cdk2 GEO Series "GSE48204" 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=GSE48204 Status: Public on Jul 26 2013 Title: Gene expression in epithelial, EMT (epithelial-mesenchymal transition) and MET (mesenchymal-epithelial transition) cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23878399 Summary & Design: Summary: NMuMG is an epithelial cell line that can be induced into EMT by TGF-Î² treatment or MET by TGF-Î² withdrawl. During EMT, several marker genes were downregulated/upregulated, which is consistent with its mesenchymal phenotype.

Transcription factors that are regulated during EMT and its reverse process MET are candidate genes for the regulations of the EMT marker genes.

Overall design: NMuMG cells treated with vehicle, TGF-Î² for 11 days, or 11days of TGF-Î² treatment followed by TGF-Î² withdrawl for another 13 days. RNA from these 3 conditions of NMuMG were extracted and subject to microarray analysis

Background corr dist: KL-Divergence = 0.0249, L1-Distance = 0.0454, L2-Distance = 0.0022, Normal std = 0.8085

0.537 Kernel fit Pairwise Correlations Normal fit

Density 0.269

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

ControlControl NMuMGNMuMG NMuMG cells, NMuMGreplicate cells cells, treated NMuMGreplicate cells 1 (0.155903) treatedbyNMuMG cells 211 (0.18755) days treatedby cells 11 with days treatedby 4ng/ml 11 with days by TGF-Î²,4ng/ml 11 with days [ TGF-Î²,4ng/mlfollowed minwith TGF-Î²,4ng/mlfollowed by ] TGF-Î² TGF-Î²,replicate by withdrawlTGF-Î² replicate 1[ (0.0893718) withdrawlmedium for 2 another(0.0596927) for another 13 days,] 13 replicate days, replicate[ 1 max(0.200048) 2 (0.307434) ] CEM 1 Cks1b 2282.7 6823.1 8123.7 P ( S | Z, I ) = 1.00 Skp2 284.7 1074.2 1373.9 Mean Corr = 0.74022 Ccne1 330.1 764.7 991.8 Cul1 1056.6 1162.4 1587.6 Skp1a 8458.6 9268.6 12111.6 Ercc6l 499.8 1225.3 1550.4 Cdc6 137.4 740.1 1008.8 Exo1 184.9 713.5 948.2 Fen1 1207.2 3258.7 3495.4 Cdk1 1300.8 4681.1 5896.1 CEM 1 + Cdca5 361.9 1109.4 1137.6 Top 10 Genes Gins1 463.5 1156.9 1850.5 Tipin 1079.6 2583.8 3962.5 Mcm5 504.5 1398.7 1939.3 Rad51 602.8 1572.0 2462.8

Null module Cdkn1b Cdk2 GEO Series "GSE11220" 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=GSE11220 Status: Public on Apr 23 2008 Title: Timecourse of developing mouse placenta, with placental and decidual tissues profiled separately Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18340042 Summary & Design: Summary: We used full genome microarrays to profile the full lifetime of the mouse placenta from embryonic day 8.5 (e8.5), at the time of chorioallantoic fusion, until postnatal day 0 (P0).

At each stage, the fetal placenta and maternal decidual tissues were dissected and profiled separately

Keywords: time course

Overall design: Mouse placentas were obtained from timed pregnant female mice at each timepoint, and fetal tissues were used to confirm embryo staging. Fetal placenta and maternal decidual tissues were dissected and pooled separately for each litter prior to RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.1391, L1-Distance = 0.0310, L2-Distance = 0.0019, Normal std = 0.3911

1.020 Kernel fit Pairwise Correlations Normal fit

Density 0.510

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

PlacentaPlacenta e8.5, biologicalPlacenta e8.5, biologicalPlacenta e8.5, rep1, biologicalPlacenta technical e8.5, rep2, biologicalPlacenta technical e8.5, rep1,rep1 biologicalPlacenta (0.0548327)technical e9.0, rep2,rep1 biologicalPlacenta (0.0616789)technical e9.0, rep3rep2 biologicalPlacenta (0.0359321)(0.0496332) e9.0, rep1rep2 biologicalPlacenta (0.035609)(0.0548389) e10.5, rep2 Placenta(0.0208863) biological e10.5, rep3 Placenta(0.0205017) biological e10.5, rep1Placenta biological (0.0298328)e12.0, rep2Placenta biological (0.0133402)e12.0, rep3Placenta biological (0.0312827)e12.0, rep1Placenta biological (0.0266433)e13.5, rep2Placenta biological (0.02055)e13.5, rep3Placenta biological (0.0301755)e15.0, rep1Placenta biological (0.00742641)e15.0, rep2Placenta biological (0.00264645)e15.0, rep1Placenta biological (0.0191902)e17.0, rep2Placenta biological (0.0121841)e17.0, rep3Placenta biological (0.00696813)e17.0, rep1Placenta biological (0.0131799)e19.0, rep2Placenta biological (0.00913211)e19.0, rep3Placenta biological (0.0164186)P0, rep1 biologicalDecidua (0.00711123)P0, rep2 biologicalDecidua rep1e8.5,(0.0140786) (0.0230747)biologicalDecidua rep2e8.5, (0.0124104)biologicalDecidua e8.5, rep1, biological Deciduatechnical e8.5, rep2, biological Deciduatechnical e9.0, rep1,rep1 biological Decidua(0.0121493)technical e9.0, rep2,rep1 biological Decidua(0.00919304)technical e10.5, rep1rep2 (0.0136528)Decidua(0.00531639)biological e10.5, rep2rep2 (0.0139772)Decidua(0.0130956)biological e12.0, rep1 Decidua biological (0.0195695)e12.0, rep2 Decidua biological (0.0203743)e15.0, rep1 Decidua biological (0.0273438)e15.0, rep2 Decidua biological (0.0175104)e17.0, rep1 Decidua biological (0.0439073)e17.0, rep2 Decidua biological (0.0114799)e19.0, rep1 Decidua biological (0.0234211)e19.0, rep2 Decidua biological (0.0179861)P0, rep1 biological (0.0240586)P0, rep2 biological rep1(0.00938159) (0.0701525) rep2 (0.0178723)[ min ] [ medium ] [ max ] CEM 1 Cks1b 330.1 974.6 3882.4 P ( S | Z, I ) = 1.00 Skp2 169.1 288.4 2451.8 Mean Corr = 0.73354 Ccne1 195.9 312.0 2190.7 Cul1 632.6 1848.6 2792.2 Skp1a 2010.1 3729.1 6084.8 Ercc6l 163.4 263.8 964.5 Cdc6 56.4 172.8 1895.8 Exo1 63.7 110.9 1089.4 Fen1 112.5 341.1 1818.0 Cdk1 212.4 1041.2 6380.4 CEM 1 + Cdca5 144.2 247.6 788.6 Top 10 Genes Gins1 140.8 245.2 979.3 Tipin 234.4 511.3 2409.0 Mcm5 206.0 606.6 4279.3 Rad51 84.6 217.8 1914.5

Null module Cdkn1b Cdk2 GEO Series "GSE28389" 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=GSE28389 Status: Public on Apr 05 2011 Title: [E-MTAB-368] Transcription profiling by array of mouse embryos at 8 different stages Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21427719 Summary & Design: Summary: Transcription profiling of mouse development

The experiment were perfomed as a part of our Vertebrate Evo-Devo project. The aim of the project is to compare transcription profiles of normal (unmanipulated, wild-type, whole embryo) vertebrate embryos.

Overall design: Total RNA was collected from wild type C57BL/6 mice, whole embryos at 8 different stages (Stages:E7.5, E8.5, E9.5, E10.5, E12.5, E14.5, E16.5, E18.5), and hybridized to Affymetrix Mouse Genome 430 2.0 Array. All the stages contains data from 2 to 3 biological replications. Each staged-samples consists of pooled total RNA from several whole embryos.

Background corr dist: KL-Divergence = 0.0441, L1-Distance = 0.0355, L2-Distance = 0.0018, Normal std = 0.5966

0.705 Kernel fit Pairwise Correlations Normal fit

Density 0.353

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

[E-MTAB-368][E-MTAB-368] Mouse[E-MTAB-368] developmentalMouse[E-MTAB-368] developmentalMouse[E-MTAB-368] developmentalMousestage[E-MTAB-368] E7.5 developmentalMousestage[E-MTAB-368] 1 (0.0333347) E7.5 developmentalMousestage[E-MTAB-368] 2 (0.0390814) E7.5 developmentalMousestage[E-MTAB-368] 3 (0.04283) E8.5 developmentalMousestage[E-MTAB-368] 1 (0.0730481) E8.5 developmentalMousestage[E-MTAB-368] 2 (0.0219459) E8.5 developmentalMousestage[E-MTAB-368] 3 (0.0348231) E9.5 developmentalMousestage[E-MTAB-368] 1 (0.0359449) E9.5 developmentalMousestage[E-MTAB-368] 2 (0.0385639) E9.5 developmentalMousestage[E-MTAB-368] 3 (0.0448855) E10.5 developmentalMousestage[E-MTAB-368] 1 E10.5 (0.0548185) developmentalMousestage[E-MTAB-368] 2 E10.5 (0.0241595) developmentalMousestage[E-MTAB-368] 3 E12.5 (0.0301496) developmentalMousestage[E-MTAB-368] 1 E12.5 (0.0570813) developmentalMousestage[E-MTAB-368] 2 E14.5 (0.0299504) developmentalMousestage 1 E14.5 (0.0330623) developmentalMousestage 2 E16.5 (0.0485106) developmentalstage 1 E16.5(0.0422548) stage[ min 2 E18.5(0.0699945) stage 1] E18.5(0.119441) 2 (0.12612)[ medium ] [ max ] CEM 1 Cks1b 1465.5 8523.7 11067.5 P ( S | Z, I ) = 1.00 Skp2 1419.9 4192.0 4995.0 Mean Corr = 0.74139 Ccne1 211.5 974.3 1560.0 Cul1 1766.1 3148.7 3933.8 Skp1a 6711.5 11184.5 12735.2 Ercc6l 433.3 1366.7 2054.2 Cdc6 502.4 1991.4 3238.2 Exo1 283.7 1493.2 2230.3 Fen1 733.8 3344.2 4419.7 Cdk1 2323.9 8286.6 10800.6 CEM 1 + Cdca5 288.2 1271.2 1948.4 Top 10 Genes Gins1 407.4 2344.5 3685.7 Tipin 2049.4 8081.5 10234.5 Mcm5 791.9 6089.6 8249.2 Rad51 599.5 3322.8 4976.8

Null module Cdkn1b Cdk2 GEO Series "GSE7430" 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=GSE7430 Status: Public on Apr 04 2007 Title: Investigate the role of Wnt/beta-catenin signaling in development of the exocrine pancreas Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17222338 Summary & Design: Summary: beta-catenin is an essential mediator of canonical Wnt signaling and a central component of the cadherin-catenin epithelial adhesion complex. Dysregulation of beta-catenin expression has been described in pancreatic neoplasia. Newly published studies have suggested that beta-catenin is critical for normal pancreatic development although these reports reached somewhat different conclusions. In addition, the molecular mechanisms by which loss of beta-catenin affects pancreas development are not well understood. The goals of this study then were; 1] to further investigate the role of beta-catenin in pancreatic development using a conditional knockout approach and 2] to identify possible mechanisms by which loss of beta-catenin disrupts pancreatic development. A Pdx1-cre mouse line was used to delete a floxed beta-catenin allele specifically in the developing pancreas, and embryonic pancreata were studied by immunohistochemistry and microarray analysis.

Keywords: Time course

Overall design: In the study, we hybridized RNA from Embryonic day 14.6 and 16.5 pancreas of wild type (WT) control and Pdx1Cre/+; beta-cateninflox/flox´beta-catenin null in the pancreas) embryonic pancreas to Affymetrix MOE430 2.0 GeneChipˆ´ﬁ arrays containing 45,101 well characterized mouse genes/ESTs.

Background corr dist: KL-Divergence = 0.0780, L1-Distance = 0.0340, L2-Distance = 0.0021, Normal std = 0.4802

0.831 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

14.5_KO_540C16.5_KO_591D 16.5_WT_628G(0.0302164) 16.5_WT_622A(0.0805102) 14.5_KO_540G(0.0378799) 14.5_KO_615A(0.0531677) 14.5_KO_615B(0.201231) 14.5_WT_522B(0.0241793) 14.5_WT_522C(0.0870598) 16.5_KO_541J(0.0170653) 16.5_KO_541L(0.0170606) (0.125615)16.5_KO_591C (0.105453) (0.220562) [ min ] [ medium ] [ max ] CEM 1 Cks1b 359.5 475.0 593.2 P ( S | Z, I ) = 1.00 Skp2 282.6 500.6 809.9 Mean Corr = 0.73107 Ccne1 412.4 504.3 604.2 Cul1 320.0 491.6 624.2 Skp1a 434.5 506.0 631.2 Ercc6l 384.7 535.6 568.3 Cdc6 292.2 476.0 577.0 Exo1 303.7 478.0 729.4 Fen1 322.7 448.8 638.9 Cdk1 347.3 505.6 749.0 CEM 1 + Cdca5 349.2 509.1 644.7 Top 10 Genes Gins1 339.2 474.3 595.1 Tipin 331.6 504.1 734.1 Mcm5 296.9 441.3 667.5 Rad51 340.0 466.3 552.7

Null module Cdkn1b Cdk2 GEO Series "GSE31598" 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=GSE31598 Status: Public on Apr 01 2012 Title: Expression data from directly induced neural stem cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22467474 Summary & Design: Summary: Induced pluripotent stem (iPS) cells give rise to neural stem cells, which are applicable for therapeutic transplantation in treatment of neural diseases. However, generation of neural stem cells from iPS cells requires a careful selection of safe iPS clones. We sought to determine whether direct induction of neural stem cells from partially reprogrammed somatic cells is able to generate safer cells rapidly. We have successfully established direct induction system from fibroblast to neural stem cells. To characterize these directly induced neural stem cells, Gene expression profiles were compared with iPS cell or ES cell-derived neurosphere. We used affymetrix microarrays to compare the global gene expression of neurospheres prepared several method.

Overall design: The mouse strain used in this study except ES/iPS cells was C57BL/6.

Background corr dist: KL-Divergence = 0.1105, L1-Distance = 0.0565, L2-Distance = 0.0068, Normal std = 0.4455

0.907 Kernel fit Pairwise Correlations Normal fit

Density 0.454

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

E14_NeurosphereMouse_adult_fibroblast38C2_iPSC (0.112214)iPSC_PNS (0.0830514)iPSC_SNS (0.0881396) (0.0599994)iNSC_1 (0.0313436) iNSC_2(0.0110553) EB3_ESC(0.0106293)ESC_PNS (0.339589)ESC_SNS (0.0953331)iNSC_3_embryo (0.0334858)iNSC_4_embryo (0.013504) (0.121655) [ min ] [ medium ] [ max ] CEM 1 Cks1b 655.0 3211.0 6768.2 P ( S | Z, I ) = 1.00 Skp2 557.3 1802.9 3766.9 Mean Corr = 0.72517 Ccne1 111.0 800.1 5694.8 Cul1 1580.3 1727.7 2832.3 Skp1a 9833.4 12838.5 17804.8 Ercc6l 108.0 758.1 2601.0 Cdc6 17.6 563.8 2261.9 Exo1 41.7 862.5 2680.8 Fen1 229.6 1261.6 2519.5 Cdk1 529.9 3645.8 7587.4 CEM 1 + Cdca5 49.2 754.4 1788.1 Top 10 Genes Gins1 146.2 1201.4 3597.9 Tipin 1014.7 3499.3 11916.3 Mcm5 117.5 1638.3 5004.1 Rad51 145.7 1326.5 3516.9

Null module Cdkn1b Cdk2 GEO Series "GSE39233" 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=GSE39233 Status: Public on Jul 10 2012 Title: Placental PPARg-Regulated Genes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Robust identification of placental PPARg target genes via mutliple PPARg-dependence criteria.

Integration of differential expression data from Pparg-null, Rxra-null, Med1-nul and Ncoa6-null placentas and from WT and Pparg-null Trophoblast stem cells (TSC) differentiated for 2 or 4 days in the presence or absence of the PPARg agonist Rosiglitazone (Rosi).

Overall design: Three independent WT TSC lines differentiated for two and four days in the presence or absence of Rosi vs two independent Pparg-null TSC lines differntiated for the same durations in the presence of Rosi

Background corr dist: KL-Divergence = 0.1354, L1-Distance = 0.0395, L2-Distance = 0.0024, Normal std = 0.3994

1.033 Kernel fit Pairwise Correlations Normal fit

Density 0.516

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

Pparg+/+Pparg+/+ placenta,Pparg+/+ placenta, bioPparg-null rep placenta, bio1 (0.0272483)Pparg-null rep placenta, bio3 (0.0236523)Pparg-null rep placenta, 4 bio(0.0182521)Rxra+/+ rep placenta, bio1 Rxra+/+ (0.00924992)placenta, rep bio3 Rxra+/+ (0.0660564)placenta, rep bio 4 rep Rxra-null (0.0177854)placenta, bio2 (0.0533117) repRxra-null placenta, bio3 (0.0239327) repRxra-null placenta, 4 bio(0.0329491)Med1+/+ rep placenta, bio2 (0.0447515)Med1+/+ rep placenta, bio3 (0.0194389)Med1+/+ rep placenta, bio 4 (0.0218846) Med1-nullrep placenta, bio1 (0.0266197) Med1-nullrep placenta, bio2 (0.026965) Med1-nullrep placenta, 3 bio(0.0275269)Ncoa6+/+ rep placenta, bio1 (0.0156167)Ncoa6+/+ rep placenta, bio2 (0.0222605)Ncoa6+/+ rep placenta, bio 3 (0.0193032)Ncoa6-null rep placenta, bio1 (0.00815258)Ncoa6-null rep placenta, bio2 (0.014889)Ncoa6-null rep placenta, 4 bio(0.00993421)WT rep TSC,placenta, bio1WT (0.007951) 2 rep dayTSC, bio2 WT diff,(0.00825845) 2 rep dayTSC, no 4 WT diff,Rosi,(0.00739757) 2 dayTSC, w/ bio WTRosi,diff, 2 rep dayTSC, no bio1 WT diff,Rosi,(0.0151328) 2rep dayTSC, w/ 1bio Pparg-nullRosi,diff,(0.0161086) 2 rep day no bio2 Pparg-null diff,Rosi,(0.0281821) rep TSC, w/ 2bio WTRosi,(0.0180331) 2 rep day TSC,TSC, bio3 WTdiff, (0.021094) 2 4rep day dayTSC, w/ 3 Rosi,WTdiff,diff,(0.0176661) 4 dayTSC, w/no bio Rosi,WTdiff,Rosi, 4rep dayTSC, w/ bio 1bio WT(0.0132798)Rosi,diff, 4rep rep dayTSC, no 2 bio1 WT(0.0141431)diff,Rosi,(0.0219483) 4rep dayTSC, w/ 1bio Pparg-nullRosi,diff,(0.0260651) 4 rep day no bio2 Pparg-null diff,Rosi,(0.0331043) rep TSC, w/ 2bio Rosi,(0.0712419) 4 rep dayTSC, bio3 diff, (0.0404433) 4 rep day w/ 3 Rosi,diff,(0.0575589) w/ bio Rosi,[ repmin bio1 (0.0266799) rep ] 2 (0.0259308)[ medium ] [ max ] CEM 1 Cks1b 1038.4 3326.8 5885.7 P ( S | Z, I ) = 1.00 Skp2 442.3 2426.3 3946.6 Mean Corr = 0.72318 Ccne1 332.9 1378.3 2053.9 Cul1 2348.5 4019.1 6548.8 Skp1a 7669.0 9573.7 12537.0 Ercc6l 351.3 953.9 1525.6 Cdc6 350.5 2537.1 3587.8 Exo1 233.4 1221.9 1847.3 Fen1 574.1 1939.1 3026.4 Cdk1 850.0 5562.5 7126.9 CEM 1 + Cdca5 109.4 646.8 994.6 Top 10 Genes Gins1 209.1 1325.6 1745.8 Tipin 1219.8 4493.9 6583.3 Mcm5 572.1 3151.7 4223.5 Rad51 667.1 2831.6 3608.4

Null module Cdkn1b Cdk2 GEO Series "GSE51628" 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=GSE51628 Status: Public on Oct 24 2013 Title: Effects of acute Notch activation on the mammary epithelial compartment in vivo Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Notch signaling is widely implicated in mouse mammary gland development and tumorigenesis. To investigate the effects of acute activation of Notch signaling in the mammary epithelial compartment, we generated bi-transgenic MMTV-rtTA; TetO-NICD1 (MTB/TICNX) mice that conditionally express a constitutively active NOTCH1 intracellular domain (NICD1) construct in the mammary epithelium upon doxycycline administration.

Overall design: Two timepoints (48h and 96h) of doxycycline induction in TetO-NICD1 (TICNX; control) and MMTV-rtTA; TetO-NICD1 (MTB/TICNX) mice with 3-4 replicates per timepoint

Background corr dist: KL-Divergence = 0.0788, L1-Distance = 0.0320, L2-Distance = 0.0014, Normal std = 0.4893

0.843 Kernel fit Pairwise Correlations Normal fit

Density 0.422

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

TICNX_48h_rep1TICNX_48h_rep2TICNX_48h_rep3 (0.0825546)TICNX_48h_rep4 (0.126893)TICNX_96h_rep1 (0.0608827)TICNX_96h_rep2 (0.0264792)TICNX_96h_rep3 (0.0470517)MTB/TICNX_48h_rep1 (0.00975268)MTB/TICNX_48h_rep2 (0.0145004)MTB/TICNX_48h_rep3 MTB/TICNX_48h_rep4(0.0206432) MTB/TICNX_96h_rep1(0.110845) MTB/TICNX_96h_rep2(0.031268) MTB/TICNX_96h_rep3(0.0499435) MTB/TICNX_96h_rep4(0.0260363) (0.100807) (0.147948) (0.144394)[ min ] [ medium ] [ max ] CEM 1 Cks1b 938.2 1621.3 2874.5 P ( S | Z, I ) = 1.00 Skp2 124.5 490.7 963.8 Mean Corr = 0.71552 Ccne1 177.5 246.9 334.2 Cul1 1089.1 1191.7 1478.2 Skp1a 11458.8 12410.6 13532.1 Ercc6l 139.2 335.2 838.3 Cdc6 57.1 145.7 379.2 Exo1 23.6 123.3 334.4 Fen1 141.9 527.1 1323.2 Cdk1 184.8 891.9 2444.0 CEM 1 + Cdca5 56.9 184.0 556.8 Top 10 Genes Gins1 199.9 330.5 866.4 Tipin 426.6 774.7 1543.0 Mcm5 55.8 355.0 999.5 Rad51 82.2 373.6 1103.5

Null module Cdkn1b Cdk2 GEO Series "GSE22180" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 60 -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=GSE22180 Status: Public on Oct 02 2010 Title: In vitro carcinogenicity testing with Balb/c 3T3 Cells treated with various chemical carcinogens Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20713471 Summary & Design: Summary: Background: Information on the carcinogenic potential of chemicals is only availably for High Production Volume products. There is however, a pressing need for alternative methods allowing for the chronic toxicity of substances, including carcinogenicity, to be detected earlier and more reliably. Here we applied advanced genomics to a cellular transformation assay to identify gene signatures useful for the prediction of risk for carcinogenicity. Methods: Genome wide gene expression analysis and qRT-PCR were applied to untransformed and transformed Balb/c 3T3 cells that exposed to 2, 4-diaminotoluene (DAT), benzo(a)pyrene (BaP), 2-Acetylaminoflourene (AAF) and 3-methycholanthrene (MCA) for 24h and 120h, at different concentrations, respectively. Furthermore, various bioinformatics tools were used to identify gene signatures predicting for the carcinogenic risk. Results: Bioinformatics analysis revealed distinct datasets for the individual chemicals tested while the number of significantly regulated genes increased with ascending treatment concentration of the cell cultures. Filtering of the data revealed a common gene signature that comprised of 13 genes whose regulation in cancer tissue has already been established. Strikingly, this gene signature was already identified prior to cell transformation therefore confirming the predictive power of this gene signature in identifying carcinogenic risks of chemicals. Comparison of fold changes determined by microarray analysis and qRT-PCR were in good agreement. Conclusion: Our data describes selective and commonly regulated carcinogenic pathways observed in an easy to use in vitro carcinogenicity assay. Here we defined a set of genes which can serve as a simply assay to predict the risk for carcinogenicity by use of an alternative in vitro testing strategy.

Overall design: Balb/c 3T3 cells were seeded at 200 cells in each 60 x 15 mm culture dish with 4 ml M10F, using six culture dishes for every treatment. When cells reached a confluence of 60-65%, the culture medium was removed and replaced with fresh medium containing all tested chemicals at a specific concentration and two time points (24 and 120h). First we treated the cells both 24h and 120h with concentrations reported in the literature (0.5´M BaP, 50´M DAT, 25´M AAF and 2´M MCA). In a second approach IC20 concentrations were investigated for each chemical at both time points. The concentrations determined for IC20 ranged from 1.5 ´M BaP to 700 ´M DAT for 24h of treatment, and from 0.1 ´M BaP or MCA to 10´M AAF for 120h of treatment. Balb/c 3T3 cells treated with 0.75% DMSO alone were kept as controls. Each experiment was run in triplicate.

Background corr dist: KL-Divergence = 0.0902, L1-Distance = 0.0536, L2-Distance = 0.0063, Normal std = 0.4799

0.897 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

AAF_25´M_24h_Replicate1AAF_25´M_24h_Replicate2AAF_25´M_24h_Replicate3AAF_25´M_120h_Replicate1 (0.00302406)AAF_25´M_120h_Replicate2 (0.00369528)AAF_25´M_120h_Replicate3 (0.00464687)BaP_0.5´M_24h_Replicate1 (0.0345792)BaP_0.5´M_24h_Replicate2 (0.020595)BaP_0.5´M_24h_Replicate3 (0.0151373)BaP_0.5´M_120h_Replicate1 (0.00507402)BaP_0.5´M_120h_Replicate2 (0.007464)BaP_0.5´M_120h_Replicate3 (0.00575596)Control_DMSO_24h_Replicate1 (0.0302999)Control_DMSO_24h_Replicate2 (0.0134157)Control_DMSO_24h_Replicate3 (0.0117261)Control_DMSO_120h_Replicate1Control_DMSO_120h_Replicate2 (0.0374675)Control_DMSO_120h_Replicate3 (0.00321804)DAT_50´M_24h_Replicate1 (0.00461934)DAT_50´M_24h_Replicate2 (0.0190135)DAT_50´M_24h_Replicate3 (0.0242045)DAT_50´M_120h_Replicate1 (0.0166802) (0.00827053)DAT_50´M_120h_Replicate2 (0.00651999)DAT_50´M_120h_Replicate3 (0.00771746)MCA_2´M_24h_Replicate1 (0.0154267)MCA_2´M_24h_Replicate2 (0.0145945)MCA_2´M_24h_Replicate3 (0.0148485)MCA_2´M_120h_Replicate1 (0.0119812)MCA_2´M_120h_Replicate2 (0.00402832)MCA_2´M_120h_Replicate3 (0.00333792)AAF_10´M_24h_Replicate1 (0.0119444)AAF_10´M_24h_Replicate2 (0.0140719)AAF_10´M_24h_Replicate3 (0.0109782)AAF_10´M_120h_Replicate1 (0.0231621)AAF_10´M_120h_Replicate2 (0.0219057)AAF_10´M_120h_Replicate3 (0.0355319)BaP_1.5´M_24h_Replicate1 (0.0191529)BaP_1.5´M_24h_Replicate2 (0.0182269)BaP_1.5´M_24h_Replicate3 (0.0107526)BaP_0.1´M_120h_Replicate1 (0.0197619)BaP_0.1´M_120h_Replicate2 (0.0225173)BaP_0.1´M_120h_Replicate3 (0.0335103)Control_DMSO_24h_E2_Replicate1 (0.0106952)Control_DMSO_24h_E2_Replicate2 (0.010218)Control_DMSO_24h_E2_Replicate3 (0.00945105)Control_DMSO_120h_E2_Replicate1Control_DMSO_120h_E2_Replicate2 (0.0411218)Control_DMSO_120h_E2_Replicate3 (0.025806)DAT_700´M_24h_Replicate1 (0.047465)DAT_700´M_24h_Replicate2 (0.0119221)DAT_700´M_24h_Replicate3 (0.0104293)DAT_0.2´M_120h_Replicate1 (0.0225451)(0.00592828)DAT_0.2´M_120h_Replicate2 (0.0226708)DAT_0.2´M_120h_Replicate3 (0.0426767)MCA_20´M_24h_Replicate1 (0.0116852)MCA_20´M_24h_Replicate2 (0.0132542)MCA_20´M_24h_Replicate3 (0.00646349)MCA_0.1´M_120h_Replicate1 (0.0232246)MCA_0.1´M_120h_Replicate2 (0.0227053)MCA_0.1´M_120h_Replicate3 (0.0391641) (0.0106961) (0.0127667) [(0.0102532) min ] [ medium ] [ max ] CEM 1 Cks1b 1056.4 4025.7 6098.7 P ( S | Z, I ) = 1.00 Skp2 359.4 930.4 2260.8 Mean Corr = 0.70751 Ccne1 86.6 310.3 632.9 Cul1 2932.1 3497.0 4720.0 Skp1a 2756.1 4644.1 8342.5 Ercc6l 196.9 1198.0 2637.1 Cdc6 87.7 801.5 2105.9 Exo1 145.6 895.3 1735.2 Fen1 422.1 1615.7 3543.8 Cdk1 1644.8 6167.2 8438.4 CEM 1 + Cdca5 144.2 786.3 1634.7 Top 10 Genes Gins1 143.3 636.1 1203.9 Tipin 885.8 2267.6 5213.7 Mcm5 574.4 3744.8 6357.5 Rad51 268.4 1511.6 4221.2

Null module Cdkn1b Cdk2 GEO Series "GSE17316" 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=GSE17316 Status: Public on Nov 23 2009 Title: Reprogramming of a B cell line into macrophages Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19896445 Summary & Design: Summary: Transcription factor induced reprogramming of one specialized cell type into another is a promising approach for regenerative medicine. However, the process still remains poorly understood, in large part because of the lack of adequate experimental models. Here we describe a robust cell reprogramming system consisting of a B cell line with an inducible form of C/EBPa that can be converted into macrophages with essentially 100% efficiency in only 2 to 3 days. The conversion involves reciprocal changes in cell surface antigen expression, increase in cell granularity and size, alterations in cellular structures, formation of membrane extensions, acquisition of phagocytic capacity and an increased inflammatory responsiveness as well as migratory activity. Analysis of the transcriptome shows complex reciprocal regulation of B cell and macrophage genes, including transcription factors required for the formation of the two lineages. The fact that the cells become irreversibly committed to a macrophage fate within 1 to 2 days after activation of C/EBPa show that they are truly reprogrammed. The system should be useful to study epigenetic and cell biological mechanisms of transcription factor induced cell reprogramming.

Overall design: time points: vehicle control, 3h, 12h, 24h, 48h.

Background corr dist: KL-Divergence = 0.0922, L1-Distance = 0.0474, L2-Distance = 0.0035, Normal std = 0.4812

0.883 Kernel fit Pairwise Correlations Normal fit

Density 0.441

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

HAFTL HAFTLcell line C10cell treated linecellC10 treatedwithline cell withbetaC10 withline an estradiol cell withinduciblebetaC10 line an estradiol cell samplewithinducibleC10 formline an cell samplewith1inducibleof (0.0353228)C10 formC/EBPa,line an cell with2inducibleof (0.0295881)C10 formC/EBPa,line treatedan cell withinducibleofC10 formC/EBPa,line treatedwithan cell withinducibleof ethanolC10 formC/EBPa,line treatedwithan cell withinducibleof ethanol C10 sampleformC/EBPa,line treatedwithan cell withinducibleof beta sampleform1C/EBPa,line treatedwith(0.062433)an estradiol withinducibleof beta form2C/EBPa, treatedwith(0.0275013)an estradiol inducibleof for beta formC/EBPa, treatedwith3 hoursestradiol of for beta [ formC/EBPa, treatedwith3 minsample hoursestradiol of for beta C/EBPa, treatedwith12 sample1 ]estradiol (0.157641)hours for beta treatedwith12 2 sampleestradiol (0.163609)hours for beta with24[ sampleestradiol1 hoursmedium for(0.0367626) beta 24 sampleestradiol2 hours for(0.033847) 48 sample1 hours for(0.0534942) ] 48 sample2 hours (0.195137) sample1 (0.135481)[ max 2 (0.0691826) ] CEM 1 Cks1b 214.3 2725.0 5514.2 P ( S | Z, I ) = 1.00 Skp2 331.9 1202.3 3969.3 Mean Corr = 0.70219 Ccne1 54.1 116.5 866.8 Cul1 1533.9 2050.7 2420.4 Skp1a 3757.8 5592.5 6639.5 Ercc6l 46.6 397.0 1872.8 Cdc6 21.5 382.8 2584.8 Exo1 11.9 489.5 1306.5 Fen1 429.0 681.5 3557.6 Cdk1 120.1 2010.1 10509.1 CEM 1 + Cdca5 100.6 573.5 1343.6 Top 10 Genes Gins1 113.9 779.9 3554.1 Tipin 424.8 2996.2 9187.3 Mcm5 88.6 1143.8 5636.3 Rad51 4.8 661.2 2710.0

Null module Cdkn1b Cdk2 GEO Series "GSE38831" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 7 -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=GSE38831 Status: Public on Dec 22 2013 Title: Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24260186 Summary & Design: Summary: High-throughput genomic studies have identified thousands of genetic alterations in colorectal cancer (CRC). Distinguishing driver from passenger mutations is critical for developing rational therapeutic strategies. Because only a few transcriptional subtypes exist in previously studied tumor types, we hypothesize that highly heterogeneous genomic alterations may converge to a limited number of distinct mechanisms that drive unique gene expression patterns in different transcriptional subtypes. In this study, we defined transcriptional subtypes for CRC and identified driver networks/pathways for each subtype, respectively. Applying consensus clustering to a patient cohort with 1173 samples identified three transcriptional subtypes, which were validated in an independent cohort with 485 samples. The three subtypes were characterized by different transcriptional programs related to normal adult colon, early colon embryonic development, and epithelial mesenchymal transition, respectively. They also showed statistically different clinical outcomes. For each subtype, we mapped somatic mutation and copy number variation data onto an integrated signaling network and identified subtype-specific driver networks using a random walk-based strategy. We found that genomic alterations in the Wnt signaling pathway were common among all three subtypes; however, unique combinations of pathway alterations including Wnt, VEGF, Notch and TGF-beta drove distinct molecular and clinical phenotypes in different CRC subtypes. Our results provide a coherent and integrated picture of human CRC that links genomic alterations to molecular and clinical consequences, and which provides insights for the development of personalized therapeutic strategies for different CRC subtypes.

Overall design: To characterize the embryonic development of colon, we conducted a time course microarray study using the inbred C57BL/6 (Jackson Laboratories, Bar Harbor, ME) mice. Seven samples corresponding to the mouse colonic development from E13.5 to E18.5 and adult (eight week post-natal) were collected. RNA samples were submitted to the Vanderbilt Functional Genomics Shared Resource (FSGR, http://array.mc.vanderbilt.edu), where RNA was hybridized to the Affymetrix Mouse Genome 430 2.0 GeneChip Expression Arrays (Santa Clara, CA) according to manufacturers instructions. The RMA algorithm was used for data normalization. Mouse gene symbols were mapped to human gene symbols by the Human and Mouse Orthology list available from the Mouse Genome Informatics (http://www.informatics.jax.org/).

Background corr dist: KL-Divergence = 0.0290, L1-Distance = 0.0333, L2-Distance = 0.0015, Normal std = 0.7069

0.606 Kernel fit Pairwise Correlations Normal fit

Density 0.303

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

C57BL/6JE13.5C57BL/6JE14.5C57BL/6JE15.5 (0.181512)C57BL/6JE16.5 (0.197123)C57BL/6JE17.5 (0.109388)C57BL/6JE18.5 (0.0326076)C57BL/6JADULT (0.0892691) (0.0851429) COLON (0.304958)[ min ] [ medium ] [ max ] CEM 1 Cks1b 121.0 870.4 1616.8 P ( S | Z, I ) = 1.00 Skp2 59.0 151.4 245.0 Mean Corr = 0.74651 Ccne1 340.0 634.4 777.6 Cul1 1063.2 1236.8 1543.5 Skp1a 2397.7 2685.0 4223.1 Ercc6l 171.6 242.6 309.0 Cdc6 86.0 277.5 507.8 Exo1 202.6 596.7 1202.7 Fen1 144.9 282.7 597.9 Cdk1 1020.2 2736.2 3935.3 CEM 1 + Cdca5 107.2 146.7 211.2 Top 10 Genes Gins1 346.7 1056.2 2235.0 Tipin 190.3 1178.6 1888.8 Mcm5 319.2 641.1 1262.7 Rad51 134.9 327.2 520.0

Null module Cdkn1b Cdk2 GEO Series "GSE11356" 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=GSE11356 Status: Public on May 06 2008 Title: Expression data from early and adult stages of mouse development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: DNA repair genes have been shown to be expressed in the early stages of mammalian development probably to reduce possible replication errors and genotoixc damages. Several birth defects and some cancers are due to inappropriate or defective DNA repair machinery indicating that a right activity of DNA repair genes in the early stages of fetal development are essential for an appropriate DNA function. Neuroblastoma (NB), an embryonal tumor deriving from neural crest cells (NCCs) is diagnosed in about 30% of patients within the first year of life. Moreover, several reports show that NB can be detected in foetus and in neonatal period.

To assess gene expression profiling of DNA repair genes during early stage of development, we performed a genome-wide analysis of Neural Crest cells (NCCs) generating a gene expression database that can help to better understand the gene(s) involved in both genetic and cancer diseases. We found 11 genes involved in DNA repair activity during mouse embryo development overexpressed in early stages. Six out 11 were never been described in mouse embryology.

Keywords: time course

Overall design: Mouse embryos were collected at successive stages of early and adult development stages for RNA extraction and hybridization on Affymetrix microarrays. We sought to obtain homogeneous populations of NCCs by Laser Capture Microdissection (LCM) from embryos and adult in order to analyze DNA repair genes during mouse development. To that end, we collected cells at three time-points: at embryonal stage of 8.5 dpc: E8.5 (neural tube closure); at embryonal stage of 13.5dpc: E13.5 (dorsal root ganglion); at adult stage of 3 months postnatal: P90 (adrenal medulla).

Background corr dist: KL-Divergence = 0.0700, L1-Distance = 0.0501, L2-Distance = 0.0047, Normal std = 0.5213

0.771 Kernel fit Pairwise Correlations Normal fit

Density 0.386

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

NCCs atNCCs E8.5, atbiologicalNCCs E8.5, atbiologicalNCCs E8.5, rep1 at biological(0.114347)NCCs E13.5, rep2 at (0.213524) NCCsbiological E13.5, rep3 at (0.202386) NCCsbiological E13.5, rep1 at NCCs biological(0.0407892)P90, rep2 biologicalatNCCs (0.0993356)P90, rep3 biologicalat (0.0720516) P90,rep1 biological(0.0723646) rep2 (0.0632197) rep3 (0.121982)[ min ] [ medium ] [ max ] CEM 1 Cks1b 170.7 542.1 3984.6 P ( S | Z, I ) = 1.00 Skp2 88.2 683.2 6732.4 Mean Corr = 0.68895 Ccne1 78.5 631.2 1633.7 Cul1 1861.9 3152.6 5265.6 Skp1a 3171.5 5599.4 6782.6 Ercc6l 11.4 233.9 4155.0 Cdc6 2.7 72.0 2311.2 Exo1 83.4 166.4 3166.7 Fen1 29.0 64.4 1045.5 Cdk1 86.4 616.4 5289.2 CEM 1 + Cdca5 90.5 184.0 2391.2 Top 10 Genes Gins1 66.4 147.9 2224.8 Tipin 116.1 236.7 2977.5 Mcm5 233.4 761.3 5188.1 Rad51 2.6 63.8 322.4

Null module Cdkn1b Cdk2 GEO Series "GSE6689" 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=GSE6689 Status: Public on Jan 07 2008 Title: Expression data during stem cell differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18184438 Summary & Design: Summary: Stem cell development requires selection of specific genetic programs to direct cellular fate. Using microarray technology, we profile expression trends at selected timepoints during stem cell differentiation to characterize these changes.

Keyword(s): timecourse

Overall design: Total RNA was isolated using the Micro-to-Midi isolation kit (Invitrogen), and subjected to comparative gene expression profiling by labelled cRNA hybridization to the mouse genome 430 2.0 microarray (Affymetrix). Data acquired using the GeneChip Scanner 3000 was analyzed with the Genespring GX 7.3 microarray data software bioinformatics suite (Agilent Technologies) restricting the derived gene list to identify differentially expressed genes defined by a >1.5-fold difference and P<0.05. Data population sets were normalized to the undifferentiated phenotype, and quality filtered to eliminate background noise prior to hierarchical clustering.

Background corr dist: KL-Divergence = 0.0505, L1-Distance = 0.0486, L2-Distance = 0.0033, Normal std = 0.5968

0.726 Kernel fit Pairwise Correlations Normal fit

Density 0.363

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_ES-LIF(+)_rep1Timepoint1_ES-LIF(-)_rep1Timepoint2_CM_rep1Control_ES-LIF(+)_rep2 (0.112898)Timepoint1_ES-LIF(-)_rep2 (0.0732935) (0.132616)Timepoint2_CM_rep2Timepoint1b_CP_rep1 (0.0300084)Control_ES-LIF(+)_rep3 (0.196652) (0.111694)Timepoint1_ES-LIF(-)_rep3 Timepoint2_CM_rep3(0.045247)Timepoint1b_CP_rep2 (0.0476479)Timepoint1b_CP_rep3 (0.0512405) (0.114299) (0.0543286) (0.0300751)[ min ] [ medium ] [ max ] CEM 1 Cks1b 3654.1 7547.2 10100.2 P ( S | Z, I ) = 1.00 Skp2 697.4 1705.3 1998.2 Mean Corr = 0.70066 Ccne1 1108.3 2995.3 4382.4 Cul1 1680.6 2075.4 3017.3 Skp1a 9217.9 10713.0 12432.5 Ercc6l 602.9 1260.7 1505.9 Cdc6 457.3 1717.1 2007.5 Exo1 563.9 1838.6 2262.9 Fen1 950.9 2641.8 3023.8 Cdk1 2883.8 6280.4 6973.3 CEM 1 + Cdca5 496.1 1768.0 1991.5 Top 10 Genes Gins1 508.6 1978.0 2240.6 Tipin 1923.5 7304.7 8792.4 Mcm5 2852.2 8658.6 10099.3 Rad51 1103.1 3047.6 3728.9

Null module Cdkn1b Cdk2 GEO Series "GSE15541" 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=GSE15541 Status: Public on Apr 09 2009 Title: Linkage of Meis1 leukemogenic activity to multiple downstream effectors including Trib2 and Ccl3 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18375036 Summary & Design: Summary: OBJECTIVE: MEIS1, a HOX cofactor, collaborates with multiple HOX and NUP98-HOX fusion proteins to accelerate the onset of acute myeloid leukemia (AML) through largely unknown molecular mechanisms. MATERIALS AND METHODS: To further resolve these mechanisms, we conducted a structure-function analysis of MEIS1 and gene-expression profiling, in the context of NUP98-HOXD13 (ND13) leukemogenesis. RESULTS: We show, in a murine bone marrow transplantation model, that the PBX-interaction domain, the homeodomain, and the C-terminal domain of MEIS1, are all required for leukemogenic collaboration with ND13. In contrast, the N-terminal domain of MEIS1 is dispensable for collaboration with ND13, but is required for Flt3 upregulation, indicating additional roles for MEIS1 in induction of leukemia independent of alterations in Flt3 expression. Gene-expression profiling of a cloned ND13 preleukemic cell line transduced with wild-type or Meis1 mutant forms revealed deregulation of multiple genes, including a set not previously implicated as MEIS1 targets. Chromatin immunoprecipitation revealed the in vivo occupancy of MEIS1 on regulatory sequences of Trib2, Flt3, Dlk1, Ccl3, Ccl4, Pf4, and Rgs1. Furthermore, engineered overexpression of Trib2 complements ND13 to induce AML while Ccl3 potentiates the repopulating ability of ND13. CONCLUSION: This study shows that Meis1-induced leukemogenesis with ND13 can occur in the absence of Flt3 upregulation and reveals the existence of other pathways activated by MEIS1 to promote leukemia.

Overall design: Establishment of pre-leukemic bone marrow cell lines following transduction with ND13 have been previously described (Pineault, Abramovich et al. 2005). In brief, lines were established from BM cells previously treated with 5-fluorouracil (5-FU) from (C57Bl/6Ly-Pep3b x C3H/HeJ) F1 (PepC3) (Ly5.1+/Ly5.2+) mice freshly transduced with the ND13-GFP or ND13pac virus and maintained in liquid culture. To generate ND13+Meis1 or ND13+Meis1 mutant BM cell lines, the ND13 BM cells were transduced by co-cultivation on irradiated (4,000 cGy) E86 producers for Meis1-YFP (or Meis1 mutant forms), respectively, for a period of 2 days in the presence of 5 ´g/ml of protamine sulfate. Three independent experiments were performed for each of the four different conditions included in the study.

Background corr dist: KL-Divergence = 0.0967, L1-Distance = 0.0283, L2-Distance = 0.0010, Normal std = 0.4561

0.888 Kernel fit Pairwise Correlations Normal fit

Density 0.444

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

NUP98-HOXD13+MIY-ctrl_rep1NUP98-HOXD13_MIY-ctrl_rep2NUP98-HOXD13+MIY-ctrl_rep3NUP98-HOXD13+MEIS1-WT_rep1NUP98-HOXD13+MEIS1-WT_rep2 (0.151469)NUP98-HOXD13+MEIS1-WT_rep3 (0.202533)NUP98-HOXD13+MEIS1-deltaHD_rep1 (0.111874)NUP98-HOXD13+MEIS1-deltaHD_rep2 (0.0599163)NUP98-HOXD13+MEIS1-deltaHD_rep3 (0.117906)NUP98-HOXD13+M33-MEIS1_rep1 (0.0264077)NUP98-HOXD13+M33-MEIS1_rep2NUP98-HOXD13+M33-MEIS1_rep3 (0.100762) (0.0660511) (0.0266058) (0.0186847) (0.0237428)[ min (0.0940485) ] [ medium ] [ max ] CEM 1 Cks1b 4781.7 7916.5 8786.3 P ( S | Z, I ) = 1.00 Skp2 649.7 1429.0 1550.8 Mean Corr = 0.68254 Ccne1 131.2 548.6 710.4 Cul1 2367.4 2832.2 3166.4 Skp1a 4702.1 6944.7 8001.9 Ercc6l 426.1 1582.6 1635.0 Cdc6 525.0 2044.8 2356.2 Exo1 517.5 1374.7 1520.4 Fen1 1124.5 4344.1 4944.1 Cdk1 2967.8 6723.3 7384.1 CEM 1 + Cdca5 785.5 1871.4 2056.7 Top 10 Genes Gins1 877.8 2337.0 2474.9 Tipin 5353.2 10398.1 11257.9 Mcm5 2938.3 7269.3 8053.6 Rad51 1046.0 2917.7 3247.3

Null module Cdkn1b Cdk2 GEO Series "GSE12078" 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=GSE12078 Status: Public on Jul 18 2008 Title: Ctr9 knockdown in mouse ES cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19345177 Summary & Design: Summary: To monitor global transcript changes after Paf1C depletion we transfected ESCs with esiRNA targeting Ctr9 and control esiRNA (Luc).

Overall design: 4 replicates of esiRNA tranfection controls (luciferase esiRNA) and 4 replicates of Ctr9 esiRNA tranfection samples

Background corr dist: KL-Divergence = 0.0399, L1-Distance = 0.0419, L2-Distance = 0.0022, Normal std = 0.6455

0.666 Kernel fit Pairwise Correlations Normal fit

Density 0.333

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

ES LUCES esiRNA LUCES esiRNA day4 LUC rep1ES esiRNA day4 LUC (0.235823) rep2ES esiRNA day4 Ctr9 (0.122533) rep3ES esiRNA day4 Ctr9 (0.153425) rep4ES esiRNA day4 Ctr9 (0.0891998) rep1ES esiRNA day4 Ctr9 (0.14572) rep2 esiRNA day4 (0.0714878) rep3 day4 (0.0803907) rep4 (0.101422)[ min ] [ medium ] [ max ] CEM 1 Cks1b 5468.0 6916.6 7264.5 P ( S | Z, I ) = 1.00 Skp2 1364.4 1748.7 2148.8 Mean Corr = 0.66273 Ccne1 1873.7 2335.1 2646.7 Cul1 1898.2 2602.5 2686.9 Skp1a 14823.8 15584.5 15925.1 Ercc6l 1206.4 1328.2 1420.9 Cdc6 2950.1 3114.9 3357.8 Exo1 1608.8 1900.4 1994.5 Fen1 3006.0 3291.3 3568.9 Cdk1 6099.7 6600.2 6856.3 CEM 1 + Cdca5 1661.4 1906.0 1939.9 Top 10 Genes Gins1 2436.5 2835.1 2914.0 Tipin 9454.1 9987.0 10432.6 Mcm5 7682.0 9345.6 10437.8 Rad51 3399.7 3537.0 3674.8

Null module Cdkn1b Cdk2 GEO Series "GSE11222" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 42 -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=GSE11222 Status: Public on Apr 23 2008 Title: Placental and decidual timecourse samples normalized and modeled with an undissected e17 sample Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18340042 Summary & Design: Summary: We used full genome microarrays to profile the full lifetime of the mouse placenta from embryonic day 8.5 (e8.5), at the time of chorioallantoic fusion, until postnatal day 0 (P0). For these samples, at each stage the fetal placenta and maternal decidual tissues were dissected and profiled separately (See series 1).

For this experiment (Series 2), placental and decidual timecourse samples were normalized and modeled with two undissected (including placental and decidual tissue) e17 placentas to allow for scaling of values for comparison to the undissected placenta samples used in the publicly available mouse GeneAtlas dataset

Keywords: time course

Overall design: Mouse placentas were obtained from timed pregnant female mice at each timepoint, and fetal tissues were used to confirm embryo staging. For all dissected samples, fetal placenta and maternal decidual tissues were dissected and pooled separately for each litter prior to RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.1507, L1-Distance = 0.0356, L2-Distance = 0.0027, Normal std = 0.3773

1.057 Kernel fit Pairwise Correlations Normal fit

Density 0.529

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

PlacentaPlacenta e8.5, biologicalPlacenta e9.0, biologicalPlacenta e9.0, rep3 biologicalPlacenta(Series e9.0, rep1 biologicalPlacenta(Series2) e10.5, rep2(0.0714859) Placenta(Series 2)biological e10.5, rep3(0.061184) Placenta(Series 2)biological e10.5, (0.0426343) rep1 Placenta 2) biological (Seriese12.0, (0.040633) rep2Placenta biological (Series2)e12.0, rep3(0.0474225)Placenta biological (Series2)e12.0, rep1(0.0292555)Placenta biological (Series2)e13.5, rep2(0.0578238)Placenta biological (Series2)e13.5, rep3(0.0435442)Placenta biological (Series2)e15.0, rep1(0.0333328)Placenta biological (Series2)e15.0, rep2(0.0521076)Placenta biological (Series2)e15.0, rep1(0.0103677)Placenta biological (Series2)e17.0, rep2(0.00257925)Placenta biological (Series2)e17.0, rep3(0.0199403)Placenta biological (Series2)e17.0, rep1(0.0137182)Placenta biological (Series2)e19.0, rep2(0.00762378)Placenta biological (Series2)e19.0, rep3(0.0126176)Placenta biological (Series2)P0, rep1(0.0091203) biologicalDecidua (Series2)P0, rep2(0.0171295) biologicalDecidua rep1e8.5,(Series2) (0.00685506) (SeriesbiologicalDecidua rep2e8.5,2) (0.0160514) (Series2)biologicalDecidua (0.0247381)e8.5, rep1, 2)biological Deciduatechnical (0.012882)e8.5, rep2, biological Deciduatechnical e9.0, rep1,rep1 biological Decidua(Seriestechnical e9.0, rep2,rep1 biological Decidua(Seriestechnical2) e10.5, rep1rep2(0.0108675) (SeriesDecidua(Series2)biological e10.5, rep2rep2(0.0074342) (Series2)Decidua(Series2)biological e12.0, (0.0119328) (0.00465939)rep1 2)Decidua 2)biological (Seriese12.0, (0.0128078) (0.0117922)rep2 Decidua biological (Series2)e15.0, rep1(0.0177324) Decidua biological (Series2)e15.0, rep2(0.0189108) Decidua biological (Series2)e17.0, rep1(0.027035) Decidua biological (Series2)e17.0, rep2(0.0167716) Decidua biological (Series2)e19.0, rep1(0.0423733) Decidua biological (Series2)e19.0, rep2(0.00987058) Decidua biological (Series2)P0, rep1(0.0213996) biologicalPlacenta (Series2)P0, rep2(0.0161003) biologicalPlacenta rep1(Series2) and (0.0227609) (SeriesDecidua rep22) and (0.00770193) (Series2)Decidua e17.0, (0.0689837) 2) biological e17.0, (0.01621) biological[ repmin 1 (Series rep ] 2 (Series2) (0.00861152) 2) (0.012998)[ medium ] [ max ] CEM 1 Cks1b 331.2 725.8 3579.0 P ( S | Z, I ) = 1.00 Skp2 150.4 266.2 2269.5 Mean Corr = 0.65854 Ccne1 196.6 303.0 2195.6 Cul1 634.6 1657.0 2799.2 Skp1a 2016.5 3644.8 5750.3 Ercc6l 164.0 244.0 818.7 Cdc6 56.5 148.0 1901.3 Exo1 64.0 110.6 931.0 Fen1 113.0 273.7 1823.1 Cdk1 213.3 959.0 6201.9 CEM 1 + Cdca5 145.0 239.3 785.2 Top 10 Genes Gins1 141.3 226.4 812.3 Tipin 235.0 451.7 2078.8 Mcm5 206.6 497.0 4293.5 Rad51 84.9 174.1 1893.8

Null module Cdkn1b Cdk2 GEO Series "GSE51385" 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=GSE51385 Status: Public on Oct 18 2013 Title: Expression profiling of ProB and PreB cells in Ebf1 heterozygous mouse bone marrow Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24078629 Summary & Design: Summary: Loss of one allele of Ebf1 impairs pre-B cell (B220+CD19+CD43low/negIgM-) expansion. In order to better understand the underlying cause of the reduced pre-B cell compartment in Ebf1+/- mice, we sorted pro-B (B220+CD19+CD43highIgM- ) as well as pre-B cells from Wt and Ebf1 heterozygote mutant mice and performed Affymetrix based microarray gene expression analysis.

While the overall gene expression patterns as well as Pax5 expression in Wt and Ebf1 pro-B cells were similar, gene set enrichment (GSE) analysis of the microarray data suggested a reduced expression of cell division (p<0.001) and mitosis (p<0.001) genes in the Ebf1+/- pre-B cells as compared to their Wt counterparts. This in combination with rather normal expression of B-lineage genes in Ebf1+/- pre-B cells opens for the possibility that the phenotypic loss of pre-B cells in Ebf1+/- mice could be a result of reduced expansion of progenitors rather than by a differentiation block.

Overall design: RNA was extracted from 20,000 or 25000 purified adult bone marrow cells using the RNAeasy microkit. RNA was labeled and amplified by dual amplification and hybridized to Affymetrix microarray MOE430_2, according to AffymetrixTM GeneChip Expression Analysis Technical Manual. Probe level expression values were calculated using the RMA algorithm.

Background corr dist: KL-Divergence = 0.0357, L1-Distance = 0.0280, L2-Distance = 0.0014, Normal std = 0.6198

0.644 Kernel fit Pairwise Correlations Normal fit

Density 0.322

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

Ebf1 heteroEbf1 PreB_1heteroEbf1 PreB_2(0.156397)heteroEbf1 ProB_2(0.153417)heteroWT PreB_2 ProB_1(0.10666)WT PreB_1(0.156442) (0.0886251)WT ProB_1(0.117627)WT ProB_2(0.071119) (0.149712) [ min ] [ medium ] [ max ] CEM 1 Cks1b 222.2 3170.2 5303.5 P ( S | Z, I ) = 1.00 Skp2 85.5 736.3 1089.0 Mean Corr = 0.64970 Ccne1 253.3 937.2 1252.1 Cul1 2809.5 3435.3 4197.6 Skp1a 2383.0 4087.6 4807.2 Ercc6l 298.1 1701.8 2399.2 Cdc6 145.8 1544.1 2359.0 Exo1 80.3 830.8 988.2 Fen1 288.0 2083.4 2575.6 Cdk1 730.5 6867.9 8942.1 CEM 1 + Cdca5 180.0 2051.1 2893.5 Top 10 Genes Gins1 562.0 3042.7 3422.4 Tipin 757.7 4472.2 5669.3 Mcm5 280.6 2113.5 2862.2 Rad51 68.0 943.4 1315.8

Null module Cdkn1b Cdk2 GEO Series "GSE12498" 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=GSE12498 Status: Public on Nov 21 2008 Title: Gene expression profiles regulated by Tead2 mutants, Yap, and cell density in NIH3T3 cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19004856 Summary & Design: Summary: Regulation of organ size is important for development and tissue homeostasis. In Drosophila, Hippo signaling controls organ size by regulating the activity of a TEAD transcription factor, Scalloped, through modulation of its coactivator protein Yki. The role of mammalian Tead proteins in growth regulation, however, remains unknown. Here we examined the role of mouse Tead proteins in growth regulation. In NIH3T3 cells, cell density and Hippo signaling regulated the activity of Tead proteins by modulating nuclear localization of a Yki homologue, Yap, and the resulting change in Tead activity altered cell proliferation. Tead2-VP16 mimicked Yap overexpression, including increased cell proliferation, reduced cell death, promotion of EMT, lack of cell contact inhibition, and promotion of tumor formation. Growth promoting activities of various Yap mutants correlated with their Tead-coactivator activities. Tead2-VP16 and Yap regulated largely overlapping sets of genes. However, only a few of the Tead/Yapregulated genes in NIH3T3 cells were affected in Tead1-/-;Tead2-/- or Yap-/- embryos. Most of the previously identified Yap-regulated genes were not affected in NIH3T3 cells or mutant mice. In embryos, levels of nuclear Yap and Tead1 varied depending on cell types. Strong nuclear accumulation of Yap and Tead1 were seen in myocardium, correlating with requirements of Tead1 for proliferation. However, their distribution did not always correlate with proliferation. Taken together, mammalian Tead proteins regulate cell proliferation and contact inhibition as a transcriptional mediator of Hippo signaling, but the mechanisms by which Tead/Yap regulate cell proliferation differ depending on cell types, and Tead, Yap and Hippo signaling may play multiple roles in mouse embryos.

We used microarrays to know the gene expression profiles regurated by Tead2-VP16, Tead2-EnR, Yap, and cell density in NIH3T3 cells.

Keywords: Cell density, genetic modification

Overall design: Tead2-VP16-, Tead2-EnR-, Yap- and control vector-expressing cells were cultured at low or high density for RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0711, L1-Distance = 0.0551, L2-Distance = 0.0045, Normal std = 0.5445

0.805 Kernel fit Pairwise Correlations Normal fit

Density 0.402

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-low-1ctrl-low-2 (0.187433)tead2VP16-conf-1 (0.187655)tead2VP16-conf-2yap-conf-1 (0.122454)yap-conf-2 (0.0450342)(0.0581089)tead2EnR-low-1 (0.0216919)tead2EnR-low-2ctrl-over-1 (0.0664286)ctrl-over-2 (0.0900336) (0.0533802)tead2VP16-over-1 (0.0549791)tead2VP16-over-2 (0.0406349) (0.0721672) [ min ] [ medium ] [ max ] CEM 1 Cks1b 1444.5 1932.6 4857.4 P ( S | Z, I ) = 1.00 Skp2 626.2 883.5 2591.3 Mean Corr = 0.64882 Ccne1 299.4 347.3 861.0 Cul1 1167.9 1392.5 1579.2 Skp1a 5814.1 7489.2 8227.3 Ercc6l 324.3 445.3 2315.4 Cdc6 138.1 361.2 2138.2 Exo1 78.8 163.3 1094.4 Fen1 536.0 1026.6 3458.4 Cdk1 1012.3 1230.8 6611.2 CEM 1 + Cdca5 141.6 196.6 1127.1 Top 10 Genes Gins1 126.9 172.5 1120.9 Tipin 1218.8 1462.1 3413.9 Mcm5 416.5 774.5 5949.3 Rad51 329.1 456.5 3226.3

Null module Cdkn1b Cdk2 GEO Series "GSE15161" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 26 -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=GSE15161 Status: Public on Apr 10 2009 Title: Expression data from retroviral vector-infected immortalized mouse embryonic fibroblasts (MEFs) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19483725 Summary & Design: Summary: Cultured cancer cells exhibit substantial phenotypic heterogeneity when measured in a variety of ways such as sensitivity to drugs or the capacity to grow under various conditions. Among these, the ability to exhibit anchorage-independent cell growth (colony forming capacity in semisolid media) has been considered to be fundamental in cancer biology because it has been connected with tumor cell aggressiveness in vivo such as tumorigenic and metastatic potentials, and also utilized as a marker for in vitro transformation. Although multiple genetic factors for anchorage-independence have been identified, the molecular basis for this capacity is still largely unknown. To investigate the molecular mechanisms underlying anchorage-independent cell growth, we have used genome-wide DNA microarray studies to develop an expression signature associated with this phenotype. Using this signature, we identify a program of activated mitochondrial biogenesis associated with the phenotype of anchorage-independent growth and importantly, we demonstrate that this phenotype predicts potential for metastasis in primary breast and lung tumors.

Keywords: c-Myc or v-Src retroviral vector-infected immortalized mouse embryonic fibroblasts.

Overall design: Expression data of c-Myc and v-Src transformed MEFs was used to validate an expression signature generated from human cultured breast cancer cell lines with anchorage-independent growth ability.

Background corr dist: KL-Divergence = 0.2660, L1-Distance = 0.0442, L2-Distance = 0.0043, Normal std = 0.2972

1.342 Kernel fit Pairwise Correlations Normal fit

Density 0.671

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

ImmortalizedImmortalized MEFsImmortalized WA, MEFsImmortalized empty WA, MEFsImmortalized retroviral empty WA, MEFsImmortalized retroviral empty vector WB, MEFsImmortalized retroviral empty infected,vector WB, MEFsImmortalized retroviral empty infected,vector WB,rep1 MEFsImmortalized retroviral empty(0.020073) infected,vector WC,rep2 MEFsImmortalized retroviral empty(0.0346528) infected,vector WC,rep3 MEFsImmortalized retroviral empty(0.0328844) infected,vector WC,rep1 MEFsImmortalized retroviral empty(0.051419) infected,vector WA,rep2 MEFsImmortalized retroviral human(0.0202) infected,vector WA,rep3 MEFsImmortalized humanc-myc(0.0340379) infected,vector WA,rep1 MEFsImmortalized expression humanc-myc(0.0637202) infected, WB,rep2 MEFsImmortalized expression humanc-myc(0.11241) WB,rep3 retroviralMEFsImmortalized expression humanc-myc(0.0458083) WB, retroviralMEFs Immortalizedvector expression humanc-myc WC, retroviralMEFs infected,Immortalizedvector expression humanc-myc WC, retroviralMEFs infected,Immortalizedvector expression rep1humanc-myc WC, retroviralMEFs (0.0326642) infected,Immortalizedvector expression rep2humanc-myc WA, retroviralMEFs (0.0329995) infected,Immortalizedvector expression rep3v-srcc-myc WA, retroviralMEFs (0.0376399) infected,Immortalizedexpressionvector expression rep1v-src WA, retroviralMEFs (0.0867693) infected,Immortalizedexpressionvector rep2v-src retroviralWB, retroviralMEFs (0.0602354) infected,Immortalizedexpressionvector rep3v-src retroviralWB, MEFs (0.062264) vector infected,Immortalizedexpressionvector rep1v-src retroviralWC, MEFs infected,(0.0106207) vector infected,expression rep2v-src retroviralWC, MEFs infected,(0.0186612)vector expressionrep1 rep3v-src retroviralWC, (0.0152677) infected,(0.0403515)vector expressionrep2 v-src retroviral (0.0250071) infected,vector [expressionrep3 min retroviral (0.0329619) infected,vector rep2 retroviral] (0.0210854) infected,vector rep3 (0.0118817) infected,vector rep1[ (0.0312922) mediuminfected, rep2 (0.0361726) rep3 (0.0289195) ] [ max ] CEM 1 Cks1b 5056.1 7365.4 10761.9 P ( S | Z, I ) = 1.00 Skp2 895.5 2033.5 2772.7 Mean Corr = 0.64638 Ccne1 622.2 1000.5 1419.3 Cul1 1378.4 1736.7 2356.2 Skp1a 5250.2 6441.1 8745.9 Ercc6l 653.3 1079.2 1215.9 Cdc6 227.8 567.9 936.5 Exo1 436.9 795.8 1182.4 Fen1 954.8 2043.3 2744.5 Cdk1 5137.1 6624.2 8377.6 CEM 1 + Cdca5 382.2 807.7 1008.6 Top 10 Genes Gins1 412.1 643.9 1115.1 Tipin 1998.3 3812.5 5140.8 Mcm5 1782.2 2896.5 5774.3 Rad51 955.3 1592.7 2202.5

Null module Cdkn1b Cdk2 GEO Series "GSE32078" 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=GSE32078 Status: Public on Sep 14 2011 Title: Differential gene expression profiles during embryonic heart development in diabetic mice pregnancy Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23287646 Summary & Design: Summary: Congenital heart defects (CHD) are one of the most common defects in offspring of diabetic mothers. There is a clear association between maternal diabetes and CHD; however the underlying molecular mechanism remains unknown. We hypothesized that maternal diabetes affects with the expression of early developmental genes that regulate the essential developmental processes of the heart, thereby resulting in the pathogenesis of CHD. We analyzed genome-wide expression profiling in the developing heart of embryos from diabetic and control mice by using the oligonucleotide microarray. Microarray analysis revealed that a total of 878 genes exhibited more than 1.5 fold changes in expression level in the hearts of experimental embryos in either E13.5 or E15.5 compared with their respective controls. Expression pattern of genes that is differentially expressed in the developing heart was further examined by the real-time reverse transcriptase-polymerase chain reaction. Several genes involved in a number of molecular signaling pathways such as apoptosis, proliferation, migration and differentiation in the developing heart were differentially expressed in embryos of diabetic pregnancy. It is concluded that altered expression of several genes involved in heart development may contribute to CHD in offspring of diabetic mothers.

Overall design: Embryos with heart malformations from diabetic mice were used as the experimental samples. At least three or four embryos each from three or four different litters of diabetic or control groups were used for each microarray experiment (n = 3). Total RNA was extracted from the pooled embryonic heart tissues at E13.5 and E15.5 of diabetic and control groups using RNeasy micro kit (Qiagen, CA, USA). RNA was quantified by Nanodrop 1000 (Thermo Scientific, MA, USA) and its quality was determined using a Bioanalyzer (Agilent, CA, USA). For each sample, 100 ng of total RNA was used for the 3 IVT Express assay according to Origen Labs SOP (Origen Labs, Singapore). The extracted total RNA was transcribed into cDNA, which was then used as a template to synthesize biotin-labeled aRNA (amplified RNA). The aRNA was then fragmented and hybridized to Affymetrix Mouse Genome 430 2.0 array(Affymetrix, CA, USA) for 16 hours at 45ÂºC with rotation at 60 rpm. Arrays were then washed and stained using the FS450_0004 fluidics protocol on 3 fluidics stations and scanned using an Affymetrix 3000 7G scanner (Affymetrix, CA, USA). The scanned images were inspected for hybridization efficiency. The raw data (CEL) files generated from GCOS (GeneChip Operating Software, Affymetrix, CA, USA) were imported into Expression Console (EC) 1.1 (Affymetrix, CA, USA) to perform the Mas5 normalization and generate the quality control (QC) metrics.

Background corr dist: KL-Divergence = 0.1298, L1-Distance = 0.0323, L2-Distance = 0.0018, Normal std = 0.3944

1.011 Kernel fit Pairwise Correlations Normal fit

Density 0.506

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

EmbryonicEmbryonic dayEmbryonic 13.5 day controlEmbryonic 13.5 day controlreplicateEmbryonic 13.5 day controlreplicate Embryonic1 13.5 (0.0452848) day diabetesreplicate Embryonic2 13.5 (0.0440124) day diabetes replicateEmbryonic3 13.5 (0.116305) day diabetes replicateEmbryonic 15.5 1 (0.098669) day control replicateEmbryonic 15.5 2 (0.173968) day controlreplicateEmbryonic 15.5 3 (0.055611) day controlreplicate Embryonic1 15.5 (0.0472041) day diabetesreplicate 2 15.5 (0.0299014) day diabetes replicate3 15.5 (0.0651567) diabetes replicate 1 (0.0471932) replicate[ 2 min(0.214296) 3 (0.0623989) ] [ medium ] [ max ] CEM 1 Cks1b 3859.2 5672.7 6208.2 P ( S | Z, I ) = 1.00 Skp2 691.7 1159.9 1359.4 Mean Corr = 0.64426 Ccne1 391.8 548.3 694.6 Cul1 1610.2 1818.8 2120.2 Skp1a 11458.2 13861.6 15595.1 Ercc6l 677.5 790.8 903.9 Cdc6 466.0 597.5 776.0 Exo1 282.9 507.5 786.9 Fen1 531.6 694.0 803.8 Cdk1 3197.4 3925.9 4329.4 CEM 1 + Cdca5 313.9 461.4 515.8 Top 10 Genes Gins1 919.1 1173.1 1428.0 Tipin 1903.0 2230.3 2662.9 Mcm5 466.0 643.1 770.6 Rad51 721.1 960.7 1184.4

Null module Cdkn1b Cdk2 GEO Series "GSE32277" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 33 -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=GSE32277 Status: Public on Apr 30 2012 Title: Kras is required for pancreatic tumor maintenance through regulation of hexosamine biosynthesis and the non-oxidative pentose phosphate pathway Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22541435 Summary & Design: Summary: The maintenance of advanced malignancies relies on continued activity of driver oncogenes, although their rate-limiting role is highly context-dependent with respect to tumor types and associated genetic alterations. Oncogenic Kras mutation is the signature event in human pancreatic ductal adenocarcinoma (PDAC), serving a critical role in tumor initiation. Here, an inducible KrasG12D-driven p53 mutant PDAC mouse model establishes that advanced PDAC remains strictly dependent on continued KrasG12D expression and that KrasG12D serves a vital role in the control of tumor metabolism, through stimulation of glucose uptake and channeling of glucose intermediates through the hexosamine biosynthesis pathway (HBP) and the pentose phosphate pathway (PPP). Notably, these studies reveal that oncogenic Kras regulates ribose biogenesis. Unlike canonical models of PPP-mediated ribose biogenesis, we demonstrate that oncogenic Kras drives intermediates from enhanced glycolytic flux into the non-oxidative arm of the PPP, thereby decoupling ribose biogenesis from NADPNADPH-mediated redox control. Together, this work provides in vivo mechanistic insights into how oncogenic Kras promotes metabolic reprogramming in native tumors and illuminates potential metabolic targets that can be exploited for therapeutic benefit in Kras-driven PDAC.

Overall design: Primary pancreatic tumor lines were established from p48Cre tetO_LKrasG12D ROSA_rtTAL+ p53L+ mice. Five independent tumor lines (iKras1-5) were used for pancreatic injection into nude mice to generate orthotopic tumors. The mice were kept on doxycycline for 2 weeks until obvious tumor formation. Half of the animals were pulled off doxycycline for 24 hours. Tumors with over 75% cellularity were collected for total RNA prepartion. For in vitro expression profiles, the same five tumor lines were cultured in the presence or absence of doxycycline for 24 hours and total cellular RNA was prepared. For control samples, two independent tumor lines from LSL-KrasG12D p53L+ tumors were cultured in the presence or absence of doxycycline for 24 hours and total cellular RNA was prepared.

Background corr dist: KL-Divergence = 0.1319, L1-Distance = 0.0356, L2-Distance = 0.0021, Normal std = 0.4008

1.012 Kernel fit Pairwise Correlations Normal fit

Density 0.506

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

iKras5-T-on-1iKras5-T-on-2 (0.0120045)iKras5-T-off-1 (0.0120293)iKras5-T-off-2 (0.00790258)iKras1-T-on-1 (0.0171355)iKras1-T-on-2 (0.0131677)iKras1-T-off-1 (0.0138594)iKras2-T-on-1 (0.0167071)iKras2-T-on-2 (0.0228611)iKras2-T-off-1 (0.0275094)iKras2-T-off-2 (0.0173716)iKras3-T-on-1 (0.0151789)iKras3-T-on-2 (0.0166644)iKras3-T-off-1 (0.0151103)iKras3-T-off-2 (0.0142854)iKras4-T-on-1 (0.0149072)iKras4-T-on-2 (0.00900073)iKras4-T-off-1 (0.011664)iKras4-T-off-2 (0.00950219)iKras5-C-on (0.0196251)iKras1-C-on (0.0133944)iKras2-C-on (0.0146876)iKras3-C-on (0.0261463)iKras4-C-on (0.011863)iKras5-C-off (0.00883717)iKras1-C-off (0.0255788)iKras2-C-off (0.0257673)iKras3-C-off (0.0231227)iKras4-C-off (0.00547381)LSL-Kras2-on (0.00661234)LSL-Kras2-off (0.06242)LSL-Kras1-on (0.088835)LSL-Kras1-off (0.200521) (0.200254) [ min ] [ medium ] [ max ] CEM 1 Cks1b 1512.6 2750.0 8045.1 P ( S | Z, I ) = 1.00 Skp2 137.0 405.0 2397.0 Mean Corr = 0.62735 Ccne1 41.8 173.9 430.2 Cul1 1140.6 1486.0 3018.9 Skp1a 5096.4 7115.0 10467.1 Ercc6l 165.7 397.5 1289.3 Cdc6 33.1 183.3 1303.8 Exo1 92.7 225.9 1100.9 Fen1 275.4 712.5 2540.8 Cdk1 1109.2 2915.1 9642.2 CEM 1 + Cdca5 165.1 454.1 1384.0 Top 10 Genes Gins1 109.1 227.0 2071.9 Tipin 200.5 749.3 3449.7 Mcm5 339.1 891.5 3504.1 Rad51 176.7 521.7 2309.6

Null module Cdkn1b Cdk2 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(0.177264) SPLENOCYTES_CD117POS_952 LEUKEMIC(0.109868) SPLENOCYTES_CD117NEG_953 (0.101123) SPLENOCYTES_CD117POS_953 (0.15744)[ min(0.0840758) (0.138676) ] (0.0951022) [(0.136451) medium ] [ max ] CEM 1 Cks1b 800.8 2327.6 2760.4 P ( S | Z, I ) = 1.00 Skp2 724.1 2201.0 2998.2 Mean Corr = 0.62565 Ccne1 148.8 228.4 301.4 Cul1 3738.9 4553.5 4990.0 Skp1a 2244.2 4384.4 5087.2 Ercc6l 750.9 1526.7 1933.3 Cdc6 1553.7 3787.0 4412.4 Exo1 333.3 973.9 1330.7 Fen1 357.0 653.4 1364.5 Cdk1 2513.2 5697.0 7605.1 CEM 1 + Cdca5 809.3 1860.0 2721.9 Top 10 Genes Gins1 1006.4 2129.7 2552.9 Tipin 1867.0 3004.7 4573.5 Mcm5 2327.7 3385.2 5487.8 Rad51 532.7 1446.7 2928.1

Null module Cdkn1b Cdk2 GEO Series "GSE46970" 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=GSE46970 Status: Public on Jun 18 2013 Title: Gene expression of 4, 5, and 6 days differentiated Flk1+ WT ES cells, and of 6 days differentiated Flk1+ Runx1-/- and Tal-1-/- ES cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19265543 Summary & Design: Summary: In order to identify genes that are activated in differentiating WT ESCs, but are missing in Tal-1-/- and Runx1-/- ESCs, and which might be involved in the generation of definitive hematopoietic progenitors and their specification thereafter, we performed microarray analyses on purified Flk-1+ cells, differentiated from these ESCs for 4, 5, and 6 days in vitro.

Overall design: Gene-expression profiling of three biological replicates was performed at days 4, 5, and 6 during the differentiation process of WT J1 ESCs (9 samples), and at day 6 during the differentiation process of either Runx1-/- J1 or Tal-1-/- J1 ESCs (3 samples each). Total RNA was extracted using the RNeasy Mini kit (Qiagen). The integrity and amount of isolated RNA was assessed for each sample using an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany) and a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE). Complementary DNA was synthesized from 3-5 Î¼g total RNA, using reagents recommended in the technical manual GeneChip Expression Analysis (Affymetrix, Santa Clara, CA). The in vitro transcription, necessary for the synthesis of biotinylated complementary RNA (cRNA) was performed using the Enzo RNA Transcript Labeling kit (Affymetrix). Fifteen micrograms of fragmented cRNA of each sample were hybridized to nine Mouse Genome 430-2 arrays (Affymetrix). Hybridization was performed in a Hybridization Oven 640, and chips were washed and stained in the Fluidics Station 400 (both Affymetrix), according to procedure 2 as described in the technical manual. Finally, the arrays were scanned with a GeneChip Scanner 3000 using the GCOS software, both Affymetrix. All relevant GCOS data of quality checked microarrays were analyzed with High Performance Chip Data Analysis (HPCDA, unpublished), using the BioRetis database (www.bioretis-analysis.de), as described and validated previously (55). Used query parameters for database filtering process was described earlier several times (56). For hierarchical cluster analysis, we used the program Genes@Work (57) with gene vectors for normalization and Pearson w/mean for similarity measure. As cluster type, we used center of mass.

Background corr dist: KL-Divergence = 0.1350, L1-Distance = 0.0345, L2-Distance = 0.0023, Normal std = 0.3999

1.009 Kernel fit Pairwise Correlations Normal fit

Density 0.505

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

129_Sv_1_WT_d4_4302129_Sv_2_WT_d4_4302129_Sv_3_WT_d4_4302129_Sv_1_WT_d5_4302 (0.168213)129_Sv_2_WT_d5_4302 (0.0769699)129_Sv_3_WT_d5_4302 (0.119194)129_Sv_1_WT_d6_4302 (0.0305774)129_Sv_2_WT_d6_4302 (0.0893207)129_Sv_3_WT_d6_4302 (0.0253196)129_Sv_1_Runx1_Ko_d6_4302 (0.0546008)129_Sv_2_Runx1_Ko_d6_4302 (0.034943)129_Sv_3_Runx1_Ko_d6_4302 (0.0268111)129_Sv_1_Tal1_Ko_d6_4302129_Sv_2_Tal1_Ko_d6_4302 (0.019825)129_Sv_3_Tal1_Ko_d6_4302 (0.106055) (0.0571931) (0.0184843) (0.0559203) (0.116572)[ min ] [ medium ] [ max ] CEM 1 Cks1b 3550.1 6534.4 9783.3 P ( S | Z, I ) = 1.00 Skp2 2111.0 3599.3 4430.5 Mean Corr = 0.62524 Ccne1 109.1 1009.6 3383.4 Cul1 2110.0 2933.2 3935.1 Skp1a 9397.6 14601.1 18427.4 Ercc6l 299.6 1146.3 2325.3 Cdc6 214.5 1804.9 2559.3 Exo1 302.6 1789.9 2609.5 Fen1 942.8 2187.8 2815.9 Cdk1 1555.3 4299.6 6442.7 CEM 1 + Cdca5 236.1 555.1 1601.6 Top 10 Genes Gins1 516.3 2394.5 3735.3 Tipin 2659.5 6642.2 10594.0 Mcm5 1236.5 3331.9 5710.3 Rad51 343.9 1969.5 4417.9

Null module Cdkn1b Cdk2 GEO Series "GSE6933" 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=GSE6933 Status: Public on Oct 11 2007 Title: Unique Molecular Signature of Multipotent Adult Progenitor Cells (Affy) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17683608 Summary & Design: Summary: We compare the transcriptome of embryonic stem cells (ESCs), adult stem cells with apparent greater differentiation potential such as multipotent adult progenitor cells (MAPCs), mesenchymal stem cells (MSCs) and neurospheres (NS). Mouse and rat MAPCs were used in this study and two different array platforms (Affymetrix and NIA) were used for mouse samples.

Keywords: mRNA expression profiling, oligonucleotide microarrays, stem cells

Overall design: Three mRNA samples (biological replicates) per cell type taken at different passage number were compared. Cell types include mouse ESCs, mouse MSCs and three clones isolated using mouse MAPC culture condition: mMAPC-1, mMAPC-2 and mClone-3. mMAPC-1 and mClone-3 were obtained from same bone marrow isolation, mMAPC-2 was obtained in a different bone marrow isolation. Two clones derived from same rat bone marrow using rat MAPC culture conditions were compared. Three mRNA samples (biological replicates) per clone were taken at different passage numbers

Background corr dist: KL-Divergence = 0.0852, L1-Distance = 0.0624, L2-Distance = 0.0067, Normal std = 0.5110

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

MSC A AffyMSC (0.041887) B AffyMSC (0.111811) C AffymMAPC-1 (0.0172089)mMAPC-1 A AffymMAPC-1 (0.0615222) B AffymMAPC-2 (0.0335124) C AffymMAPC-2 (0.0309084) A AffymMAPC-2 (0.0437924) B AffymClone-3 (0.0185562) C AffymClone-3 (0.0285655)A AffymClone-3 (0.0798269) B AffyESC (0.0824351) C AffyA AffyESC (0.0944896) (0.128072) B AffyESC (0.11508) C Affy (0.112332) [ min ] [ medium ] [ max ] CEM 1 Cks1b 992.8 2742.9 5668.4 P ( S | Z, I ) = 1.00 Skp2 360.7 2498.9 3435.5 Mean Corr = 0.62764 Ccne1 476.5 912.2 4494.4 Cul1 2936.4 5403.7 9641.6 Skp1a 7127.9 8375.5 14087.4 Ercc6l 382.2 1463.3 2919.2 Cdc6 363.1 4292.2 8343.1 Exo1 167.8 1632.7 3349.0 Fen1 328.0 2016.2 2356.6 Cdk1 2742.6 7282.7 9384.7 CEM 1 + Cdca5 396.3 1251.4 3739.6 Top 10 Genes Gins1 313.0 1744.2 3074.0 Tipin 1157.5 4430.7 9965.7 Mcm5 627.6 3874.7 6617.1 Rad51 584.1 3109.0 3731.6

Null module Cdkn1b Cdk2 GEO Series "GSE21278" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 48 -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=GSE21278 Status: Public on May 04 2010 Title: A genomic atlas of mouse hypothalamic development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20436479 Summary & Design: Summary: The hypothalamus is a central regulator of many behaviors essential for survival such as temperature regulation, food intake and circadian rhythms. However, the molecular pathways that mediate hypothalamic development are largely unknown. To identify genes expressed in developing mouse hypothalamus, microarray analysis at 12 different developmental time points was performed. Developmental in situ hybridization was conducted for 1,045 genes dynamically expressed by microarray analysis. In this way, we identified markers that stably labeled each major hypothalamic nucleus over the entire course of neurogenesis, and thus constructed a detailed molecular atlas of the developing hypothalamus. As proof of concept for the utility of this data, we used these markers to analyze the phenotype of mice where Sonic Hedgehog (Shh) was selectively deleted from hypothalamic neuroepithelium, demonstrating an essential role for Shh in anterior hypothalamic patterning. Our results serve as a resource for functional investigations of hypothalamic development, connectivity, physiology, and dysfunction.

Overall design: Affymetrix MOE430 microarrays were used to analyze the expression patterns of mouse hypothalamic and preoptic area tissues. The results were compared across the variables of Strain, Sex and Age.

Background corr dist: KL-Divergence = 0.1534, L1-Distance = 0.0326, L2-Distance = 0.0023, Normal std = 0.3769

1.058 Kernel fit Pairwise Correlations Normal fit

Density 0.529

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

C57Bl/6C57Bl/6 E10 Female,C57Bl/6 E10 Male, hypothalamusC57Bl/6 E11 hypothalamus Female,C57Bl/6 E11 Male, andhypothalamusC57Bl/6 E12 preopticandhypothalamus Female, C57Bl/6 preopticE12 area Male, andhypothalamusC57Bl/6 E13 area(0.136874) preopticandhypothalamus Female, (0.109278) C57Bl/6 preopticE13 area Male, andhypothalamusC57Bl/6 E14 area(0.0452336) preopticandhypothalamus Female, (0.0733743) C57Bl/6 preopticE14 area Male, andhypothalamusC57Bl/6 E15 area(0.0145915) preopticandhypothalamus Female, (0.0165203) C57Bl/6 preopticE15 area Male, andhypothalamusC57Bl/6 E16 area(0.0160576) preopticandhypothalamus Female, (0.000907983) C57Bl/6 preopticE16 area Male, andhypothalamusC57Bl/6 E17 area(0.00822564) preopticandhypothalamus Female, (0.0329854) C57Bl/6 preopticE17 area Male, andhypothalamusC57Bl/6 E18 area(0.00795102) preopticandhypothalamus Female, (0.00909464) C57Bl/6 preopticE18 area Male, andhypothalamusC57Bl/6 P0 area(0.00487902) preoptic andhypothalamusFemale, (0.012679) C57Bl/6 preopticP0 Male, areahypothalamus andC57Bl/6 P21 area(0.00563523)hypothalamus preopticand Female, (0.00482352) C57Bl/6 preopticP21 areaandMale, hypothalamusC57Bl/6 P42 preopticarea(0.00741823)and hypothalamus Female, preoptic(0.00417541)CD-1 P42 area Male,E10 andhypothalamusCD-1 area(0.00523479) Female, preopticandhypothalamus E10(0.00534718) CD-1preoptic Male, hypothalamus area E11 andCD-1 hypothalamus area(0.00904902)Female, preopticand E11 (0.0112256) CD-1preoptic Male, andhypothalamus area E12 CD-1 preopticandhypothalamus area(0.00668973)Female, preopticE12 (0.00747606)CD-1 area Male, andhypothalamus E13 area(0.0833533) CD-1 preopticandhypothalamus Female, (0.0352041) preopticE13CD-1 area Male, andhypothalamus E14 area(0.0316032) CD-1 preopticandhypothalamus Female, (0.0357115) preopticE14CD-1 area Male, andhypothalamus E15 area(0.026864) CD-1 preopticandhypothalamus Female, (0.00449768) preopticE15CD-1 area Male, andhypothalamus E16 area(0.0111717) CD-1 preopticandhypothalamus Female, (0.00394345) preopticE16CD-1 area Male, andhypothalamus E17 area(0.01027) CD-1 preopticandhypothalamus Female, (0.006118) preopticE17CD-1 area Male, andhypothalamus E18 area(0.0436086) CD-1 preopticandhypothalamus Female, (0.00427603) preopticE18CD-1 area Male, andhypothalamus P0 area(0.00263614) CD-1 preoptic andhypothalamusFemale, (0.00478353) preopticP0CD-1 Male, areahypothalamus and P21 area(0.00565668)hypothalamus CD-1 preopticand Female, (0.00368664) preopticP21CD-1 areaandMale, hypothalamus P42 preopticarea(0.0209449)andCD-1 hypothalamus Female, preoptic(0.0291489) P42 area Male, andhypothalamus area(0.0100411) preopticandhypothalamus (0.0190542) preoptic area and area(0.00837692) [ preopticand min (0.0216393) preoptic area ] area(0.00842386) (0.0132596)[ medium ] [ max ] CEM 1 Cks1b 105.5 936.7 7685.2 P ( S | Z, I ) = 1.00 Skp2 66.1 450.4 3284.9 Mean Corr = 0.60495 Ccne1 62.2 258.1 1518.1 Cul1 1120.7 1469.8 3376.7 Skp1a 4230.4 7332.6 10162.4 Ercc6l 4.3 67.2 1473.5 Cdc6 3.3 70.3 1877.4 Exo1 63.7 181.7 2339.4 Fen1 118.7 306.1 2749.4 Cdk1 9.3 719.5 8404.8 CEM 1 + Cdca5 25.3 193.9 1292.2 Top 10 Genes Gins1 25.2 222.2 2344.2 Tipin 330.9 683.2 3954.8 Mcm5 3.3 313.7 4953.3 Rad51 11.7 144.3 2608.6

Null module Cdkn1b Cdk2 GEO Series "GSE21841" 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=GSE21841 Status: Public on May 15 2010 Title: Expression data from LPS-stimulated RAW 264.7 mouse macrophages treated with Hypericum perforatum fraction and bioactive constituents Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20303133 Summary & Design: Summary: Hypericum perforatum extracts have been used as dietary supplements to treat conditions including mild-moderate depression and inflammation. A group of four bioactive constituents were identified from an active fraction of the extract.

In order to identify the mechanism for the potential anti-inflammatory activity of the identified compounds, we used Affymatrix microarray to study the gene expression profile impacteded by these compounds, as well as the active fraction in LPS-stimulated mouse macrophages.

Overall design: We treated RAW264.7 mouse macrophages with DMSO control, active fraction from Hypericum perforaum extract, and a combination of the 4 putative bioactive compounds, called the 4-component system, all with and without LPS induction. A total of six treatment combinations were included in the final gene expression analysis using microarray.

Background corr dist: KL-Divergence = 0.1757, L1-Distance = 0.0331, L2-Distance = 0.0020, Normal std = 0.3605

1.109 Kernel fit Pairwise Correlations Normal fit

Density 0.554

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+DMSOFraction rep4CS rep 1 rep (0.077087)1 (0.0290635)Media+DMSO+LPS 1 (0.0672781)Fraction+LPS4CS+LPS rep repMedia+DMSO 1 rep (0.0357475)1 (0.0629776) 1Fraction (0.111039) rep4CS rep 2 rep (0.0451315)2 (0.0422943)Media+DMSO+LPS 2 (0.0572215)Fraction+LPS4CS+LPS rep repMedia+DMSO 2 rep (0.0208319)2 (0.107395) 2Fraction (0.0219543) rep4CS rep 3 rep (0.0778981)3 (0.0458042)Media+DMSO+LPS 3 (0.0456921)Fraction+LPS4CS+LPS rep rep 3 rep (0.077445)3 (0.0538566) 3 (0.0212822) [ min ] [ medium ] [ max ] CEM 1 Cks1b 3901.3 5543.4 7550.0 P ( S | Z, I ) = 1.00 Skp2 956.7 1806.1 2879.0 Mean Corr = 0.60414 Ccne1 168.5 363.3 941.0 Cul1 1702.4 2093.7 2567.3 Skp1a 3687.5 4770.7 5728.7 Ercc6l 347.7 567.3 1112.7 Cdc6 149.9 397.3 2120.4 Exo1 347.2 565.7 1261.8 Fen1 1256.1 2127.1 4412.5 Cdk1 3992.8 5504.8 7938.0 CEM 1 + Cdca5 240.2 486.4 971.7 Top 10 Genes Gins1 734.6 1158.0 1956.5 Tipin 5468.0 7671.4 10560.0 Mcm5 2365.1 3828.9 5559.3 Rad51 1204.0 2125.2 3555.5

Null module Cdkn1b Cdk2 GEO Series "GSE7863" 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=GSE7863 Status: Public on Mar 01 2009 Title: Gene expression profiling of Galgt2 overexpression in mdx skeletal muscle Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Transgenic overexpression of Galgt2 in the skeletal muscles of mdx mice inhibits the development of disease pathology associated with muscular dystrophy. This is the case both in transgenic mice, where Galgt2 overexpression occurs from embryonic timepoints onward and in mdx mice where Galgt2 is overexpressed in the early postnatal period using Adeno-associated virus (AAV). Here, we use gene expression profiling to compare transcriptional changes resulting from embryonic and postnatal Galgt2 overexpression in mdx skeletal muscle. A surprising number of changes were in genes known to ameliorate muscular dystrophy when overexpressed (agrin, integrin alpha 7, ADAM12, Bcl2) or to cause muscular dystrophy when mutated (collagen VI (alpha1,alpha2), plectin 1, dystroglycan, selenoprotein N1, integrin alpha7, biglycan, dysferlin). Several genes involved in calcium homeostasis were also changed. In Galgt2 transgenic mice, where embryonic overexpression of Galgt2 in skeletal muscles alters neuromuscular development and muscle growth, the number of gene expression changes was vastly greater, however, 14% of genes altered in postnatal AAV-Galgt2 infected mdx muscles were also changed with embryonic overexpression. These experiments suggest that postnatal overexpression of Galgt2 inhibits muscular dystrophy in mdx mice via induction of a group of genes that, in aggregate, can govern membrane stability, membrane repair, calcium homeostasis, and apoptosis.

Keywords: disease state analysis, gene therapy, comparative gene expression, muscular dystrophy, glycosylation, collagens, integrins, dysferlin, dystroglycan

Overall design: Microarrays were done in three groups at a time. 1) Transgenic Overexpression of Galgt2 - comprised to Wild Type (WT), Galgt2 Transgenic (CT), Dystrophin-Deficient (mdx), and Galgt2 Transgenic and Dystrophin-Deficient (CTmdx) each in duplicate 2) AAV-Mediated Galgt2 Gene Delivery in to the mdx gastrocnemius muscle in the postnatal period - comprised of AAVGalgt2 and PBS each in duplicate, and 3) Myoblasts and myotubes - comptised of one sample each of C1C12 myoblasts and myotubes, C2C12 myoblasts and myotubes stably transfected with Galgt2

Background corr dist: KL-Divergence = 0.0693, L1-Distance = 0.0383, L2-Distance = 0.0029, Normal std = 0.5016

0.795 Kernel fit Pairwise Correlations Normal fit

Density 0.398

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

GastrocnemiusGastrocnemiusGastrocnemius MuscleGastrocnemius MuscleWT rep1Gastrocnemius MuscleWT (0.0286476) rep2Gastrocnemius Musclemdx (0.0307109) rep1Gastrocnemius Musclemdx (0.0458386) rep2Gastrocnemius MuscleGalgt2 (0.0238773)Gastrocnemius TransgenicMuscleGalgt2Gastrocnemius TransgenicMuscleGalgt2 rep1Gastrocnemius TransgenicMuscleGalgt2 (0.0385977) rep2Gastrocnemius TransgenicMusclemdx (0.0178251) mdx AAV-Galgt2-TreatedMyoblast Musclemdx rep1 mdx AAV-Galgt2-Treated Myoblast(0.0273322) Musclemdx Cellrep2 PBS-TreatedLine Myoblast(0.0636841) mdx Cell rep1 PBS-TreatedLineMyoblast (0.0903203)(0.0569698)Cell Differentiatedrep2rep1 Line (0.0766567)(0.0578344)Cell Stablyrep2 Line (0.0428718) rep1 TransfectedStably (0.277376) Transfected[ with min Galgt2 with ] rep1Galgt2 (0.0688126) Differentiated[ medium rep1 (0.0526452) ] [ max ] CEM 1 Cks1b 93.1 229.9 953.8 P ( S | Z, I ) = 1.00 Skp2 30.5 41.4 223.0 Mean Corr = 0.60268 Ccne1 57.3 90.3 278.9 Cul1 1294.3 2090.5 3351.6 Skp1a 1663.9 3400.1 4285.4 Ercc6l 19.3 42.7 192.7 Cdc6 21.9 59.0 278.3 Exo1 21.1 56.6 390.5 Fen1 81.8 262.7 1089.5 Cdk1 72.7 257.9 2058.8 CEM 1 + Cdca5 18.5 31.2 150.3 Top 10 Genes Gins1 111.2 217.9 605.0 Tipin 286.0 436.2 1032.8 Mcm5 24.1 59.1 174.3 Rad51 26.5 63.9 338.9

Null module Cdkn1b Cdk2 GEO Series "GSE15872" 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=GSE15872 Status: Public on Oct 01 2009 Title: Dynamic patterning at the pylorus: formation of an epithelial intestine-stomach boundary in late fetal life Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19877272 Summary & Design: Summary: In the adult mouse, distinct morphological and transcriptional differences separate stomach from intestinal epithelium. Remarkably, the epithelial boundary between these two organs is literally one cell thick. This discrete junction is established suddenly and precisely at embryonic day (E) 16.5, by sharpening a previously diffuse intermediate zone. In the present study, we define the dynamic transcriptome of stomach, pylorus and intestinal tissues between E14.5 and E16.5. We show that establishment of this boundary is concomitant with the induction of over a thousand genes in intestinal epithelium, and these gene products provide intestinal character. Hence, we call this process intestinalization. We identify specific transcription factors (Hnf4g, Creb3l3 and Tcfec) and examine signaling pathways (Hedgehog and Wnt) that may play a role in this process. Finally, we define a unique expression domain at the pylorus itself and detect novel pylorus-specific patterns for the transcription factor Gata3 and the secreted protein nephrocan.

Overall design: Stomach, pylorus and duodenum tissue from E14.5 and E16.5 mouse embryos were collected for RNA extraction and hybridization on Affymetrix microarrays. We sought to study the gene expression profiles and identify genes and pathways enriched in these three tissues at two important developmental times.

Background corr dist: KL-Divergence = 0.0387, L1-Distance = 0.0489, L2-Distance = 0.0046, Normal std = 0.6254

0.638 Kernel fit Pairwise Correlations Normal fit

Density 0.319

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

stomachstomach at E14.5,stomach at biological E14.5,pylorus at biological E14.5, rep1pylorus at E14.5, biological(0.0343878) rep2pylorus at biological E14.5, (0.0391451) rep3duodenum at biological E14.5, (0.0470205) rep1duodenum biological(0.0285163) at rep2 E14.5,duodenum (0.0670696) at rep3biological E14.5,stomach (0.0581587) at biological E14.5,stomach rep1 at E16.5, biological(0.0737976)stomach rep2 at biological E16.5, (0.0382655)pylorus rep3 at biological E16.5, (0.0668392)rep1pylorus at E16.5, biological(0.0705112) rep2pylorus at biological E16.5, (0.0315996) rep3duodenum at biological E16.5, (0.0581837) rep1duodenum biological(0.0680555) at rep2 E16.5,duodenum (0.0488464) at rep3biological E16.5, (0.0495792) at biological E16.5, rep1 biological(0.0614747) rep2 (0.0791727)[ rep3 min (0.0793767) ] [ medium ] [ max ] CEM 1 Cks1b 1212.4 4614.9 5473.5 P ( S | Z, I ) = 1.00 Skp2 1006.9 2869.6 3485.7 Mean Corr = 0.74035 Ccne1 246.2 573.4 731.2 Cul1 1552.3 2119.9 2498.1 Skp1a 3917.5 6479.4 7903.4 Ercc6l 460.1 852.4 1133.5 Cdc6 142.6 837.4 1132.1 Exo1 171.9 572.0 790.5 Fen1 463.3 963.5 1389.0 Cdk1 1765.3 4666.9 5183.8 CEM 1 + Cdca5 318.6 757.7 921.8 Top 10 Genes Gins1 309.9 843.2 1207.9 Tipin 1057.0 3640.2 4476.8 Mcm5 586.4 2008.8 2736.8 Rad51 432.3 1488.6 1929.5

Null module Cdkn1b Cdk2