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

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

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

CLIC PDF output has three sections:

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

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

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

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

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

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

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

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

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

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

Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Ncor1 Snw1 Num ofGenesinQueryGeneset:5.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Glis3 Npat Ski

Snw1 Ncor1 Glis3 Npat Ski CEM 1(36datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 2610008E11Rik Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page1 BC018507 Zmynd11 Fam179b Fam199x Rabgap1 Ccdc88a Dync1li2 Ankrd12 Camk2d Zfp518a Zfp955a Zfyve16 Rb1cc1 Phf20l1 March7 Arfgef1 Ythdc1 Rbm27 Smap1 Zbtb26 Zfp329 Fbxw7 Arid4a Kif16b Ddx42 Ncoa1 Ep300 Baz2b Tnks2 Ncor1 Kat6a Phf20 Zbtb6 Scaf8 Zfp26 Snw1 Adnp Bdp1 Glis3 Sos2 Epc1 Epc2 Npat Dlg5 Rlim Scai Skil Ski Zfr 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE15772 [8] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE30192 [6] GSE34423 [40] GSE30855 [6] GSE8684 [10] GSE25088 [24] GSE8681 [25] GSE39449 [6] GSE17553 [16] GSE42047 [24] GSE22381 [12] GSE13044 [59] GSE35961 [12] GSE32103 [6] GSE13302 [30] GSE23408 [39] GSE8503 [6] GSE5324 [48] GSE6210 [12] GSE12389 [8] GSE11274 [20] GSE14458 [12] GSE9146 [27] GSE56482 [8] GSE9441 [36] GSE47694 [10] GSE32095 [24] GSE30083 [12] GSE54215 [13] GSE13259 [10] GSE17266 [59] GSE17796 [39] GSE43620 [8] GSE22925 [14] GSE10776 [15] GSE6998 [32] GSE6526 [16] GSE35979 [6] GSE21996 [14] GSE17462 [8] GSE43928 [12] GSE40939 [10] GSE45941 [8] GSE55622 [22] GSE51365 [28] GSE46094 [10] GSE21755 [25] GSE4734 [61] GSE12498 [12] GSE12950 [6] GSE27092 [6] GSE20696 [8] GSE2527 [6] GSE24121 [9] GSE16048 [6] GSE4739 [19] GSE11201 [18] GSE37431 [6] GSE26355 [6] GSE23002 [8] GSE30012 [6] GSE22251 [9] GSE34114 [12] GSE27261 [8] GSE24243 [6] GSE24813 [10] GSE7863 [16] GSE31702 [10] GSE8044 [6] GSE31378 [9] GSE54349 [6] GSE1986 [17] GSE4323 [6] GSE10659 [6] GSE44355 [10] GSE43381 [26] GSE28559 [30] GSE17985 [8] GSE51080 [18] GSE37676 [6] GSE46209 [21] GSE56345 [9] GSE41942 [6] GSE32020 [26] GSE21224 [16] GSE33121 [10] GSE7141 [6] GSE16110 [16] GSE11443 [6] GSE56755 [13] GSE12730 [24] GSE31244 [6] GSE47421 [24] GSE44261 [12] GSE32334 [19] GSE28417 [12] GSE15587 [6] GSE1435 [27] GSE10589 [6] GSE56162 [18] GSE34629 [6] GSE11382 [10] GSE8512 [207] GSE26745 [24] GSE17794 [44] GSE5959 [6] GSE24350 [8] GSE50687 [38] GSE21711 [6] GSE21393 [6] GSE19709 [168] GSE28035 [9] GSE25257 [6] GSE21716 [28] GSE15324 [8] GSE19517 [6] GSE11796 [18] GSE51883 [30] GSE6810 [10] GSE27547 [17] GSE15610 [12] GSE11356 [9] GSE14354 [6] GSE14769 [24] GSE17112 [8] GSE12432 [15] GSE11918 [9] GSE8621 [12] GSE20918 [6] GSE47719 [6] GSE22506 [12] GSE20577 [12] GSE26151 [20] GSE28025 [18] GSE19079 [6] GSE15121 [6] GSE42061 [12] GSE46942 [7] GSE9977 [24] GSE13805 [7] GSE22935 [24] GSE53299 [6] GSE5800 [6] GSE48369 [36] GSE58262 [18] GSE13120 [10] GSE15315 [6] GSE40513 [6] GSE15871 [18] GSE11148 [6] GSE55855 [6] GSE18500 [35] CEM+ CEM GSE10902 [6] GSE19403 [12] GSE9763 [20] GSE4189 [14] GSE46646 [12] GSE26668 [6] 0.0 GSE29572 [21] GSE6383 [6]

GSE8434 [6] Scale ofaveragePearsoncorrelations GSE38531 [35] GSE7275 [8] GSE4936 [8] GSE11035 [6] GSE4694 [6] GSE10644 [18] 0.2 GSE50122 [10] GSE41789 [45] GSE11982 [6] GSE9735 [9] GSE27114 [6] GSE8025 [21] GSE15733 [6] GSE13149 [25] GSE46298 [64] 0.4 GSE18460 [16] GSE36826 [12] GSE9810 [13] GSE12388 [8] GSE36237 [64] GSE4098 [16] GSE12769 [20] GSE16266 [6] GSE33688 [12] 0.6 GSE6875 [8] GSE14024 [12] GSE46871 [6] GSE35435 [6] GSE39233 [40] GSE12810 [6] GSE11723 [9] GSE46242 [12] GSE21063 [24] 0.8 GSE7707 [18] GSE48338 [8] GSE10740 [6] GSE22448 [6] Score 15.97 15.98 16.09 16.21 16.23 16.49 16.70 16.84 16.86 16.99 17.16 17.19 17.49 17.98 18.59 18.60 18.88 19.09 19.46 19.63 19.78 20.06 20.13 20.16 20.39 20.49 20.77 20.99 21.09 21.18 21.23 22.01 22.02 22.11 22.31 24.21 24.93 24.95 25.29 26.20 26.57 27.24 29.32 30.51 32.98 1.0 Notes B230219D22Rik Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page2 AU019823 Casp8ap2 Tmem87a Fam168b Fam102b Csnk1g1 Csnk1a1 Zdhhc17 Ankrd44 Ralgapb Appbp2 Dnmt3a Ddx26b Fbxo11 Kbtbd2 Hivep1 Tnrc6c Tnrc6a Zfp788 Lemd3 Zfp317 Zfp251 Rrm2b Arid1b Usp33 Dmxl1 Slmap Exoc4 Exoc5 Casc4 Socs6 Afap1 Dctn4 Cpsf7 Rnf38 Smg1 Zfp62 Taf9b Zfp68 Ttc28 Napg Rbak Lrig2 Pan3 Itpkb Bcor Ofd1 Upf2 Ctcf 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE8434 [6] Scale ofaveragePearsoncorrelations GSE38531 [35] GSE7275 [8] GSE4936 [8] GSE11035 [6] GSE4694 [6] GSE10644 [18] 0.2 GSE50122 [10] GSE41789 [45] GSE11982 [6] GSE9735 [9] GSE27114 [6] GSE8025 [21] GSE15733 [6] GSE13149 [25] GSE46298 [64] 0.4 GSE18460 [16] GSE36826 [12] GSE9810 [13] GSE12388 [8] GSE36237 [64] GSE4098 [16] GSE12769 [20] GSE16266 [6] GSE33688 [12] 0.6 GSE6875 [8] GSE14024 [12] GSE46871 [6] GSE35435 [6] GSE39233 [40] GSE12810 [6] GSE11723 [9] GSE46242 [12] GSE21063 [24] 0.8 GSE7707 [18] GSE48338 [8] GSE10740 [6] GSE22448 [6] Score 11.15 11.16 11.16 11.19 11.25 11.40 11.46 11.50 11.54 11.58 11.61 11.62 11.63 11.69 11.75 11.79 11.79 11.86 11.87 11.93 12.18 12.22 12.33 12.43 12.55 12.58 12.90 12.93 13.03 13.25 13.47 13.53 13.72 13.77 13.97 14.01 14.12 14.15 14.25 14.34 14.58 14.71 14.74 14.76 14.89 15.41 15.48 15.78 15.89 15.95 1.0 Notes Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page3 Commd8 R3hdm1 Adam10 Gltscr1l Ankhd1 Ube2q2 Ppp1cb Cep120 Cdc14a Papolg Trim33 Zfp292 Zfp148 Zfp451 Prpf4b Nufip2 Rsbn1 Wdr47 Akap8 Bclaf1 Klhl15 Mtmr6 Lnpep Snx18 Esco1 Casc3 Mbnl2 Prkg1 Ptbp2 Kat6b Lrch1 Smg7 Pcm1 Foxj3 Gnaq Strn3 Klhl9 Scoc Nck2 Rpgr Brd1 Chm Prkx Bcl9 Git2 Aff1 Bbx Fryl Dr1 Hltf 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE8434 [6] Scale ofaveragePearsoncorrelations GSE38531 [35] GSE7275 [8] GSE4936 [8] GSE11035 [6] GSE4694 [6] GSE10644 [18] 0.2 GSE50122 [10] GSE41789 [45] GSE11982 [6] GSE9735 [9] GSE27114 [6] GSE8025 [21] GSE15733 [6] GSE13149 [25] GSE46298 [64] 0.4 GSE18460 [16] GSE36826 [12] GSE9810 [13] GSE12388 [8] GSE36237 [64] GSE4098 [16] GSE12769 [20] GSE16266 [6] GSE33688 [12] 0.6 GSE6875 [8] GSE14024 [12] GSE46871 [6] GSE35435 [6] GSE39233 [40] GSE12810 [6] GSE11723 [9] GSE46242 [12] GSE21063 [24] 0.8 GSE7707 [18] GSE48338 [8] GSE10740 [6] GSE22448 [6] Score 7.48 7.49 7.60 7.66 7.77 7.88 7.89 8.01 8.06 8.24 8.25 8.26 8.30 8.48 8.54 8.55 8.60 8.61 8.68 8.75 8.77 8.80 8.80 8.86 9.03 9.03 9.11 9.38 9.40 9.46 9.49 9.51 9.61 9.65 9.90 9.93 9.98 10.00 10.03 10.10 10.13 10.19 10.30 10.31 10.40 10.50 10.56 10.62 10.63 11.10 1.0 Notes B630005N14Rik 8430427H17Rik Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page4 D14Abb1e Smarcad1 Secisbp2l Zswim6 Anapc4 Exoc6b Impad1 Tsga10 Osbpl8 Kdm6a Rnf146 Gpkow Zfp131 Zfp799 Ino80d Zfp236 Zfp426 Zfp827 Fem1c Lmbr1 Ubxn7 Ap4e1 Fubp3 Top2b Fmnl2 Srpk2 Upf3a Tdrd3 Spopl Stag2 Esyt2 Ano6 Xpo1 Nbea Tab3 Mbip Brd9 Rnf2 Gja1 Lrif1 Naf1 Rfx7 Eid1 Dsel Slit2 Helz Ctgf Gls 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE8434 [6] Scale ofaveragePearsoncorrelations GSE38531 [35] GSE7275 [8] GSE4936 [8] GSE11035 [6] GSE4694 [6] GSE10644 [18] 0.2 GSE50122 [10] GSE41789 [45] GSE11982 [6] GSE9735 [9] GSE27114 [6] GSE8025 [21] GSE15733 [6] GSE13149 [25] GSE46298 [64] 0.4 GSE18460 [16] GSE36826 [12] GSE9810 [13] GSE12388 [8] GSE36237 [64] GSE4098 [16] GSE12769 [20] GSE16266 [6] GSE33688 [12] 0.6 GSE6875 [8] GSE14024 [12] GSE46871 [6] GSE35435 [6] GSE39233 [40] GSE12810 [6] GSE11723 [9] GSE46242 [12] GSE21063 [24] 0.8 GSE7707 [18] GSE48338 [8] GSE10740 [6] GSE22448 [6] Score 4.97 5.12 5.14 5.20 5.25 5.29 5.40 5.41 5.43 5.57 5.57 5.59 5.61 5.62 5.67 5.72 5.73 5.73 5.75 5.80 5.83 5.86 5.98 6.15 6.15 6.17 6.18 6.25 6.32 6.40 6.53 6.53 6.59 6.66 6.70 6.92 6.92 7.01 7.01 7.05 7.06 7.12 7.15 7.20 7.23 7.23 7.24 7.36 7.39 7.44 1.0 Notes 2810474O19Rik Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page5 Tmem127 Rbm12b2 AI597479 Gprasp1 Tspan13 Zc2hc1a Kctd12b Hmg20a Traf3ip1 Slc18b1 Zfp354c Pik3c2a Map4k3 Ccdc66 Zmym4 Otud7b Skiv2l2 Scaper Kctd18 Nap1l1 Zfp952 Zfc3h1 Zfp763 Lrrcc1 Rc3h1 Ylpm1 Nuak1 Cep95 Usp34 Tnpo1 Fubp1 Sash1 Zmat3 Zc3h4 Micu3 Cstf2t Aggf1 Atp7a Aftph Birc6 Chd8 Uba6 Klhl7 Ppil4 Cnst Cul3 Styx Stx3 Zfx 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE8434 [6] Scale ofaveragePearsoncorrelations GSE38531 [35] GSE7275 [8] GSE4936 [8] GSE11035 [6] GSE4694 [6] GSE10644 [18] 0.2 GSE50122 [10] GSE41789 [45] GSE11982 [6] GSE9735 [9] GSE27114 [6] GSE8025 [21] GSE15733 [6] GSE13149 [25] GSE46298 [64] 0.4 GSE18460 [16] GSE36826 [12] GSE9810 [13] GSE12388 [8] GSE36237 [64] GSE4098 [16] GSE12769 [20] GSE16266 [6] GSE33688 [12] 0.6 GSE6875 [8] GSE14024 [12] GSE46871 [6] GSE35435 [6] GSE39233 [40] GSE12810 [6] GSE11723 [9] GSE46242 [12] GSE21063 [24] 0.8 GSE7707 [18] GSE48338 [8] GSE10740 [6] GSE22448 [6] Score 2.41 2.43 2.54 2.60 2.76 2.78 2.91 2.91 2.97 3.12 3.14 3.22 3.23 3.23 3.28 3.42 3.49 3.51 3.51 3.59 3.61 3.73 3.79 3.80 3.80 3.83 3.84 3.85 3.95 3.96 3.99 4.07 4.20 4.23 4.27 4.29 4.31 4.35 4.44 4.52 4.56 4.67 4.70 4.70 4.84 4.86 4.86 4.90 4.92 4.97 1.0 Notes A630007B06Rik A530054K11Rik Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page6 Tctex1d2 Fam117b Fam118a Tmem68 Tsc22d1 Chmp2b Smndc1 Fam76b Slc12a2 Fam73a Cep290 Sipa1l2 Sipa1l3 Fbxo28 Zcchc7 Ap3m2 Ankib1 Cluap1 Zbtb41 Zbtb10 Zfp871 Zfp438 Mex3b Prpf39 Rab6b Ccpg1 Rab31 Cdk19 Ube3a Pde7a Zmiz1 Appl2 Pptc7 Zfp11 Lztfl1 Lrrc1 Agps Ago1 Chd6 Dph6 Asb7 Mllt3 Sirt1 Msl2 Phip Fat1 Msn Fry 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE8434 [6] Scale ofaveragePearsoncorrelations GSE38531 [35] GSE7275 [8] GSE4936 [8] GSE11035 [6] GSE4694 [6] GSE10644 [18] 0.2 GSE50122 [10] GSE41789 [45] GSE11982 [6] GSE9735 [9] GSE27114 [6] GSE8025 [21] GSE15733 [6] GSE13149 [25] GSE46298 [64] 0.4 GSE18460 [16] GSE36826 [12] GSE9810 [13] GSE12388 [8] GSE36237 [64] GSE4098 [16] GSE12769 [20] GSE16266 [6] GSE33688 [12] 0.6 GSE6875 [8] GSE14024 [12] GSE46871 [6] GSE35435 [6] GSE39233 [40] GSE12810 [6] GSE11723 [9] GSE46242 [12] GSE21063 [24] 0.8 GSE7707 [18] GSE48338 [8] GSE10740 [6] GSE22448 [6] Score 0.48 0.48 0.48 0.48 0.49 0.76 0.76 0.85 0.88 0.90 0.95 1.01 1.03 1.04 1.05 1.06 1.07 1.08 1.10 1.13 1.14 1.19 1.22 1.24 1.34 1.37 1.45 1.48 1.51 1.52 1.57 1.60 1.72 1.79 1.80 1.86 1.94 1.94 1.95 1.95 2.08 2.15 2.30 2.31 2.32 2.34 2.36 2.38 2.39 2.40 1.0 Notes Symbol Num ofCEMGenes:5.Predicted310.SelectedDatasets:36.Strength:0.1 CEM 1,Geneset"[G]nuclearpart",Page7 Tmem168 Nup214 Fbxo25 Prkaa1 Golm1 Apbb2 Abca9 Appl1 Wsb1 Actr2 Gab1 Vgll3 Pkd2 Irgq Klf7 0.0 1.0

GSE18907 [12] GSE23895 [18]

GSE15772 [8] Only showingfirst200datasets-Seetxtoutputforfulldetails . GSE30192 [6] GSE34423 [40] GSE30855 [6] GSE8684 [10] GSE25088 [24] GSE8681 [25] GSE39449 [6] GSE17553 [16] GSE42047 [24] GSE22381 [12] GSE13044 [59] GSE35961 [12] GSE32103 [6] GSE13302 [30] GSE23408 [39] GSE8503 [6] GSE5324 [48] GSE6210 [12] GSE12389 [8] GSE11274 [20] GSE14458 [12] GSE9146 [27] GSE56482 [8] GSE9441 [36] GSE47694 [10] GSE32095 [24] GSE30083 [12] GSE54215 [13] GSE13259 [10] GSE17266 [59] GSE17796 [39] GSE43620 [8] GSE22925 [14] GSE10776 [15] GSE6998 [32] GSE6526 [16] GSE35979 [6] GSE21996 [14] GSE17462 [8] GSE43928 [12] GSE40939 [10] GSE45941 [8] GSE55622 [22] GSE51365 [28] GSE46094 [10] GSE21755 [25] GSE4734 [61] GSE12498 [12] GSE12950 [6] GSE27092 [6] GSE20696 [8] GSE2527 [6] GSE24121 [9] GSE16048 [6] GSE4739 [19] GSE11201 [18] GSE37431 [6] GSE26355 [6] GSE23002 [8] GSE30012 [6] GSE22251 [9] GSE34114 [12] GSE27261 [8] GSE24243 [6] GSE24813 [10] GSE7863 [16] GSE31702 [10] GSE8044 [6] GSE31378 [9] GSE54349 [6] GSE1986 [17] GSE4323 [6] GSE10659 [6] GSE44355 [10] GSE43381 [26] GSE28559 [30] GSE17985 [8] GSE51080 [18] GSE37676 [6] GSE46209 [21] GSE56345 [9] GSE41942 [6] GSE32020 [26] GSE21224 [16] GSE33121 [10] GSE7141 [6] GSE16110 [16] GSE11443 [6] GSE56755 [13] GSE12730 [24] GSE31244 [6] GSE47421 [24] GSE44261 [12] GSE32334 [19] GSE28417 [12] GSE15587 [6] GSE1435 [27] GSE10589 [6] GSE56162 [18] GSE34629 [6] GSE11382 [10] GSE8512 [207] GSE26745 [24] GSE17794 [44] GSE5959 [6] GSE24350 [8] GSE50687 [38] GSE21711 [6] GSE21393 [6] GSE19709 [168] GSE28035 [9] GSE25257 [6] GSE21716 [28] GSE15324 [8] GSE19517 [6] GSE11796 [18] GSE51883 [30] GSE6810 [10] GSE27547 [17] GSE15610 [12] GSE11356 [9] GSE14354 [6] GSE14769 [24] GSE17112 [8] GSE12432 [15] GSE11918 [9] GSE8621 [12] GSE20918 [6] GSE47719 [6] GSE22506 [12] GSE20577 [12] GSE26151 [20] GSE28025 [18] GSE19079 [6] GSE15121 [6] GSE42061 [12] GSE46942 [7] GSE9977 [24] GSE13805 [7] GSE22935 [24] GSE53299 [6] GSE5800 [6] GSE48369 [36] GSE58262 [18] GSE13120 [10] GSE15315 [6] GSE40513 [6] GSE15871 [18] GSE11148 [6] GSE55855 [6] GSE18500 [35] CEM+ CEM GSE10902 [6] GSE19403 [12] GSE9763 [20] GSE4189 [14] GSE46646 [12] GSE26668 [6] 0.0 GSE29572 [21] GSE6383 [6]

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18907 Status: Public on Mar 19 2011 Title: Gene expression profiling of pregnant and virgin mouse lung and liver Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21646719 Summary & Design: Summary: Metastasis depends on the ability of tumor cells to establish a relationship with the newly seeded host tissue that is conducive to their survival and proliferation. Recent evidence suggests that tumor cells regulate their own dissemination by preparing permissive metastatic niches within host tissues. However, the factors that are implicated in rendering tissues permissive for metastatic tumor growth have yet to be fully elucidated. Breast tumors arising during pregnancy display highly aggressive behaviour and early metastatic proclivity, raising the possibility that pregnancy may constitute a physiological condition of permissiveness for tumor dissemination. We show that during murine gestation, both the rate and degree of metastatic tumor growth are enhanced irrespective of tumor type and that decreased natural killer (NK) cell activity is responsible for the observed increase in experimental metastasis. We identify gene expression changes in pregnant mouse lung and liver that bear striking similarity with reported pre-metastatic niche signatures and several of the up-regulated genes are indicative of myeloid-cell infiltration. We provide evidence, that CD11b+ Gr-1+ myeloid-derived suppressor cells accumulate in pregnant mice and exert an inhibitory effect on NK cell activity, thereby enhancing metastatic tumor growth. MDSC have never been evoked in the context of pregnancy and our observations suggest that they may represent a further shared mechanism of immune suppression occurring during gestation and tumor growth.

Overall design: Three chips were done per organ (liver/lung) and per condition (virgin/pregnant), with equal amounts of RNA from two mice pooled for one chip.

Background corr dist: KL-Divergence = 0.0162, L1-Distance = 0.0642, L2-Distance = 0.0067, Normal std = 0.9265

0.431 Kernel fit Pairwise Correlations Normal fit

Density 0.215

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

Lung VirginLung 1 Virgin (0.0497662)Lung 2 Virgin (0.0675523)Lung 3 Pregnant (0.077703)Lung Pregnant Lung1 (0.118221) Pregnant Liver2 (0.0901412) Virgin Liver3 (0.106494) 1 Virgin (0.0905154)Liver 2 Virgin (0.0626414)Liver 3 Pregnant (0.087297)Liver Pregnant Liver1 (0.0813517) Pregnant 2 (0.0855071) 3 (0.0828093) [ min ] [ medium ] [ max ] CEM 1 Snw1 927.6 1930.4 2151.2 P ( S | Z, I ) = 1.00 Ncor1 1832.0 2796.7 3162.9 Mean Corr = 0.95200 Glis3 25.8 132.8 184.3 Npat 74.8 295.8 349.0 Ski 532.7 1334.4 1816.1 Epc2 532.8 1687.9 2070.9 Bdp1 579.4 1070.6 1343.1 Zfp26 299.7 923.3 1020.4 Zbtb6 276.8 467.9 547.0 Epc1 499.0 1365.8 1599.1 CEM 1 + Tnks2 2684.3 6054.3 7341.0 Top 10 Genes Phf20 460.0 745.3 1011.6 Ep300 556.0 1123.0 1516.3 Arid4a 80.5 380.6 522.1 Rbm27 391.5 863.4 945.7

Null module GEO Series "GSE23895" 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=GSE23895 Status: Public on Jan 19 2011 Title: Selenium toxicity but not deficient or super-nutritional selenium status vastly alters the transcriptome in rodents Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21226930 Summary & Design: Summary: Protein and mRNA levels for several selenoproteins, such as glutathione peroxidase-1 (Gpx1), are down-regulated dramatically by selenium (Se) deficiency.

Selenoprotein levels in rats increase sigmoidally with increasing dietary Se and reach defined plateaus at the Se requirement, making them sensitive biomarkers for Se deficiency, but not high for Se status. Biomarkers for high Se status are needed as super-nutritional Se intakes are associated with beneficial and adverse health outcomes, but conventional biomarkers are not especially useful above the Se requirement. To characterize Se regulation of the transcriptome, we conducted 3 microarray experiments in weanling mice and rats fed Se-deficient diets supplemented with levels of Se up to 5 ´g Se/g diet.

Overall design: Rats or mice were fed Se-deficient diets supplemented with sodium selenite up to 5 ug Se/g diet for 28 or 35 days. Affymetrix Rat 230 2.0 and Mouse 430 2.0 Genome Arrays were used to analyze gene expression in liver in all studies plus kidney in the mouse study.

Background corr dist: KL-Divergence = 0.0133, L1-Distance = 0.0509, L2-Distance = 0.0031, Normal std = 0.9121

0.437 Kernel fit Pairwise Correlations Normal fit

Density 0.219

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

MouseLiver_SeDef_rep1MouseLiver_SeDef_rep2MouseLiver_SeDef_rep3MouseLiver_0.05ugSe_rep1 (0.0346855)MouseLiver_0.05ugSe_rep2 (0.0483908)MouseLiver_0.05ugSe_rep3 (0.0571944)MouseLiver_0.2ugSe_rep1 (0.0385222)MouseLiver_0.2ugSe_rep2 (0.0690413)MouseLiver_0.2ugSe_rep3 (0.0440439)MouseKidney_SeDef_rep1 (0.0776063)MouseKidney_SeDef_rep2 (0.055746)MouseKidney_SeDef_rep3 (0.0506879)MouseKidney_0.05ugSe_rep1 (0.0340719)MouseKidney_0.05ugSe_rep2 (0.0786868)MouseKidney_0.05ugSe_rep3 (0.097625)MouseKidney_0.2ugSe_rep1 MouseKidney_0.2ugSe_rep2(0.0381931) MouseKidney_0.2ugSe_rep3(0.0607445) (0.0728076) (0.0370883) (0.036367) (0.0684974)[ min ] [ medium ] [ max ] CEM 1 Snw1 1059.4 1720.5 2061.6 P ( S | Z, I ) = 1.00 Ncor1 1038.2 1403.2 1909.1 Mean Corr = 0.91342 Glis3 22.2 440.8 586.5 Npat 109.3 153.1 209.3 Ski 464.4 898.5 1062.6 Epc2 385.7 587.8 813.0 Bdp1 453.4 586.9 748.2 Zfp26 421.7 633.9 921.4 Zbtb6 196.6 237.3 343.2 Epc1 672.8 962.2 1240.8 CEM 1 + Tnks2 2266.7 4172.6 4966.2 Top 10 Genes Phf20 185.3 309.5 478.7 Ep300 489.0 732.6 869.9 Arid4a 98.3 164.8 229.0 Rbm27 335.8 458.2 717.9

Null module GEO Series "GSE15772" 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=GSE15772 Status: Public on May 20 2009 Title: WT Dorsal Skin Time Course Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19494835 Summary & Design: Summary: Skin and bladder epithelia form effective permeability barriers through the activation of distinct differentiation gene programs. Employing a genome-wide gene expression study, we identified transcription regulators whose expression correlates highly with that of differentiation markers both in bladder and skin, including the Grainyhead factor Get1/Grhl3, already known to be important for epidermal barrier formation. In the bladder, Get1 is most highly expressed in the differentiated umbrella cells and its mutation in mice leads to a defective bladder epithelial barrier formation due to failure of apical membrane specialization. Genes encoding components of the specialized urothelial membrane, the uroplakins, were downregulated in Get1-/- mice. At least one of these genes, Uroplakin II, is a direct target of Get1. The urothelial-specific activation of the Uroplakin II gene is due to selective binding of Get1 to the Uroplakin II promoter in urothelial cells, most likely regulated by histone modifications. These results demonstrate a key role for Get1 in urothelial differentiation and barrier formation.

Overall design: To gain insights into common and unique transcriptional regulatory programs during epidermal differentiation, we profiled global gene expression in mouse dorsal skin at E14.5, E16.5, and E18.5.

Background corr dist: KL-Divergence = 0.0139, L1-Distance = 0.0232, L2-Distance = 0.0006, Normal std = 0.8175

0.488 Kernel fit Pairwise Correlations Normal fit

Density 0.244

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

E14.5 WTE14.5 Dorsal WTE16.5 SkinDorsal WT 1-2E16.5 SkinDorsal (0.2905) WT 1-3E16.5 SkinDorsal (0.395794) WT 6E18.5 (0.0292103) SkinDorsal WT 7E18.5 (0.0613051) SkinDorsal WT 8E18.5 (0.0485628) SkinDorsal WT 5-5 SkinDorsal (0.0579357) 6-4 Skin (0.078584) 1-4 (0.0381084)[ min ] [ medium ] [ max ] CEM 1 Snw1 1423.6 1690.2 3552.2 P ( S | Z, I ) = 1.00 Ncor1 1828.8 2853.1 4102.7 Mean Corr = 0.88917 Glis3 22.4 120.5 473.5 Npat 441.6 634.9 1156.4 Ski 1587.1 2107.1 4458.5 Epc2 1003.9 1227.5 2895.2 Bdp1 1098.0 1282.6 5468.4 Zfp26 800.9 1298.7 6885.7 Zbtb6 294.3 455.6 2644.5 Epc1 1492.1 1815.5 10406.5 CEM 1 + Tnks2 4994.7 7229.3 10740.2 Top 10 Genes Phf20 621.2 807.0 5156.3 Ep300 910.9 1863.1 1922.7 Arid4a 188.3 220.6 1910.5 Rbm27 518.0 1021.8 5130.3

Null module GEO Series "GSE30192" 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=GSE30192 Status: Public on Jan 01 2012 Title: Effect of 5-azacytidine on gene expression in C2C12 myoblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21795504 Summary & Design: Summary: Mesenchymal progenitor cells can be differentiated in vitro into myotubes that exhibit many characteristic features of primary mammalian skeletal muscle fibers. However, in general, they do not show the functional excitation-contraction coupling or the striated sarcomere arrangement typical of mature myofibers. Epigenetic modifications have been shown to play a key role in regulating the progressional changes in transcription necessary for muscle differentiation. In this study, we demonstrate that treatment of murine C2C12 mesenchymal progenitor cells with 10 ´M of the DNA methylation inhibitor 5-azacytidine (5AC) promotes myogenesis, resulting in myotubes with enhanced maturity as compared to untreated myotubes. Specifically, 5AC treatment resulted in the upregulation of muscle genes at the myoblast stage while at later stages nearly 50 % of the 5AC-treated myotubes displayed a mature, well-defined sarcomere organization as well as spontaneous contractions that coincided with action potentials and intracellular calcium transients. Both the percentage of striated myotubes and their contractile activity could be inhibited by 20 nM TTX, 10 ´M ryanodine and 100 ´M nifedipine, suggesting that action potential-induced calcium transients are responsible for these characteristics. Our data suggest that genomic demethylation induced by 5AC overcomes an epigenetic barrier that prevents untreated C2C12 myotubes from reaching full maturity.

Overall design: C2C12 cells were plated at 1500 cells/cm2 (day -1), cultured for 1 day in DMEM 10%NCS, then treated (d0) with or without 10uM 5-azacytidine (5AC) for an additional 3 days. RNA was extracted on day 3 and hybridized to GeneChip Mouse Genome 430 2.0 array (Affymetrix).

Background corr dist: KL-Divergence = 0.0286, L1-Distance = 0.0590, L2-Distance = 0.0044, Normal std = 0.7900

0.581 Kernel fit Pairwise Correlations Normal fit

Density 0.290

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

C2C12 untreatedC2C12 untreatedC2C12 day3 untreated C2C12rep1 day3 (0.223103) 5AC C2C12rep2 day3 treated (0.128212) 5AC C2C12rep3 treatedday3 (0.177454) 5AC rep1 treatedday3 (0.194294) rep2 day3 (0.151753) rep3 [(0.125183) min ] [ medium ] [ max ] CEM 1 Snw1 2216.7 3079.2 3213.4 P ( S | Z, I ) = 1.00 Ncor1 1419.4 2008.3 2092.4 Mean Corr = 0.87289 Glis3 104.4 259.3 293.0 Npat 896.6 1042.4 1109.6 Ski 827.2 1423.6 1462.1 Epc2 1418.7 1764.0 1867.6 Bdp1 1209.3 1545.5 1593.3 Zfp26 712.3 787.1 842.0 Zbtb6 704.3 795.2 813.3 Epc1 911.7 1066.1 1210.5 CEM 1 + Tnks2 3157.1 3893.4 4029.3 Top 10 Genes Phf20 1112.7 1269.1 1350.3 Ep300 1399.8 1759.5 1965.0 Arid4a 191.3 260.2 260.6 Rbm27 756.6 841.1 919.6

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

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

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

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

0.829 Kernel fit Pairwise Correlations Normal fit

Density 0.415

0.000 CEM 1

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

Pre-normalization Quantiles

PB_Kidney_Control_5PB_Kidney_Control_1PB_Kidney_Control_9 PB_Kidney_Control_4(0.0210648) PB_Kidney_Control_10(0.0271937) PB_Kidney_Control_8(0.0337988) PB_Kidney_Control_3(0.0101911)PB_Kidney_Control_7 (0.0118993) PB_Kidney_Control_2(0.0340595) PB_Kidney_Control_6(0.0122894) PB_Liver_Control_10(0.0194756) PB_Liver_Control_9(0.0137324) PB_Liver_Control_2(0.0417694) (0.0209508)PB_Liver_Control_3 (0.0270585)PB_Liver_Control_6 (0.0468233)PB_Liver_Control_5 (0.032971)PB_Liver_Control_4 (0.0225787)PB_Liver_Control_8 (0.0269844)PB_Liver_Control_1 (0.0255781)PB_Liver_Control_7 (0.0148152)PB_Kidney_treated_20 (0.019704)PB_Kidney_treated_18 (0.0266093)PB_Kidney_treated_12PB_Kidney_treated_11 (0.0167648)PB_Kidney_treated_17 (0.0155142)PB_Kidney_treated_16 (0.0295931)PB_Kidney_treated_14 (0.0196045)PB_Kidney_treated_15 (0.0274781)PB_Kidney_treated_13 (0.0241087)PB_Kidney_treated_19 (0.0235959)PB_Liver_treated_12 (0.0343637)PB_Liver_treated_13 (0.0350035)PB_Liver_treated_14 (0.0223595) (0.024441)PB_Liver_treated_15 (0.0409899)PB_Liver_treated_11 (0.0331288)PB_Liver_treated_16 (0.0365042)PB_Liver_treated_18 (0.0255568)PB_Liver_treated_19 (0.0153462)PB_Liver_treated_20 (0.0279406)PB_Liver_treated_17 (0.016612) (0.0147559) (0.0267909)[ min ] [ medium ] [ max ] CEM 1 Snw1 761.1 1150.2 1516.8 P ( S | Z, I ) = 1.00 Ncor1 1692.8 3078.4 3899.6 Mean Corr = 0.78051 Glis3 3.4 1149.9 1447.2 Npat 173.8 334.5 526.9 Ski 170.4 431.2 616.0 Epc2 526.1 974.5 1288.9 Bdp1 801.3 1228.3 1564.8 Zfp26 494.2 663.5 842.3 Zbtb6 203.0 364.7 593.2 Epc1 640.5 1172.6 1474.0 CEM 1 + Tnks2 1435.5 2879.9 4130.4 Top 10 Genes Phf20 316.3 751.4 1013.7 Ep300 523.9 949.4 1490.6 Arid4a 222.4 364.0 481.0 Rbm27 335.8 539.2 691.3

Null module GEO Series "GSE30855" 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=GSE30855 Status: Public on Sep 01 2011 Title: Establishment of Enhancer Repertoires that Orchestrate the Myeloid and Lymphoid Cell Fates (gene expression dataset 1) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21903424 Summary & Design: Summary: Recent studies have documented genome-wide binding patterns of transcriptional regulators and their associated epigenetic marks in hematopoietic cell lineages. In order to determine how epigenetic marks are established and maintained during developmental progression, we have generated long-term cultures of hematopoietic progenitors by enforcing the expression of the E-protein antagonist Id2. Hematopoietic progenitors that express Id2 are multipotent and readily differentiate upon withdrawal of Id2 expression into committed B lineage cells, thus indicating a causative role for E2A in promoting the B cell fate. Genome-wide analyses revealed that a substantial fraction of lymphoid and myeloid enhancers are pre-marked by H3K4me1 in multipotent progenitors. However, H3K4me1 levels at a subset of enhancers are elevated during developmental progression, resulting in evolving enhancer repertoires that we propose orchestrate the myeloid and B cell fates.

Overall design: To characterize Id2-HPCs, we performed microarray analysis using RNA derived from cultured E2A-deficient cells, EBF-deficient cells and Id2-HPCs. Id2-HPC cells were cultured in IMDM medium supplemented with 10% FCS/2% PSG/Î²-me and IL7, Flt3-ligand, and SCF cytokines on S17 feeder cells in a humidified incubator at 37 degrees C with 5% CO2. Id2-HPC expanded cells were depleted of small (<1-5%) numbers of CD19-, CD25- and CD11b-positive cells by auto-MACS. E2A -/- and EBF -/- cells were cultured in IMDM supplemented with 10% FCS/2% PSG/Î²-me on S17 feeder cells in the presence of IL-7, Flt3-ligand, and SCF cytokines in a humidified incubator at 37 degree C with 5% CO2.

Background corr dist: KL-Divergence = 0.0252, L1-Distance = 0.0216, L2-Distance = 0.0004, Normal std = 0.7208

0.568 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

UninducedUninduced Id2-HPC,Cultured Id2-HPC, biologicalCultured E2A-deficient, biologicalCultured replicateE2A-deficient,Cultured replicatebiologicalEBF-deficient, 1 (0.419724) biologicalEBF-deficient, 2 replicate(0.126399) biological replicate 1 (0.189942) biological replicate 2 [(0.144107) min replicate 1 (0.0528548) ] 2 (0.0669738)[ medium ] [ max ] CEM 1 Snw1 3333.6 3789.0 4031.9 P ( S | Z, I ) = 1.00 Ncor1 2910.4 4261.0 5194.8 Mean Corr = 0.77587 Glis3 29.3 30.7 35.2 Npat 1120.4 1613.0 1977.8 Ski 489.9 545.4 813.1 Epc2 1998.2 2523.9 2721.2 Bdp1 1436.5 1652.0 1921.2 Zfp26 1300.5 1803.2 2111.1 Zbtb6 824.3 1028.9 1173.5 Epc1 3366.4 3865.2 5216.9 CEM 1 + Tnks2 6302.9 7945.2 10208.8 Top 10 Genes Phf20 1017.1 1316.2 1319.6 Ep300 1221.4 1474.5 1688.5 Arid4a 351.4 564.1 580.1 Rbm27 1083.2 1181.6 1834.5

Null module GEO Series "GSE8684" 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=GSE8684 Status: Public on Jan 11 2008 Title: Gene expression in mouse 3T3-L1 adipocyte tissue culture treated with cis-9,trans-11 conjugated linoleic acid(c9t11 CLA) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17878318 Summary & Design: Summary: Trans-10, Cis-12 conjugated linoleic acid (t10c12 CLA) causes fat loss in mouse 3T3-L1 adipocyte tissue culture; however cis-9, trans-11 CLA does not (this series). The early transcriptome changes were analyzed using high-density microarrays to better characterize the signaling pathways responding to c9t11 CLA. Their gene expression responses between 8 to 12 hr after treatment showed no gene expression changes indicative of an integrated stress response (ISR).

Keywords: control/treatment time course

Overall design: Mouse 3T3-L1 RNA for each time point was isolated from control and treatment samples for analysis on microarrays; there are four biological reps for the controls for each timepoint, and only one rep for the treatment.

Background corr dist: KL-Divergence = 0.0618, L1-Distance = 0.0610, L2-Distance = 0.0079, Normal std = 0.5509

0.858 Kernel fit Pairwise Correlations Normal fit

Density 0.429

0.000 CEM 1

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

Pre-normalization Quantiles

3T3-L1 adipocyte3T3-L1 adipocyte3T3-L1 tissue adipocyte3T3-L1 culture, tissue adipocyte3T3-L1 culture, c9t11tissue adipocyte3T3-L1 CLA culture, c9t11tissue treated, adipocyte3T3-L1 CLA culture, LAtissue treated, T1,adipocyte3T3-L1 culture, LAtissuebiological treated, T1,T2,adipocyte3T3-L1 culture, LAtissuebiological rep1treated, T1,adipocyte3T3-L1 culture, LAtissuebiological (0.112095) rep1treated, T1,adipocyte culture, LAtissue biological(0.118807)(0.0508706) rep2treated, T1, culture, LAtissue biological(0.0135981) rep3treated, T2, culture, LA biological(0.00451581) rep4treated, T2,[ LAmin biological(0.170741) rep1treated, T2, biological(0.101491)] rep2 T2, biological(0.0692525) rep3[ (0.00850973) mediumrep4 (0.350119) ] [ max ] CEM 1 Snw1 806.7 1342.7 2382.4 P ( S | Z, I ) = 1.00 Ncor1 465.8 1730.3 2492.5 Mean Corr = 0.72665 Glis3 28.6 331.2 899.8 Npat 81.4 506.6 863.8 Ski 453.4 555.0 1092.9 Epc2 113.9 1090.8 2194.9 Bdp1 188.2 754.1 1073.5 Zfp26 190.4 541.9 953.2 Zbtb6 9.8 718.3 1002.3 Epc1 518.0 1019.0 1718.8 CEM 1 + Tnks2 1296.7 5531.8 8485.7 Top 10 Genes Phf20 498.1 1090.3 1947.8 Ep300 341.2 852.9 1534.0 Arid4a 9.8 180.5 363.6 Rbm27 9.8 417.9 817.7

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

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

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

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

1.233 Kernel fit Pairwise Correlations Normal fit

Density 0.616

0.000 CEM 1

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

Pre-normalization Quantiles

1 Wild-type1 Wild-type control1 Wild-type controlmacrophage1 Wild-type IL-4macrophage+RSG2 macrophageWild-type (0.155422) IL-42 macrophage+RSGWild-type control (0.0731436)2 (0.162837)Wild-type controlmacrophage2 Wild-type IL-4macrophage+RSG (0.0354807)3 macrophageWild-type (0.0916687) IL-43 macrophage+RSGWild-type control (0.038533)3 (0.0327304)Wild-type controlmacrophage3 Wild-type IL-4macrophage+RSG (0.0155994)4 macrophageSTAT6KO (0.00430701) IL-44 macrophage+RSGSTAT6KO control (0.0448635)4 (0.092143)STAT6KO controlmacrophage4 STAT6KO IL-4macrophage+RSG(0.0248457)5 macrophageSTAT6KO (0.00270008) IL-45 macrophage+RSGSTAT6KO control (0.014527)5 (0.0807589)STAT6KO controlmacrophage5 STAT6KO IL-4macrophage+RSG (0.0170333)6 macrophageSTAT6KO (0.00425166) IL-46 macrophage+RSGSTAT6KO control (0.0116438)6 (0.0207734)STAT6KO controlmacrophage6 STAT6KO IL-4macrophage+RSG (0.0160681) macrophage (0.0240198) IL-4 macrophage+RSG (0.0137414) (0.00882421)[ min (0.0140845) ] [ medium ] [ max ] CEM 1 Snw1 391.7 434.2 591.4 P ( S | Z, I ) = 1.00 Ncor1 391.7 439.3 516.4 Mean Corr = 0.71005 Glis3 391.7 439.3 1082.7 Npat 391.7 432.9 545.6 Ski 391.7 435.9 533.2 Epc2 402.3 435.5 561.9 Bdp1 399.4 434.8 532.8 Zfp26 391.7 435.9 541.2 Zbtb6 402.3 440.1 646.1 Epc1 392.8 431.8 555.8 CEM 1 + Tnks2 414.3 435.3 527.4 Top 10 Genes Phf20 394.5 431.8 659.1 Ep300 391.7 432.6 587.2 Arid4a 391.7 431.8 568.7 Rbm27 399.4 435.5 530.9

Null module GEO Series "GSE8681" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 25 -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=GSE8681 Status: Public on Jan 11 2008 Title: Gene expression in mouse 3T3-L1 adipocyte tissue culture treated with CLA Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17878318 Summary & Design: Summary: Trans-10, Cis-12 conjugated linoleic acid (t10c12 CLA) causes fat loss in mouse 3T3-L1 adipocyte tissue culture. The early transcriptome changes were analyzed using high-density microarrays to better characterize the signaling pathways responding to t10c12 CLA. Their gene expression responses between 4 to 24 hr after treatment showed a common set of early gene expression changes indicative of an integrated stress response (ISR).

Keywords: control/treatment time course

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

Background corr dist: KL-Divergence = 0.1410, L1-Distance = 0.0407, L2-Distance = 0.0032, Normal std = 0.3886

1.078 Kernel fit Pairwise Correlations Normal fit

Density 0.539

0.000 CEM 1

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

Pre-normalization Quantiles

3T3-L1 adipocyte3T3-L1 adipocyte3T3-L1 tissue adipocyte3T3-L1 culture, tissue adipocyte3T3-L1 culture, LAtissue fed, adipocyte3T3-L1 culture, LAtissueT1, fed,biological adipocyte3T3-L1 culture, LAtissueT1, fed,biological adipocyte3T3-L1 culture, rep1 CLAtissueT1, biological (0.0920088)adipocyte3T3-L1fed, culture, rep2CLAtissue T1, (0.00209905)adipocyte3T3-L1 fed,biological culture, rep3LAtissue T1, fed, (0.0886101)adipocyte3T3-L1 biological culture, LAtissueT2, rep1 fed,biological adipocyte3T3-L1 (0.0668879) culture, LAtissueT2, rep2 fed,biological adipocyte3T3-L1 (0.0102953) culture, rep1 CLAtissueT2, biological (0.0546518)adipocyte3T3-L1fed, culture, rep2CLAtissue T2, (0.0040393)adipocyte3T3-L1 fed,biological culture, rep3CLAtissue T2, (0.0966039)adipocyte3T3-L1 fed,biological culture, LAtissue rep1 T2, fed, adipocyte3T3-L1 biological(0.0222545) culture, LAtissueT3, rep2 fed,biological adipocyte3T3-L1 (0.00762336) culture, LAtissueT3, rep3 fed,biological adipocyte3T3-L1 (0.0109224) culture, rep1 LAtissueT3, fed, biological(0.0660845)adipocyte3T3-L1 culture, rep2 CLAtissueT3, biological (0.0120405)adipocyte3T3-L1fed, culture, rep3CLAtissue T3, (0.00702928)adipocyte3T3-L1 fed,biological culture, rep4CLAtissue T3, (0.0815936)adipocyte3T3-L1 fed,biological culture, CLAtissue rep1 T3, adipocyte3T3-L1 fed, biological(0.058698) culture, LAtissue rep2 T3, fed, adipocyte3T3-L1 biological(0.00989075) culture, LAtissueT4, rep3 fed,biological adipocyte (0.0126671) culture, LAtissueT4, rep4 fed,biological (0.0561947) culture, rep1 CLAtissueT4, biological (0.101896)fed, culture, rep2CLA T4, (0.0148105)[ fed,biological rep3CLAmin T4, (0.00572645) fed,biological rep1 ]T4, biological(0.0729066) rep2 (0.0163688)[ rep3 medium (0.0280968) ] [ max ] CEM 1 Snw1 806.7 1737.5 2821.5 P ( S | Z, I ) = 1.00 Ncor1 465.8 1872.4 2756.0 Mean Corr = 0.61326 Glis3 77.2 265.6 909.0 Npat 81.4 550.8 966.0 Ski 300.0 642.8 1114.1 Epc2 276.4 1210.4 2431.2 Bdp1 195.7 886.4 1262.5 Zfp26 190.4 603.7 1064.7 Zbtb6 96.7 761.0 1212.7 Epc1 552.1 1124.2 2030.4 CEM 1 + Tnks2 1296.7 6182.1 8972.5 Top 10 Genes Phf20 359.9 1205.6 2019.2 Ep300 502.6 926.2 1577.3 Arid4a 13.0 181.8 363.6 Rbm27 25.1 525.9 859.0

Null module GEO Series "GSE39449" 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=GSE39449 Status: Public on Feb 25 2014 Title: Differentially activated CD8 T cells in liver and gut Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19265543 Summary & Design: Summary: NaÃ¯ve, liver- and gut-activated CD8 OT-I T cells show differential migration behaviour. To analyze which genes could be responsible for different migration patterns, naÃ¯ve, liver-activated and gut-activated CD8 T cells were isolated and compared for their gene expression profile.

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: naÃ¯ve, Group2: liver-activated Group3: gut-activated. 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 = 0.0358, L1-Distance = 0.0497, L2-Distance = 0.0032, Normal std = 0.6979

0.630 Kernel fit Pairwise Correlations Normal fit

Density 0.315

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

DifferentiallyDifferentially activatedDifferentially activatedDifferentially CD8 Tactivated cellsDifferentially CD8 in Tactivated cellsDifferentially liverCD8 andin Tactivated cells liverCD8 gut: andin Tactivated Liver-activated cells liverCD8 gut: andinT Liver-activated cells liverCD8 gut: andinT Gut-activated CD8cells[liver gut:min OT-I andin Gut-activated CD8liver Tgut: cells OT-I ]and CD8 NaÃ¯ve (liver)Tgut: OT-I cells CD8 NaÃ¯veCD8 ChipT (liver) cells [OT-I OT-I 1medium CD8 (0.0851156)(mes)ChipT T cells cells OT-I 2 Chip (0.0769137)(mes) (naÃ¯ve)T cells 1 (0.210367)Chip (naÃ¯ve)] Chip 2 (0.0860766) 1 (0.188022)Chip[ 2 (0.353505)max ] CEM 1 Snw1 2326.3 2595.0 3250.0 P ( S | Z, I ) = 1.00 Ncor1 2923.7 3325.3 5873.9 Mean Corr = 0.56273 Glis3 5.0 6.4 33.0 Npat 1190.3 1288.0 1638.3 Ski 363.3 498.9 1119.8 Epc2 1196.6 1312.0 2301.6 Bdp1 1700.6 2063.8 2716.3 Zfp26 1205.3 1313.9 2026.7 Zbtb6 387.1 508.9 619.0 Epc1 1655.7 2006.9 3585.9 CEM 1 + Tnks2 5730.0 6489.1 7561.6 Top 10 Genes Phf20 636.5 722.4 837.9 Ep300 1132.4 1576.2 2888.3 Arid4a 915.5 1252.4 2971.4 Rbm27 1892.5 1952.5 2775.8

Null module GEO Series "GSE17553" 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=GSE17553 Status: Public on Dec 31 2009 Title: Estradiol or Testosterone treated efferent duct and caput epididymis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19553595 Summary & Design: Summary: The role of estrogen and testosterone in the regulation of gene expression in the proximal reproductive tract is not completely understood. To address this question, mice were treated with testosterone or estradiol and RNA from the efferent ducts and caput epididymis was processed and hybridized to Affymetrix MOE 430 2.0 microarrays. Analysis of array output identified probe sets in each tissue with altered levels in hormone treated versus control animals. Hormone treatment efficacy was confirmed by determination of serum hormone levels pre- and post-treatment and observed changes in transcript levels of previously reported hormone-responsive genes. Tissue-specific hormone sensitivity was observed with 2867 and 3197 probe sets changing significantly in the efferent ducts after estrogen and testosterone treatment, respectively. In the caput epididymis, 117 and 268 probe sets changed after estrogen and testosterone treatment, respectively, demonstrating a greater response to hormone in the efferent ducts than the caput epididymis. Transcripts sharing similar profiles in the intact and hormone-treated animals compared with castrated controls were also identified. Ontological analysis of probe sets revealed a significant number of hormone-regulated transcripts encode proteins associated with lipid metabolism, transcription and steroid metabolism in both tissues. Real-time RT-PCR was employed to confirm array data and investigate other potential hormone-responsive regulators of proximal reproductive tract function. The results of this work reveal previously unknown responses to estrogen in the caput epididymis and to testosterone in the efferent ducts as well as tissue specific hormone sensitivity in the proximal reproductive tract.

Overall design: Adult animals were castrated or sham-castrated, allowed to recover for 14 days, and then treated with 0.015 mg estradiol (castrated), 0.015 mg testosterone propionate (castrated), or vehicle (castrated and sham-castrated as biological controls) in duplicate. Efferent duct and caput epididymis was collected from each sample and analyzed. Duplicates are included in the provided data and numbered 1 or 2 for each treatment regimen.

Background corr dist: KL-Divergence = 0.0449, L1-Distance = 0.0261, L2-Distance = 0.0011, Normal std = 0.5797

0.688 Kernel fit Pairwise Correlations Normal fit

Density 0.344

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

EfferentCaput duct castratedepididymisCaput epididymisCaput 1 (0.198257)castrated epididymisCaput castrated 1 epididymis Caput(0.0278997) sham-castrated 2 epididymis Caput(0.0276532) sham-castrated epididymisCaput TP 1 (0.0708242)treatedepididymisEfferent TP 2 (0.0598806)treated1Efferent (0.0255582)duct E2 sham-castratedtreated2Efferent (0.0282094)duct sham-castrated1Efferent (0.0282742)duct castrated 1Efferent duct (0.101565) TP 2Efferent duct 2(0.0879639)treated (0.15166) TPEfferent duct treated1 (0.0198311) E2Caput duct treated2 (0.123789) E2epididymis treated1 (0.0126961) 2 E2(0.0129083) treated 2[ (0.0230298) min ] [ medium ] [ max ] CEM 1 Snw1 1708.3 2377.8 5221.6 P ( S | Z, I ) = 1.00 Ncor1 1737.8 2958.0 5030.8 Mean Corr = 0.56124 Glis3 195.9 1929.3 9803.2 Npat 497.2 727.5 1511.8 Ski 1226.8 2027.7 3526.0 Epc2 1546.5 2369.4 3209.9 Bdp1 1314.5 2094.4 5067.3 Zfp26 1058.4 1453.9 5432.3 Zbtb6 423.6 952.6 2368.1 Epc1 1408.3 3284.4 12846.8 CEM 1 + Tnks2 3804.4 4754.4 9542.3 Top 10 Genes Phf20 515.9 2205.8 5023.2 Ep300 1356.6 1953.8 3006.8 Arid4a 556.7 1120.8 4147.1 Rbm27 596.9 1891.3 4654.1

Null module GEO Series "GSE42047" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42047 Status: Public on Oct 04 2013 Title: TWEAK-treated time course in Pan02 cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23974006 Summary & Design: Summary: Tumor necrosis factor-related weak inducer of apoptosis, TWEAK, is a TNF superfamily member that mediates signaling through its receptor fibroblast growth factor inducible-14, Fn14. In tumor cell lines, TWEAK induces proliferation, survival and NF-kappaB signaling and gene expression that promote tumor growth and suppress antitumor immune responses. Anti-TWEAK antibody, RG7212, inhibits tumor growth in vivo with decreases in pathway activation markers and modulation of tumor, blood and spleen immune cell composition. Candidate response prediction markers, including Fn14, have been identified in mouse models. Phase I pharmacodynamic data from patients are consistent with preclinical results. TWEAK:Fn14 signaling is upregulated in human cancer and pathway activation induces tumor proliferation and survival signaling. Blockade with anti-TWEAK mAb, RG7212, inhibits tumor growth in multiple models in mice. TWEAK induces changes that suppress anti-tumor immune responses and RG7212 blocks these effects resulting in changes in tumor immune cell composition and decreases in cytokines that promote immunosuppression. Antitumor efficacy in mice was observed in a range of Fn14 expressing models with pathway activation and expressing either wild-type or mutant p53, BRAF or KRAS suggesting both a patient selection strategy and potential broad clinical applicability. Preclinical mechanism of action hypotheses are supported by Phase I clinical data, with decreases in proliferation markers and increased tumor T cell infiltration.

Overall design: Pan02 cells untreated or treated with 1090-TW (TWEAK) for 4 hours, 8 hours, or 24 hours. Four replicates for each condition were performed.

Background corr dist: KL-Divergence = 0.2309, L1-Distance = 0.0329, L2-Distance = 0.0016, Normal std = 0.3208

1.244 Kernel fit Pairwise Correlations Normal fit

Density 0.622

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

JH_120319_Tweak_Cell_Lines_038JH_120319_Tweak_Cell_Lines_040JH_120319_Tweak_Cell_Lines_041JH_120319_Tweak_Cell_Lines_042JH_120319_Tweak_Cell_Lines_044 (0.0633847)JH_120319_Tweak_Cell_Lines_045 (0.133561)JH_120319_Tweak_Cell_Lines_046 (0.091238)JH_120319_Tweak_Cell_Lines_047 (0.0460728)JH_120319_Tweak_Cell_Lines_049 (0.0646472)JH_120319_Tweak_Cell_Lines_050 (0.0142588)JH_120319_Tweak_Cell_Lines_051 (0.0537309)JH_120319_Tweak_Cell_Lines_053 (0.0438557)JH_120319_Tweak_Cell_Lines_054 (0.0243585)JH_120319_Tweak_Cell_Lines_056 (0.0132524)JH_120319_Tweak_Cell_Lines_057 (0.0333345)JH_120319_Tweak_Cell_Lines_060 (0.00239488)JH_120319_Tweak_Cell_Lines_062 (0.0930925)JH_120319_Tweak_Cell_Lines_063 (0.0391953)JH_120319_Tweak_Cell_Lines_065 (0.0231367)JH_120319_Tweak_Cell_Lines_066 (0.0282592)JH_120319_Tweak_Cell_Lines_069 (0.0437174)JH_120319_Tweak_Cell_Lines_070 (0.0171396)JH_120319_Tweak_Cell_Lines_071 (0.0225003)JH_120319_Tweak_Cell_Lines_072 (0.0123991) (0.0214298) (0.0370053) (0.0342003)[ min (0.0438347) ] [ medium ] [ max ] CEM 1 Snw1 2930.9 3086.1 3505.4 P ( S | Z, I ) = 1.00 Ncor1 2564.2 2857.2 3425.2 Mean Corr = 0.45018 Glis3 996.1 1189.7 1562.1 Npat 637.3 714.6 890.8 Ski 906.4 1047.9 1224.4 Epc2 1023.2 1156.1 1240.0 Bdp1 710.9 831.3 976.9 Zfp26 635.5 684.7 803.0 Zbtb6 662.6 725.5 850.8 Epc1 834.1 953.3 1201.6 CEM 1 + Tnks2 8060.5 8980.0 10543.4 Top 10 Genes Phf20 975.4 1055.8 1287.5 Ep300 1333.9 1501.0 1973.3 Arid4a 477.9 666.5 778.4 Rbm27 1032.2 1137.4 1241.7

Null module GEO Series "GSE22381" 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=GSE22381 Status: Public on Jul 01 2011 Title: Identification of downstream transcriptional targets of Dlx5 during early mouse inner ear (otocyst/otic vesicle) development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21227998 Summary & Design: Summary: Several transcription factors are known to be expressed in discrete regions of the otic vesicle and Dlx5 is one of those that is expressed highly in the presumptive dorsal vestibular region. Mice lacking Dlx5 have vestibular defects. Specifically, they fail to form the endolymphatic duct (a defect visible as early as E10) as well as the anterior and posterior semi-circular canals. The lateral canal does form but is smaller, whereas the saccule, the utricle and the cochlea appear relatively normal. The goal of this study was to use microarrays to identify differentially expressed genes between wild-type and Dlx5-null otic vesicles microdissected from E10 and 10.5 and identify downstream targets of Dlx5 by searching the immediate 3kb promoter regions of the differentially expressed genes for homeodomain binding sites followed by chromatin immunoprecipitation in an otic vesicle-derived cell line over-expressing Dlx5.

Normal vestibular morphogenesis is compromised in mice lacking Dlx5, a member of the Distal-less family of homeobox transcription factors. We identified its direct downstream targets in the developing mouse inner ear by gene expression profiling wild-type and Dlx5 null otic vesicles from embryonic stages E10 and E10.5. Four hundred genes were differentially expressed in mutants when compared to wild-type in at least one of the two stages. To further constrain the list of likely direct targets of Dlx5, we examined the genomic DNA sequences in the 3kb promoter regions immediately proximal to the transcriptional start sites of these genes. We searched for (i) one or more previously described binding site for Dlx5, (ii) one or more novel 12bp-long motifs with a canonical homeodomain response element (HDRE) shared by promoters of two or more genes, and (iii) 100% conservation of the 12bp-long HDRE-containing motifs in promoter regions of human orthologs. Forty genes passed one or more of these filters, 12 of which are known to be expressed in the developing otic vesicle in domains that at least partially overlap with that of Dlx5 in one or both stages that we examined. Chromatin immunoprecipitation using a Dlx5 antibody confirmed direct binding of Dlx5 to promoter regions of seven of these genes (Atbf1, Bmper, Large, Lrrtm1, and Msx1, all of which were down-regulated in mutants, and Ebf1 and Lhx1, both of which were up-regulated in mutants) in an otic vesicle-derived cell line over-expressing Dlx5. Gene expression profiling of this cell line showed that Bmper and Lrrtm1 transcripts were up-regulated, further supporting their identification as direct targets of Dlx5 activity.

Overall design: Otic vesicles from wild-type and Dlx5-null embryos were microdissected from mouse developmental stages E10 and E10.5 and expression profiled in duplicate for each stage and genotype. Dlx5-transfected and empty vector-transfected 2B1 cell line samples were also profiled in duplicate (independent cell cultures).

Background corr dist: KL-Divergence = 0.0129, L1-Distance = 0.0464, L2-Distance = 0.0028, Normal std = 0.8888

0.449 Kernel fit Pairwise Correlations Normal fit

Density 0.224

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

E10_otic_vesicle_wt_replicate1E10_otic_vesicle_wt_replicate2E10_otic_vesicle_mut_replicate1E10_otic_vesicle_mut_replicate2E10.5_otic_vesicle_wt_replicate1 (0.105614)E10.5_otic_vesicle_wt_replicate2 (0.0646235)E10.5_otic_vesicle_mut_replicate1 (0.033907)E10.5_otic_vesicle_mut_replicate2 (0.0207842)2B1_Dlx5_replicate1 (0.0458368)2B1_Dlx5_replicate2 (0.0480666)2B1_empty_vector_replicate1 (0.0639172) (0.18461)2B1_empty_vector_replicate2 (0.0700428) (0.154675) (0.0677894) [(0.140133) min ] [ medium ] [ max ] CEM 1 Snw1 1813.2 2315.1 5108.2 P ( S | Z, I ) = 0.98 Ncor1 534.1 790.6 1439.8 Mean Corr = 0.55421 Glis3 21.1 30.4 237.0 Npat 48.2 54.4 133.3 Ski 432.7 543.8 591.9 Epc2 469.3 669.5 1081.3 Bdp1 166.7 256.3 519.9 Zfp26 124.3 240.3 321.6 Zbtb6 86.3 148.2 350.1 Epc1 303.3 393.2 572.9 CEM 1 + Tnks2 1230.9 2289.6 2551.9 Top 10 Genes Phf20 224.3 317.7 511.5 Ep300 132.4 163.2 287.1 Arid4a 24.4 56.3 100.3 Rbm27 2490.3 6169.2 11564.0

Null module GEO Series "GSE13044" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 59 -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=GSE13044 Status: Public on Oct 07 2008 Title: Gene expression profiling in the lung and liver of low and high dose Perfluorooctanoic Acid exposed mouse fetuses Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17681415 Summary & Design: Summary: Exposure to PFOA during gestation altered the expression of genes related to fatty acid catabolism in both the fetal liver and lung. In the fetal liver, the effects of PFOA were robust and also included genes associated with lipid transport, ketogenesis, glucose metabolism, lipoprotein metabolism, cholesterol biosynthesis, steroid metabolism, bile acid biosynthesis, phospholipid metabolism, retinol metabolism, proteosome activation, and inflammation. These changes are consistent with activation of PPAR alpha. Non-PPAR alpha related changes were suggested as well.

Keywords: gene expression, microarray,PFOA, mouse, fetus, liver

Overall design: Please note that each dose experiment had separate concurrent controls.

Background corr dist: KL-Divergence = 0.0397, L1-Distance = 0.0327, L2-Distance = 0.0022, Normal std = 0.6008

0.664 Kernel fit Pairwise Correlations Normal fit

Density 0.332

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

0mg/kg/day0mg/kg/day PFOA,0mg/kg/day RepPFOA,0mg/kg/day 1, Block RepPFOA,0mg/kg/day 1, 2 Block ReplungPFOA,0mg/kg/day 2,(high 2 Block RepliverPFOA, 0mg/kg/daydose) 2,(high 1 Block ReplungPFOA, (0.0126725) 0mg/kg/daydose) 3,(high 1 Block RepliverPFOA, (0.0166708) 0mg/kg/daydose) 3,(high 3 Block ReplungPFOA, (0.0126105) 0mg/kg/daydose) 4,(high 3, Block Rep PFOA,liver (0.0202294) 5mg/kg/daydose) 4, (high4, Block Rep PFOA,lung (0.0150419)5mg/kg/day dose) 5, (high4, Block Rep PFOA,liver (0.0131763)5mg/kg/day dose)5, (high5, Block Rep PFOA,lung (0.010609)5mg/kg/day dose) 1, (high5, Block Rep PFOA,liver (0.012794)5mg/kg/day dose)1, (high5, Block Rep PFOA,lung (0.00986585)5mg/kg/day dose) 2, (high5, Block Rep PFOA,liver (0.0195073)5mg/kg/day dose)2, (high1, Block Rep PFOA,lung (0.0284572)5mg/kg/day dose) 3, (high1, Block Rep PFOA,liver (0.0191062)5mg/kg/day dose)3, (high2, Block Rep PFOA,lung (0.0218849)5mg/kg/day dose) 4, (high2, Block Rep PFOA,liver (0.0115101)10mg/kg/day dose)4, (high3, Block Rep PFOA,lung (0.0105318)10mg/kg/day dose) 5, (high3, BlockRep liver PFOA, (0.0151386)10mg/kg/day dose)5, (high4, Block lung RepPFOA, (0.00420701)10mg/kg/day dose) (high1,4, Blockliver RepPFOA, (0.020417)10mg/kg/day dose) (high1, 2, Block Rep PFOA,lung (0.0147915)10mg/kg/day dose) 2, (high2, Block Rep PFOA,liver (0.0137396)10mg/kg/day dose)2, (high1, Block Rep PFOA,lung10mg/kg/day (0.00522087) dose) 3, (high1, Block Rep PFOA,liver10mg/kg/day (0.0122751) dose)3, (high3, Block Rep PFOA,lung10mg/kg/day (0.0117626) dose) 4, (high3, Block Rep PFOA,liver0mg/kg/day (0.0150277) dose)4, (high4, Block Rep PFOA,lung0mg/kg/day (0.0129605) dose) 5, (high4, PFOA, BlockRep liver0mg/kg/day (0.00998263) dose)5, (high 5, RepPFOA,Block lung0mg/kg/day (0.0174849) 1,dose) (highBlock5, RepPFOA, liver0mg/kg/day (0.00949132) 1, dose) 5 (high Block ReplungPFOA,0mg/kg/day (0.0122534) 2,dose)(low 5 Block RepliverPFOA, dose)0mg/kg/day (0.0163225) 2,(low 1 Block ReplungPFOA, (0.0251529) dose)0mg/kg/day 3,(low 1 Block RepliverPFOA, (0.0144368) dose)0mg/kg/day 3,(low 2 Block ReplungPFOA, (0.0313692) dose)0mg/kg/day 4,(low 2, Block Rep PFOA, liver(0.0145363) dose)1mg/kg/day 4, (low4, Block Rep PFOA, lung(0.0177394) dose)1mg/kg/day 5, (low4, Block Rep PFOA,liver (0.038126) dose)1mg/kg/day 5, (low3, Block Rep PFOA,lung (0.017504) dose)1mg/kg/day 1, (low3, Block Rep PFOA,liver (0.0217729) dose)1mg/kg/day 1, (low5, Block Rep PFOA,liver (0.00869922) dose)1mg/kg/day 1, (low2, Block Rep PFOA,lung (0.0133206) dose)1mg/kg/day 2, (low2, Block Rep PFOA,liver (0.0113228) dose)1mg/kg/day 2, (low3, Block Rep PFOA,lung (0.0314863) dose)1mg/kg/day 3, (low3, Block Rep PFOA,liver (0.0107591) dose)3mg/kg/day 3, (low4, Block Rep PFOA,lung (0.0119794) dose)3mg/kg/day 4, (low4, Block Rep PFOA,liver (0.0130357) dose)3mg/kg/day 4, (low1, Block Rep PFOA,lung (0.0179832) dose)3mg/kg/day 1, (low1, Block Rep PFOA,liver (0.0179419) dose)3mg/kg/day 1, (low3, Block Rep PFOA,lung (0.0553448) dose)3mg/kg/day 2, (low3, Block Rep PFOA,liver (0.0192575) dose)3mg/kg/day 2, (low1, Block Rep PFOA,lung (0.0255236) dose)3mg/kg/day 3, (low1, Block Rep PFOA,liver (0.0116784) dose)3mg/kg/day 3, (low5, Block Rep PFOA,lung (0.0143758) dose)3mg/kg/day 4, (low5, Block Rep PFOA,liver (0.0211671) dose) 4, (low4, Block Rep PFOA,lung (0.0289236) dose) 5, (low4, BlockRep liver (0.0127241) dose) 5, (low2, Block lung (0.0217622) dose)[ (low2,min liver (0.0139377) dose) (low ] (0.0178895) dose) (0.0145071)[ medium ] [ max ] CEM 1 Snw1 808.0 1519.7 2201.3 P ( S | Z, I ) = 0.98 Ncor1 1460.9 2019.2 2709.5 Mean Corr = 0.72491 Glis3 45.8 96.7 175.0 Npat 208.6 374.3 627.4 Ski 512.5 942.9 2419.0 Epc2 552.8 904.6 1782.2 Bdp1 721.2 1014.4 1422.4 Zfp26 552.9 893.5 2759.8 Zbtb6 418.4 624.5 789.6 Epc1 1083.8 1655.7 2863.7 CEM 1 + Tnks2 3647.3 5338.8 9763.0 Top 10 Genes Phf20 324.4 529.9 785.6 Ep300 967.6 1405.8 2075.9 Arid4a 63.2 112.7 294.7 Rbm27 487.0 696.1 939.1

Null module GEO Series "GSE35961" 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=GSE35961 Status: Public on Feb 21 2012 Title: Expression data from mouse liver treated with metformin Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23028442 Summary & Design: Summary: Optimal treatment for nonalcoholic steatohepatitis (NASH) has not yet been established, particularly for individuals without diabetes.

We examined the effects of metformin, commonly used to treat patients with type 2 diabetes, on liver pathology in a non-diabetic NASH mouse model.

Overall design: Eight-week-old C57BL/6 mice were fed a methionine- and choline-deficient (MCD) + high fat (HF) diet with or without 0.1% metformin for 8 weeks.

Background corr dist: KL-Divergence = 0.0889, L1-Distance = 0.0223, L2-Distance = 0.0007, Normal std = 0.4619

0.864 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

Liver_normal_no.1Liver_normal_no.2Liver_normal_no.3 (0.0690961)Liver_normal_no.4 (0.125094)Liver_nash_no.1 (0.14808)Liver_nash_no.2 (0.207558)Liver_nash_no.3 (0.0628067)Liver_nash_no.4 (0.0678296)Liver_nash (0.0162608)Liver_nash (0.0284132) metformin_no.1Liver_nash metformin_no.2Liver_nash metformin_no.3 (0.0162393) metformin_no.4 (0.0568718) (0.113375) (0.0883762)[ min ] [ medium ] [ max ] CEM 1 Snw1 739.2 1062.5 1246.9 P ( S | Z, I ) = 0.98 Ncor1 1535.1 1922.8 2285.6 Mean Corr = 0.52278 Glis3 34.2 241.8 311.1 Npat 163.5 305.9 386.5 Ski 221.4 577.3 766.6 Epc2 792.4 1081.4 1226.8 Bdp1 933.3 1134.7 1365.5 Zfp26 492.1 629.2 708.9 Zbtb6 220.7 293.5 402.6 Epc1 806.7 1172.1 1472.5 CEM 1 + Tnks2 1635.7 2394.1 2780.8 Top 10 Genes Phf20 255.6 475.7 651.1 Ep300 606.4 791.6 1139.0 Arid4a 211.6 310.0 358.6 Rbm27 520.3 627.4 816.1

Null module GEO Series "GSE32103" 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=GSE32103 Status: Public on Sep 01 2012 Title: Expression data from mice mammary glands from Elf5 knockout (KO) and wildtype controls Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23086238 Summary & Design: Summary: We developed conditional knockout mice where the transcription factor Elf5 (also called ESE-2) is deleted in the mammary glands. Loss of Elf5 results in block in alveologenesis and epithelial differentiation defects. Mammary gland samples from Elf5 knockout and wild type animals were analyzed for global transcriptome changes.

Overall design: We used microarrays to performing transcriptional profiling of Elf5KO and control mammary glands at Lac1 (Lactation day 1)

Background corr dist: KL-Divergence = 0.0299, L1-Distance = 0.0253, L2-Distance = 0.0009, Normal std = 0.6722

0.594 Kernel fit Pairwise Correlations Normal fit

Density 0.297

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

pregnantpregnant mammarypregnant mammary glandpregnant mammary of gland wildpregnant mammary typeof gland wildpregnant animal, mammary typeof gland wild animal, biologicalmammary typeof gland Elf5 animal,biological KOof rep1 gland Elf5 animal, biological(0.221439) KOof rep2 Elf5 animal,[biological (0.0726903)min KO rep3 animal,biological (0.0393636) rep1 ] biological(0.0814698) rep2 (0.166689) [rep3 medium (0.418348) ] [ max ] CEM 1 Snw1 1286.6 2228.1 3803.8 P ( S | Z, I ) = 0.98 Ncor1 1646.0 2926.0 3152.9 Mean Corr = 0.61563 Glis3 20.8 132.8 232.4 Npat 223.6 482.4 900.7 Ski 560.9 936.7 1966.8 Epc2 687.0 1085.1 2791.8 Bdp1 717.9 1217.1 2773.7 Zfp26 522.2 748.7 771.0 Zbtb6 121.4 330.9 613.5 Epc1 1450.1 1728.6 3856.0 CEM 1 + Tnks2 3689.8 5401.3 10887.5 Top 10 Genes Phf20 448.4 606.2 735.9 Ep300 669.2 933.3 2454.3 Arid4a 179.9 419.9 591.5 Rbm27 608.3 756.1 1011.3

Null module GEO Series "GSE13302" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 30 -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=GSE13302 Status: Public on May 12 2009 Title: Gene expression profiling in the lung and liver of Perfluorooctane sulfonate (PFOS) exposed mouse fetuses Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19429403 Summary & Design: Summary: Most of the transcriptional changes induced by PFOS in the fetal mouse liver and lung were related to activation of PPARalpha. When compared to the transcript profiles induced by PFOA (Pubmed ID 17681415), few remarkable differences were found other than up-regulation of Cyp3a genes. Because PFOS and PFOA have been shown to differ in their mode of action in the murine neonate, these data suggest that changes related to PFOS-induced neonatal toxicity may not be evident in the fetal transcriptome at term.

Overall design: Thirty timed-pregnant CD-1 mice were orally dosed from gestation day 1-17 with either 0, 5, or 10 mg/kg/day PFOS in 0.5% Tween 20. At term, fetal lung and liver were collected, total RNA prepared, and samples pooled from three fetuses per litter. Five biological replicates consisting of individual litter samples were then evaluated for each treatment group using Affymetrix mouse 430_2 microarrays.

Background corr dist: KL-Divergence = 0.0214, L1-Distance = 0.0694, L2-Distance = 0.0077, Normal std = 0.8465

0.471 Kernel fit Pairwise Correlations Normal fit

Density 0.236

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

0mg/kg/day0mg/kg/day PFOS,0mg/kg/day lungPFOS,0mg/kg/day rep1 liverPFOS, (0.0302977)0mg/kg/day rep1 lungPFOS, (0.028076)0mg/kg/day rep2 liverPFOS, (0.0263209)0mg/kg/day rep2 lungPFOS, (0.0207771)0mg/kg/day rep3 liverPFOS, (0.0258832)0mg/kg/day rep3 lungPFOS, (0.0342059)0mg/kg/day rep4 liverPFOS, (0.0263418)5mg/kg/day rep4 lungPFOS, (0.0306858)5mg/kg/day rep5 liverPFOS, (0.0297669)5mg/kg/day rep5 lungPFOS, (0.0248176)5mg/kg/day rep1 liverPFOS, (0.0123216)5mg/kg/day rep1 lungPFOS, (0.0260192)5mg/kg/day rep2 liverPFOS, (0.0424147)5mg/kg/day rep2 lungPFOS, (0.0332233)5mg/kg/day rep3 liverPFOS, (0.0308178)5mg/kg/day rep3 lungPFOS, (0.0438725)5mg/kg/day rep4 liverPFOS, (0.0454071)10mg/kg/day rep4 lungPFOS, (0.0285931)10mg/kg/day rep5 liver PFOS, (0.0392567)10mg/kg/day rep5 lungPFOS, (0.0431048)10mg/kg/day rep1 liverPFOS, 10mg/kg/day(0.0462656) rep1 lungPFOS, 10mg/kg/day(0.0226848) rep2 liverPFOS, 10mg/kg/day(0.0810647) rep2 lungPFOS, 10mg/kg/day(0.0134153) rep3 liverPFOS, 10mg/kg/day(0.0252579) rep3 lungPFOS, 10mg/kg/day(0.0428085) rep4 liverPFOS, (0.0386763) rep4 lungPFOS, (0.0414154) rep5 liver (0.0258092) rep5 [(0.0403984) min ] [ medium ] [ max ] CEM 1 Snw1 1151.9 1461.3 1937.7 P ( S | Z, I ) = 0.97 Ncor1 1342.8 2013.9 2504.9 Mean Corr = 0.76129 Glis3 46.2 163.6 297.9 Npat 367.7 464.2 639.0 Ski 591.1 1790.5 2561.5 Epc2 740.1 1491.1 1793.4 Bdp1 1019.0 1521.1 2022.1 Zfp26 619.6 1614.4 2048.9 Zbtb6 622.3 725.5 923.2 Epc1 986.6 1890.4 2183.5 CEM 1 + Tnks2 4385.9 6897.4 8576.5 Top 10 Genes Phf20 430.1 695.1 835.5 Ep300 945.4 1602.7 2017.2 Arid4a 213.0 417.0 537.2 Rbm27 886.7 1203.3 1370.3

Null module GEO Series "GSE23408" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 39 -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=GSE23408 Status: Public on Aug 02 2011 Title: Global gene expression profiles and the progression of pro- and anti-inflammatory pathways in mouse models Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Gaucher Disease (GD) is caused by defective glucocerebrosidase (GCase) activity and the consequent accumulation of its substrate, glucosylceramide (GC). This excess of accumulation of GC leads to broad functional impairments in multiple organs, but the pathogenic pathways leading to lipid laden macrophages (Gaucher cells) in visceral organs and their abnormal function is obscure. To understand the molecular pathogenesis of GD, developmental global gene expression was conducted by microarray analyses of total mRNAs from lung and liver of two distinct GCase point-mutated mice (V394L/V394L and D409V/null) and genetic background matched wild-type controls. INFg regulated pro-inflammatory and IL-4 regulated anti-inflammatory cytokine/mediator network were constructed in the lung and liver of GCase mutant mice. Progressive alterations of the INFg and IL-4 pathways were similar, but to different degrees, in visceral tissues from the two different GCase mutated mice. These analyses implicate IFNg regulated pro-inflammatory and IL-4 regulated anti-inflammatory networks in the differential pathophysiological progression.

Overall design: In order to understand the molecular pathogenesis of GD, the disease progression in those models were inverstigated in two visceral tissues (lung and liver) at four time points according to the genotypes. 9V/null: 4 weeks (4w), 12 weeks (12w), 18 weeks (18w), 28 weeks (28w); 4L: weeks (4w), 12 weeks (12w), 18 weeks (18w), 28 weeks (28w). The data from those models were analyzed relative to the adult wild type at 28 weeks.

Background corr dist: KL-Divergence = 0.0891, L1-Distance = 0.0753, L2-Distance = 0.0105, Normal std = 0.4948

0.925 Kernel fit Pairwise Correlations Normal fit

Density 0.463

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

lung_9V/null_lung_9V/null_ 4w_rep1lung_9V/null_ 4w_rep2lung_9V/null_ (0.067229) 12w_rep1lung_9V/null_ (0.0356347) 12w_rep2lung_9V/null_ (0.0219092) 18w_rep1lung_9V/null_ (0.0472646) 18w_rep2lung_9V/null_ (0.00685358) 28w_rep1liver_9V/null_ (0.0119732) 28w_rep2liver_9V/null_ (0.00827645) 4w_rep1liver_9V/null_ (0.0105716) 4w_rep2liver_9V/null_ (0.0210991) 12w_rep1liver_9V/null_ (0.0187993) 12w_rep2liver_9V/null_ (0.01337) 18w_rep1liver_9V/null_ (0.020913) 18w_rep2liver_9V/null_ (0.0253193) 28w_rep1lung_4L_ (0.0146439) 28w_rep2lung_4L_ (0.0254137)4w_rep1lung_4L_ (0.0192055)4w_rep2 (0.0162708)lung_4L_ 12w_rep1 (0.00307798)lung_4L_ 12w_rep2 (0.0107062)lung_4L_ 18w_rep1 (0.0103837)lung_4L_ 18w_rep2 (0.0153119)lung_4L_ 28w_rep1 (0.0221953)liver_4L_ 28w_rep2 (0.0340406)liver_4L_ 4w_rep1 (0.0343765)liver_4L_ 4w_rep2 (0.0168648)liver_4L_ 12w_rep1 (0.0159348)liver_4L_ 12w_rep2 (0.0195703)liver_4L_ 18w_rep1 (0.0216605)liver_4L_ 18w_rep2 (0.0176569)liver_4L_ 28w_rep1 (0.0192876)lung_WT_ 28w_rep2 (0.0211221)lung_WT_ 28w_rep1 (0.0243598)lung_WT_ 28w_rep2 (0.0555109)lung_WT_ 28w_rep3 (0.0852039)liver_WT_ 28w_rep4 (0.0649603)liver_WT_ 28w_rep1 (0.0716566)liver_WT_ 28w_rep2 (0.0141317) 28w_rep3 (0.0206077) (0.0166328)[ min ] [ medium ] [ max ] CEM 1 Snw1 597.4 1394.5 2616.3 P ( S | Z, I ) = 0.96 Ncor1 838.3 1724.9 3434.4 Mean Corr = 0.68242 Glis3 4.8 61.7 307.3 Npat 98.0 251.7 838.4 Ski 273.9 1179.2 3626.7 Epc2 217.4 917.5 2424.3 Bdp1 220.3 718.4 1948.0 Zfp26 196.2 482.8 1469.5 Zbtb6 97.3 217.0 557.3 Epc1 564.4 1239.3 1947.7 CEM 1 + Tnks2 1098.1 2787.9 5357.6 Top 10 Genes Phf20 150.4 529.5 1154.0 Ep300 384.3 902.0 2974.0 Arid4a 73.2 237.7 1015.3 Rbm27 162.4 415.5 1141.3

Null module GEO Series "GSE8503" 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=GSE8503 Status: Public on Jan 01 2008 Title: mRNA expression analysis of undifferentiated Dicer -/- (27H10) embryonic stem cells after miRNA transfection Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18311153 Summary & Design: Summary: We have analyzed the transcript expression levels in Dicer knock-out embryonic stem (ES) cells 24 hours after transfection with either control siRNA agains Renilla luciferase or miRNA Mimics (Dharmacon) of mmu-miR-290 cluster members in order to identify primary targets of miR-290 cluster miRNAs.

Keywords: Comparison of effect of two different transfections on transcriptome of Dicer-KO ES cells

Overall design: Cell were analysed 24h after transfections in an undifferentiated state. Triplicates of both transfections were analyzed.

Background corr dist: KL-Divergence = 0.0399, L1-Distance = 0.0219, L2-Distance = 0.0005, Normal std = 0.6216

0.653 Kernel fit Pairwise Correlations Normal fit

Density 0.327

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

UndifferentiatedUndifferentiatedUndifferentiated Dicer Undifferentiated-/- Dicer (27H) Undifferentiated-/- ES Dicer (27H) cell Undifferentiated-/- ES lineDicer (27H) cell transfected -/- ES lineDicer (27H) cell transfected -/- ES lineDicer with(27H) cell transfected siRL-/- ESline with(27H) cell replicate_1transfected siRL[ ESline withmin cell replicate_2transfected siRL line(0.145428) with ] replicate_3transfected miR-290 (0.0835718) with miR-290 cluster(0.332036) with[ medium miR-290 clusterreplicate_1 clusterreplicate_2 (0.123031) replicate_3] (0.181754) (0.134179)[ max ] CEM 1 Snw1 3905.1 4143.3 4529.1 P ( S | Z, I ) = 0.92 Ncor1 4369.6 4825.4 4946.2 Mean Corr = 0.52418 Glis3 224.4 389.6 573.3 Npat 774.3 910.4 1015.8 Ski 660.5 1059.0 1199.8 Epc2 1252.7 1448.0 1694.2 Bdp1 935.2 1118.3 1254.0 Zfp26 613.4 782.9 875.0 Zbtb6 276.1 403.3 451.1 Epc1 1421.9 1816.8 1879.7 CEM 1 + Tnks2 6885.6 8235.6 9363.4 Top 10 Genes Phf20 3299.2 3652.1 3787.6 Ep300 1059.9 1334.4 1681.5 Arid4a 291.6 419.5 674.8 Rbm27 2161.1 2252.3 2484.6

Null module GEO Series "GSE5324" 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=GSE5324 Status: Public on Oct 17 2006 Title: TTP mRNA targets identified by global analysis of stabilized transcripts in TTP-deficient fibroblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17030620 Summary & Design: Summary: Tristetraprolin (TTP) is a tandem CCCH zinc finger protein that was identified through its rapid induction by mitogens in fibroblasts. Studies of TTP-deficient mice, and cells derived from them, showed that TTP could bind to certain AU-rich elements in mRNAs, leading to increases in the rates of mRNA deadenylation and destruction. Known physiological target

mRNAs for TTP include tumor necrosis factor alpha (TNF), granulocyte macrophage colony stimulating factor (GM-CSF) and interleukin 2 beta (IL2 beta). Here we used microarray analysis of RNA from wild-type and TTP-deficient fibroblast cell lines to identify transcripts with different decay rates, after serum stimulation and actinomycin D treatment. Of 250 mRNAs apparently stabilized in the absence of TTP, 23 contained conserved TTP binding sites; 10 of these were shown by secondary analyses to be stabilized. The most dramatically affected transcript encoded the protein Ier3, recently implicated in the physiological control of blood pressure. The Ier3 transcript contained several conserved TTP binding sites that could bind TTP directly, and conferred TTP sensitivity to the mRNA in cell transfection studies. These studies have identified several new, physiologically relevant TTP target transcripts in fibroblasts; these target mRNAs encode proteins from a variety of functional classes.

Keywords: mRNA degradation, time course, knockout experiment

Overall design: 90 min and another sample taken, after which 5Î¼g/ml actinomycin D was added; samples for RNA analysis were then removed at 30, 60, 90 and 120 min after actinomycin D treatment. In all experiments, each sample represented three combined 100 mm dishes of cells.

Background corr dist: KL-Divergence = 0.1605, L1-Distance = 0.0418, L2-Distance = 0.0041, Normal std = 0.3654

1.092 Kernel fit Pairwise Correlations Normal fit

Density 0.546

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

TTP_KO_0ActD_BioRep1TTP_KO_30ActD_BioRep1TTP_KO_60ActD_BioRep1TTP_KO_90ActD_BioRep1 (0.0924137)TTP_KO_120ActD_BioRep1 (0.00879213)TTP_WT_0ActD_BioRep1 (0.0148174)TTP_WT_30ActD_BioRep1 (0.0271075)TTP_WT_60ActD_BioRep1 (0.0107581)TTP_WT_90ActD_BioRep1 (0.00872958)TTP_WT_120ActD_BioRep1 (0.00631941)TTP_KO_0ActD_BioRep2 (0.00999426)TTP_KO_30ActD_BioRep2 (0.0172644)TTP_KO_60ActD_BioRep2 (0.0585044)TTP_KO_90ActD_BioRep2 (0.0568678)TTP_KO_120ActD_BioRep2 (0.0158088)TTP_WT_0ActD_BioRep2 (0.0183378)TTP_WT_30ActD_BioRep2 (0.0245701)TTP_WT_60ActD_BioRep2 (0.0239393)TTP_WT_90ActD_BioRep2 (0.0321914)TTP_WT_120ActD_BioRep2 (0.0376905)TTP_KO_0ActD_BioRep3 (0.00121699)TTP_KO_30ActD_BioRep3 (0.00638947)TTP_KO_60ActD_BioRep3 (0.0124749)TTP_KO_90ActD_BioRep3 (0.0141522)TTP_KO_120ActD_BioRep3 (0.0181256)TTP_WT_0ActD_BioRep3 (0.00218731)TTP_WT_30ActD_BioRep3 (0.0128743)TTP_WT_60ActD_BioRep3 (0.0229983)TTP_WT_90ActD_BioRep3 (0.0116609)TTP_WT_120ActD_BioRep3 (0.00608794)TTP_KO_0ActD_BioRep4 (0.00291695)TTP_KO_30ActD_BioRep4 (0.0214803)TTP_KO_90ActD_BioRep4 (0.0274025)TTP_KO_120ActD_BioRep4 (0.0376164)TTP_WT_0ActD_BioRep4 (0.0132877)TTP_WT_30ActD_BioRep4 (0.00640892)TTP_WT_60ActD_BioRep4 (0.0122739)TTP_WT_90ActD_BioRep4 (0.0510625)TTP_WT_120ActD_BioRep4 (0.0061756)TTP_KO_30ActD_BioRep5 (0.0076226)TTP_KO_60ActD_BioRep5 (0.0192493)TTP_KO_90ActD_BioRep5 (0.0160034)TTP_KO_120ActD_BioRep5 (0.0144219)TTP_WT_0ActD_BioRep5 (0.00526854)TTP_WT_30ActD_BioRep5 (0.00333191)TTP_WT_60ActD_BioRep5 (0.0129272)TTP_WT_90ActD_BioRep5 (0.0887158)TTP_WT_120ActD_BioRep5 (0.0174604) (0.0126306) (0.0166614) (0.0348079)[ min ] [ medium ] [ max ] CEM 1 Snw1 774.0 934.7 1255.4 P ( S | Z, I ) = 0.92 Ncor1 682.4 867.5 1025.2 Mean Corr = 0.56785 Glis3 631.9 802.2 992.5 Npat 328.0 503.5 778.7 Ski 785.7 980.2 1346.4 Epc2 425.6 647.8 963.1 Bdp1 544.0 773.8 1251.7 Zfp26 370.0 458.2 642.1 Zbtb6 472.3 536.6 811.2 Epc1 342.1 382.1 675.5 CEM 1 + Tnks2 1108.5 1379.0 1604.2 Top 10 Genes Phf20 394.1 609.6 841.2 Ep300 448.3 741.7 1171.9 Arid4a 429.8 579.6 751.6 Rbm27 507.9 791.5 941.0

Null module GEO Series "GSE6210" 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=GSE6210 Status: Public on Jan 01 2007 Title: Hypomorphic Mutation in PGC1beta causes mitochondrial dysfunction and liver insulin resistance Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17141629 Summary & Design: Summary: PGC1beta is a transcriptional coactivator that potently stimulates mitochondrial biogenesis and respiration of cells. Here, we have generated mice lacking exons 3 to 4 of the Pgc1beta gene (PGC1beta E3,4-/E3,4- mice). These mice express a mutant protein that has reduced coactivation activity on a subset of transcription factors, including ERRalpha, a major target of PGC1beta in the induction of mitochondrial gene expression. The mutant mice have reduced expression of OXPHOS genes and mitochondrial dysfunction in liver and skeletal muscle as well as elevated liver triglycerides. Euglycemic-hyperinsulinemic clamp and insulin signaling studies show that PGC1beta mutant mice have normal skeletal muscle response to insulin, but have hepatic insulin resistance. These results demonstrate that PGC1beta is required for normal expression of OXPHOS genes and mitochondrial function in liver and skeletal muscle. Importantly, these abnormalities do not cause insulin resistance in skeletal muscle but cause substantially reduced insulin action in the liver.

Keywords: Liver and quadricpes muscle gene expression, WT vs. PGC1beta mutant

Overall design: Gene expression levels in liver tissue and quadriceps muscle were compared between WT/Control and PGC1beta mutant tissue. Total RNA was extracted from liver and skeletal muscle using RNAeasy kit (Qiagen, Valencia, CA), according to the manufacturers instructions. Synthesis of cRNA, hybridization and scanning of the Affymetrix Murine 430 2.0 chip was performed by Dana Farber Cancer Institute Microarray Core Facility. The microarray data was analyzed by Clustering Analysis using the d-Chip software (Li and Wong, 2001).

Background corr dist: KL-Divergence = 0.0507, L1-Distance = 0.0691, L2-Distance = 0.0068, Normal std = 0.6428

0.709 Kernel fit Pairwise Correlations Normal fit

Density 0.354

0.000 CEM 1

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

Pre-normalization Quantiles

Liver ExperimentLiver ControlLiver 3 (0.0884469) Control 2 Liver(0.049183) Experiment 3 Liver(0.0902883) ExperimentLiver 1 (0.0809151) ControlMuscle 2 (0.0741316) 1 MuscleControl(0.0492316) MuscleControl 1 (0.0442368) MuscleControl 2 (0.13394) MuscleExperiment 3 (0.116709) MuscleExperiment 1 (0.0823743) Experiment 2 (0.0772576) 3 (0.113286)[ min ] [ medium ] [ max ] CEM 1 Snw1 940.6 1751.9 2023.4 P ( S | Z, I ) = 0.91 Ncor1 975.0 2473.5 2741.7 Mean Corr = 0.65706 Glis3 4.2 17.7 91.4 Npat 110.1 156.7 257.2 Ski 266.0 1102.3 1564.6 Epc2 364.8 1005.1 1346.1 Bdp1 281.4 567.2 776.1 Zfp26 214.6 620.6 915.0 Zbtb6 177.8 276.9 377.7 Epc1 484.3 1360.9 1557.6 CEM 1 + Tnks2 1898.2 8044.9 10769.9 Top 10 Genes Phf20 242.9 873.5 1715.0 Ep300 408.7 1618.2 2263.3 Arid4a 53.8 153.7 227.7 Rbm27 176.5 501.1 717.4

Null module GEO Series "GSE12389" 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=GSE12389 Status: Public on Oct 31 2008 Title: Interferon-Î³-dependent regulatory circuits in immune inflammation highlighted in diabetes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18981116 Summary & Design: Summary: We demonstrate diverse roles of interferongamma (IFN-˛‡) in the induction and regulation of immune-mediated inflammation using a transfer model of autoimmune diabetes. The diabetogenic CD4+BDC2.5 (BDC) T cell clone upon transfer into NOD.scid mice induced destruction of islets of Langerhans leading to diabetes. Administration of a neutralizing antibody to IFN-Î³ (H22) resulted in long term protection (LTP) from diabetes, with inflammation but persistence of a significant, albeit decreased numbers of Î²-cells. BDC T cells were a mixture of cells expressing high, intermediate and low levels of the T cell receptor. Clonotype-low BDC T cells were required for LTP. Furthermore, islet infiltrating leukocytes in the LTP mice contained Foxp3+CD4 T cells. Islet inflammation in both diabetic and LTP mice was characterized by heavy infiltration of macrophages. Gene expression profiles indicated that macrophages in diabetic mice were M1-type, while LTP mice contained M2-differentiated. The LTP was abolished if mice were treated with either an antibody depleting CD4 T cells, or a neutralizing antibody to CTLA-4, in this case, only at a late stage. Neutralization of IL-10, TGF-Î², GITR or CD25 had no effect. Transfer of only clonotype-high expressing BDC T cells induced diabetes but in contrast, H22 antibodies did not inhibit diabetes. While clonotype high T cells induced diabetes even when IFN-Î³ was neutralized, paradoxically, there was reduced inflammation and no diabetes if host myeloid cells lacked IFN-Î³ receptor. Hence, using monoclonal CD4 T cells, IFN-Î³ can have a wide diversity of roles, depending on the setting of the immune process.

Overall design: Pancreatic islets were laser-capture microdissected from mice injected with diabetogenic T cells. One cohort of mice also received injections with anti-interfereon gamma monoclonal antibody, which protected those mice from developing diabetes. RNA prepared from islets was amplified and analyzed by Affymetrix GeneChips. Each GeneChip was prepared from RNA pooled from 5 mice at each timepoint. GeneChips were prepared from RNA extracted at different days following injection of T cells. The following days were assayed day 0 (i.e., untreated), day 3 (for diabetic and protected islets), day 4 (diabetic and protected), day 5 (only for protected, as diabetic islets were too edematous to dissect), day 8 (diabetic and protected).

Background corr dist: KL-Divergence = 0.0589, L1-Distance = 0.0528, L2-Distance = 0.0047, Normal std = 0.5629

0.711 Kernel fit Pairwise Correlations Normal fit

Density 0.355

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

UntreatedDiabetogenic, NOD.ScidProtected, (d0) d3Diabetogenic, (0.108119)(0.172758) d3 (0.129235)Protected, d4Protected, (0.243793) d4 (0.0474483)Diabetogenic, d5 (0.126038)Protected, d8 (0.126506) d8 (0.0461046) [ min ] [ medium ] [ max ] CEM 1 Snw1 352.2 1305.4 2774.1 P ( S | Z, I ) = 0.90 Ncor1 138.4 1522.3 1994.5 Mean Corr = 0.65129 Glis3 146.7 431.6 754.4 Npat 114.6 1121.2 1660.9 Ski 114.6 715.6 1350.5 Epc2 218.5 1186.0 1908.1 Bdp1 283.2 817.3 1893.4 Zfp26 337.0 595.5 704.1 Zbtb6 154.1 411.5 721.0 Epc1 652.5 1446.4 2892.2 CEM 1 + Tnks2 739.2 5660.0 7242.1 Top 10 Genes Phf20 139.8 582.1 812.2 Ep300 167.6 291.1 1019.1 Arid4a 156.0 341.8 549.8 Rbm27 151.5 250.5 670.7

Null module GEO Series "GSE11274" 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=GSE11274 Status: Public on Jul 15 2009 Title: Induction of Pluripotency in Adult Unipotent Germline Stem Cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19570517 Summary & Design: Summary: Mouse and human stem cells with features similar to those of embryonic stem cells have been derived from testicular cells. Although pluripotent stem cells have been obtained from defined germline stem cells (GSCs) of mouse neonatal testis, only multipotent stem cells have been obtained so far from defined cells of mouse adult testis. In this study we describe a robust and reproducible protocol for obtaining germline-derived pluripotent stem (gPS) cells from adult unipotent GSCs. Pluripotency of gPS cells was confirmed by in vitro and in vivo differentiation, including germ cell contribution and transmission. As determined by clonal analyses, gPS cells indeed originate from unipotent GSCs. We propose that the conversion process requires a GSC culture microenvironment that depends on the initial number of plated GSCs and the length of culture time.

Overall design: - ESC_like_3

Background corr dist: KL-Divergence = 0.1113, L1-Distance = 0.0446, L2-Distance = 0.0038, Normal std = 0.4495

0.911 Kernel fit Pairwise Correlations Normal fit

Density 0.456

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

GermlineGermline stem Germlinecells stem (GSC_1) Germlinecells stem (GSC_2) sample_1 Germlinecells pluripotent (GSC_3) sample_2Germline pluripotent(0.294115) stem sample_3Germline pluripotent(0.182753) cells stemGermline pluripotent(gPSC_1)(0.14969) cells stemNeural pluripotent(gPSC_2) cellssample_1 stem stemNeural (gPSC_3) cells sample_2cells stem stemNeural(0.0331509) (gPSC_4) (NSC_1) cells sample_3cells stemMouse(0.0175595) (gPSC_5) (NSC_2) sample_1 sample_4cells embryonicMouse(0.0122199) (NSC_3) sample_2sample_5 (0.0157217)embryonicMouse(0.0173197) fibroblasts sample_3 (0.0180993)embryonicEmbryonic(0.038275) fibroblasts (0.0124282)Embryonic(MEF_1) fibroblastsstem Embryonic(MEF_2) sample_1 cells stem (ESC_1)ESC(MEF_3) sample_2 cells stem(0.0299472) like (ESC_2)ESC sample_1sample_3 cellscells (0.0321199) like 1(ESC_3)ESC sample_2(0.00906357)cells (0.0240066)(0.0384201) like 2 sample_3(0.00644922)cells (0.0285146) 3 (0.012937) (0.0272096)[ min ] [ medium ] [ max ] CEM 1 Snw1 1791.8 2668.8 3676.1 P ( S | Z, I ) = 0.90 Ncor1 741.3 2737.9 3813.2 Mean Corr = 0.20277 Glis3 41.0 98.9 1907.0 Npat 680.6 1160.5 1741.5 Ski 745.3 1184.1 7488.3 Epc2 909.0 1557.4 2061.2 Bdp1 1126.0 1529.4 2107.0 Zfp26 572.6 713.4 1381.2 Zbtb6 397.9 674.1 1446.4 Epc1 628.7 885.1 1593.0 CEM 1 + Tnks2 3488.9 8677.9 10779.6 Top 10 Genes Phf20 707.5 1573.1 5691.0 Ep300 775.2 1290.6 1964.8 Arid4a 82.2 223.2 345.1 Rbm27 606.5 1291.2 1842.2

Null module GEO Series "GSE14458" 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=GSE14458 Status: Public on Nov 10 2009 Title: Gene expression profiles of 344SQ lung adenocarcinoma cells with high metastatic potential (syngeneic mouse model) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19759262 Summary & Design: Summary: The biologic basis for NSCLC metastasis is not well understood. Here we addressed this deficiency by transcriptionally profiling tumors from a genetic mouse model of human lung adenocarcinoma that develops metastatic disease owing to the expression of K-rasG12D and p53R172H. As a tool to investigate the biologic basis for metastasis in this model and to query the roles of specific genes in this signature, we isolated adenocarcinoma cell lines from these mice and used them to develop a syngeneic tumor model in wild-type littermates. Transcriptional profiling of the highly metastatic subcutaneous tumors revealed genes that regulate, among other processes, epithelial-to-mesenchymal transition and intra-tumoral inflammation and angiogenesis, whereas the non-metastatic tumors did not.

Keywords: two group comparison

Overall design: Expression profiling performed on 344SQ, 393P, and 393LN

Background corr dist: KL-Divergence = 0.1273, L1-Distance = 0.0325, L2-Distance = 0.0019, Normal std = 0.3978

1.003 Kernel fit Pairwise Correlations Normal fit

Density 0.501

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

344SQ, 344SQ,sample 344SQ, samplea1192 (0.24307) 393LN, samplea1193 (0.129587)344SQ,sample a1194 (0.0815229) 393P,samplea0930 sample (0.0269616)393LN, a1202 a1158 (0.00685428)393P,sample (0.183537) sample 393LN,a0808 a1173(0.0751059) 393P,sample (0.043505) sample 393LN,a0858 a1195(0.0879894) 393P,sample (0.0447242) sample a0859 a1249(0.0199551) (0.0571881)[ min ] [ medium ] [ max ] CEM 1 Snw1 1740.2 1963.4 3234.5 P ( S | Z, I ) = 0.88 Ncor1 1194.6 1484.6 2119.2 Mean Corr = 0.34412 Glis3 314.3 728.7 1178.4 Npat 1094.3 1229.7 1565.7 Ski 1274.4 1883.8 3724.0 Epc2 1628.3 1930.8 2361.6 Bdp1 941.9 1056.9 1369.4 Zfp26 365.1 469.5 641.1 Zbtb6 635.7 799.3 1063.4 Epc1 818.7 1047.2 1318.2 CEM 1 + Tnks2 5313.9 5850.7 6273.3 Top 10 Genes Phf20 781.0 976.2 1258.2 Ep300 1214.2 1971.4 2488.3 Arid4a 333.0 447.1 582.3 Rbm27 614.1 812.3 1280.6

Null module GEO Series "GSE9146" 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=GSE9146 Status: Public on Apr 04 2008 Title: Irradiation response in PKBalpha MEF Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18439899 Summary & Design: Summary: MEF proficient or deficient in PKBalpha, or PKBalpha knockout MEF where PKBalpha expression was reconstituted by stable transfection were subjected to 10Gy gamma-IR treatment. 4 or 24 hours after treatment, gene expression changes were analyzed.

Keywords: genotype0-specific stress response in PKBalpha MEF

Overall design: three biological replicates were included in the experiment for each condition analyzed. overall, 27 samples were included in the study. the reference samples were untreated MEF of each respective genotype.

Background corr dist: KL-Divergence = 0.2065, L1-Distance = 0.0377, L2-Distance = 0.0026, Normal std = 0.3367

1.192 Kernel fit Pairwise Correlations Normal fit

Density 0.596

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

bh20061215m430v2_U_02_PKBa-MEF-WT_-_1bh20061215m430v2_U_01_PKBa-MEF-WT_-_0bh20061215m430v2_U_03_PKBa-MEF-WT_-_2bh20061215m430v2_U_04_PKBa-MEF-WT_4h_0bh20061215m430v2_U_05_PKBa-MEF-WT_4h_1bh20061215m430v2_U_06_PKBa-MEF-WT_4h_2bh20061215m430v2_U_07_PKBa-MEF-WT_24h_0 (0.0258228)bh20061215m430v2_U_08_PKBa-MEF-WT_24h_1 (0.0429136)bh20061215m430v2_U_09_PKBa-MEF-WT_24h_2 (0.0476475)bh20061215m430v2_U_10_PKBa_-_-_MEF_-_0 (0.00804293)bh20061215m430v2_U_11_PKBa_-_-_MEF_-_1 (0.0176052)bh20061215m430v2_U_12_PKBa_-_-_MEF_-_2 (0.017625)bh20061215m430v2_U_13_PKBa_-_-_MEF_4h_0 (0.0260914)bh20061215m430v2_U_14_PKBa_-_-_MEF_4h_1 (0.0191897)bh20061215m430v2_U_15_PKBa_-_-_MEF_4h_2 (0.0447931)bh20061215m430v2_U_16_PKBa_-_-_MEF_24h_0 (0.0108702)bh20061215m430v2_U_17_PKBa_-_-_MEF_24h_1 (0.00896642)bh20061215m430v2_U_18_PKBa_-_-_MEF_24h_2 (0.067111)bh20061215m430v2_U_19_PKBa_-_-_R_MEF_-_0 (0.0303398)bh20061215m430v2_U_20_PKBa_-_-_R_MEF_-_1 (0.020812)bh20061215m430v2_U_21_PKBa_-_-_R_MEF_-_2 (0.0301346)bh20061215m430v2_U_22_PKBa_-_-_R_MEF_4h_0 (0.0479796)bh20061215m430v2_U_23_PKBa_-_-_R_MEF_4h_1 (0.00742921)bh20061215m430v2_U_24_PKBa_-_-_R_MEF_4h_2 (0.0167793)bh20061215m430v2_U_25_PKBa_-_-_R_MEF_24h_0 (0.00533902)bh20061215m430v2_U_26_PKBa_-_-_R_MEF_24h_1 (0.204376)bh20061215m430v2_U_27_PKBa_-_-_R_MEF_24h_2 (0.0098995) (0.0384745) (0.0275799) (0.0230394)[ min (0.019444) ] (0.00879629) (0.172898)[ medium ] [ max ] CEM 1 Snw1 1568.8 1970.4 3798.4 P ( S | Z, I ) = 0.84 Ncor1 1256.1 1671.1 2409.5 Mean Corr = 0.37090 Glis3 141.4 295.0 543.5 Npat 497.4 849.5 1273.8 Ski 928.9 1381.3 2743.3 Epc2 824.4 1122.2 1429.7 Bdp1 573.2 848.0 1116.4 Zfp26 609.5 937.0 1311.4 Zbtb6 362.6 548.2 798.2 Epc1 825.5 937.2 1651.7 CEM 1 + Tnks2 4307.5 6112.5 8427.2 Top 10 Genes Phf20 1195.1 1708.9 2364.1 Ep300 557.4 832.1 1363.1 Arid4a 70.6 139.8 284.2 Rbm27 719.3 851.3 1039.5

Null module GEO Series "GSE56482" 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=GSE56482 Status: Public on Jul 04 2014 Title: Expression Data comparing Gene Expression in 27-day old testes of wild-type and Brwd1-/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Brwd1-/- mice are infertile with post-meiotic defects in the male. BRWD1 contains bromodomains and may function as a transcriptional regulator important for post-meiotic development in the male germline.

This microarray compares post-meiotic gene expression between WT and mutant mice.

Overall design: We collected total RNA from testes of 27-day old WT and Brwd1-/- (MT) mice. At this age, germ cells have completed meiosis and are mid-way in post-meiotic development. Any gene expression changes in spermatids would be apparent at this time-point. We decided to do this with 4 WT and 4 Brwd1-/- mice.

Background corr dist: KL-Divergence = 0.0388, L1-Distance = 0.0285, L2-Distance = 0.0010, Normal std = 0.6239

0.660 Kernel fit Pairwise Correlations Normal fit

Density 0.330

0.000 CEM 1

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

Pre-normalization Quantiles

Wild-typeWild-type testis,Wild-type replicate testis,Wild-type replicate testis, 1 (0.179298)Mutant replicate testis, 2 (0.108486) Mutanttestis, replicate 3 (0.041306) replicate Mutanttestis, 4 (0.173955) replicate Mutanttestis, 1 (0.135426) replicate testis, 2 (0.141265) replicate 3 (0.113155) 4 (0.107109)[ min ] [ medium ] [ max ] CEM 1 Snw1 1743.9 2088.1 2257.4 P ( S | Z, I ) = 0.84 Ncor1 1255.5 1771.3 2147.1 Mean Corr = 0.54418 Glis3 47.8 73.4 107.1 Npat 187.5 434.5 673.5 Ski 351.3 532.8 719.4 Epc2 518.2 790.0 1244.2 Bdp1 224.1 502.1 696.7 Zfp26 300.8 624.9 862.9 Zbtb6 155.3 201.1 332.1 Epc1 1523.4 1960.7 2292.1 CEM 1 + Tnks2 1748.6 2560.8 2885.8 Top 10 Genes Phf20 854.2 1074.6 1331.0 Ep300 654.1 894.1 1066.8 Arid4a 105.7 196.5 370.5 Rbm27 385.8 724.2 920.0

Null module GEO Series "GSE9441" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 36 -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=GSE9441 Status: Public on Dec 07 2007 Title: The effect of sleep deprivation on gene expression in the brain and the liver of three inbred mouse strains Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18077435 Summary & Design: Summary: These studies adress differential changes in gene expression between 6h sleep deprived and control mice in the brain and the liver. We profiled gene expression in three different inbred strains to understand the influence of genetic background.

Keywords: brain, genetic background, sleep deprivation

Overall design: Experiments were performed on male mice (C57BL/6J (B6), AKR/J (AK), DBA/2J (D2)), 12-13 weeks of aged, purchased from Jackson Laboratory. Animals were housed in a light/dark cycle of 24 hrs with water and food available ad libitum. Mice of the 3 inbred strains were sleep deprived for 6h starting at light onset (ZT0) and sacrificed together with their home-cage controls at ZT6 (n=9 / strain =3 / condition =2 / tissues =2; total = 108 mice).

Background corr dist: KL-Divergence = 0.0092, L1-Distance = 0.0360, L2-Distance = 0.0014, Normal std = 0.9491

0.436 Kernel fit Pairwise Correlations Normal fit

Density 0.218

0.000 CEM 1

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

Pre-normalization Quantiles

B_AK_Control_ZTB_AK_Control_ZTB_AK_Control_ZT 6_1 B_AK_SleepDep_ZT(0.0121059) 6_2 B_AK_SleepDep_ZT(0.0267477) 6_3 B_AK_SleepDep_ZT(0.0199519) 6_1B_B6_Control_ZT (0.0200667) 6_2B_B6_Control_ZT (0.0501406) 6_3B_B6_Control_ZT (0.0281904) 6_1 B_B6_SleepDep_ZT(0.0187177) 6_2 B_B6_SleepDep_ZT(0.0488229) 6_3 B_B6_SleepDep_ZT(0.0172231) 6_1B_D2_Control_ZT (0.0454858) 6_2B_D2_Control_ZT (0.02767) 6_3B_D2_Control_ZT (0.0224258) 6_1 B_D2_SleepDep_ZT(0.0247276) 6_2 B_D2_SleepDep_ZT(0.0142828) 6_3 B_D2_SleepDep_ZT(0.0380307) 6_1L_AK_Control_ZT (0.0290705) 6_2L_AK_Control_ZT (0.0374739) 6_3L_AK_Control_ZT (0.0406858) 6_1 L_AK_SleepDep_ZT(0.0271292) 6_2 L_AK_SleepDep_ZT(0.0177132) 6_3 L_AK_SleepDep_ZT(0.0265909) 6_1L_B6_Control_ZT (0.0204753) 6_2L_B6_Control_ZT (0.0224099) 6_3L_B6_Control_ZT (0.0227194) 6_1 (0.0768662)L_B6_SleepDep_ZT 6_2 (0.023902)L_B6_SleepDep_ZT 6_3 (0.0263692)L_B6_SleepDep_ZT 6_1L_D2_Control_ZT (0.027885) 6_2L_D2_Control_ZT (0.0232247) 6_3L_D2_Control_ZT (0.0201832) 6_1 (0.0178328)L_D2_SleepDep_ZT 6_2 (0.0145054)L_D2_SleepDep_ZT 6_3 (0.0303719)L_D2_SleepDep_ZT 6_1 (0.0249254) 6_2 (0.0310162) 6_3 (0.0240606)[ min ] [ medium ] [ max ] CEM 1 Snw1 987.4 1279.8 1628.1 P ( S | Z, I ) = 0.80 Ncor1 1196.4 1765.2 2067.9 Mean Corr = 0.76582 Glis3 38.2 63.3 89.4 Npat 67.4 145.8 287.0 Ski 511.1 1248.2 1877.9 Epc2 422.4 1058.8 1828.6 Bdp1 416.5 632.7 808.9 Zfp26 204.0 918.0 1373.8 Zbtb6 250.9 413.7 718.7 Epc1 656.5 1650.8 2001.5 CEM 1 + Tnks2 1799.1 2511.9 3571.0 Top 10 Genes Phf20 144.6 1120.5 1547.9 Ep300 522.9 770.7 1072.4 Arid4a 46.2 81.5 159.4 Rbm27 219.4 697.8 990.6

Null module GEO Series "GSE47694" 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=GSE47694 Status: Public on Jul 01 2013 Title: Regulation of Mouse Lens Development and Gene Expression by KrÃ¼ppel-Like Factor 4 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Conditional disruption of Klf4 in the ectoderm-derived tissues of the eye results in defective cornea, conjunctiva and the lens.

Expression of Klf4 is first detected in the embryonic day-12 (E12) mouse lens, peaks at E16, and declines thereafter.

Lenses from Mice which were conditional null for Klf4 (Klf4CN) were characterized by morphology and transcriptome.

Overall design: Wild type and Klf4-conditional null mouse lens gene expression at embryonic day 16.5 (E16.5) and postnatal day 56 (PN56) was surveyed using Affymetrix mouse whole genome 430 2 arrays.

Background corr dist: KL-Divergence = 0.0301, L1-Distance = 0.0216, L2-Distance = 0.0005, Normal std = 0.6597

0.605 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

E16.5_WT_sample_1E16.5_WT_sample_2E16.5_WT_sample_3 (0.116061)E16.5_Klf4CN_sample_1 (0.0690303)E16.5_Klf4CN_sample_2 (0.105741)E16.5_Klf4CN_sample_3PN56_WT_sample_1 (0.0722148)PN56_WT_sample_2 (0.0621899)PN56_Klf4CN_sample_1 (0.0525034) (0.130855)PN56_Klf4CN_sample_2 (0.144689) (0.105484) (0.141231)[ min ] [ medium ] [ max ] CEM 1 Snw1 1624.4 2188.9 2676.9 P ( S | Z, I ) = 0.79 Ncor1 1490.4 2307.6 2554.5 Mean Corr = 0.66063 Glis3 9.2 28.4 38.4 Npat 340.1 674.7 730.5 Ski 339.7 867.9 1143.4 Epc2 958.9 1835.9 2081.8 Bdp1 495.6 971.7 1248.2 Zfp26 663.8 1315.2 1634.2 Zbtb6 403.5 677.8 827.1 Epc1 1623.7 2122.8 2640.1 CEM 1 + Tnks2 4640.7 10066.6 11138.3 Top 10 Genes Phf20 555.2 827.9 921.0 Ep300 378.5 1350.4 1533.2 Arid4a 247.9 356.5 422.3 Rbm27 734.5 1029.1 1157.0

Null module GEO Series "GSE32095" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32095 Status: Public on Feb 22 2012 Title: GPR120 mediates high-fat diet induced obesity Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22343897 Summary & Design: Summary: Analysis of GPR120 which play roles for the fatty acid sensor in adipose tissue. Results provide insight into the transcriptional effects caused by the loss of the GPR120 proteins and provide further insight into their functions.

Overall design: GPR120 KO mice and the corresponding wild-type with normal diet(ND) or high fat diet(HFD), were subjected to Affymetrix Mus musculus microarrays. Epididymal adipose tissue and liver were analyzed in triplicates.

Background corr dist: KL-Divergence = 0.1001, L1-Distance = 0.0645, L2-Distance = 0.0080, Normal std = 0.4859

0.914 Kernel fit Pairwise Correlations Normal fit

Density 0.457

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

EpididymalLiver adipose GPR120KOEpididymal GPR120KOLiver HFD adipose GPR120KO Epididymal#427 HFD (0.0504221)GPR120KO #427Liver HFD adipose (0.0289456)GPR120KO Epididymal#428 HFD (0.0312477)GPR120KO #428Liver HFD adipose (0.0178055)WT Epididymal#429 HFDHFD (0.0336956)WT #546#429Liver HFD adipose (0.0283302) (0.030804)WT #546Epididymal HFD (0.0978085) WT #547Liver HFD adipose(0.0269054) WT #547Liver HFD (0.0674857) WT #560Epididymal HFDND (0.0253207) #686 #560Liver (0.0294265) adipose(0.0562942) WTEpididymal ND WT#687Liver ND (0.0280384) adipose #687WTEpididymal ND (0.0538517) WT#690Liver ND (0.036545) adipose #690GPR120KOEpididymal (0.0307536) GPR120KOLiver ND adipose GPR120KO#718Epididymal ND (0.0337004) GPR120KO#718Liver ND (0.039104)adipose GPR120KO#719Epididymal ND (0.0395699) GPR120KO#719 ND (0.039547)adipose #720 ND (0.0562872) WT#720 ND (0.0684841) #686[ min(0.049627) ] [ medium ] [ max ] CEM 1 Snw1 931.0 1646.4 1840.3 P ( S | Z, I ) = 0.71 Ncor1 1937.4 2593.9 4458.6 Mean Corr = 0.54191 Glis3 12.1 123.8 309.7 Npat 203.9 389.6 695.9 Ski 153.4 591.4 989.3 Epc2 791.6 1154.7 1792.5 Bdp1 1026.1 1395.3 2005.4 Zfp26 496.3 618.1 959.5 Zbtb6 179.9 338.2 540.3 Epc1 1156.9 1592.8 2158.9 CEM 1 + Tnks2 1976.7 3618.6 5990.8 Top 10 Genes Phf20 303.1 806.4 1308.4 Ep300 924.8 1309.6 1690.0 Arid4a 265.5 524.1 672.0 Rbm27 672.1 825.2 1309.6

Null module GEO Series "GSE30083" 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=GSE30083 Status: Public on Feb 13 2012 Title: Expression data from CD4 single positive thymocyte subsets from C57BL/6 mice of 6-8 wks of age Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22022412 Summary & Design: Summary: After positive selection in the thymus, the newly generated single positive (SP) thymocytes are phenotypically and functionally immature and undergo apoptosis upon antigen stimulation. In the thymic medullary microenvironment, SP cells progressively acquire immunocompetence. Negative selection to remove autoreactive T cells also occur at this stage. We have defined four subsets of CD4 SP, namely, SP1, SP2, SP3, and SP4 that follow a functional maturation program and a sequential emergence during mouse ontogeny.

We used microarray to detail the global programm of gene expression during the maturation of murine CD4 single positive thymocytes

Overall design: Four subsets of CD4+CD8-CD25-NK1.1- thymocytes from C57BL/6 mice of 6-8 wks of age were purified for RNA extraction and hybridization on Affymetrix microarrays, namely, SP1 (Qa-2-6C10+CD69+), SP2 (Qa-2-6C10-CD69+), SP3 (Qa-2-6C10-CD69-), SP4 (Qa-2+6C10-CD69-).

Background corr dist: KL-Divergence = 0.0812, L1-Distance = 0.0208, L2-Distance = 0.0005, Normal std = 0.4748

0.840 Kernel fit Pairwise Correlations Normal fit

Density 0.420

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

SP1, biologicalSP2, biologicalSP3, rep1 biological(0.0981467)SP4, rep1 biological(0.0803109)SP1, rep1 biological(0.0638987)SP2, rep1 biological(0.0320989)SP3, rep2 biological(0.0305524)SP4, rep2 biological(0.0476097)SP1, rep2 biological(0.0128896)SP2, rep2 biological(0.0647734)SP3, rep3 biological(0.134809)SP4, rep3 biological(0.134588) rep3 (0.110917) rep3 (0.189406)[ min ] [ medium ] [ max ] CEM 1 Snw1 1489.1 1825.7 2379.8 P ( S | Z, I ) = 0.70 Ncor1 3831.6 4828.9 7439.2 Mean Corr = 0.43367 Glis3 17.0 21.1 37.5 Npat 409.9 572.7 913.9 Ski 1024.0 1739.0 2481.3 Epc2 1437.6 1643.2 2204.5 Bdp1 1286.1 1917.3 2277.1 Zfp26 753.7 1247.8 1563.2 Zbtb6 418.5 534.4 654.6 Epc1 2615.9 3667.2 4550.7 CEM 1 + Tnks2 5700.8 6260.2 10356.8 Top 10 Genes Phf20 536.8 715.4 1171.8 Ep300 1075.5 1614.0 2937.8 Arid4a 689.3 1122.2 1482.3 Rbm27 784.5 1225.6 2014.7

Null module GEO Series "GSE54215" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 13 -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=GSE54215 Status: Public on Mar 02 2014 Title: Comparison of gene expression profiles of naÃ¯ve and in vitro effector CD8+ T cells from wild-type and BATF-/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24584090 Summary & Design: Summary: The transcription factor BATF is required for Th17 and TFH differentiation. Here, we show that BATF also has a fundamental role in regulating effector CD8+ T cell differentiation. BATF-deficient CD8+ T cells show profound defects in effector expansion and undergo proliferative and metabolic catastrophe early after antigen encounter. BATF, together with IRF4 and Jun proteins, binds to and promotes early expression of genes encoding lineage-specific transcription-factors (T-bet and Blimp-1) and cytokine receptors, while paradoxically repressing genes encoding effector molecules (IFNg and granzyme B). Thus, BATF amplifies TCR-dependent transcription factor expression and augments inflammatory signal propagation but restrains effector gene expression. This checkpoint prevents irreversible commitment to an effector fate until a critical threshold of downstream transcriptional activity has been achieved.

Overall design: P14 TCR transgenic CD8+ T cells from wild-type or BATF-/- mice were examined either as naÃ¯ve cells or after 3 days of in vitro stimulation with antibodies to CD3 and CD28 in the presence of IL-2

Background corr dist: KL-Divergence = 0.0486, L1-Distance = 0.0713, L2-Distance = 0.0070, Normal std = 0.6584

0.695 Kernel fit Pairwise Correlations Normal fit

Density 0.348

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_P14_Naive_rep1WT_P14_Naive_rep2BATF_KO_P14_Naive_rep1 (0.171685)BATF_KO_P14_Naive_rep2 (0.146104)BATF_KO_P14_Naive_rep3WT_P14_D3_Effector_rep1 (0.125123)WT_P14_D3_Effector_rep2 (0.0652702)WT_P14_D3_Effector_rep3 (0.0775795)WT_P14_D3_Effector_rep4 (0.104248)BATF_KO_P14_D3_Effector_rep1 (0.047779)BATF_KO_P14_D3_Effector_rep2 (0.0433274)BATF_KO_P14_D3_Effector_rep3 (0.0250226)BATF_KO_P14_D3_Effector_rep4 (0.0439904) (0.0227044) (0.0941485)[ min (0.0330182) ] [ medium ] [ max ] CEM 1 Snw1 2108.0 2477.8 2791.2 P ( S | Z, I ) = 0.69 Ncor1 2940.2 3176.8 4936.4 Mean Corr = 0.60722 Glis3 13.8 18.3 22.0 Npat 613.1 681.7 790.9 Ski 265.8 314.5 1190.7 Epc2 978.3 1110.9 2030.1 Bdp1 1247.6 1405.2 2609.0 Zfp26 844.8 968.1 1702.6 Zbtb6 368.8 435.1 718.7 Epc1 1168.8 1274.2 3066.4 CEM 1 + Tnks2 7109.9 7652.6 9909.6 Top 10 Genes Phf20 857.1 1084.6 1186.7 Ep300 1452.5 1770.6 2152.0 Arid4a 967.4 1177.4 2233.0 Rbm27 1092.9 1186.0 2241.6

Null module GEO Series "GSE13259" 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=GSE13259 Status: Public on Apr 01 2009 Title: Comparisons of epithelial and mesenchymal murine breast tumor cell lines Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19276366 Summary & Design: Summary: Epithelial tumor cells (E) underwent EMT in vivo in FVB/N mice generating mesenchymal tumors. Mesenchymal cell lines (M1-M4) were each derived from a different mouse. This study compares gene expression between these two different tumor types.

Keywords: cell type comparison

Overall design: Two replicates were prepared for each of five cell lines, one epithelial cell line (E) and 4 mesenchymal cell lines M1-M4.

Background corr dist: KL-Divergence = 0.0778, L1-Distance = 0.0460, L2-Distance = 0.0031, Normal std = 0.5332

0.799 Kernel fit Pairwise Correlations Normal fit

Density 0.400

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

SpontaneousSpontaneous epithelialRelapsed epithelialRelapsed mammary mesenchymalRelapsed mammary mesenchymal tumorRelapsed mammarymesenchymal cell tumor Relapsedline, mammarymesenchymal cell replicatetumor Relapsedline, mammarymesenchymal cell replicatetumor 1Relapsed line(0.316795) mammarymesenchymal cell 1,tumor 2 Relapsedreplicate line(0.151235) mammarymesenchymal cell 1,tumor replicate line 1 mammarymesenchymal (0.0744956) cell 2,tumor replicate line 2mammary (0.111094) cell 2,tumor replicate line 1mammary (0.0385109) cell 3,tumor replicate[ line 2min (0.0384878) cell 3,tumor replicate line 1 (0.105944) cell ]4, replicate line 2 (0.0563674) 4, replicate 1[ (0.0193755) medium 2 (0.0876959) ] [ max ] CEM 1 Snw1 1307.0 1848.7 2529.3 P ( S | Z, I ) = 0.68 Ncor1 1217.0 1790.8 2050.5 Mean Corr = 0.52426 Glis3 184.7 303.3 331.8 Npat 578.3 699.6 1105.3 Ski 424.9 496.2 713.0 Epc2 725.6 1018.9 1481.7 Bdp1 923.5 1329.8 1570.6 Zfp26 431.5 612.9 820.9 Zbtb6 264.3 446.1 901.0 Epc1 688.5 1220.4 1498.9 CEM 1 + Tnks2 2664.8 3558.3 4016.1 Top 10 Genes Phf20 672.1 979.7 1224.3 Ep300 818.9 1004.7 1067.1 Arid4a 135.6 222.3 324.6 Rbm27 555.6 694.1 791.5

Null module GEO Series "GSE17266" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 59 -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=GSE17266 Status: Public on Jan 12 2010 Title: Expression data from B6C3F1 mice treated with baclofen Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice were treated with either 100mg/kg baclofen or 0.5% methylcellulose alone by oral gavage for 1 or 5 days.

Overall design: Mice were sacrificed by cervical dislocation after either a single dose (1day) or 5 daily doses (5 days) of either baclofen or 0.5% methylcellulose two hours after the last dose. The bone marrow from the right humerus, a portion of the left lateral liver lobe and half a cross-section of the spleen were harvested and the RNA was isolated from these tissues using standard Qiagen reagents. Standard Affymetrix protocols were used for GeneChip probe preparations. 59 arrays.

Background corr dist: KL-Divergence = 0.0198, L1-Distance = 0.0483, L2-Distance = 0.0033, Normal std = 0.7864

0.507 Kernel fit Pairwise Correlations Normal fit

Density 0.254

0.000 CEM 1

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

Pre-normalization Quantiles

liver-vehicle-1day-repliver-baclofen-1day-repliver-baclofen-1day-rep 1liver-vehicle-1day-rep (0.0249014)liver-baclofen-1day-rep 1 (0.038977)liver-vehicle-1day-rep 2 (0.0329688) 2liver-baclofen-1day-rep (0.0235249)liver-vehicle-5day-rep 3 (0.0379611) 3liver-baclofen-5day-rep (0.0266297)liver-vehicle-5day-rep 4 (0.0422357) 1liver-baclofen-5day-rep (0.0246096)liver-vehicle-5day-rep 1 (0.0258326) 2liver-baclofen-5day-rep (0.0238272)liver-vehicle-5day-rep 2 (0.0311309) 3liver-baclofen-5day-rep (0.0226551)liver-baclofen-5day-rep 3 (0.0289259) 4liver-baclofen-5day-rep (0.0250063)liver-baclofen-5day-rep 4 (0.0251572)liver-baclofen-5day-rep 5 (0.0264564)bone 6 (0.0231194) marrow-vehicle-1day-repbone 7 (0.0237872) marrow-baclofen-1day-repbone 8 (0.0207866) marrow-vehicle-1day-repbone marrow-baclofen-1day-repbone 1 (0.0192979) marrow-vehicle-1day-repbone 1 (0.00556452) marrow-baclofen-1day-repbone 2 (0.0080896) marrow-vehicle-1day-repbone 2 (0.00901058) marrow-baclofen-1day-repbone 3 (0.0130346) marrow-vehicle-5day-repbone 3 (0.00676578) marrow-baclofen-5day-repbone 4 (0.014055) marrow-vehicle-5day-repbone 4 (0.0134009) marrow-baclofen-5day-repbone 1 (0.0172654) marrow-vehicle-5day-repbone 1 (0.0107081) marrow-baclofen-5day-repbone 2 (0.00591446) marrow-vehicle-5day-repbone 2 (0.00713548) marrow-baclofen-5day-repbone 3 (0.00657209) marrow-baclofen-5day-repbone 3 (0.0138643) marrow-baclofen-5day-repbone 4 (0.00935903) marrow-baclofen-5day-repbone 4 (0.0115416) marrow-baclofen-5day-repspleen-vehicle-1day-rep 5 (0.00937139)spleen-baclofen-1day-rep 6 (0.00744012)spleen-vehicle-1day-rep 7 (0.00714847)spleen-baclofen-1day-rep 1 8 (0.0149608) (0.00471183)spleen-vehicle-1day-rep 1 (0.00705712)spleen-baclofen-1day-rep 2 (0.00936932)spleen-vehicle-1day-rep 2 (0.0104536)spleen-baclofen-1day-rep 3 (0.0294084)spleen-vehicle-5day-rep 3 (0.00920715)spleen-baclofen-5day-rep 4 (0.00807567)spleen-vehicle-5day-rep 4 (0.00851256)spleen-baclofen-5day-rep 1 (0.00634568)spleen-vehicle-5day-rep 1 (0.0150245)spleen-baclofen-5day-rep 2 (0.00857572)spleen-vehicle-5day-rep 2 (0.0269386)spleen-baclofen-5day-rep 3 (0.019237)spleen-baclofen-5day-rep 3 (0.00829145)spleen-baclofen-5day-rep 4 (0.00833727)spleen-baclofen-5day-rep 4 (0.0147413)spleen-baclofen-5day-rep 5 (0.0148559) 6 (0.018611) 7 (0.00915399) 8 (0.0240987)[ min ] [ medium ] [ max ] CEM 1 Snw1 818.2 1486.3 1738.7 P ( S | Z, I ) = 0.67 Ncor1 1642.3 2734.6 3666.2 Mean Corr = 0.68945 Glis3 25.7 51.0 122.3 Npat 99.2 478.1 729.5 Ski 437.6 712.5 1019.6 Epc2 482.5 1582.3 2076.7 Bdp1 642.8 1212.1 1744.0 Zfp26 323.1 1008.4 1412.5 Zbtb6 201.0 928.2 1269.7 Epc1 797.9 1902.5 2899.0 CEM 1 + Tnks2 1908.4 4621.2 7625.6 Top 10 Genes Phf20 203.5 494.7 928.8 Ep300 451.2 1962.4 2695.5 Arid4a 96.7 750.9 1130.5 Rbm27 504.6 1276.9 1531.3

Null module GEO Series "GSE17796" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 39 -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=GSE17796 Status: Public on Jan 11 2010 Title: Expression data from B6C3F1 mice treated with reduced oxygen Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice received decreasing oxygen concentrations from 21% to 6% O2 for ~ 30 minutes. Then, the mice remained an additional 120 minutes at 6% O2, control mice were placed insimilarchambers but recieved normal (21%) oxygen.

Overall design: Mice were euthanased by cervical dislocation under ketamine / acepromazine (100 mg/kg / 5 mg/kg, I.P) anesthesia. The bone marrow from the right humerus, a portion of the left lateral liver lobe and half a cross-section of the spleen were harvested and the RNA was isolated from these tissues using standard Qiagen reagents. Standard Affymetrix protocols were used for GeneChip probe preparations. 39 arrays.

Background corr dist: KL-Divergence = 0.0270, L1-Distance = 0.0739, L2-Distance = 0.0083, Normal std = 0.7950

0.502 Kernel fit Pairwise Correlations Normal fit

Density 0.251

0.000 CEM 1

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

Pre-normalization Quantiles

liver-vehicle-2hours-repliver-vehicle-2hours-repliver-vehicle-2hours-repliver-vehicle-2hours-rep 1 (0.0206536)liver-hypoxia-2hours-rep 2 (0.0159207)liver-hypoxia-2hours-rep 3 (0.0146919)liver-hypoxia-2hours-rep 4 (0.0272687)liver-hypoxia-2hours-rep 1 (0.0282317)liver-hypoxia-2hours-rep 2 (0.0204321)liver-hypoxia-2hours-rep 3 (0.0367642)liver-hypoxia-2hours-rep 4 (0.0350047)liver-hypoxia-2hours-rep 5 (0.0321087)liver-vehicle-2hours-rep 6 (0.0365984)liver-vehicle-2hours-rep 7 (0.0402672)liver-vehicle-2hours-rep 8 (0.0398321)liver-vehicle-2hours-rep 5 (0.0276003)bone 6 (0.036919) marrow-vehicle-2hours-repbone 7 (0.0352874) marrow-vehicle-2hours-repbone 8 (0.0338607) marrow-vehicle-2hours-repbone marrow-hypoxia-2hours-repbone 1 (0.0159417)marrow-hypoxia-2hours-repbone 2 (0.0228131)marrow-hypoxia-2hours-repbone 3 (0.0223851)marrow-hypoxia-2hours-repspleen-vehicle-2hours-rep 1 (0.0141276)spleen-vehicle-2hours-rep 2 (0.0164417)spleen-vehicle-2hours-rep 3 (0.0131667)spleen-vehicle-2hours-rep 41 (0.025655)(0.0149519)spleen-hypoxia-2hours-rep 2 (0.0144675)spleen-hypoxia-2hours-rep 3 (0.00880911)spleen-hypoxia-2hours-rep 4 (0.00889462)spleen-hypoxia-2hours-rep 1 (0.0168311)spleen-vehicle-2hours-rep 2 (0.0218015)spleen-hypoxia-2hours-rep 3 (0.0185982)spleen-hypoxia-2hours-rep 4 (0.074191)spleen-vehicle-2hours-rep 5 (0.0184689)spleen-vehicle-2hours-rep 7 (0.00531215)spleen-vehicle-2hours-rep 8 (0.00682711)spleen-hypoxia-2hours-rep 6 (0.0457379)spleen-hypoxia-2hours-rep 7 (0.0585049) 8 (0.0508427) 5 (0.0162037) 6 (0.00758545)[ min ] [ medium ] [ max ] CEM 1 Snw1 742.7 1293.7 1554.7 P ( S | Z, I ) = 0.56 Ncor1 1693.1 2511.6 3267.2 Mean Corr = 0.70898 Glis3 26.6 58.7 128.1 Npat 87.9 385.3 710.2 Ski 472.1 651.7 976.4 Epc2 528.8 1506.9 1883.8 Bdp1 580.6 860.7 1681.0 Zfp26 231.8 982.4 1460.1 Zbtb6 148.9 903.5 1132.6 Epc1 799.3 1836.6 2541.1 CEM 1 + Tnks2 2360.3 4366.1 7484.3 Top 10 Genes Phf20 240.6 494.5 829.7 Ep300 370.5 1720.0 2728.3 Arid4a 74.6 598.4 886.6 Rbm27 371.2 1217.7 1653.5

Null module GEO Series "GSE43620" 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=GSE43620 Status: Public on Jan 19 2014 Title: Effects of sodium tungstate administration in Irs2 -/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24253047 Summary & Design: Summary: Relative beta cell deficit and increased beta cell apoptosis are hallmarks of type 2 diabetes (T2D). The Insulin/Insulin Growth Factor (Igf) signaling pathway is an established regulator of beta cell survival and is found downregulated in human T2D islets. The Insulin Receptor Substrate 2 (Irs2) plays a central role in the coordination of this pathway in beta cells. Thus, Irs2 knockout mice (Irs2 -/-) exhibit increased beta cell apoptosis that leads to a progressive decline of beta cell mass and hyperglycaemia. In this study, we sought to determine whether the anti-diabetic compound sodium tungstate could prevent the onset of diabetes in Irs2 -/- mice. Oral administration of tungstate resulted in an overall improvement in whole-body glucose tolerance in Irs2 -/- mice which correlated with increased beta cell mass. Enhanced beta cell mass was due to a dramatic reduction of beta cell apoptosis without changes in proliferation. Whole genome gene profiling analysis of islets isolated from treated Irs2 -/- mice confirmed a broad impact of tungstate on cell death pathways. Mechanistically, tungstate induced Erk1/2 phosphorylation in islets in vitro and, in agreement, treated Irs2 -/- islets exhibited increased basal Erk1/2 phosphorylation. Tungstate also downregulated expression of apoptosis-related genes in Irs2-/- islets in vitro, uncovering a direct effect of this compound in islets. All together, our data demonstrate that tungstate can restore beta cell mass and glucose homeostasis in a context of deficient Insulin/Igf signaling. This study underscores the importance of developing strategies specifically designed to arrest beta cell apoptosis as a means to prevent progressive beta cell failure in diabetes.

Overall design: 10-week old WT and Irs2 -/- mice were randomly divided into two treatment group, in a total of 4 experimental groups. For 21 days one group received distilled water as drinking water (untreated group) whilst the other received ad libitum a solution of 2mg/ml of sodium tungstate in distilled water (treated group). For each experimental group 2 independent samples were analysed, in a total of 8 samples.

Background corr dist: KL-Divergence = 0.0481, L1-Distance = 0.0167, L2-Distance = 0.0003, Normal std = 0.5662

0.705 Kernel fit Pairwise Correlations Normal fit

Density 0.352

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 Control-rep1WT Control-rep2WT (0.173169) treated-rep1WT (0.084096) treated-rep2Irs2-/- (0.039583) Control-rep1Irs2-/- (0.188092) Control-rep2Irs2-/- (0.174518) treated-rep1Irs2-/- (0.180306) treated-rep2 (0.0970854) (0.0631507)[ min ] [ medium ] [ max ] CEM 1 Snw1 2153.3 2465.4 2601.4 P ( S | Z, I ) = 0.53 Ncor1 2702.1 3867.8 4197.1 Mean Corr = 0.65347 Glis3 943.3 1110.5 1176.7 Npat 644.8 810.5 1050.2 Ski 634.6 783.3 977.8 Epc2 1540.3 1624.9 2034.3 Bdp1 1154.3 1514.6 1607.2 Zfp26 754.5 1039.0 1191.6 Zbtb6 379.7 496.4 564.1 Epc1 1610.2 1920.1 2296.9 CEM 1 + Tnks2 4015.7 5231.3 5525.9 Top 10 Genes Phf20 672.7 781.5 887.6 Ep300 805.4 1212.7 1387.8 Arid4a 241.4 367.0 506.0 Rbm27 1263.5 1555.2 1742.6

Null module GEO Series "GSE22925" 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=GSE22925 Status: Public on Jul 14 2010 Title: Murine Bone Marrow Stromal Cell Response to Granulocyte Colony-Stimulating Factor Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20516641 Summary & Design: Summary: Neutrophil homeostasis is maintained, in part, by the regulated release of neutrophils from the bone marrow. Constitutive expression of the chemokine CXCL12 by bone marrow stromal cells provides a key retention signal for neutrophils in the bone marrow through activation of its receptor CXCR4. Herein, we show that the ELR chemokines CXCL1 and CXCL2 are constitutively expressed by bone marrow endothelial cells and osteoblasts, and CXCL2 expression is induced in endothelial cells during granulocyte colony-stimulating factor (G-CSF)-induced neutrophil mobilization. Neutrophils lacking CXCR2, the receptor for CXCL1 and CXCL2, are preferentially retained in the bone marrow, reproducing a myelokathexis phenotype. Transient disruption of CXCR4 failed to mobilize CXCR2 neutrophils. However, doubly deficient neutrophils (CXCR2-/- CXCR4-/-) displayed constitutive mobilization, showing that CXCR4 plays a dominant role. Collectively, these data suggest that CXCR2 signaling is a second chemokine axis that interacts antagonistically with CXCR4 to regulate neutrophil release from the bone marrow.

We used gene expression microarrays to determine the changes in osteoblasts and bone marrow endothelial cells after G-CSF treatment.

Overall design: 3 untreated and G-CSF-treated osteoblast samples and 4 untreated and G-CSF-treated endothelial samples.

Background corr dist: KL-Divergence = 0.1124, L1-Distance = 0.0289, L2-Distance = 0.0014, Normal std = 0.4248

0.939 Kernel fit Pairwise Correlations Normal fit

Density 0.470

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

pOBcol2.3-GFPpOBcol2.3-GFPpOBcol2.3-GFP cells, untreated,pOBcol2.3-GFP cells, untreated,pOBcol2.3-GFP cells, replicate untreated,pOBcol2.3-GFP cells, replicate 1 (0.170817)G-CSFCD31 cells, replicate 2 cells, (0.0213438)xG-CSFCD31 5cells, days, untreated,3 cells, (0.161063)xG-CSFCD31 5replicate days, untreated, cells, x CD31replicate 5replicate days,1 untreated,(0.111907) cells, CD31replicate replicate 1 2 (0.0830574) untreated,(0.0231429) cells, CD31replicate 2 3 (0.0473039) G-CSF(0.102727) cells, CD31replicate 3 (0.0127274)xG-CSF 5cells, CD31days, 4 (0.043347)xG-CSF 5cells,replicate days, xG-CSF 5replicate days,1 (0.0620372) x 5replicate days,2 (0.0665886) replicate [3 (0.0507573)min 4 (0.0431799) ] [ medium ] [ max ] CEM 1 Snw1 1792.8 2295.7 2747.3 P ( S | Z, I ) = 0.52 Ncor1 1143.5 2135.4 3969.6 Mean Corr = 0.45596 Glis3 54.1 122.9 643.8 Npat 251.4 372.6 831.2 Ski 972.0 1536.9 1952.5 Epc2 994.8 1525.8 2204.7 Bdp1 826.5 1155.1 2105.2 Zfp26 545.4 859.1 1384.6 Zbtb6 298.3 404.6 872.5 Epc1 1675.0 2226.8 2909.7 CEM 1 + Tnks2 3467.8 6842.5 10294.2 Top 10 Genes Phf20 663.4 935.3 1567.6 Ep300 591.5 1172.1 1614.6 Arid4a 206.2 477.0 1252.9 Rbm27 386.3 625.9 1154.6

Null module GEO Series "GSE10776" 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=GSE10776 Status: Public on Dec 31 2008 Title: Expression profiles of Embryonic stem cells derived from normal fertilization and parthenogenesis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: To identify the imprinting loci, we designed microarray analysis on the parthenogenetic embryonic stem cells and normal embryos. We could predict 217 imprinting domains associated with embryo development and maternal imprinting.

Keywords: Cell type comparison

Overall design: Five embryonic stem (ES) cell lines were derived from two F1 hybrid strains that were produced by mating female C57BL6 mice with male DBA2 or CBA/Ca mice. Two-week-old prepubertal female was used for follicle retrieval. All procedures for animal management, breeding, and surgery followed the standard protocols of Seoul National University, Korea. The Institutional Animal Care and Use Committee Review Board at Seoul National University approved our research proposal in April 2005 (approval number: SNU0050331-02). Three parthonogenetic ES embryo cell lines were established from parthenogenetic activation on naturally ovulated oocytes (OpB6D2-SNU-1) and in vitro-growth oocytes (FpB6CBA-SNU8 and FpB6D2-SNU2). Two normal ES embryo cell lines were derived from mating naturally ovulated female mice in estrus with male mice (NmB6D2-SNU-1) and purchased from ATCC. Detailed procedures, including establishment of ES cell lines can be found elsewhere (FpB6CBA-SNU8, FpB6D2-SNU2 and OpB6D2-SNU-1 for and NmB6D2-SNU-1 and OP1 for manuscript in preparation).

Background corr dist: KL-Divergence = 0.0921, L1-Distance = 0.0287, L2-Distance = 0.0011, Normal std = 0.4649

0.876 Kernel fit Pairwise Correlations Normal fit

Density 0.438

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 stemembryonic cells stem derivedembryonic cells stem derived embryonicfrom cells stem preantral derived embryonicfrom cells stem preantral derived embryonicfolliclefrom cells stem preantral derivedembryonicculturefolliclefrom cells stem preantral derivedembryoniccultureandfolliclefrom cells stem oocyte preantral derivedembryoniccultureandfolliclefrom cells stem parthenogenesisoocyte preantral derivedembryoniccultureandfolliclefrom cells stem parthenogenesisoocyte normal derivedembryoniccultureandfolliclefrom cells stem parthenogenesisoocyte normalfertilization ofderivedR1cultureandfrom cellsB6CBAF1 embryonicstem parthenogenesisoocyte normalfertilization of derivedR1andfrom cells B6CBAF1of embryonic parthenogenesisoocyte hybridfemaleparthenogeneticfertilization ofstemderived R1from B6CBAF1of embryonic parthenogenesismouse hybridC57BL6cellsfemaleparthenogenetic ofstem from B6D2F1of3 (0.0506464)mouse(0.185852) hybridC57BL6cellsfemale parthenogeneticand of stemblastocyst B6D2F1 male4hybrid 1mouse(0.204279)C57BL6cells and(0.0569741) of blastocyst DBA2 B6D2F1 mousemale5hybrid of 3(0.0735615) and(0.0791352)B6D2F1 mice[blastocyst DBA2 1mouseminmalehybrid of (0.0270357) 2 B6D2F1 (0.0317976)micehybrid DBA2 2mouse of (0.0247194) ]4 B6D2F1 (0.0440028)mousemicehybrid 3 (0.0642286) 3 (0.0463282)(0.0433075)mousehybrid[ medium 4mouse (0.0489151) 5 (0.0192162) ] [ max ] CEM 1 Snw1 2340.8 2538.4 2932.5 P ( S | Z, I ) = 0.48 Ncor1 905.0 1345.0 2540.8 Mean Corr = 0.54574 Glis3 38.5 46.9 65.8 Npat 494.4 670.2 921.0 Ski 971.3 1598.7 1971.2 Epc2 548.3 758.4 1385.9 Bdp1 565.8 973.0 1359.7 Zfp26 450.4 625.6 832.4 Zbtb6 143.3 253.1 416.4 Epc1 337.7 697.9 977.3 CEM 1 + Tnks2 6728.5 10058.9 13357.5 Top 10 Genes Phf20 706.1 1712.3 2689.8 Ep300 934.0 1287.5 2080.9 Arid4a 37.3 76.4 123.5 Rbm27 960.9 1666.9 2059.9

Null module 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, (0.0143597)sampleregeneration rep2 (0.0204347) sampleatregeneration T1, rep1 sampleatregeneration T1, (0.015041) rep2 sampleatregeneration T2, (0.0117495) rep1 sampleatregeneration T2, (0.00944523) rep2 sampleatregeneration T6, (0.0124346) rep1 sampleatregeneration T6, (0.0480641) rep2 sampleatregeneration T12, (0.0216483) samplerep1atregeneration T12, (0.0247634) samplerep2atregeneration T18, (0.0291197) samplerep1atregeneration T18, (0.0134363) samplerep2atregeneration T24, (0.0225566) samplerep1atregeneration T24, (0.0143365) samplerep2atregeneration T30, (0.0158516) samplerep1atregeneration T30, (0.0273023) samplerep2atregeneration T48, (0.0158826) samplerep1atdevelopmental T48, (0.0137218) samplerep2atdevelopmental T72, (0.114504) rep1at developmentalsample T72, (0.00467922) rep2 developmental sampleat T105,(0.0121498) developmental sampleat rep1 T105, (0.05632) developmental sampleat rep2 T115, (0.0945851) developmental sampleat rep1 T115, (0.0464408) developmental sampleat rep2 T125, (0.0624965) developmental sampleat rep1 T125, (0.0464187) developmental sampleat rep2 T135, (0.0397052) developmental sampleat rep1 T135, (0.0248727) developmental sampleat rep2 T145, (0.0572433) sampleat rep1 T145, (0.0268096) sampleat rep2 T165, (0.0327247) at rep1 T165, (0.0366563)[ rep2min (0.014246) ] [ medium ] [ max ] CEM 1 Snw1 290.3 497.5 1486.6 P ( S | Z, I ) = 0.48 Ncor1 368.8 667.5 1042.3 Mean Corr = 0.36845 Glis3 44.9 141.4 439.0 Npat 391.5 508.4 990.8 Ski 157.3 568.1 1526.1 Epc2 472.2 656.5 1327.9 Bdp1 437.7 690.1 1376.5 Zfp26 876.0 1157.5 1616.5 Zbtb6 216.0 329.4 604.1 Epc1 386.6 527.0 1221.2 CEM 1 + Tnks2 529.0 935.2 4953.4 Top 10 Genes Phf20 96.1 284.4 765.1 Ep300 400.7 741.3 1815.7 Arid4a 110.0 241.0 382.1 Rbm27 76.0 215.9 873.3

Null module GEO Series "GSE6526" 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=GSE6526 Status: Public on Mar 01 2007 Title: Expression time course data HEY2 KO and WT MASMC treated with PDGF Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17327490 Summary & Design: Summary: The cardiovascular restricted transcription factor CHF1/Hey2 has been previously shown to regulate the smooth muscle response to growth factors. To determine how CHF1/Hey2 affects the smooth muscle response to growth factors, we performed a genomic screen for transcripts that are differentially expressed in wild type and knockout smooth muscle cells after stimulation with platelet derived growth factor.

We screened 45101 probes representing more than 39,000 transcripts derived from at least 34,000 genes, at eight different time points. We analyzed the expression data utilizing an algorithm based on Bayesian statistics to derive the best polynomial clustering model to fit the expression data. We found that in a total of 9827 transcripts the normalized ratio of knockout to wild type expression diverged more than 3 fold from baseline in at least one time point, and these transcripts separated into 17 distinct clusters. Further analysis of each cluster revealed distinct alterations in gene expression patterns for immediate early genes, transcription factors, matrix metalloproteinases, signaling molecules and other molecules important in vascular biology.

Keywords: time course

Overall design: WT and Hey2 knockout mouse aortic smooth muscle cells were treated in parallel with PDGF and harvested at successive time points for RNA extraction and hybridization on Affymetrix microarrays. We sought to identify differentially expressed transcripts through Bayesian statistical methods that would explain the differential response to PDGF observed in vitro.

Background corr dist: KL-Divergence = 0.1370, L1-Distance = 0.0306, L2-Distance = 0.0015, Normal std = 0.3962

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

MASMC_Hey2_KO_PDGF_T0MASMC_Hey2_KO_PDGF_T120MASMC_Hey2_KO_PDGF_T15MASMC_Hey2_KO_PDGF_T180 (0.00675072)MASMC_Hey2_KO_PDGF_T240MASMC_Hey2_KO_PDGF_T30 (0.0622395)MASMC_Hey2_KO_PDGF_T480 (0.0280352)MASMC_Hey2_KO_PDGF_T60 (0.0438993)MASMC_WT_PDGF_T0 (0.131667)MASMC_WT_PDGF_T120 (0.00967153)MASMC_WT_PDGF_T15 (0.0294359)MASMC_WT_PDGF_T180 (0.00926998)(0.145352)MASMC_WT_PDGF_T240 (0.0395374)MASMC_WT_PDGF_T30 (0.16526)MASMC_WT_PDGF_T480 (0.0372294)MASMC_WT_PDGF_T60 (0.0907592) (0.061741) (0.04674) (0.0924113)[ min ] [ medium ] [ max ] CEM 1 Snw1 2199.6 2672.7 3207.1 P ( S | Z, I ) = 0.46 Ncor1 2505.7 2999.5 3978.4 Mean Corr = 0.27897 Glis3 310.3 437.1 1087.7 Npat 551.9 671.2 931.7 Ski 1375.2 1924.4 2329.6 Epc2 1591.1 2287.6 2711.3 Bdp1 1496.6 2264.5 3516.1 Zfp26 785.9 1065.2 1259.3 Zbtb6 720.5 1058.2 1283.3 Epc1 2109.2 2947.7 4039.3 CEM 1 + Tnks2 7078.2 8896.4 9985.4 Top 10 Genes Phf20 993.8 1733.0 2113.3 Ep300 1619.1 2193.9 3575.8 Arid4a 326.4 478.8 539.3 Rbm27 1467.7 1979.4 2747.0

Null module GEO Series "GSE35979" 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=GSE35979 Status: Public on Feb 23 2012 Title: Gene expression data from IL13-induced allergic airway inflammation of mice lungs Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22611474 Summary & Design: Summary: Asthma is a common chronic inflammatory airway condition with a strong genetic and inheritability component, as siblings and first-degree relatives of those with the disease are often affected.

For our studies, we used a well-characterized transgenic mouse model of allergic airway inflammation induced by IL13. In this model, IL13 is conditionally overexpressed in the mouse lung when treated with doxycycline. Upon IL13 induction, these mice showed inflammatory cell infiltration, pronounced emphysema, increased pulmonary compliance, lung volume enlargement, mucus metaplasia, and increased expression of matrix metalloproteinases and cathepsins in the lung. We performed gene expression microarray to examine the changes in gene expression during IL13-induced allergic airway inflammation.

Overall design: The CC10-rtTA-IL13 transgenic (TG) and wildtype (WT) mice were treated with doxycycline for seven days. Mice were euthanized and the left upper lobes from all mice were removed for RNA extraction using the TRIzol method.

Background corr dist: KL-Divergence = 0.0277, L1-Distance = 0.0161, L2-Distance = 0.0003, Normal std = 0.6879

0.583 Kernel fit Pairwise Correlations Normal fit

Density 0.291

0.000 CEM 1

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

Pre-normalization Quantiles

TG mouseTG lung,mouseWT biological lung,mouseWT biological lung,mouse rep1WT biological(0.30746) lung,mouse rep2WT biological(0.18669) lung,mouse rep1 biological(0.176527) lung, rep2 biological(0.146021) rep3 (0.0655585) rep4[ (0.117743)min ] [ medium ] [ max ] CEM 1 Snw1 2000.0 2310.5 2607.7 P ( S | Z, I ) = 0.42 Ncor1 2845.0 3463.9 3572.6 Mean Corr = 0.59670 Glis3 233.5 279.5 318.9 Npat 326.5 520.4 670.7 Ski 1383.8 1714.7 1827.7 Epc2 1799.2 2707.4 3018.3 Bdp1 1161.7 1628.7 1754.2 Zfp26 829.6 906.8 1216.1 Zbtb6 609.8 870.6 1031.0 Epc1 1662.5 2542.8 2979.9 CEM 1 + Tnks2 6419.7 7625.4 7845.8 Top 10 Genes Phf20 888.0 1049.1 1266.7 Ep300 1968.1 2747.7 2993.8 Arid4a 321.7 558.0 753.4 Rbm27 1164.9 1572.0 1932.2

Null module GEO Series "GSE21996" 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=GSE21996 Status: Public on Jan 23 2013 Title: Trpm4-induced gene expression changes in Th1 and Th2 cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20656926 Summary & Design: Summary: T helper cell subsets have unique calcium (Ca2+) signals when activated with identical stimuli. The regulation of these Ca2+ signals and their correlation to the biological function of each T cell subset remains unclear. Trpm4 is a Ca2+-activated cation channel that we found is expressed at higher levels in Th2 cells compared to Th1 cells. Inhibition of Trpm4 expression increased Ca2+ influx and oscillatory levels in Th2 cells and decreased influx and oscillations in Th1 cells. This inhibition of Trpm4 expression also significantly altered T cell cytokine production and motility. Our experiments revealed that decreasing Trpm4 levels divergently regulates nuclear localization of NFAT. Consistent with this, gene profiling did not show Trpm4 dependent transcriptional regulation and T-bet and GATA-3 levels remain identical. Thus, Trpm4 is expressed at different levels on T helper cells and plays a distinctive role in T cell function by differentially regulating Ca2+ signaling and NFAT localization.

T helper cell gene expression levels when Trpm4 is inhibited by siRNA or dominant negative Trpm4 construct.

Overall design: The ion channel Trpm4 was inhibited in Th1 or Th2 cells using either siRNA or a dominant negative Trpm4 retrovirus and changes in gene profiles were analyzed.

Background corr dist: KL-Divergence = 0.0803, L1-Distance = 0.0323, L2-Distance = 0.0020, Normal std = 0.4842

0.824 Kernel fit Pairwise Correlations Normal fit

Density 0.412

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

Th1 (0.182087)Th2 (0.0711583)Th1-Thy1Th1-Trpm4 siRNATh2-Thy1 (0.0725269) siRNATh2-Trpm4 siRNA (0.0741775)Th1 (0.0112897) siRNAvectorTh1 (0.015096) (12hr)DN Th1Trpm4 (0.0663365) vector Th1(12hr) (4hr)DN (0.0909101) Th2Trpm4 (0.128127) vector Th2(4hr) (12hr)DN (0.127341) Th2Trpm4 (0.0355557) vector Th2(12hr) (4hr)DN (0.0503256) Trpm4 (0.0474923) (4hr) (0.0275763)[ min ] [ medium ] [ max ] CEM 1 Snw1 1844.2 2196.2 2947.8 P ( S | Z, I ) = 0.34 Ncor1 1709.0 2410.9 3535.4 Mean Corr = 0.44100 Glis3 7.2 18.1 61.4 Npat 551.0 1133.0 1847.6 Ski 613.4 1602.7 2451.7 Epc2 893.1 1319.4 2700.8 Bdp1 1219.1 2021.0 3693.8 Zfp26 676.7 1038.8 2694.1 Zbtb6 309.2 730.1 1457.8 Epc1 904.9 1464.4 2083.4 CEM 1 + Tnks2 2029.2 3109.8 5732.5 Top 10 Genes Phf20 257.5 583.4 1269.6 Ep300 1486.8 2143.0 2766.9 Arid4a 440.5 1096.5 1771.9 Rbm27 1005.7 1341.1 1730.0

Null module GEO Series "GSE17462" 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=GSE17462 Status: Public on Aug 01 2009 Title: Expression data from Bmi1-overexpressing Ink4a-Arf-null hepatoblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Forced expression of Bmi1 accelerated the self-renewal of hepatic stem/progenitor cells and eventually induced their transformation in an in vivo transplant model. The Ink4a/Arf locus, which encodes a cyclin-dependent kinase inhibitor, p16Ink4a, and a tumor suppressor, p19Arf, is a pivotal target of Bmi1. Therefore, it would be of importance to understand the contribution of the Ink4a/Arf locus to Bmi1 oncogenic functions in cancer and search for as-yet-unknown Bmi1 target genes other than Ink4a/Arf. We used microarrays to explore novel candidate downstream targets for Bmi1 in hepatic stem/progenitor cells

Overall design: Purified Dlk-positive hepatoblasts at day 28 of culture were subjected to RNA extraction and hybridization on Affymetrix microarrays. Data were obtained for quadrant samples from four independent experiments.

Background corr dist: KL-Divergence = 0.0597, L1-Distance = 0.0375, L2-Distance = 0.0025, Normal std = 0.5470

0.741 Kernel fit Pairwise Correlations Normal fit

Density 0.370

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

DKO, HB-Control,DKO, HB-Control,DKO, rep1 HB-Bmi1,DKO, (0.215473) rep2 HB-Bmi1,DKO, (0.010285)rep1 HB-Control,(0.100145)DKO, rep2 HB-Control,(0.0938213)DKO, rep3 HB-Bmi1,DKO, (0.0284572) rep4 HB-Bmi1, (0.26476)rep3 (0.156396) rep4 (0.130662)[ min ] [ medium ] [ max ] CEM 1 Snw1 1751.8 2728.1 3259.8 P ( S | Z, I ) = 0.32 Ncor1 1271.9 2030.9 2310.8 Mean Corr = 0.39296 Glis3 396.9 968.9 1254.3 Npat 495.4 850.7 1460.3 Ski 534.8 664.2 886.8 Epc2 780.9 1622.0 2664.8 Bdp1 639.9 1171.1 2092.1 Zfp26 698.7 1011.0 2038.8 Zbtb6 433.2 666.3 1109.3 Epc1 1246.5 1939.9 3029.8 CEM 1 + Tnks2 9708.8 12305.5 12620.5 Top 10 Genes Phf20 1566.5 1986.8 2164.8 Ep300 681.8 919.4 1048.2 Arid4a 53.1 175.4 430.3 Rbm27 469.9 669.8 1280.4

Null module GEO Series "GSE43928" 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=GSE43928 Status: Public on Sep 11 2013 Title: Expression data from TNF-stimulated mouse glomeruli Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23869211 Summary & Design: Summary: The specific contribution of the two TNF-receptors Tnfr1 and Tnfr2 to TNF-induced inflammation in the glomerulus is unknown. In mice, TNF exposure induces glomerular expression of inflammatory mediators like adhesion molecules and chemokines in vivo, and glomerular accumulation of leukocytes.

To examine Tnfr-specific inflammatory responses in intrinsic glomerular cells but not infiltrating leukocytes we performed microarray gene expression profiling on intact glomeruli isolated from wild-type and Tnfr-deficient mice following TNF exposure in vitro.

Overall design: Glomeruli were isolated from male C57BL/6J wild-type and Tnfr-deficient mice applying a magnetic bead-based isolation technique. Isolated intact glomeruli were stimulated with TNF for 12 hours in vitro for subsequent RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0686, L1-Distance = 0.0204, L2-Distance = 0.0006, Normal std = 0.5034

0.792 Kernel fit Pairwise Correlations Normal fit

Density 0.396

0.000 CEM 1

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

Pre-normalization Quantiles

Wild-typeWild-type glomeruli,Wild-type glomeruli, TNF-stimulated,Tnfr1/Tnfr2-deficient glomeruli, TNF-stimulated,Tnfr1/Tnfr2-deficient TNF-stimulated, rep1Tnfr1/Tnfr2-deficient (0.043239) glomeruli, rep2Tnfr1-deficient (0.0660749) glomeruli, rep3Tnfr1-deficient TNF-stimulated, (0.0431654) glomeruli, Tnfr1-deficientglomeruli, TNF-stimulated, Tnfr2-deficientglomeruli, TNF-stimulated, TNF-stimulated,rep1 Tnfr2-deficientglomeruli, (0.051267) TNF-stimulated,rep2 Tnfr2-deficientglomeruli, (0.0387634) TNF-stimulated,rep3 rep1 glomeruli, (0.387565) (0.0980171) TNF-stimulated, rep2 glomeruli, (0.0787218) TNF-stimulated, rep3 (0.0480385) TNF-stimulated, rep1[ (0.0362574)min rep2 (0.0923955) ]rep3 (0.0164946)[ medium ] [ max ] CEM 1 Snw1 2566.5 3263.9 4608.1 P ( S | Z, I ) = 0.31 Ncor1 2989.6 4175.3 5940.5 Mean Corr = 0.39545 Glis3 271.4 373.2 667.7 Npat 425.8 539.8 1202.6 Ski 1469.3 2092.1 3168.3 Epc2 1038.9 1176.4 1596.9 Bdp1 1205.5 1460.3 2297.5 Zfp26 760.4 991.8 1893.0 Zbtb6 645.8 750.5 1000.7 Epc1 1693.0 2690.9 3581.4 CEM 1 + Tnks2 6300.4 7643.3 8494.1 Top 10 Genes Phf20 1005.5 1309.6 1621.8 Ep300 1272.5 1842.4 2652.5 Arid4a 223.1 323.8 773.2 Rbm27 835.7 1049.5 1195.9

Null module GEO Series "GSE40939" 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=GSE40939 Status: Public on Dec 21 2012 Title: Leukemogenesis by CDX2 involves KLF4 repression and deregulated PPARgamma signaling. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23202735 Summary & Design: Summary: Aberrant expression of the homeodomain transcription factor CDX2 occurs in most cases of acute myeloid leukemia (AML) and promotes leukemogenesis, making CDX2, in principle, an attractive therapeutic target. Conversely, CDX2 acts as a tumor suppressor in colonic epithelium. The effectors mediating the leukemogenic activity of CDX2 and the mechanism underlying its context-dependent properties are poorly characterized, and strategies for interfering with CDX2 function in AML remain elusive. We report data implicating repression of the transcription factor KLF4 as important for the oncogenic activity of CDX2, and demonstrate that CDX2 differentially regulates KLF4 in AML versus colon cancer cells through a mechanism that involves tissue-specific patterns of promoter binding and epigenetic modifications. Furthermore, we identified deregulation of the PPARÎ³ signaling pathway as a feature of AML expressing CDX2, and observed that PPARÎ³ agonists derepress KLF4 and are preferentially toxic to CDX2-positive leukemic cells. These data delineate transcriptional programs associated with CDX2 expression in hematopoietic cells; provide insight into the antagonistic duality of CDX2 function in AML versus colon cancer; and suggest reactivation of KLF4 expression, through modulation of PPARÎ³ signaling, as a new therapeutic modality in a large proportion of AML patients.

Overall design: Experiment 2 (Samples 7-10): The transcriptional changes induced by Cdx2 were assessed in vivo in Cdx2-initiated murine leukemias and compared with those of leukemias initiated by 5 different MLL fusion oncogenes (previously published data, available at GSE13690). Bone marrow cells isolated from C57BL/6 mice were transduced with pMSCV-Cdx2-IRES-GFP, and 8x10e5 GFP-positive cells were injected into lethally irradiated syngeneic recipient mice after 48 hours, followed by injection of 1x10e6 spleen cells from primary leukemic animals into sublethally irradiated secondary recipients. Spleen cells from secondary leukemic animals were harvested.

Background corr dist: KL-Divergence = 0.0204, L1-Distance = 0.0686, L2-Distance = 0.0061, Normal std = 0.8753

0.456 Kernel fit Pairwise Correlations Normal fit

Density 0.228

0.000 CEM 1

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

Pre-normalization Quantiles

control controlrep1 (0.0848649) controlrep2 (0.0491981) murinerep3 (0.099161) murineCdx2 rep1 murineCdx2 (0.0521035) rep2 Cdx2 (0.0298464) inducedrep3Cdx2 (0.0202553) induced leukemia_secondary_rep1Cdx2 induced leukemia_secondary_rep2Cdx2 induced leukemia_primary leukemia_primary (0.199327) rep1 (0.116496) [(0.292428) minrep2 (0.0563199) ] [ medium ] [ max ] CEM 1 Snw1 1676.1 2208.2 3263.6 P ( S | Z, I ) = 0.18 Ncor1 2955.5 3321.7 4030.1 Mean Corr = 0.68585 Glis3 120.7 275.4 1250.0 Npat 520.4 588.4 928.2 Ski 815.0 1104.0 2061.5 Epc2 955.6 1098.0 1557.0 Bdp1 1219.8 1425.1 1839.5 Zfp26 634.6 901.0 1221.6 Zbtb6 413.3 589.5 745.5 Epc1 646.5 830.7 2283.1 CEM 1 + Tnks2 3458.7 3946.7 4769.5 Top 10 Genes Phf20 391.3 665.3 720.2 Ep300 1434.1 1720.2 2067.7 Arid4a 436.9 613.1 802.0 Rbm27 1094.3 1377.1 1764.8

Null module GEO Series "GSE45941" 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=GSE45941 Status: Public on Jan 30 2014 Title: Transcription factor TFAP2C regulates major programs required for murine fetal germ cell maintenance and haploinsufficiency predisposes to teratomas in male mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23967156 Summary & Design: Summary: Maintenance and maturation of primordial germ cells is controlled by complex genetic and epigenetic cascades, and disturbances in this network lead to either infertility or malignant aberration. Transcription factor Tcfap2c / TFAP2C has been described to be essential for primordial germ cell maintenance and to be upregulated in several human germ cell cancers. Using global gene expression profiling, we identified genes deregulated upon loss of Tcfap2c in primordial germ cell-like cells. We show that loss of Tcfap2c affects many aspects of the genetic network regulating germ cell biology, such as downregulation maturation markers and induction of markers indicative of somatic differentiation, cell cycle, epigenetic remodeling, and pluripotency associated genes. Chromatin-immunoprecipitation analyses demonstrated binding of Tcfap2c to regulatory regions of deregulated genes (Sfrp1, Dmrt1, Nanos3, c-Kit, Cdk6, Cdkn1a, Fgf4, Klf4, Dnmt3b and Dnmt3l) suggesting that these genes are direct transcriptional targets of Tcfap2c in primordial germ cells. Since Tcfap2c deficient primordial germ cell like cells display cancer related deregulations in epigenetic remodeling, cell cycle and pluripotency control, the Tcfap2c-knockout allele was bred onto 129S2/Sv genetic background. There, mice heterozygous for Tcfap2c develop germ cell cancer with high incidence. Precursor lesions can be observed as early as E16.5 in developing testes displaying persisting expression of pluripotency markers. We further demonstrate, that mice with a heterozygous deletion of the Tcfap2c target gene Nanos3 are also prone to develop teratoma. These data highlight Tcfap2c as a critical and dose-sensitive regulator of germ cell fate.

Overall design: KO PGC: Tcfap2c knock-out mouse primordial germ cells (PGCs), 2 biological rep

Background corr dist: KL-Divergence = 0.0560, L1-Distance = 0.0176, L2-Distance = 0.0004, Normal std = 0.5390

0.740 Kernel fit Pairwise Correlations Normal fit

Density 0.370

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 ESCCtrl rep1 ESC (0.0386111)KO rep2 ESC (0.266143)KO rep1 ESC (0.127744)Ctrl rep2 PGC (0.029078)Ctrl rep1 PGC (0.102439)KO rep2 PGC (0.20999)KO rep1 PGC (0.0753677) rep2 (0.150628) [ min ] [ medium ] [ max ] CEM 1 Snw1 2452.3 2870.6 3103.8 P ( S | Z, I ) = 0.17 Ncor1 2318.7 3330.0 4432.3 Mean Corr = 0.56370 Glis3 91.8 143.2 644.4 Npat 1672.1 1965.4 2301.8 Ski 756.0 1276.9 1348.3 Epc2 1641.7 2090.6 2557.1 Bdp1 1439.0 1698.2 2110.8 Zfp26 1322.8 1749.1 2072.3 Zbtb6 520.9 607.2 700.2 Epc1 1074.7 1697.8 1891.7 CEM 1 + Tnks2 11243.8 13432.7 16563.3 Top 10 Genes Phf20 2133.9 2782.3 3193.3 Ep300 1363.5 2758.4 3585.9 Arid4a 433.4 475.4 630.7 Rbm27 2648.9 3104.1 3596.1

Null module GEO Series "GSE55622" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 22 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55622 Status: Public on Jun 26 2014 Title: Cytoplasmic YAP and TAZ are intrinsic components of the b-catenin destruction complex Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: To investigate the role of YAP/TAZ as b-catenin inhibitors, we compared the expression profiles of Rex1GFPd2 ES cells transfected with siControl#1, siControl#2, siYAP/TAZ#1, siYAP/TAZ#2 and cultured in 2i medium or PD-only medium

Overall design: We collected RNA from Rex1GFPd2 embryonic stem (ES) cells transfected with siControl#1, siControl#2, siYAP/TAZ#1, siYAP/TAZ#2. Cells were maintained in 2i medium (2i=PD0325901+CHIR99021) or switched to PD (PD0325901)-only medium after 24 hours from siRNA transfection. Cells were harvested 72 hours post-siRNA transfection. Samples were then processed for total RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0811, L1-Distance = 0.0749, L2-Distance = 0.0091, Normal std = 0.5416

0.851 Kernel fit Pairwise Correlations Normal fit

Density 0.425

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

Rex1GFPd2Rex1GFPd2 ESRex1GFPd2 cells ES siControl#1Rex1GFPd2 cells ES siControl#1Rex1GFPd2 cells in ES 2isiControl#1Rex1GFPd2 medium,cells in ES 2isiContro#1Rex1GFPd2 medium,cells biological in ES 2isiControl#2Rex1GFPd2 medium,cells biologicalin ES2ireplicate siControl#2 Rex1GFPd2medium, cells biological in ES replicate2isiControl#2 Rex1GFPd2 Amedium,cells biological (0.056125) in ES replicate2isiControl#1 Rex1GFPd2 Bmedium,cells biological(0.0334735) in ESreplicate 2isiControl#1 Rex1GFPd2 Cmedium,cells biological(0.0517301) in ES replicatePD-onlysiControl#1 DRex1GFPd2 cells (0.0609563)biological in ES replicatePD-onlysiControl#1 medium, Rex1GFPd2 Acells (0.0412767) in ES replicatePD-onlysiControl#2 medium, Rex1GFPd2 B cellsbiological (0.0538655) in ES PD-onlysiControl#2 medium, Rex1GFPd2 C cellsbiological (0.0868584) in replicate ES PD-onlysiControl#2 medium,Rex1GFPd2 cellsbiological in replicate ES PD-only siYAP/TAZ#1Amedium,Rex1GFPd2 cellsbiological(0.0503853) in replicate ES PD-only siYAP/TAZ#1Bmedium,Rex1GFPd2 cellsbiological(0.0497081) replicate ESin siYAP/TAZ#1C medium,PD-onlyRex1GFPd2 cellsbiological(0.0877995) replicate ESin siYAP/TAZ#1D PD-onlyRex1GFPd2 cellsmedium,biological(0.0641835) replicate ESin siYAP/TAZ#2A PD-onlyRex1GFPd2 cellsmedium,(0.0621776) biological replicate ESin siYAP/TAZ#2B PD-only cellsmedium,(0.0819781) biological ESin replicate siYAP/TAZ#2C PD-only cellsmedium,(0.0979909) biological in replicatesiYAP/TAZ#2 PD-only Amedium, biological(0.0301155) in replicate PD-only[ Bmedium, minbiological(0.013017) in replicate PD-only Cmedium, biological(0.0128411) ] replicate Dmedium, biological(0.0175874) replicate A biological(0.0180606)[ mediumreplicate B (0.00483251) replicate C (0.0119581) D] (0.0130791) [ max ] CEM 1 Snw1 2740.9 2926.7 3466.4 P ( S | Z, I ) = 0.17 Ncor1 3282.1 3895.8 4380.4 Mean Corr = 0.11719 Glis3 146.1 365.0 439.4 Npat 1448.7 1717.4 1923.1 Ski 739.9 838.4 1084.7 Epc2 1795.9 2070.9 2610.2 Bdp1 1630.5 1753.5 1855.6 Zfp26 870.1 1391.3 1674.2 Zbtb6 484.3 553.0 611.8 Epc1 1031.4 1426.7 1674.2 CEM 1 + Tnks2 11256.7 11915.1 12517.8 Top 10 Genes Phf20 2915.7 3286.3 4302.9 Ep300 2021.3 2238.8 2360.8 Arid4a 533.9 713.5 830.9 Rbm27 2591.6 3417.7 3842.1

Null module GEO Series "GSE51365" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 28 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51365 Status: Public on Oct 18 2013 Title: Latent gammaherpesvirus 68 infection induces distinct transcriptional changes in different organs Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24155394 Summary & Design: Summary: Previous studies identified a role for latent herpesvirus infection in cross-protection to infection and exacerbation of chronic inflammatory diseases. Here, we compared the gene expression signature from livers, spleens and brains of mice infected with wild-type gammaherpesvirus 68 (MHV68), a mutant virus defective in the establishment of latency (ORF73.stop) or mockulum. We identified over 600 genes differentially expressed in organs of mice latently infected with MHV68 and found distinct sets of genes linked to different pathways were altered in spleen compared to liver. Several of the most differentially expressed latency-specific genes (e.g. IFNÎ³, Cxcl9, Ccl5) are associated with known latency-specific phenotypes.

Overall design: RNA was extracted from livers, spleens and brains of 7-9 week old male C57Bl/6 mice infected with gammaherpesvirus 68 (MHV68), a virus defective in establishment of latency (ORF73.stop) or mockulum. RNA from 3-4 mice per treatment was pooled and analyzed by M430 2.0 Affymetrix Gene Chip. Three biologic replicates were analyzed for all conditions, except mock livers, for which four biologic replicates were analyzed.

Background corr dist: KL-Divergence = 0.0674, L1-Distance = 0.0734, L2-Distance = 0.0082, Normal std = 0.6075

0.657 Kernel fit Pairwise Correlations Normal fit

Density 0.328

0.000 CEM 1

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

Pre-normalization Quantiles

Null module GEO Series "GSE46094" 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=GSE46094 Status: Public on May 01 2014 Title: Expression data from PML-RARÎ± transgenic mouse APL(acute promyelocyte leukemia) cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: The differentiation of leukemia stem cells (LSCs) is generally regarded as a one-way alterative process to self-renewal. However, how differentiation impacts LSC stemness has largely been unexplored. Here we show that before reaching terminal differentiation (TD), apical LSCs of mouse acute promyelocytic leukemia passed through a partial differentiation (PD) stage, wherein the leukemia cells re-initiated leukemia via de-differentiation albeit at a reduced rate. Notably, while retinoic acid (RA) preferentially drove the transition of LSC to PD, monocytic Irf8 skewed PD cells to terminal maturation over de-differentiation and/or expansion. Remarkably, the combined use of RA and Irf8 induction depleted the total leukemogenic potential, which indicates that discrete stage- or lineage-specific mechanisms elaborate a step-wise LSC differentiation.

We used microarrays to detail the global programme of gene expression indicating the molecular mechanisms unerlying the the process of LSC step-wise differentiation.

Overall design: Retroviral GFP-labled mouse APL cells (bone marrow sample) were repopulated in vivo through transplantation into syngenic recipients. At the proper time points, the GFP positive APL bone marrow cells were collected and sorted for UNSC, UNPD and UNTD samples through FACS. RA-PD and RA-TD cells were sorted from bone marrow tissue treated with ATRA (all trans retinoic acid) for 5 days. The freshly isolated samples were then lysed for RNA extration. Each sample had two biological replicates.

Background corr dist: KL-Divergence = 0.0755, L1-Distance = 0.0335, L2-Distance = 0.0016, Normal std = 0.5022

0.816 Kernel fit Pairwise Correlations Normal fit

Density 0.408

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

APL SCAPL subset, SCAPL subset,biological PDAPL subset,biological rep1PDAPL subset, biological(0.143257) rep2RAPDAPL biological(0.128118) subset, rep1RAPDAPL (0.243745) subset, rep2biologicalTDAPL subset, (0.128038) biologicalTD rep1APL subset,biological RATD(0.0402097) rep2APL biological subset, rep1RATD(0.0800622) (0.0345737) subset,rep2biological (0.0333412) biological rep1 (0.0341825) rep2[ min (0.134473) ] [ medium ] [ max ] CEM 1 Snw1 1115.1 2062.8 2237.5 P ( S | Z, I ) = 0.14 Ncor1 926.3 3489.3 4623.9 Mean Corr = 0.42211 Glis3 241.0 352.8 526.0 Npat 186.1 588.7 800.5 Ski 313.7 753.1 1145.5 Epc2 301.4 1252.5 1646.4 Bdp1 230.3 1505.4 1915.6 Zfp26 210.7 591.7 771.0 Zbtb6 112.2 448.7 514.6 Epc1 642.5 767.7 871.8 CEM 1 + Tnks2 1233.6 3345.7 3798.9 Top 10 Genes Phf20 306.4 540.1 731.3 Ep300 821.0 2965.5 4644.3 Arid4a 95.4 681.6 940.2 Rbm27 329.4 1196.6 1335.3

Null module GEO Series "GSE21755" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 25 -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=GSE21755 Status: Public on Jul 30 2010 Title: Rapamycin effect on Wild Type and TSC deficient Mouse Embryonic Fibroblasts : Time Course Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20670887 Summary & Design: Summary: Aberrant activation of the mammalian target of rapamycin (mTOR) complex 1 (mTORC1) is a common molecular event in a large variety of pathological settings, including genetic tumor syndromes, cancer, and obesity. However, the cell intrinsic consequences of mTORC1 activation remain poorly defined. Here, we identify global trancriptional changes in TSC1 and TSC2 null MEFs, which exhibit constitutive activation of mTORC1, compared to wild-type littermate control lines. A rapamycin time course is included to determine those changes that are dependent on mTORC1 signaling, revealing mTORC1 induced and repressed transcripts.

In order to identify mTORC1-dependent transcriptional changes, we compared wild-type MEFs to both Tsc1-/- and Tsc2-/- MEFs following serum starvation, where mTORC1 signaling is off in wild-type cells and fully active in TSC-deficient cells. All cell lines were serum-starved for 24 h, and the Tsc1-/- and Tsc2-/- cells were treated with a time course of rapamycin prior to the isolation of mRNA for microarray analysis.

Overall design: Immortalized wild-type (Tsc2+/+ p53-/-), Tsc1-/- (p53+/+, 3T3-immortalized), and Tsc2-/- (p53-/-, derived from a littermate of the wild-type cell line) MEFs are the three cell lines used in this study and were derived in the laboratory of David J. Kwiatkowski (Brigham and Women's Hospital, Harvard Medical School, Boston, MA). Wild-type and null MEFs were grown to 70% confluence in 10 cm plates and were serum starved for 24 h in the presence of vehicle (DMSO) for 24 h or rapamycin (20 nM) for 2, 6, 12, or 24 h. All vehicle-treated samples (0 h time points) were plated in triplicate and all rapamycin time course samples were plated in duplicate. For each replicate, expression analysis was performed by hybridization to an Affymetrix Mouse 430_2 oligonucleotide microarray chip.

Background corr dist: KL-Divergence = 0.1004, L1-Distance = 0.0271, L2-Distance = 0.0010, Normal std = 0.4442

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

TSC2+/+TSC2+/+ p53-/-,TSC2+/+ biological p53-/-,TSC2-/- biological p53-/-, replicate TSC2-/- p53-/-,biological replicate 1, biological TSC2-/-p53-/-,no treatmentreplicate 2, biological TSC1-/-,p53-/-,no replicate treatment 3, (0.0426889) biological TSC1-/-, nobiological replicate treatment 1, (0.0281596)noTSC1-/-, biological treatmentreplicate replicate2, (0.0307732)noTSC2-/- biological treatment replicate3, (0.0439821)1, no TSC2-/-p53-/-,no treatment treatmentreplicate (0.0486066)2, biological TSC1-/-,p53-/-,no treatment (0.0548459)3, (0.00484402) biologicalTSC1-/-, nobiological replicate treatment (0.0043457)TSC2-/- biological replicate replicate1, (0.00457)treated, TSC2-/-p53-/-, replicate2, 1, treated, biologicalTCS1-/-, timep53-/-,treated, course 2, biologicalTSC1-/-, time treated, biologicaltime replicate course24 courseTSC2-/- hours biologicaltime replicate replicate1, 24 course24treated,(0.0362639) TSC2-/-p53-/-,hours hours replicate2, 1, 24 treated, (0.0176521)biologicalTSC1-/-, timep53-/-,treated,(0.0853335) hours course 2, biologicalTSC1-/-, time treated, (0.192765)biologicaltime replicate course12 courseTSC2-/- hours biologicaltime replicate replicate1, 12 course12treated,(0.0116005) TSC2-/-p53-/-,hours hours replicate2, 1, 12 treated, (0.00962402)biologicalTSC1-/-, timep53-/-,treated,(0.0624337) hours course 2, biologicalTSC1-/-, time treated, (0.0797003)biologicaltime replicate course6 coursehours biologicaltime replicate replicate1, 6 (0.0133887) course6treated,hours hours replicate2, 1, (0.0211402) 6treated, (0.0253285) timetreated,hours course 2, (0.0319835)[ timetreated, time min course2 coursehours time ] 2 (0.0530327) course2hours hours (0.0577241)2 (0.0131801) hours[ medium (0.0260335) ] [ max ] CEM 1 Snw1 1682.7 2121.3 2657.4 P ( S | Z, I ) = 0.12 Ncor1 1446.4 2132.9 2681.6 Mean Corr = 0.57092 Glis3 50.4 106.9 551.5 Npat 379.4 555.5 849.8 Ski 509.0 962.5 1707.5 Epc2 590.2 983.8 1475.4 Bdp1 469.6 548.9 794.0 Zfp26 449.9 684.3 969.6 Zbtb6 352.7 476.2 665.8 Epc1 887.7 1334.5 2385.7 CEM 1 + Tnks2 5824.0 6263.6 7572.5 Top 10 Genes Phf20 991.0 1259.5 1407.7 Ep300 719.5 882.0 1258.1 Arid4a 34.9 69.5 124.8 Rbm27 468.7 619.6 1232.8

Null module GEO Series "GSE4734" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 61 -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=GSE4734 Status: Public on Mar 05 2007 Title: Mouse brain region gene expression (430 2.0 Array) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17324278 Summary & Design: Summary: Gene expression patterns were determined from five brain regions (bed nucleus of the stria terminalis, hippocampus, hypothalamus, periaqueductal gray, and pituitary gland) in six mouse strains (129S6/SvEvTac, A/J, C57BL/6J, C3H/HeJ, DBA/2J, and FVB/NJ). At least two replicate samples per brain region/strain were analyzed using Affymetrix Mouse Genome 430 2.0 arrays.

Keywords: mouse strain and brain region comparison

Overall design: six mouse strains and five brain regions were analyzed

Background corr dist: KL-Divergence = 0.1388, L1-Distance = 0.0659, L2-Distance = 0.0086, Normal std = 0.4122

1.079 Kernel fit Pairwise Correlations Normal fit

Density 0.539

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

129S6/SvEvTac129S6/SvEvTacA/J bed bed nucleusA/J nucleusbed bed nucleus ofC57BL/6J nucleus theof the stria ofC57BL/6J stria theof bedterminalis the striaterminalis nucleusC3H/HeJ stria bedterminalis terminalisrep1 nucleusC3H/HeJ of rep1bed the(430 rep2nucleus(430 striaC3H/HeJ of 2.0 rep2bed the(4302.0 Array)terminalis nucleus(430 striaofArray)DBA/2J 2.0 bedthe 2.0(0.00312637) Array)terminalis strianucleus(0.00516052) ofArray)DBA/2J rep1bed the terminalis(0.00564026) nucleus(430 stria(0.0118535) ofFVB/NJ rep2bed the2.0 terminalis nucleus(430 ofstriaArray) rep1FVB/NJ bedthe 2.0 terminalis (430 strianucleus (0.0114195)ofArray) rep2129S6/SvEvTac bed the2.0 terminalis (430 strianucleusArray) (0.00430113)of rep3129S6/SvEvTac the2.0 terminalis (430(0.0042413) stria Array) rep1ofA/J hippocampusthe2.0 terminalis (430 hippocampus (0.00478007) stria Array)rep2 A/J2.0 hippocampus terminalis (430 hippocampus Array)(0.00510854) rep1 C57BL/6Jrep12.0 (430rep1(0.0017989) Array) (430rep2 C57BL/6J rep22.0(430 hippocampus2.0(430rep2(0.00151236) Array) (4302.0 Array) C3H/HeJ2.0(430 Array) hippocampus 2.0(0.00378857) Array) 2.0(0.0451527) Array)C3H/HeJ (0.0108847) Array)hippocampusrep1 (0.00734994) (0.0371512) (430DBA/2J (0.00461652) hippocampusrep2 2.0 (430 DBA/2JArray) hippocampusrep1 2.0 (430 (0.00752473) FVB/NJArray) hippocampusrep2 2.0 (430 Array)(0.0156044)FVB/NJrep1 hippocampus 2.0 (430 (0.00658336) Array)129S6/SvEvTacrep2 hippocampus 2.0 (430 Array)(0.0374325) 129S6/SvEvTacrep1 2.0 (430(0.0133021) Array) A/Jrep2 hypothalamus 2.0 hypothalamus (430(0.00982164) Array)A/J hypothalamus 2.0 hypothalamus (0.0202426) Array)C57BL/6J rep1 rep1 (0.012919) (430C57BL/6J rep2(430 hypothalamus 2.0rep2 (4302.0 Array)C3H/HeJ (430 Array)hypothalamus 2.0 2.0(0.00265479) Array)C3H/HeJ (0.00471862) hypothalamus Array)rep1 (0.0167522) DBA/2J(430 (0.00592168)hypothalamus rep2 2.0 DBA/2J (430 hypothalamusArray) rep1 2.0 (430 FVB/NJ(0.00508796) hypothalamusArray) rep2 2.0 (430 FVB/NJ Array)(0.00458249)rep1hypothalamus 2.0 (430 (0.00440798) 129S6/SvEvTac Array)rep2hypothalamus 2.0 (430 Array)(0.00262371)129S6/SvEvTac rep1 2.0 (430(0.00888825) Array)A/J rep2periaqueductal 2.0 periaqueductal (430(0.00242358) Array)A/J periaqueductal 2.0 periaqueductal (0.00649385) Array)C57BL/6J gray gray (0.00610231) rep1C57BL/6J grayrep1 periaqueductal (430gray rep2(430C3H/HeJ 2.0rep2 periaqueductal (4302.0 Array) (430 C3H/HeJArray) 2.0periaqueductal gray 2.0(0.0217131) Array) (0.016917) DBA/2J Array)rep1 periaqueductal gray (0.0215893) (430 (0.0102578)DBA/2J periaqueductalrep2 gray 2.0 (430 Array) FVB/NJ rep1periaqueductal gray 2.0 (430 (0.011067) Array) FVB/NJ rep2periaqueductal gray 2.0 (430 Array)(0.00850245)rep1129S6/SvEvTac periaqueductal gray 2.0 (430 (0.0178077) Array)rep2129S6/SvEvTac 2.0gray (430 Array)(0.0112497) rep1A/J pituitary2.0gray pituitary(430(0.00615127) Array) rep2A/J pituitary2.0 gland pituitary(430(0.0115732) Array)glandC57BL/6J 2.0rep1 gland rep1(0.00808316) Array)gland (430C57BL/6J rep2(430 pituitary 2.0rep2(0.0152625) (4302.0 Array)C3H/HeJ (430 Array)pituitary 2.0gland 2.0(0.0172228) Array)C3H/HeJ pituitary(0.028507) Array)rep1 gland (0.017981) DBA/2J(430 pituitary(0.0229986) rep2gland 2.0 DBA/2J(430pituitary Array) rep1 gland 2.0 (430FVB/NJ pituitary(0.0301807) Array) rep2gland 2.0 (430 FVB/NJ Array)pituitary(0.033241)rep1 gland 2.0 (430 (0.0532864) Array)pituitaryrep2 gland 2.0 (430 Array)(0.0762534) rep1 gland 2.0 (430(0.0559425) Array) rep2 2.0 (430(0.0602418) Array)[ min2.0 (0.0586661) Array) ] (0.0233305) [ medium ] [ max ] CEM 1 Snw1 1198.4 1501.6 3017.9 P ( S | Z, I ) = 0.12 Ncor1 1148.7 1801.0 3514.6 Mean Corr = 0.44590 Glis3 3.4 65.5 377.6 Npat 335.7 502.3 826.5 Ski 603.8 905.2 2430.9 Epc2 1391.4 1939.9 2955.8 Bdp1 654.9 884.7 1189.5 Zfp26 705.0 980.7 1890.6 Zbtb6 310.1 501.5 1013.8 Epc1 1521.1 1903.0 2826.3 CEM 1 + Tnks2 2050.3 2865.2 7838.8 Top 10 Genes Phf20 872.6 1535.3 2219.9 Ep300 1151.2 1485.2 2015.8 Arid4a 158.1 308.6 475.1 Rbm27 423.7 631.0 810.1

Null module