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: 8 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. Pafah1b1 Dync2h1 Dync2li1 Num ofGenesinQueryGeneset:8.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Pkd1 Pkd2 Ift46 Ift88 Gli2

Dync2li1 Pkd2 Ift88 Dync2h1 Gli2 Pkd1 Ift46 Pafah1b1 CEM 1(48datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 1110051M20Rik 2610008E11Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page1 Pafah1b1 Fam229b Fam115a Dync2h1 Dync2li1 Gprasp1 Tbc1d19 Zc2hc1a Hmg20a Specc1l Zfp354c Armcx1 Cbfa2t2 Leprel2 Akap11 Cc2d2a Zfp383 Zfp449 Slc4a3 Prrc2b Tspyl4 Tceal1 Ehbp1 Wdr19 Trip12 Zc4h2 Gulp1 Ltbp3 Pias2 Ttc26 Ift122 Cntln Phtf1 Chd6 Glis2 Clip3 Cbx6 Neo1 Bbs1 Pkd1 Pkd2 Evc2 Purg Ttc8 Ift46 Ift88 Arl3 Gli2 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE5891 [6] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE25257 [6] GSE23495 [6] GSE12498 [12] GSE13044 [59] GSE18907 [12] GSE31028 [6] GSE39621 [51] GSE17263 [6] GSE15872 [18] GSE16073 [6] GSE13563 [6] GSE40156 [42] GSE9441 [36] GSE12730 [24] GSE16675 [72] GSE23408 [39] GSE38257 [14] GSE25423 [10] GSE20696 [8] GSE6383 [6] GSE30488 [52] GSE21568 [12] GSE45820 [6] GSE9297 [27] GSE37431 [6] GSE22925 [14] GSE31013 [12] GSE20684 [12] GSE14004 [9] GSE42548 [29] GSE49346 [6] GSE1871 [12] GSE52474 [154] GSE11898 [9] GSE21861 [8] GSE31561 [36] GSE49128 [17] GSE11679 [25] GSE27987 [31] GSE34423 [40] GSE39458 [6] GSE13032 [18] GSE27811 [9] GSE23895 [18] GSE56777 [8] GSE9061 [6] GSE41759 [14] GSE40087 [15] GSE4734 [61] GSE27159 [8] GSE15155 [12] GSE7694 [12] GSE9338 [42] GSE7430 [12] GSE12078 [8] GSE39897 [36] GSE6487 [30] GSE9368 [12] GSE5332 [12] GSE6526 [16] GSE7069 [8] GSE33101 [8] GSE38831 [7] GSE26096 [10] GSE4260 [6] GSE17096 [20] GSE51883 [30] GSE9131 [6] GSE46185 [6] GSE11201 [18] GSE13963 [15] GSE15794 [6] GSE52597 [7] GSE51080 [18] GSE38277 [18] GSE13071 [15] GSE3181 [6] GSE33471 [12] GSE27302 [16] GSE15871 [18] GSE6933 [15] GSE48338 [8] GSE51365 [28] GSE14007 [8] GSE48811 [20] GSE46496 [9] GSE11796 [18] GSE13874 [14] GSE15587 [6] GSE7685 [12] GSE33688 [12] GSE21247 [60] GSE39391 [21] GSE31244 [6] GSE12073 [12] GSE6196 [9] GSE21755 [25] GSE34902 [6] GSE15772 [8] GSE28025 [18] GSE8156 [6] GSE5202 [12] GSE58368 [15] GSE13873 [27] GSE32095 [24] GSE11687 [12] GSE12333 [6] GSE49351 [6] GSE34215 [6] GSE22841 [12] GSE41095 [6] GSE42047 [24] GSE51686 [9] GSE55607 [18] GSE37316 [31] GSE53077 [8] GSE6837 [8] GSE41185 [8] GSE47607 [12] GSE33891 [19] GSE55809 [8] GSE15433 [9] GSE17797 [19] GSE27378 [8] GSE25029 [56] GSE31106 [18] GSE46871 [6] GSE13106 [10] GSE40612 [16] GSE26668 [6] GSE51483 [45] GSE27675 [14] GSE5255 [6] GSE11291 [60] GSE47414 [18] GSE30160 [6] GSE15326 [10] GSE30176 [12] GSE18395 [8] GSE45968 [6] GSE22251 [9] GSE29681 [32] GSE46209 [21] GSE27605 [8] GSE48884 [12] GSE24291 [6] GSE16902 [21] GSE8357 [6] GSE51804 [10] GSE28389 [20] GSE8726 [7] CEM+ CEM GSE46942 [7] GSE21309 [9] GSE5313 [6] GSE7141 [6] GSE22506 [12] GSE38001 [12] 0.0 GSE8683 [11] GSE40939 [10]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 27.58 27.59 27.69 27.70 27.73 28.31 28.32 28.33 28.36 28.43 28.64 29.17 29.32 29.40 29.40 29.55 29.98 30.11 30.27 30.35 30.83 30.87 30.94 31.27 31.33 31.36 31.39 31.45 31.47 31.57 32.56 32.92 33.02 33.78 34.10 34.48 34.54 36.29 37.16 37.49 38.85 40.63 1.0 Notes 5730409E04Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page2 Cacna2d1 Tmem231 AI597479 Map3k12 Smarcd3 Rabgap1 Ccdc157 Zkscan1 Slc2a13 Maged1 Leprel4 Vps37d Tspan6 Zmym4 Dzank1 Gpsm1 Scaper Ptpdc1 Rbms3 Ttc30b Zfp763 Glt8d1 Apbb1 Hook3 Ddah2 Abca5 Klhl22 Klhl17 Thbs3 Mxra8 Megf8 Btbd2 Nlgn2 Kat6b Large Dact3 Tctn2 Zfp37 Bbs2 Sspn Nek1 Pbx1 Sall2 Cul7 Dtx3 Dsel Pja1 Ift74 Fto 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 22.73 22.76 22.80 22.94 22.95 22.96 22.97 23.00 23.03 23.17 23.21 23.22 23.33 23.45 23.59 23.59 23.71 23.73 23.76 23.85 24.11 24.40 24.41 24.55 24.58 24.79 24.81 24.98 25.02 25.11 25.19 25.33 25.68 26.24 26.33 26.35 26.48 26.56 26.59 26.61 26.67 26.68 26.89 26.94 27.04 27.13 27.32 27.34 27.43 27.45 1.0 Notes 2610301B20Rik D630045J12Rik 2510009E07Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page3 AW549877 Cdc42bpa Fam188b Arhgef25 Slc22a17 Dennd2a Ccdc112 Dync1li2 Tmem8b Prickle2 Mpped2 Sertad4 Armcx2 Poglut1 Cacnb3 Tspan3 Zbtb20 Pcnxl4 Ccl27a Zfp503 Fbxl16 Gsk3b Wdr60 Npdc1 Cryzl1 Morn4 Casc4 Ndrg4 Sfxn4 Il17rd Zfp12 Zfp74 Zfp68 Ptprs Rftn2 Wdr6 Nbea Triqk Agrn Fzd2 Npr2 Gtf2i Pfn2 Ulk2 Scai Boc Islr 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 19.07 19.14 19.18 19.25 19.34 19.39 19.43 19.55 19.55 19.70 19.70 19.79 19.87 19.87 20.16 20.24 20.24 20.32 20.39 20.50 20.51 20.57 20.61 20.62 20.66 20.74 20.79 20.83 21.02 21.09 21.09 21.10 21.23 21.33 21.47 21.57 21.57 21.64 21.70 21.75 21.80 21.86 21.88 22.03 22.13 22.13 22.22 22.36 22.37 22.72 1.0 Notes 2700081O15Rik 9230110C19Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page4 Tmem55a Fam168a Smarca1 Tbc1d32 Gprasp2 Zfp955a Maged2 Magee1 Pcdh18 Fundc1 Fkbp14 Crebbp Rcbtb2 Zfp637 Zfp260 Zfp799 Zfp651 Lamb2 Zfp512 Rab34 Rab23 Cdk14 Fkbp7 Nrbp2 Cpt1c Dip2c Ric8b Jam3 Adnp Lrig2 B9d1 Pcnx Zeb1 Fstl1 Lix1l Nrep Ppig Smo Elp3 Slit3 Eid1 Tcf4 Ift57 Tle2 Cpe Irs1 Ski Tef 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 16.77 16.84 16.87 16.94 16.94 17.07 17.27 17.31 17.43 17.45 17.47 17.49 17.49 17.52 17.52 17.52 17.56 17.62 17.74 17.77 17.80 17.80 18.00 18.01 18.02 18.03 18.03 18.07 18.15 18.25 18.30 18.31 18.34 18.37 18.37 18.41 18.51 18.52 18.55 18.57 18.62 18.62 18.71 18.73 18.73 18.74 18.81 18.85 18.86 18.92 1.0 Notes B230219D22Rik 2310022B05Rik D3Ertd254e Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page5 Fam195b B3galnt1 Pcdhb17 Ccdc136 Txndc16 Tmem47 Zcchc14 Camk2g Rasl11b Ccdc66 Mbtps1 Atp8b2 Pou6f1 Scara3 Tnrc6c Smad2 Samd4 Zfp647 Zfp532 Zfp867 Olfml3 Med23 Nphp1 Rbbp9 Lrrcc1 Kifap3 Usp22 Dock7 Lphn1 Eif1ax Tanc2 Mtch1 Ubtd2 Btf3l4 Phf20 Rabl2 Dnal4 Vezf1 Map4 Gas1 Klhl7 Glg1 Vldlr Abi2 Eid2 Atl1 Tril 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 14.74 14.74 14.74 14.81 14.83 14.87 14.93 14.95 14.95 14.98 14.98 15.11 15.14 15.17 15.26 15.36 15.39 15.42 15.42 15.42 15.46 15.48 15.52 15.53 15.55 15.56 15.56 15.62 15.69 15.70 15.74 15.79 15.82 15.86 15.87 15.95 16.06 16.06 16.06 16.19 16.23 16.31 16.33 16.45 16.51 16.55 16.58 16.61 16.67 16.67 1.0 Notes Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page6 Tmem237 Map1lc3a Mapkbp1 Gucy1a2 Pcdhb21 Pcdhb20 Ccdc173 Tbc1d12 Ankrd46 Col16a1 Zfyve16 Fbxo25 Fbxo18 Sorcs2 Stoml1 Snapin Rnf150 Wdpcp Podxl2 Trim32 Zfp251 Zfp563 Inpp5e Zfp704 Abhd8 Clstn1 Cdh11 Brwd1 Ephb3 P4htm Reep5 Usp11 Emc8 Stk36 Tfcp2 Ift172 Ttc28 Sfrp2 Gpx8 Bnc2 Clip4 Selm Fgd1 Mras Nenf Zfp9 Six5 Ogn Ndn Evc 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 12.52 12.53 12.62 12.63 12.69 12.75 12.75 12.84 12.91 12.91 12.94 12.96 12.97 13.01 13.15 13.19 13.22 13.24 13.25 13.25 13.39 13.43 13.48 13.53 13.60 13.63 13.66 13.71 13.73 13.76 13.91 13.91 13.95 13.95 13.96 13.96 14.02 14.11 14.14 14.20 14.37 14.39 14.40 14.41 14.48 14.54 14.54 14.56 14.64 14.66 1.0 Notes 3632451O06Rik 1700029J07Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page7 Uhrf1bp1l Zmynd11 AI314180 Dennd5a Tbc1d16 Ankrd50 Ppp1r26 Zfp354a Prpf40b Rb1cc1 Zmym3 Mmp11 Cd99l2 Zbtb10 Zfp423 Zfp931 Zfp462 Zfp810 Apbb2 Scarf2 Rsph9 Rcan3 Sned1 Pcbp3 Cxx1c Fmnl2 Zc3h6 Ptprm Mnat1 Mfap2 Qser1 Porcn Prmt2 Rsrc1 Prkd1 Srek1 Lpar1 H2afv Zfp61 Zfp90 Map9 Praf2 Chd3 Rbak Ints6 Mllt3 Nbl1 Pja2 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 10.35 10.38 10.38 10.43 10.45 10.46 10.48 10.49 10.49 10.57 10.60 10.60 10.61 10.76 10.77 10.78 10.80 10.80 10.91 10.95 10.95 10.95 11.06 11.06 11.12 11.18 11.24 11.29 11.29 11.31 11.37 11.41 11.59 11.59 11.64 11.72 11.77 11.90 11.98 12.01 12.02 12.08 12.09 12.16 12.17 12.29 12.42 12.48 12.48 12.51 1.0 Notes 2210016L21Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page8 BC034090 Rab11fip3 Tmem107 Camsap2 Zc3hav1l Pcdhb22 Ccdc88a Epb4.1l3 Zdhhc17 Gpatch8 Ankrd40 Slc18b1 Slc2a10 Mageh1 Exoc6b Fbxo10 Gpr125 Gpr153 Col6a1 Spata7 Zfp286 Zfp329 Pdgfrb Rab2b Nuak1 Sesn3 Tmtc1 Zmat1 Tcea2 Negr1 Meis1 Tdrd3 Sar1a Stox2 Nicn1 Trim2 Dact1 Bicc1 Plcg1 Foxj3 Prepl Kif3a Pdp1 Eml1 Dkk3 Sgtb Helz Wls Ttl 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 8.57 8.62 8.66 8.66 8.67 8.74 8.74 8.76 8.79 8.79 8.80 8.81 8.90 8.93 9.04 9.09 9.11 9.17 9.20 9.20 9.27 9.29 9.36 9.36 9.44 9.50 9.53 9.55 9.56 9.61 9.69 9.69 9.72 9.76 9.82 9.87 9.91 9.93 9.94 9.94 9.95 9.99 10.02 10.09 10.14 10.16 10.22 10.27 10.29 10.34 1.0 Notes 6330403K07Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page9 Tmem119 Fam110b Fam184a Ankdd1b Cacna1g Epb4.1l5 Trabd2b Runx1t1 Zfp280d Slc36a4 Slc39a3 Armcx3 Sparcl1 B4galt2 Rab33b Dyx1c1 Pmp22 Zfp583 Zfp229 Zfp580 Zfp788 Gkap1 Lmbr1 Wdr78 Wdr13 Zmat3 Timp2 Prkg1 Srpk2 Sugt1 Ctxn1 Trim3 Sf3b1 Lekr1 Plcd1 Zfp11 Iqcb1 Gab1 Gas6 Oaz2 Epc2 Ppil6 Phc1 Ldb2 Rpgr Mib2 Cyld Rsf1 Dlg5 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 6.92 6.99 7.07 7.11 7.13 7.14 7.14 7.15 7.19 7.22 7.23 7.24 7.25 7.26 7.33 7.42 7.46 7.46 7.46 7.51 7.56 7.60 7.63 7.69 7.81 7.81 7.81 7.85 7.86 7.87 7.89 7.92 7.92 7.92 7.92 8.00 8.00 8.00 8.01 8.03 8.06 8.09 8.18 8.28 8.30 8.47 8.52 8.52 8.56 8.57 1.0 Notes 3830406C13Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page10 Pcdhgc4 Sh3glb1 Camkk1 Fam53c Cachd1 St8sia2 C78339 Zmym2 B3gnt9 B3gnt1 Cluap1 Stxbp1 Efcab7 Kdelc2 Zfp420 Zfp438 Zfp248 Lrrc51 Hsbp1 Pik3r2 Dhx30 Soga1 Usp30 Akap9 Cd248 Gorab Btbd1 Auts2 Cpsf6 Appl2 Phpt1 Mpzl1 Zfp60 Zfp40 Zfp93 Fbln1 Pias3 Prrg3 Itm2c Serf1 Trpt1 Sgcb Pbx3 Cul5 Dlg3 Ift80 Invs Trio Efs 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 5.30 5.30 5.30 5.33 5.41 5.41 5.42 5.44 5.46 5.46 5.48 5.60 5.61 5.68 5.68 5.73 5.75 5.77 5.81 5.82 5.84 5.89 5.92 5.93 6.08 6.12 6.14 6.14 6.15 6.15 6.16 6.17 6.25 6.29 6.34 6.39 6.43 6.49 6.50 6.52 6.53 6.54 6.56 6.63 6.69 6.75 6.77 6.82 6.86 6.89 1.0 Notes Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page11 BC030336 Trp53bp1 Arhgef28 Ccdc90b Ccdc104 Fam69b Man2a2 Anapc2 Mterfd3 Papss1 Fbxo11 Osbpl5 Brms1l Amotl1 B3galtl Kctd17 Kctd15 Dpysl3 H2afy2 Zfp275 Lamb1 Zfp521 Zfp451 Zfp937 Zfp551 Plk1s1 Slc9a6 Myo9a Lrrc45 Cand2 Ddx50 Rab28 Dhx57 Mtmr9 Fkbp9 Pdgfrl Ptch1 Efhc1 Nme5 Pcgf3 Dph3 Reck Sdk2 Nav1 Ror1 Pigp Pkia Ift43 Fat4 Mn1 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 3.96 4.03 4.09 4.17 4.23 4.29 4.31 4.31 4.35 4.37 4.37 4.38 4.41 4.43 4.44 4.44 4.46 4.53 4.54 4.57 4.60 4.60 4.61 4.63 4.67 4.69 4.70 4.72 4.73 4.77 4.79 4.79 4.83 4.83 4.85 4.90 4.92 4.97 5.03 5.09 5.12 5.12 5.13 5.14 5.21 5.23 5.24 5.26 5.27 5.30 1.0 Notes Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page12 Tmem110 Calcoco1 Atp6v0e2 Dcun1d5 Cacna1c Tram1l1 Slc35e3 Mum1l1 Caprin2 Map4k3 Pcdhb3 Pcdhb9 Minos1 Rnf215 Hnrnpr Col6a2 Ldoc1l Slc7a6 Garnl3 Wdr35 Wdr48 Rab6b Sepn1 Rcan2 Nova1 Foxc1 Mfap4 Tshz3 Sparc Pacrg Ackr3 Afap1 Lrch2 Zbtb4 Nr2f2 Nr2f1 Lzts2 Rhoq Dbn1 Sulf1 Sub1 Dag1 Eny2 Itgb8 Tial1 Rtn2 Ebf4 Fat1 Kif7 Id4 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 2.58 2.59 2.72 2.74 2.75 2.79 2.87 2.89 2.98 3.01 3.08 3.10 3.11 3.11 3.16 3.22 3.27 3.32 3.34 3.40 3.42 3.43 3.44 3.44 3.44 3.44 3.46 3.47 3.47 3.48 3.49 3.53 3.54 3.55 3.60 3.61 3.61 3.62 3.65 3.67 3.70 3.73 3.73 3.81 3.83 3.83 3.85 3.87 3.94 3.95 1.0 Notes 1700088E04Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page13 Adamts10 Fam211a Ccdc85b Hspa12b Ccdc181 Tmem35 Zkscan4 Flywch1 Adam22 Zfp955b Hdgfrp3 Fam92a Fam65a Dnmt3a Anapc4 Pnmal2 Lrsam1 Shank3 Hnrnpd Tspan5 Klhdc1 Dab2ip Sptan1 Zfp629 Zfp507 Zfp105 Tspyl5 Tspyl2 Wdr47 Kmt2a Pik3r4 Rock2 Kank3 Dmwd Ndrg3 Cetn4 Ube2i Tgfb2 Tgfb3 Ltbp4 Efr3b Pxdn Pcnp Nkd1 Mbip Lca5 Tsc2 Pura Fbf1 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 1.17 1.19 1.19 1.26 1.31 1.32 1.32 1.36 1.36 1.38 1.38 1.39 1.39 1.40 1.42 1.51 1.60 1.62 1.70 1.72 1.72 1.73 1.74 1.77 1.78 1.84 1.94 1.97 2.08 2.10 2.12 2.12 2.14 2.17 2.19 2.21 2.26 2.28 2.29 2.31 2.33 2.36 2.40 2.48 2.48 2.49 2.50 2.53 2.55 2.56 1.0 Notes A630007B06Rik D430019H16Rik Symbol Num ofCEMGenes:8.Predicted695.SelectedDatasets:48.Strength:0.4 CEM 1,Geneset"[G]motileprimarycilium",Page14 Tmem136 Arhgap28 Pcdhb19 Dync1h1 Irak1bp1 Ralgapb Ankmy2 Prdm11 Efemp2 Spock2 Pik3ip1 Srgap3 Pard6g Sptbn1 Acvr2a Dixdc1 Col4a5 Zfp362 Impact Mical3 Wdr34 Kcnh2 Cdh13 Usp34 Hdac5 Bclaf1 Senp8 Usp47 Usp54 Senp6 Lphn2 Phka1 Mxra7 Fxyd6 Matn2 Arfip2 Tshz1 Meis2 Ptpn9 Pomk Gnaq Rcn3 Celf5 Bbs5 Oxr1 Thra Slit2 Bcl9 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE1566 [6] Scale ofaveragePearsoncorrelations GSE55622 [22] GSE58296 [9] GSE48204 [6] GSE32615 [10] GSE33942 [12] GSE28559 [30] 0.2 GSE39583 [21] GSE19299 [6] GSE44162 [6] GSE30684 [6] GSE14024 [12] GSE33308 [10] GSE4718 [6] GSE20391 [11] GSE41342 [26] 0.4 GSE46150 [8] GSE24813 [10] GSE6675 [8] GSE32214 [6] GSE5241 [9] GSE36229 [14] GSE15267 [8] GSE36384 [12] GSE6055 [8] 0.6 GSE47065 [8] GSE31776 [10] GSE4752 [6] GSE43145 [12] GSE44175 [18] GSE42049 [8] GSE16691 [12] GSE31004 [8] GSE10895 [8] 0.8 GSE22180 [60] GSE12985 [14] GSE4535 [6] GSE40655 [6] Score 0.12 0.17 0.18 0.22 0.26 0.26 0.27 0.27 0.27 0.28 0.31 0.32 0.33 0.36 0.36 0.38 0.39 0.42 0.44 0.44 0.44 0.48 0.50 0.51 0.55 0.57 0.60 0.60 0.61 0.63 0.64 0.66 0.66 0.66 0.69 0.72 0.73 0.76 0.77 0.80 0.81 0.83 0.84 0.84 0.85 0.88 0.96 1.01 1.12 1.12 1.0 Notes Symbol Num ofCEMGenes:8.Predicted695. Num ofSelectedDatasets:48.CEMStrength:0.4 CEM 1,Geneset"[G]motileprimarycilium", Page15 Gxylt2 Sox12 Trps1 0.0 1.0

GSE13302 [30] GSE32529 [224]

GSE5891 [6] Only showingfirst200datasets-Seetxtoutputforfulldetails . GSE25257 [6] GSE23495 [6] GSE12498 [12] GSE13044 [59] GSE18907 [12] GSE31028 [6] GSE39621 [51] GSE17263 [6] GSE15872 [18] GSE16073 [6] GSE13563 [6] GSE40156 [42] GSE9441 [36] GSE12730 [24] GSE16675 [72] GSE23408 [39] GSE38257 [14] GSE25423 [10] GSE20696 [8] GSE6383 [6] GSE30488 [52] GSE21568 [12] GSE45820 [6] GSE9297 [27] GSE37431 [6] GSE22925 [14] GSE31013 [12] GSE20684 [12] GSE14004 [9] GSE42548 [29] GSE49346 [6] GSE1871 [12] GSE52474 [154] GSE11898 [9] GSE21861 [8] GSE31561 [36] GSE49128 [17] GSE11679 [25] GSE27987 [31] GSE34423 [40] GSE39458 [6] GSE13032 [18] GSE27811 [9] GSE23895 [18] GSE56777 [8] GSE9061 [6] GSE41759 [14] GSE40087 [15] GSE4734 [61] GSE27159 [8] GSE15155 [12] GSE7694 [12] GSE9338 [42] GSE7430 [12] GSE12078 [8] GSE39897 [36] GSE6487 [30] GSE9368 [12] GSE5332 [12] GSE6526 [16] GSE7069 [8] GSE33101 [8] GSE38831 [7] GSE26096 [10] GSE4260 [6] GSE17096 [20] GSE51883 [30] GSE9131 [6] GSE46185 [6] GSE11201 [18] GSE13963 [15] GSE15794 [6] GSE52597 [7] GSE51080 [18] GSE38277 [18] GSE13071 [15] GSE3181 [6] GSE33471 [12] GSE27302 [16] GSE15871 [18] GSE6933 [15] GSE48338 [8] GSE51365 [28] GSE14007 [8] GSE48811 [20] GSE46496 [9] GSE11796 [18] GSE13874 [14] GSE15587 [6] GSE7685 [12] GSE33688 [12] GSE21247 [60] GSE39391 [21] GSE31244 [6] GSE12073 [12] GSE6196 [9] GSE21755 [25] GSE34902 [6] GSE15772 [8] GSE28025 [18] GSE8156 [6] GSE5202 [12] GSE58368 [15] GSE13873 [27] GSE32095 [24] GSE11687 [12] GSE12333 [6] GSE49351 [6] GSE34215 [6] GSE22841 [12] GSE41095 [6] GSE42047 [24] GSE51686 [9] GSE55607 [18] GSE37316 [31] GSE53077 [8] GSE6837 [8] GSE41185 [8] GSE47607 [12] GSE33891 [19] GSE55809 [8] GSE15433 [9] GSE17797 [19] GSE27378 [8] GSE25029 [56] GSE31106 [18] GSE46871 [6] GSE13106 [10] GSE40612 [16] GSE26668 [6] GSE51483 [45] GSE27675 [14] GSE5255 [6] GSE11291 [60] GSE47414 [18] GSE30160 [6] GSE15326 [10] GSE30176 [12] GSE18395 [8] GSE45968 [6] GSE22251 [9] GSE29681 [32] GSE46209 [21] GSE27605 [8] GSE48884 [12] GSE24291 [6] GSE16902 [21] GSE8357 [6] GSE51804 [10] GSE28389 [20] GSE8726 [7] CEM+ CEM GSE46942 [7] GSE21309 [9] GSE5313 [6] GSE7141 [6] GSE22506 [12] GSE38001 [12] 0.0 GSE8683 [11] GSE40939 [10]

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, (0.0337355)0mg/kg/day rep1 lungPFOS, (0.027897)0mg/kg/day rep2 liverPFOS, (0.0376643)0mg/kg/day rep2 lungPFOS, (0.0279772)0mg/kg/day rep3 liverPFOS, (0.0351193)0mg/kg/day rep3 lungPFOS, (0.0289713)0mg/kg/day rep4 liverPFOS, (0.0339416)5mg/kg/day rep4 lungPFOS, (0.0242818)5mg/kg/day rep5 liverPFOS, (0.0307499)5mg/kg/day rep5 lungPFOS, (0.032968)5mg/kg/day rep1 liverPFOS, (0.0194644)5mg/kg/day rep1 lungPFOS, (0.0418547)5mg/kg/day rep2 liverPFOS, (0.0459606)5mg/kg/day rep2 lungPFOS, (0.0295076)5mg/kg/day rep3 liverPFOS, (0.03665)5mg/kg/day rep3 lungPFOS, (0.0283195)5mg/kg/day rep4 liverPFOS, (0.0323181)10mg/kg/day rep4 lungPFOS, (0.0316808)10mg/kg/day rep5 liver PFOS, (0.0441398)10mg/kg/day rep5 lungPFOS, (0.0341086)10mg/kg/day rep1 liverPFOS, 10mg/kg/day(0.0376518) rep1 lungPFOS, 10mg/kg/day(0.0290356) rep2 liverPFOS, 10mg/kg/day(0.0385958) rep2 lungPFOS, 10mg/kg/day(0.0319194) rep3 liverPFOS, 10mg/kg/day(0.0434376) rep3 lungPFOS, 10mg/kg/day(0.0395909) rep4 liverPFOS, (0.0256131) rep4 lungPFOS, (0.0334094) rep5 liver (0.0228133) rep5 [(0.0406233) min ] [ medium ] [ max ] CEM 1 Dync2li1 315.1 879.3 1238.5 P ( S | Z, I ) = 1.00 Pkd2 291.5 1354.0 1670.8 Mean Corr = 0.92549 Ift88 179.6 425.5 579.5 Dync2h1 139.2 347.2 449.7 Gli2 125.0 371.5 552.0 Pkd1 118.1 634.4 1130.8 Ift46 721.2 1188.8 1602.1 Pafah1b1 801.4 1081.1 1330.7 Ttc8 204.5 477.2 671.0 1110051M20Rik 197.8 408.6 557.3 Wdr19 86.3 254.8 366.2 Zfp354c 43.0 275.3 402.2 Bbs1 52.1 145.7 204.5 CEM 1 + Chd6 245.3 711.2 901.8 Top 10 Genes Glis2 176.4 725.6 918.3 Tbc1d19 198.2 744.5 911.2 Cc2d2a 223.7 510.2 703.8 Fam115a 155.4 455.8 514.8

Null module GEO Series "GSE32529" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 224 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

Details of this dataset are not shown due to large number of samples and the page size limit. Find details in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32529

Background corr dist: KL-Divergence = 0.0225, L1-Distance = 0.0447, L2-Distance = 0.0023, Normal std = 0.7763 GEO Series "GSE5891" 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=GSE5891 Status: Public on Sep 22 2006 Title: Nuclear organization of active and inactive chromatin domains revealed by 4C technology Organism: Mus musculus Experiment type: Other Platform: GPL1261 Pubmed ID: 17033623 Summary & Design: Summary: The spatial organization of DNA in the cell nucleus is an emerging key contributor to genomic function. We have developed 4C technology, or 3C-on-chip, which allows for an unbiased genome-wide search for DNA loci that contact a given locus in the nuclear space. We demonstrate here that active and inactive genes are engaged in many long-range intrachromosomal interactions and can also form interchromosomal contacts. The active b-globin locus in fetal liver contacts mostly transcribed, but not necessarily tissue-specific, loci elsewhere on chromosome 7, while the inactive locus in fetal brain contacts different, transcriptionally silent, loci. A housekeeping gene in a gene dense region on chromosome 8 forms long-range contacts predominantly with other active gene clusters, both in cis and in trans, and many of these intra- and interchromosomal interactions are conserved between the tissues analyzed. Our data demonstrate that chromosomes fold into areas of active chromatin and areas of inactive chromatin and establish 4C technology as a powerful tool to study nuclear architecture.

Keywords: 4C technology

Overall design: Gene expression arrays were performed in triplicate, according to standard procedures (Affymetrix). 4C experiments were performed in duplo (biologically independent samples), dye swap was included. Hybriisation was performed on dedicated micro-arrays. Probes (60-mers) were selected from the sequences 100 bp up and downstream of HindIII sites. To prevent cross-hybridization, probes that had any similarity with highly abundant repeats (RepBase 10.09) were removed from the probeset. In addition, probes that gave more than two BLAST hits in the genome were also removed from the probeset. Sequence alignments were performed using MegaBLAST using the standard settings. A hit was defined as an alignment of 30 nt or longer.

Background corr dist: KL-Divergence = 0.0158, L1-Distance = 0.0653, L2-Distance = 0.0070, Normal std = 0.9745

0.409 Kernel fit Pairwise Correlations Normal fit

Density 0.205

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_fetal_brain_1E14.5_fetal_brain_2E14.5_fetal_brain_3 (0.245863)E14.5_fetal_liver_1 (0.174693)E14.5_fetal_liver_2 (0.146304)E14.5_fetal_liver_3 (0.132999) (0.153567) (0.146575) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 51.6 134.1 188.5 P ( S | Z, I ) = 1.00 Pkd2 124.2 573.4 717.6 Mean Corr = 0.81491 Ift88 40.4 122.1 151.4 Dync2h1 45.1 345.9 424.3 Gli2 49.3 218.3 379.0 Pkd1 21.3 28.6 41.8 Ift46 476.4 626.1 1184.3 Pafah1b1 1095.1 5069.7 6264.5 Ttc8 67.4 470.9 764.2 1110051M20Rik 90.9 943.5 1058.4 Wdr19 21.0 118.0 164.9 Zfp354c 41.4 1798.9 2469.2 Bbs1 30.6 213.1 295.1 CEM 1 + Chd6 144.3 994.1 1447.8 Top 10 Genes Glis2 114.9 402.5 572.5 Tbc1d19 103.3 852.9 1365.4 Cc2d2a 78.4 176.8 238.1 Fam115a 65.1 1348.8 1966.5

Null module GEO Series "GSE25257" 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=GSE25257 Status: Public on Nov 11 2010 Title: Expression data from wild-type and Zmpste24-/- mouse embryonic fibroblasts (MEFs) at an early passage (passage 3, P3) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Zmpste24 is a metalloproteinase processing prelamin A into mature lamin A, a nuclear structure protein. Zmpste24-/- mice which accumulate prelamin A in cells recapitulate accelerated aging phenotypes observed in human premature aging disorder, Hutchinson Gilford progeria sydrome (HGPS). Zmpste24-/- mouse embryonic fibroblasts (MEFs) exhibited genomic instabiliy and accelerated aging at cellular level, which is premature senescence.

We performed microarray analysis on Zmpste24-/- MEFs, compared to wild-type littermates' MEFs, at an early passage (P3), which is a pre-symptom stage before cellular senescence occurs in the mutant MEFs, in order to examine gene expression profile and figure out the underneath mechanism triggering the premature aging process.

Overall design: Early passage wild-type and Zmpste24-/- MEFs were collected for RNA extraction, the quality of RNAs were determinded by Electrophoresis Assay (2100 Bioanalyzer, Agilent) and RNA extractions were used for hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0217, L1-Distance = 0.0450, L2-Distance = 0.0023, Normal std = 0.8008

0.542 Kernel fit Pairwise Correlations Normal fit

Density 0.271

0.000 CEM 1

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

Pre-normalization Quantiles

WT1 (0.340223)WT2 (0.0812912)WT3 (0.104802)NT1 (0.279681)NT2 (0.137308)NT3 (0.056695) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 365.1 403.6 1255.6 P ( S | Z, I ) = 1.00 Pkd2 2198.6 2450.2 8994.2 Mean Corr = 0.81241 Ift88 130.9 173.9 246.1 Dync2h1 100.2 156.6 281.9 Gli2 429.1 528.7 875.9 Pkd1 290.9 425.0 454.4 Ift46 1490.6 1637.1 2140.5 Pafah1b1 715.5 1016.7 1365.0 Ttc8 431.0 601.6 862.0 1110051M20Rik 434.2 549.2 753.3 Wdr19 116.4 165.1 403.1 Zfp354c 287.8 438.9 1129.3 Bbs1 27.5 73.0 142.1 CEM 1 + Chd6 140.0 219.8 476.5 Top 10 Genes Glis2 881.3 1071.8 1117.4 Tbc1d19 894.0 1056.1 1175.2 Cc2d2a 201.0 274.9 298.9 Fam115a 533.6 600.2 634.6

Null module GEO Series "GSE23495" 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=GSE23495 Status: Public on Aug 09 2010 Title: Lmnadelta9 mouse gene expression study Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20833363 Summary & Design: Summary: Lmnadelta9 mice derived in the C57bl6X129S3/J background have been identified as exhibiting a progeric phenotype. Using this mouse model we show that a truncated variant of Lamin A (Lmna9) causes the proliferative arrest of post-natal fibroblasts. Arrest is due to the cells inability to produce a functional extracellular matrix (ECM).

We used microarrays to compare gene expression of adult primary fibroblasts from wildtype and Lmnadelta9 mice in order to understand whether the Lmnadelta9 adult MEF defective proliferation is due to alterations of specific signaling associated with ECM functions.

Overall design: Three independent replicate samples of sibling-derived wild-type and Lmna9 post-natal fibroblast lines at passage 3 were serum-starved for 72 hours and used as the source of mRNA for microarray analysis. RNA was extracted with Trizol, and hybridized to Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0360, L1-Distance = 0.0186, L2-Distance = 0.0004, Normal std = 0.6348

0.636 Kernel fit Pairwise Correlations Normal fit

Density 0.318

0.000 CEM 1

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

Pre-normalization Quantiles

Delta9,rep1Delta9,rep2 (0.19257)Delta9,rep3 (0.0688575)WT, rep1(0.181239)WT, (0.0564215) rep2WT, (0.0885736) rep3 (0.412338) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 273.2 322.8 431.5 P ( S | Z, I ) = 1.00 Pkd2 1426.3 2641.1 3016.7 Mean Corr = 0.79831 Ift88 167.8 236.7 298.6 Dync2h1 138.7 212.5 262.1 Gli2 329.1 533.6 771.5 Pkd1 502.8 833.5 1113.5 Ift46 1055.5 1170.6 1481.9 Pafah1b1 624.0 685.5 812.2 Ttc8 155.7 175.7 188.4 1110051M20Rik 463.4 550.8 754.9 Wdr19 228.2 292.8 417.0 Zfp354c 383.4 789.1 799.1 Bbs1 66.1 72.8 83.5 CEM 1 + Chd6 159.1 203.0 319.9 Top 10 Genes Glis2 954.0 1170.7 1463.2 Tbc1d19 422.9 541.2 738.4 Cc2d2a 362.3 458.8 601.8 Fam115a 291.2 377.4 485.5

Null module GEO Series "GSE12498" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

Keywords: Cell density, genetic modification

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

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

0.805 Kernel fit Pairwise Correlations Normal fit

Density 0.402

0.000 CEM 1

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

Pre-normalization Quantiles

ctrl-low-1ctrl-low-2 (0.213314)tead2VP16-conf-1 (0.207219)tead2VP16-conf-2yap-conf-1 (0.0784323)yap-conf-2 (0.0182643)(0.00454632)tead2EnR-low-1 (0.00953085)tead2EnR-low-2ctrl-over-1 (0.0194886)ctrl-over-2 (0.0375876) (0.127368)tead2VP16-over-1 (0.117507)tead2VP16-over-2 (0.0822249) (0.0845172) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 145.8 423.5 518.0 P ( S | Z, I ) = 1.00 Pkd2 2773.0 4150.8 5607.7 Mean Corr = 0.74129 Ift88 167.1 259.3 316.4 Dync2h1 151.7 193.2 248.4 Gli2 100.6 130.4 141.5 Pkd1 186.1 614.7 720.9 Ift46 1405.2 1783.8 2225.9 Pafah1b1 967.4 1448.6 1791.4 Ttc8 229.1 501.9 755.0 1110051M20Rik 958.1 1384.8 1669.9 Wdr19 66.2 112.2 188.3 Zfp354c 74.6 208.8 438.9 Bbs1 115.0 178.6 258.7 CEM 1 + Chd6 185.4 334.2 474.5 Top 10 Genes Glis2 902.1 1665.9 2029.7 Tbc1d19 642.7 786.5 1141.5 Cc2d2a 158.1 280.4 324.0 Fam115a 568.6 803.7 1051.0

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, (0.0165552) 0mg/kg/daydose) 3,(high 1 Block RepliverPFOA, (0.0127361) 0mg/kg/daydose) 3,(high 3 Block ReplungPFOA, (0.00656027) 0mg/kg/daydose) 4,(high 3, Block Rep PFOA,liver (0.0130225) 5mg/kg/daydose) 4, (high4, Block Rep PFOA,lung (0.0251132)5mg/kg/day dose) 5, (high4, Block Rep PFOA,liver (0.0142172)5mg/kg/day dose)5, (high5, Block Rep PFOA,lung (0.020158)5mg/kg/day dose) 1, (high5, Block Rep PFOA,liver (0.0122332)5mg/kg/day dose)1, (high5, Block Rep PFOA,lung (0.0196465)5mg/kg/day dose) 2, (high5, Block Rep PFOA,liver (0.0155095)5mg/kg/day dose)2, (high1, Block Rep PFOA,lung (0.0209361)5mg/kg/day dose) 3, (high1, Block Rep PFOA,liver (0.0145491)5mg/kg/day dose)3, (high2, Block Rep PFOA,lung (0.0176651)5mg/kg/day dose) 4, (high2, Block Rep PFOA,liver (0.0122463)10mg/kg/day dose)4, (high3, Block Rep PFOA,lung (0.0151212)10mg/kg/day dose) 5, (high3, BlockRep liver PFOA, (0.0142344)10mg/kg/day dose)5, (high4, Block lung RepPFOA, (0.0174659)10mg/kg/day dose) (high1,4, Blockliver RepPFOA, (0.0117304)10mg/kg/day dose) (high1, 2, Block Rep PFOA,lung (0.0292031)10mg/kg/day dose) 2, (high2, Block Rep PFOA,liver (0.0152988)10mg/kg/day dose)2, (high1, Block Rep PFOA,lung10mg/kg/day (0.0136473) dose) 3, (high1, Block Rep PFOA,liver10mg/kg/day (0.0133597) dose)3, (high3, Block Rep PFOA,lung10mg/kg/day (0.0176088) dose) 4, (high3, Block Rep PFOA,liver0mg/kg/day (0.0134972) dose)4, (high4, Block Rep PFOA,lung0mg/kg/day (0.0197996) dose) 5, (high4, PFOA, BlockRep liver0mg/kg/day (0.0102268) dose)5, (high 5, RepPFOA,Block lung0mg/kg/day (0.020338) 1,dose) (highBlock5, RepPFOA, liver0mg/kg/day (0.0167678) 1, dose) 5 (high Block ReplungPFOA,0mg/kg/day (0.0184266) 2,dose)(low 5 Block RepliverPFOA, dose)0mg/kg/day (0.013013) 2,(low 1 Block ReplungPFOA, (0.0158295) dose)0mg/kg/day 3,(low 1 Block RepliverPFOA, (0.0126862) dose)0mg/kg/day 3,(low 2 Block ReplungPFOA, (0.0188894) dose)0mg/kg/day 4,(low 2, Block Rep PFOA, liver(0.0129284) dose)1mg/kg/day 4, (low4, Block Rep PFOA, lung(0.0414378) dose)1mg/kg/day 5, (low4, Block Rep PFOA,liver (0.0124922) dose)1mg/kg/day 5, (low3, Block Rep PFOA,lung (0.0214727) dose)1mg/kg/day 1, (low3, Block Rep PFOA,liver (0.0107893) dose)1mg/kg/day 1, (low5, Block Rep PFOA,liver (0.014407) dose)1mg/kg/day 1, (low2, Block Rep PFOA,lung (0.0131484) dose)1mg/kg/day 2, (low2, Block Rep PFOA,liver (0.0126417) dose)1mg/kg/day 2, (low3, Block Rep PFOA,lung (0.0301612) dose)1mg/kg/day 3, (low3, Block Rep PFOA,liver (0.0120213) dose)3mg/kg/day 3, (low4, Block Rep PFOA,lung (0.0258757) dose)3mg/kg/day 4, (low4, Block Rep PFOA,liver (0.0147712) dose)3mg/kg/day 4, (low1, Block Rep PFOA,lung (0.0284399) dose)3mg/kg/day 1, (low1, Block Rep PFOA,liver (0.0155341) dose)3mg/kg/day 1, (low3, Block Rep PFOA,lung (0.0127675) dose)3mg/kg/day 2, (low3, Block Rep PFOA,liver (0.0115143) dose)3mg/kg/day 2, (low1, Block Rep PFOA,lung (0.0316252) dose)3mg/kg/day 3, (low1, Block Rep PFOA,liver (0.0154525) dose)3mg/kg/day 3, (low5, Block Rep PFOA,lung (0.0207831) dose)3mg/kg/day 4, (low5, Block Rep PFOA,liver (0.0174455) dose) 4, (low4, Block Rep PFOA,lung (0.014761) dose) 5, (low4, BlockRep liver (0.0112911) dose) 5, (low2, Block lung (0.0185248) dose)[ (low2,min liver (0.0145732) dose) (low ] (0.0202877) dose) (0.0165616)[ medium ] [ max ] CEM 1 Dync2li1 260.8 468.8 1179.8 P ( S | Z, I ) = 1.00 Pkd2 181.4 470.1 1822.3 Mean Corr = 0.72187 Ift88 147.3 269.4 614.5 Dync2h1 167.6 301.0 544.9 Gli2 146.7 292.6 687.0 Pkd1 121.2 227.2 778.8 Ift46 1017.4 1367.8 2685.4 Pafah1b1 525.4 792.6 1821.2 Ttc8 106.0 255.6 475.0 1110051M20Rik 196.8 360.5 747.8 Wdr19 58.3 111.9 305.6 Zfp354c 54.6 101.2 292.1 Bbs1 52.4 82.3 149.4 CEM 1 + Chd6 111.2 277.8 643.6 Top 10 Genes Glis2 135.6 235.6 1016.1 Tbc1d19 133.1 246.4 1047.2 Cc2d2a 134.5 310.9 677.4 Fam115a 117.9 310.3 643.5

Null module GEO Series "GSE18907" 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=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 (0.132278)Lung 2 Virgin (0.060787)Lung 3 Pregnant (0.070425)Lung Pregnant Lung1 (0.0703748) Pregnant Liver2 (0.0730207) Virgin Liver3 (0.0829905) 1 Virgin (0.0700366)Liver 2 Virgin (0.0885495)Liver 3 Pregnant (0.0595898)Liver Pregnant Liver1 (0.12482) Pregnant 2 (0.0658571) 3 (0.101272) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 70.2 416.4 590.0 P ( S | Z, I ) = 1.00 Pkd2 482.6 2557.3 3257.4 Mean Corr = 0.71679 Ift88 125.3 275.9 338.5 Dync2h1 165.7 266.6 302.8 Gli2 54.2 82.4 134.3 Pkd1 114.0 416.2 541.8 Ift46 1360.1 1575.3 1817.0 Pafah1b1 570.2 810.8 936.5 Ttc8 177.3 313.1 387.7 1110051M20Rik 259.8 611.5 850.4 Wdr19 80.5 287.0 338.1 Zfp354c 36.4 81.4 141.4 Bbs1 59.3 154.3 257.7 CEM 1 + Chd6 165.3 370.3 477.7 Top 10 Genes Glis2 129.5 1671.4 2239.7 Tbc1d19 225.5 1048.0 1364.4 Cc2d2a 165.0 382.7 517.7 Fam115a 117.4 290.2 334.2

Null module GEO Series "GSE31028" 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=GSE31028 Status: Public on Sep 02 2011 Title: Genome-wide maps of histone modifications unwind in vivo chromatin states of the hair follicle lineage Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21885018 Summary & Design: Summary: Mouse hair follicles (HFs) undergo synchronized cycles. Cyclical regeneration and hair growth is fueled by stem cells (SCs). During the rest phase, the HF-SCs remain quiescent due to extrinsic inhibitory signals within the niche. As activating cues accumulate, HF-SCs become activated, proliferate, and grow downward to form transient-amplifying matrix progenitor cells. We used microarrays to detect the relative levels of global gene expression underlying the states of hair follicle stem cells and their transient-amplifying progeny before differentiation.

Overall design: Quiescent hair follicle stem cells (qHF-SCs), activated hair follicle stem cells (aHF-SCs) and transient-amplifying matrix cells (HF-TACs) were FACS-purified for RNA extraction and hybridization on Affymetrix microarrays. To obtain homogeneous populations of expression profiles, we applied the FACS technique to purify SC and TACs according to their cell surface markers.

Background corr dist: KL-Divergence = 0.0298, L1-Distance = 0.0230, L2-Distance = 0.0006, Normal std = 0.6841

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

QuiescentQuiescent hair Activatedfollicle hair Activatedstemfollicle hair cells, follicleTransient-amplifyingstem hair rep1 cells, stemfollicleTransient-amplifying (0.153742) rep2 cells, stem (0.212821) rep1 cells, matrix (0.0459715) rep2 cells,matrix (0.0765493) rep1 cells,[ (0.319545)min rep2 (0.191371) ] [ medium ] [ max ] CEM 1 Dync2li1 679.8 965.5 1107.6 P ( S | Z, I ) = 1.00 Pkd2 222.7 839.3 913.1 Mean Corr = 0.71193 Ift88 215.5 281.8 349.5 Dync2h1 177.4 275.5 283.6 Gli2 621.3 1971.4 2596.3 Pkd1 86.6 445.9 1503.0 Ift46 998.4 1439.4 1632.9 Pafah1b1 671.0 955.6 1162.2 Ttc8 354.8 658.4 744.2 1110051M20Rik 690.0 824.8 1013.1 Wdr19 193.5 257.4 356.5 Zfp354c 62.4 106.7 128.8 Bbs1 126.1 278.3 379.9 CEM 1 + Chd6 249.4 720.7 2985.2 Top 10 Genes Glis2 97.1 373.5 515.4 Tbc1d19 543.2 735.6 986.2 Cc2d2a 218.0 304.9 387.6 Fam115a 172.5 519.9 659.1

Null module GEO Series "GSE39621" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 51 -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=GSE39621 Status: Public on Dec 27 2012 Title: Expression data from brain, liver and spleen of Npc1-/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23094108 Summary & Design: Summary: Niemann-Pick Type C (NPC) disease is a rare, genetic, lysosomal disorder with progressive neurodegeneration. Poor understanding of the pathophysiology and lack of blood-based diagnostic markers are major hurdles in the treatment and management of NPC and several additional neurological, lysosomal disorders. To identify disease severity correlates, we undertook whole genome expression profiling of sentinel organs, brain, liver, and spleen of Balb/c Npc1-/- mice (Npc1nih)relative to Npc1+/- at an asymptomatic stage, as well as early- and late-symptomatic stages. Unexpectedly, we found prominent up regulation of innate immunity genes with age-dependent change in their expression, in all three organs. We shortlisted a set of 12 secretory genes whose expression steadily increased with age in both brain and liver, as potential plasma correlates for the neurological disease. Ten were innate immune genes with eight ascribed to lysosomes. Several are known to be elevated in diseased organs of murine models of other lysosomal diseases including Gauchers disease, Sandhoff disease and MPSIIIB. We validated the top candidate lysozyme, in the plasma of Npc1-/- as well as Balb/c Npc1nmf164 mice (bearing a point mutation closer to human disease mutants) and show its reduction in response to an emerging therapeutic. We further established elevation of innate immunity in Npc1-/- mice through multiple functional assays including inhibition of bacterial infection as well as cellular analysis and immunohistochemistry.

We used microarrays on the diseased organs, brain, liver and spleen of the Npc1-/- mice to unserstand the molecular changes occur during the progression of NPC diseases. From the data, we have identified 12 potential genes which can be potentially developed as blood-based biomarker. We have also discovered up regulation of innate iimunity genes in all three organs of Npc1-/- mice and functionally validated them in liver and spleen.

Overall design: Brain from 11 female Npc1/ and 16 control female mice (Npc1+/+ and Npc1+/) from 6 age groups (20-25, 37-40, 54-55, 59-62, 67-71 and 81-84 days) were surgically harvested. Liver and spleen from 6 Npc1-/- and 6 Npc1+/- female mice from three age group ( 20-25, 54-55 and 67-71 days) were surgically harvested. Organs were kept in RNA later and stored at -20 ´C until used. RNA was isolated and Affymetrix mouse 430 2.0 array hybridizations were performed by UCLA Clinical Microarray Core, UCLA, Los Angeles, CA, USA. Subsequent raw data were analyzed using DNA-Chip Analyzer (D-Chip) with the .CEL files obtained from AGCC. Data from Npc1-/- mice from all age groups were compared to control mice (Npc1+/- and/or Npc1-/- mice) from all age groups separately for brain, liver and spleen. 'Matrix Table1' corrsponds for brain, 'Matrix Table2' corresponds for liver and 'Matrix Table3' corresponds for spleen. Thresholds for selecting significant genes were set at a relative difference Â³1.5-fold, absolute difference Â³100 signal intensity units and p<0.05. Genes that met all three criteria simultaneously were considered as significant change.

Background corr dist: KL-Divergence = 0.0594, L1-Distance = 0.0598, L2-Distance = 0.0057, Normal std = 0.5712

0.698 Kernel fit Pairwise Correlations Normal fit

Density 0.349

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 BrainWT 20d Brain Mouse1HET 25d Brain Mouse1 HET(0.0291934) 20d Brain NPCMouse1(0.0164389) 25d Brain NPCMouse1 (0.0160851) 20d Brain HETMouse1 (0.012995) 25d Brain HETMouse1 (0.0169621) 37d Brain NPCMouse1 (0.0123627) 40d Brain NPCMouse1 (0.0116625) 37d Brain HETMouse1 (0.0146711) 40d Brain HETMOuse1 (0.0121971) 54d Brain NPCMouse1 (0.0162545) 55d Brain NPCMouse1 (0.013009) 54d Brain WTMOuse1 (0.0218085) 55dBrain WTMouse1 (0.0189784) 60d Brain Mouse1HET (0.0208057) 60d Brain Mouse2 HET(0.0177552) 59d Brain NPCMouse1(0.0182742) 62d Brain NPCMouse1 (0.0154698) 59d Brain WTMouse1 (0.0125703) 62dBrain HETMouse1 (0.0330674) 67d Brain Mouse1NPC (0.00875221) 67d Brain HETMouse1(0.0146558) 67d Brain HETMouse1 (0.0118786) 81d Brain NPCMouse1 (0.0193042) 82d Brain NPCMouse1 (0.0147372) 82d Brain HETMouse1 (0.0113492) 84d Liver HETMouse1 (0.0191213) 20d Liver Mouse1NPC (0.0207089) 25d Liver Mouse1NPC (0.01304) 20d Liver Mouse1HET (0.0182423) 25d Liver Mouse1HET (0.0142028) 54 Liver Mouse1NPC (0.0146907) 55d Liver (0.0229393)Mouse1NPC 54d Liver Mouse1HET (0.0182837) 55d Liver Mouse1HET (0.0132266) 67d Liver Mouse1NPC (0.0123477) 67d Liver Mouse2NPC (0.0195814) 67 Liver Mouse1HET (0.0238637) 71d Spleen (0.0171116)Mouse1HET Spleen20dNPC (0.0158325) Mouse1 25dSpleenNPC Mouse1 (0.0343377) Spleen20dHET Mouse1 (0.0263598) Spleen25dHET Mouse1 (0.0285949) Spleen54dNPC Mouse1 (0.0311527) 55dSpleenNPC Mouse1 (0.0239298) Spleen54dHET Mouse1 (0.0346566) Spleen55dHET Mouse1 (0.0312578) Spleen67dNPC Mouse1 (0.0224509) 67dSpleenNPC Mouse2 (0.037535) Spleen67 Mouse1 (0.0270904) 71d (0.0239652)Mouse1 (0.0242382)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 24.8 707.0 1043.9 P ( S | Z, I ) = 1.00 Pkd2 544.7 1334.8 2012.0 Mean Corr = 0.69147 Ift88 27.1 332.4 493.2 Dync2h1 163.7 383.6 562.0 Gli2 9.6 573.2 896.3 Pkd1 292.7 892.5 1668.6 Ift46 383.6 1057.2 1455.6 Pafah1b1 359.4 1855.7 3088.2 Ttc8 107.0 586.5 1241.9 1110051M20Rik 120.8 1401.5 2001.8 Wdr19 59.1 509.8 690.3 Zfp354c 72.8 785.3 1321.8 Bbs1 73.5 707.9 1267.1 CEM 1 + Chd6 236.9 897.6 1470.7 Top 10 Genes Glis2 120.8 296.2 529.9 Tbc1d19 174.7 595.3 1213.2 Cc2d2a 230.9 579.7 959.2 Fam115a 50.2 873.7 1241.0

Null module GEO Series "GSE17263" 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=GSE17263 Status: Public on Apr 13 2010 Title: Gene expression profiling of constitutive activation of Smoothened in the mouse uterus Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20130264 Summary & Design: Summary: In order to gain a better understanding of Ihh action during embryo implantation, we constitutively activated Smo in the murine uterus using the PRcre mouse model (PRcre/+SmoM2+; SmoM2). Female SmoM2 mice were infertile. They exhibited normal serum progesterone levels and normal ovulation, but ova failed to be fertilized in vivo and the uterus failed to undergo the artificially induced decidual response. SmoM2 mice exhibited uterine hypertrophy. The endometrium had a reduced number of uterine glands and the endometrial stroma lost its normal morphologic characteristics. Microarray analysis of 3 month old SmoM2 uteri demonstrated a chondrocytic signature and confirmed that constitutive activation of SmoM2 increased extracellular matrix production. Thus, constitutive activation of Smo in the mouse uterus alters the extracellular matrix which interferes with early pregnancy.

Keywords: two group comparison

Overall design: We constitutively activated Hh signaling in the uterus by the expression of a mutant SmoM2 allele. We crossed these mice to the PRcre mouse model to constitutively activate Smo in the murine uterus (PRcre/+SmoM2+; SmoM2). High density DNA microarray analysis was performed on 3 month old control and SmoM2 uteri.

Background corr dist: KL-Divergence = 0.0278, L1-Distance = 0.0182, L2-Distance = 0.0003, Normal std = 0.6861

0.590 Kernel fit Pairwise Correlations Normal fit

Density 0.295

0.000 CEM 1

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

Pre-normalization Quantiles

Control,Control, replicateControl, replicate 1 (0.296481)SmoM2, replicate 2 (0.113764)SmoM2, replicate 3 (0.191123)SmoM2, replicate 1 (0.119529) replicate 2 (0.0897674) 3 (0.189336)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 615.0 1135.3 1235.1 P ( S | Z, I ) = 1.00 Pkd2 2919.4 5544.2 7038.7 Mean Corr = 0.69102 Ift88 312.7 401.4 462.4 Dync2h1 184.6 324.9 367.3 Gli2 735.4 981.0 1188.4 Pkd1 448.1 849.2 919.2 Ift46 1202.0 1436.7 1741.1 Pafah1b1 691.3 873.3 953.5 Ttc8 415.5 616.1 695.4 1110051M20Rik 292.4 488.1 575.1 Wdr19 236.2 313.0 385.6 Zfp354c 199.4 807.6 1080.5 Bbs1 107.4 160.5 226.1 CEM 1 + Chd6 412.0 583.9 624.5 Top 10 Genes Glis2 238.6 812.3 1014.2 Tbc1d19 501.1 781.7 805.4 Cc2d2a 402.2 834.1 986.8 Fam115a 641.7 961.3 1003.3

Null module GEO Series "GSE15872" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.638 Kernel fit Pairwise Correlations Normal fit

Density 0.319

0.000 CEM 1

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

Pre-normalization Quantiles

stomachstomach at E14.5,stomach at biological E14.5,pylorus at biological E14.5, rep1pylorus at E14.5, biological(0.0878717) rep2pylorus at biological E14.5, (0.0465918) rep3duodenum at biological E14.5, (0.0357385) rep1duodenum biological(0.00883935) at rep2 E14.5,duodenum (0.114551) at rep3biological E14.5,stomach (0.0585483) at biological E14.5,stomach rep1 at E16.5, biological(0.0145479)stomach rep2 at biological E16.5, (0.0186886)pylorus rep3 at biological E16.5, (0.0375595)rep1pylorus at E16.5, biological(0.0392379) rep2pylorus at biological E16.5, (0.0136166) rep3duodenum at biological E16.5, (0.0524589) rep1duodenum biological(0.0497551) at rep2 E16.5,duodenum (0.0546378) at rep3biological E16.5, (0.0475586) at biological E16.5, rep1 biological(0.110545) rep2 (0.106711)[ rep3 min (0.102542) ] [ medium ] [ max ] CEM 1 Dync2li1 326.3 660.4 960.2 P ( S | Z, I ) = 1.00 Pkd2 343.9 1437.9 2427.8 Mean Corr = 0.68394 Ift88 195.0 272.0 316.4 Dync2h1 204.5 360.5 438.2 Gli2 221.9 910.0 1435.4 Pkd1 184.0 312.3 488.9 Ift46 754.9 1048.4 1249.6 Pafah1b1 1024.1 1328.4 1894.0 Ttc8 156.5 533.7 960.2 1110051M20Rik 191.8 412.9 713.2 Wdr19 75.0 111.9 141.0 Zfp354c 184.8 670.8 1242.7 Bbs1 43.9 108.6 166.0 CEM 1 + Chd6 237.8 674.6 1071.5 Top 10 Genes Glis2 301.4 802.2 1242.7 Tbc1d19 151.2 538.7 769.8 Cc2d2a 241.5 551.3 665.9 Fam115a 336.3 974.1 1623.4

Null module GEO Series "GSE16073" 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=GSE16073 Status: Public on Oct 22 2009 Title: Expression Data from Pten Null Fibroblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19847259 Summary & Design: Summary: The tumor stroma is believed to contribute to some of the most malignant characteristics of epithelial tumors. However, signaling between stromal and tumor cells is complex and remains poorly understood. Here we show that genetic inactivation of Pten in stromal fibroblasts of mouse mammary glands accelerated the initiation, progression and malignant transformation of mammary epithelial tumors.

Global gene expression profiling in mammary stromal cells identified a Pten-specific signature associated with massive extra-cellular matrix (ECM) remodeling, innate immune cell infiltraion and increased angiogenesis. Execution of this transcriptional program was mediated, in part, by the induction, phosphorylation and recruitment of Ets2 to target promoters. Remarkably, Ets2 inactivation in Pten stroma-deleted tumors was sufficient to decrease tumor growth and progression. These findings identify the Pten-Ets2 axis as a critical stroma-specific signaling pathway that suppresses mammary epithelial tumors.

Overall design: Wild type and Pten null primary mammary fibroblasts isolated from 8 week old female mice were cultured, RNA was extracted and Affymetrix gene expression arrays were performed.

Background corr dist: KL-Divergence = 0.0385, L1-Distance = 0.0292, L2-Distance = 0.0012, Normal std = 0.6328

0.639 Kernel fit Pairwise Correlations Normal fit

Density 0.320

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

Pten nullPten fibroblasts, nullPten fibroblasts, null biologicalWild fibroblasts, type biologicalWild rep1fibroblasts, type biological(0.0954222)Wild rep2fibroblasts, type biological(0.125661) rep3fibroblasts, biological(0.223387) rep1 biological(0.360235) rep2 (0.142742)[ rep3min (0.0525532) ] [ medium ] [ max ] CEM 1 Dync2li1 283.6 543.7 695.0 P ( S | Z, I ) = 1.00 Pkd2 2025.0 2496.6 3318.3 Mean Corr = 0.67633 Ift88 58.3 74.3 100.1 Dync2h1 197.0 255.4 315.6 Gli2 169.1 378.3 902.5 Pkd1 336.3 446.7 554.8 Ift46 1768.7 2474.6 2658.2 Pafah1b1 1373.5 1771.7 1864.8 Ttc8 405.0 490.4 559.8 1110051M20Rik 531.0 663.4 887.6 Wdr19 137.4 184.9 274.0 Zfp354c 222.0 353.8 504.9 Bbs1 17.0 19.9 33.7 CEM 1 + Chd6 114.0 205.3 278.5 Top 10 Genes Glis2 470.5 789.5 1043.2 Tbc1d19 1659.7 2093.6 2188.5 Cc2d2a 284.2 306.3 386.4 Fam115a 820.0 1091.3 1105.3

Null module GEO Series "GSE13563" 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=GSE13563 Status: Public on Nov 15 2008 Title: Pilot study: Basal gene expression in bone Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23182809 Summary & Design: Summary: Pilot study

Analysis of basal gene expression of the protective bones of the skull (parietals), weight-bearing bones of the limb (ulnae) and mandibular bone and teeth #!#

Overall design: RNA extraction from normal bone

Background corr dist: KL-Divergence = 0.0312, L1-Distance = 0.0280, L2-Distance = 0.0008, Normal std = 0.6863

0.603 Kernel fit Pairwise Correlations Normal fit

Density 0.301

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

CalvarialCalvarial bone_1Mandible_1 bone_2(0.0609404)Mandible_2 (0.0935834) (0.102222)Ulna_1 (0.276578) Ulna_2(0.150284) (0.316393) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 133.6 352.4 681.3 P ( S | Z, I ) = 1.00 Pkd2 645.5 1954.1 2019.3 Mean Corr = 0.67627 Ift88 173.5 247.3 316.3 Dync2h1 171.7 320.8 398.7 Gli2 32.3 268.4 448.7 Pkd1 264.0 413.4 454.3 Ift46 286.5 674.3 983.2 Pafah1b1 760.2 967.1 1230.0 Ttc8 121.3 362.3 418.1 1110051M20Rik 238.4 540.2 730.6 Wdr19 115.9 215.7 333.2 Zfp354c 92.3 791.8 881.8 Bbs1 76.5 82.3 190.5 CEM 1 + Chd6 336.8 512.2 586.6 Top 10 Genes Glis2 319.3 744.1 861.3 Tbc1d19 275.4 583.3 737.9 Cc2d2a 241.7 460.7 563.6 Fam115a 80.2 251.7 382.7

Null module GEO Series "GSE40156" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 42 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40156 Status: Public on Oct 30 2013 Title: Transcript atlases reveal that artery tertiary lymphoid organs but not secondary lymphoid organs control key steps of atherosclerosis T cell immunity in aged apoe-/- mice. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Tertiary lymphoid organs (TLOs) emerge in response to nonresolving inflammation but their roles in adaptive immunity remain unknown. Here, we explored artery TLOs (ATLOs) to delineate atherosclerosis T cell responses in apoe-/- mice during aging. Though the T cell repertoire showed systemic age-associated contractions in size and modifications in subtype composition and activation, wt and apoe-/- mice were equally affected. In contrast, ATLOs - but not wt aortae, apoe-/- aorta segments without ATLOs or atherosclerotic plaques - promoted T cell recruitment, altered characteristics of T cell motility, primed and imprinted T cells in situ, generated CD4+/FoxP3-, CD4+/FoxP3+, CD8+/FoxP3- effector and central memory cells, and converted naÃ¯ve CD4+/FoxP3- T cells into induced Treg cells. ATLOs also showed substantially increased antigen presentation capability by conventional dendritic cells (DCs) and monocyte-derived DCs but not by plasmacytoid DCs. Thus, the senescent immune system specifically employs ATLOs to control dichotomic atherosclerosis T cell immune responses. We assembled transcriptome maps of wt and apoe-/- aortae and aorta-draining RLNs and identified ATLOs as major sites of atherosclerosis-specific T cell responses during aging: Transcriptome atlases of wt and apoe-/- abdominal aortae and associated draining RLNs were constructed from laser capture microdissection (LCM)-based whole genome mRNA expression microarrays yielding 6 maps: wt adventitia (tissue-1); wt RLN (tissue-2); apoe-/- ATLOs (tissue-3); apoe-/- RLN (tissue-4); apoe-/- adventitia without adjacent plaques (tissue-5), and plaques (tissue-6). Several two-tissue comparisons within the transcriptome atlases are noteworthy: Unexpectedly, transcriptomes of wt and apoe-/- RLNs were virtually identical; additonal data revealed that transcriptomes of RLNs were strikingly similar to those of inguinal LNs which do not drain the aorta adventitia (as shown of India ink injection experiments of surgically exposed aortae); in sharp contrast, wt adventitia versus ATLOs revealed 1405 differentially expressed transcripts many of which encoded members of GO terms immune response and inflammatory response; the ATLO-plaque comparison also showed > 1000 differentially expressed transcripts; however, wt adventitia versus apoe-/- adventitia without plaque showed few genes (< 5 % of differentially expressed transcripts of the wt adventitia-ATLO comparison). Thus, the aorta transcriptome atlases support the conclusion that neither aorta-draining apoe-/- RLNs nor ILNs participate in atherosclerosis-specific T cell responses. In addition, they demonstrate that T cell responses in the diseased aorta are highly territorialized. Finally, these data show that the immune responses carried out in ATLOs differ significantly from those carried out in plaques. We next identified three major clusters within the transcriptome atlases through ANOVA analyses and application of strict filters: An adventitia cluster, a plaque/ATLO cluster, and a LN/plaque cluster. The total number of differentially expressed genes in each cluster were examined for GO terms immune response, inflammatory response, T cell activation, positive regulation of T cell response, and T cell proliferation. Within the adventitia cluster, similarities of transcriptomes of wt adventitia and apoe-/- adventitia without associated plaque versus ATLOs indicate that a robust number of immune response-regulating genes are selectively expressed in ATLOs which are located within a distance of few ´m of the adventitia without associated plaques indicating a very high degree of territoriality of the atherosclerosis T cell response. Furthermore, unlike the total number of differentially regulated transcripts, the majority of transcripts among GO terms immune response and inflammatory response, was up-regulated. Inspection of the plaque/ATLO cluster provided further information: The majority of immune response regulating genes where expressed at a higher level in ATLOs when compared to plaques though plaques also contained a significant number of immune response regulating genes; the reverse is true for genes regulating inflammation. Finally, the lymph node cluster revealed that though the majority of immune response regulating genes resides in both wt and apoe-/- RLNs (with little differences between them) ATLOs express a selected set of immune response regulating genes at a higher level when compared to LNs. In addition, the inflammatory component of ATLOs when compared to LNs is documented by the finding that many more genes regulating inflammation reside in ATLOs even when compared to those of plaques.

Key words:

T cell response in atherosclerosis; Laser capture microdissection; transcriptome atlas of atherosclerosis.

Citations:

GrÃ¤bner R. et al. Lymphotoxin beta receptor signaling promotes tertiary lymphoid organogenesis in the aorta adventitia of aged ApoE-/- mice. J Exp Med 2009 Jan 16;206(1):233-48. PMID: 19139167;

Moos M. et al. The lamina adventitia is the major site of immune cell accumulation in standard chow-fed apolipoprotein E-deficient mice. Arterioscler Thromb Vasc Biol. 2005 Nov;25(11):2386-91. Epub 2005 Sep 22. PMID: 16179593;

Beer M. et al. Laser-capture microdissection of hyperlipidemic/ApoE-/- mouse aorta atherosclerosis. Methods Mol Biol. 2011;755:417-28. PMID: 21761324;

Weih F. et al. Control of Dichotomic Innate and Adaptive Immune Responses by Artery Tertiary Lymphoid Organs in Atherosclerosis. Front Physiol. 2012;3:226. Epub 2012 Jul 6. PMID: 22783198.

Overall design: Wild-type and apoE-deficient mice on the C57BL/6J genetic background were maintained on a standard mouse chow. Total aortae were removed at the age of 6 (n=3), 32 (n=3), or 78 (n=3) w and microarrays were prepared from total RNA extracts or extracts of atherosclerotic lesions and adventitiae obtained by the use of a laser dissection microscope. In addition, aorta associated LNs or distant LNs were prepared from both mouse genotypes.

Background corr dist: KL-Divergence = 0.1004, L1-Distance = 0.0740, L2-Distance = 0.0098, Normal std = 0.4788

0.955 Kernel fit Pairwise Correlations Normal fit

Density 0.478

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-Aorta-32-weeks-1wt-Aorta-32-weeks-3apoE-Aorta-32-weeks-1 (0.0428558)apoE-Aorta-32-weeks-2 (0.0452873)apoE-Aorta-32-weeks-3wt-Aorta-32-weeks-2 (0.0202882)wt-Aorta-6-weeks-1 (0.0436811)wt-Aorta-6-weeks-2 (0.0154379) (0.021877)wt-Aorta-6-weeks-3 (0.0366668)apoE-Aorta-6-weeks-1 (0.0426495)apoE-Aorta-6-weeks-2 (0.0280171)apoE-Aorta-6-weeks-3 wt-Aorta-78-weeks-1(0.0389701) wt-Aorta-78-weeks-2(0.0540521) wt-Aorta-78-weeks-3(0.0347774) (0.0347543)apoE-Aorta-78-weeks-1 (0.0417761)apoE-Aorta-78-weeks-2 (0.0305931)apoE-Aorta-78-weeks-3apoE-Spleen-32-weeks-1 (0.0109666)apoE-Spleen-32-weeks-2 (0.0126796)apoE-Spleen-32-weeks-3 (0.0128048)apoE-Spleen-78-weeks-1 (0.0135343)apoE-Spleen-78-weeks-2 (0.00816991)apoE-Spleen-78-weeks-3 (0.0205714)wt-Spleen-32-weeks-1 (0.016384)wt-Spleen-32-weeks-2 (0.00946895)wt-Spleen-32-weeks-3 (0.0101653) wt-Spleen-78-weeks-1(0.0133803) wt-Spleen-78-weeks-2(0.024821) wt-Spleen-78-weeks-3(0.0187209) apoE-Blood-32-weeks-1(0.0111368) apoE-Blood-32-weeks-2(0.00658535) apoE-Blood-32-weeks-3(0.00924033)apoE-Blood-78-weeks-1 (0.0159526)apoE-Blood-78-weeks-2 (0.0139573)apoE-Blood-78-weeks-3 (0.0212723)wt-Blood-32-weeks-1 (0.0308171)wt-Blood-32-weeks-2 (0.0223345)wt-Blood-32-weeks-3 (0.0289606) (0.0231676)wt-Blood-78-weeks-1 (0.019425)wt-Blood-78-weeks-2 (0.023775)wt-Blood-78-weeks-3 (0.0242115) (0.0270025) (0.0188108)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 86.1 312.7 999.1 P ( S | Z, I ) = 1.00 Pkd2 136.2 1204.3 4985.1 Mean Corr = 0.66895 Ift88 185.7 346.6 555.8 Dync2h1 413.4 647.4 933.2 Gli2 9.4 71.9 1092.9 Pkd1 439.7 861.6 3439.6 Ift46 362.2 643.4 1573.0 Pafah1b1 754.5 1034.4 1660.4 Ttc8 53.5 253.7 817.5 1110051M20Rik 298.1 483.7 1018.1 Wdr19 102.8 198.9 402.4 Zfp354c 66.5 162.0 858.9 Bbs1 10.7 136.1 414.5 CEM 1 + Chd6 467.3 931.2 1733.9 Top 10 Genes Glis2 78.8 474.7 1992.5 Tbc1d19 89.5 355.9 1370.0 Cc2d2a 39.1 383.5 1150.7 Fam115a 12.0 200.1 821.0

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(0.0200359) 6_2 B_AK_SleepDep_ZT(0.0283999) 6_3 B_AK_SleepDep_ZT(0.0252446) 6_1B_B6_Control_ZT (0.0329742) 6_2B_B6_Control_ZT (0.0188597) 6_3B_B6_Control_ZT (0.0387713) 6_1 B_B6_SleepDep_ZT(0.0215529) 6_2 B_B6_SleepDep_ZT(0.0277928) 6_3 B_B6_SleepDep_ZT(0.0286182) 6_1B_D2_Control_ZT (0.0359729) 6_2B_D2_Control_ZT (0.0299137) 6_3B_D2_Control_ZT (0.0325492) 6_1 B_D2_SleepDep_ZT(0.0245451) 6_2 B_D2_SleepDep_ZT(0.0242796) 6_3 B_D2_SleepDep_ZT(0.0289284) 6_1L_AK_Control_ZT (0.0216137) 6_2L_AK_Control_ZT (0.0379497) 6_3L_AK_Control_ZT (0.0194329) 6_1 L_AK_SleepDep_ZT(0.0371744) 6_2 L_AK_SleepDep_ZT(0.0415628) 6_3 L_AK_SleepDep_ZT(0.0280526) 6_1L_B6_Control_ZT (0.0239404) 6_2L_B6_Control_ZT (0.0226758) 6_3L_B6_Control_ZT (0.0248419) 6_1 (0.0323476)L_B6_SleepDep_ZT 6_2 (0.0266322)L_B6_SleepDep_ZT 6_3 (0.0265744)L_B6_SleepDep_ZT 6_1L_D2_Control_ZT (0.0244062) 6_2L_D2_Control_ZT (0.0275349) 6_3L_D2_Control_ZT (0.0212694) 6_1 (0.0282602)L_D2_SleepDep_ZT 6_2 (0.0312444)L_D2_SleepDep_ZT 6_3 (0.0267774)L_D2_SleepDep_ZT 6_1 (0.0264362) 6_2 (0.0265855) 6_3 (0.026249)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 105.9 381.3 517.2 P ( S | Z, I ) = 1.00 Pkd2 190.1 427.2 578.0 Mean Corr = 0.64815 Ift88 138.9 269.4 421.9 Dync2h1 112.1 420.4 611.4 Gli2 51.3 169.5 335.9 Pkd1 167.8 597.8 856.1 Ift46 955.8 1442.9 1988.4 Pafah1b1 781.8 1556.8 2544.6 Ttc8 138.7 439.8 732.4 1110051M20Rik 79.4 1648.3 2105.9 Wdr19 76.1 284.9 360.9 Zfp354c 43.2 562.4 911.6 Bbs1 46.8 312.9 435.5 CEM 1 + Chd6 100.3 526.7 831.5 Top 10 Genes Glis2 81.4 144.7 228.1 Tbc1d19 88.1 564.4 802.4 Cc2d2a 96.1 308.5 471.1 Fam115a 59.0 1557.9 1965.8

Null module GEO Series "GSE12730" 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=GSE12730 Status: Public on Nov 07 2009 Title: Mouse gestational protein restriction: Newborn offspring liver and hindleg muscle Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19823102 Summary & Design: Summary: Gestational protein restriction is a model for low birth size. We hypothesized that taurine supplementation would protect against changes in newborn liver and muscle caused by a maternal low protein diet.

Overall design: The liver and muscle samples were normalized separately.

Background corr dist: KL-Divergence = 0.0311, L1-Distance = 0.0319, L2-Distance = 0.0015, Normal std = 0.6489

0.615 Kernel fit Pairwise Correlations Normal fit

Density 0.307

0.000 CEM 1

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

Pre-normalization Quantiles

MaternalMaternal normalMaternal normalproteinMaternal normalproteinoffspringMaternal normalproteinoffspring liver,Maternal normalprotein offspringbiological liver,Maternal normalprotein +biological 1%liver, replicate Maternaltaurine lowprotein +biological 1% replicateprotein 1Maternaltaurineoffspring (0.0531662) low+ 1% replicateproteinoffspring 2Maternaltaurineoffspring (0.0274307)low liver, proteinoffspring 3Maternal offspringbiologicalliver, (0.0391717)low liver, protein offspringbiologicalMaternal biologicalliver, low liver, replicate protein +biological Maternal 1%biologicalliver, lowreplicate replicatetaurine 1protein +biological (0.037302) Maternal1% normalreplicate replicate1taurineoffspring 2(0.0287531) + (0.0321114) Maternal1% normalproteinreplicate 2taurineoffspring 3(0.0485841) liver, (0.0430778)Maternal normalproteinoffspring 3 offspringbiological (0.0544238) liver,Maternal normalproteinoffspring muscle,biological liver, Maternalreplicate normalproteinoffspring muscle,biological biological Maternalreplicate normalprotein1+ (0.0293512) 1%muscle, biological Maternalreplicatetaurine replicate lowprotein2+ (0.0232976)1% biologicalprotein Maternaltaurineoffspring replicate low3 +1 (0.0282147) 1%(0.0379879) proteinoffspring Maternaltaurineoffspring replicate low muscle,2 (0.0499964) proteinoffspring Maternaloffspring muscle, low muscle,3 biological (0.0202306) proteinoffspringMaternal muscle, lowbiological muscle, biological protein +replicate 1%muscle, lowbiological biologicaltaurine replicate protein +replicate 1%1 biological (0.0528596) taurineoffspring replicate +replicate1 1%2(0.113892) (0.0543395) taurineoffspring replicate muscle,2[ 3(0.0502289) (0.0133614)min offspring muscle,3 biological (0.048945) ] muscle, biological replicate biological [replicate 1medium (0.0413366) replicate 2 (0.0386078) 3 (0.0333297) ] [ max ] CEM 1 Dync2li1 152.3 290.3 520.3 P ( S | Z, I ) = 1.00 Pkd2 236.6 1977.8 2935.8 Mean Corr = 0.64281 Ift88 148.1 224.4 372.1 Dync2h1 174.8 283.9 455.7 Gli2 76.6 780.1 2383.8 Pkd1 103.8 584.6 1414.9 Ift46 778.8 1070.2 1471.0 Pafah1b1 481.7 752.0 976.3 Ttc8 72.1 211.5 535.1 1110051M20Rik 168.2 309.9 529.7 Wdr19 63.5 82.9 151.3 Zfp354c 42.3 813.4 1436.7 Bbs1 64.7 83.3 110.5 CEM 1 + Chd6 84.1 271.1 711.2 Top 10 Genes Glis2 112.8 568.2 1404.0 Tbc1d19 71.1 191.1 625.7 Cc2d2a 135.6 427.8 613.8 Fam115a 123.4 677.5 1044.8

Null module GEO Series "GSE16675" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 72 -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=GSE16675 Status: Public on Nov 17 2010 Title: The influence of segmental copy number variation on tissue transcriptomes through development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21084671 Summary & Design: Summary: A preliminary understanding of the phenotypic effect of copy number variation (CNV) of DNA segments is emerging. These rearrangements were demonstrated to influence, in a somewhat dose-dependent manner, the expression of genes mapping within. They were shown to also affect the expression of genes located on their flanks, sometimes at great distance. Here, we show by monitoring these effects at multiple life stages, that these controls over expression are effective throughout mouse development. Similarly, we observe that the more specific spatial expression patterns of CNV genes are maintained throughout life. However, we find that some brain-expressed genes appear to be under compensatory loops only at specific time-points, indicating that the influence of CNVs on these genes is modulated through development. We also observe that CNV genes are significantly enriched upon transcripts that show variable time-course of expression in different strains. Thus modifying the number of copy of a gene not only potentially alters its expression level, but possibly also its time of expression.

Keywords: comparative genomic

Overall design: Expression from brain and liver tissues from C57BL/6J, DBA2/J and 129S2 mouse strains at different developmental time points.

Background corr dist: KL-Divergence = 0.0580, L1-Distance = 0.0593, L2-Distance = 0.0060, Normal std = 0.5608

0.711 Kernel fit Pairwise Correlations Normal fit

Density 0.356

0.000 CEM 1

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

Pre-normalization Quantiles

129_E14.5_brain_rep1129_E14.5_brain_rep2129_E14.5_brain_rep3 B6_E14.5_brain_rep1(0.0334637) B6_E14.5_brain_rep2(0.036379) B6_E14.5_brain_rep3(0.0294444) (0.0194402)D2_E14.5_brain_rep1 (0.014626)D2_E14.5_brain_rep2 (0.0211341)D2_E14.5_brain_rep3 (0.0393337)129_E14.5_liver_rep1 (0.0447365)129_E14.5_liver_rep2 (0.0425948)129_E14.5_liver_rep3 (0.00911508)B6_E14.5_liver_rep1 (0.0100668)B6_E14.5_liver_rep2 (0.00964601)B6_E14.5_liver_rep3 (0.015259)D2_E14.5_liver_rep1 (0.0190273)D2_E14.5_liver_rep2 (0.012257)D2_E14.5_liver_rep3 (0.00822195)129_P1_brain_rep1 (0.0076792)129_P1_brain_rep2 (0.00627013)129_P1_brain_rep3 (0.00956907)B6_P1_brain_rep1 (0.00643907)B6_P1_brain_rep2 (0.00915249)B6_P1_brain_rep3 (0.0103263)D2_P1_brain_rep1 (0.00626545)D2_P1_brain_rep2 (0.00564138)D2_P1_brain_rep3 (0.0137103)129_P1_liver_rep1 (0.0136041)129_P1_liver_rep2 (0.0117755)129_P1_liver_rep3 (0.00869835)B6_P1_liver_rep1 (0.0117985)B6_P1_liver_rep2 (0.0145849)B6_P1_liver_rep3 (0.00944935)D2_P1_liver_rep1 (0.0110629)D2_P1_liver_rep2 (0.0145371)D2_P1_liver_rep3 (0.0102003)129_P7_brain_rep1 (0.00986471)129_P7_brain_rep2 (0.00789093)129_P7_brain_rep3 (0.00799597)B6_P7_brain_rep1 (0.00669975)B6_P7_brain_rep2 (0.00613112)B6_P7_brain_rep3 (0.00907541)D2_P7_brain_rep1 (0.00723655)D2_P7_brain_rep2 (0.0159493)D2_P7_brain_rep3 (0.00958196)129_P7_liver_rep1 (0.0107137)129_P7_liver_rep2 (0.0139727)129_P7_liver_rep3 (0.00870521)B6_P7_liver_rep1 (0.00747111)B6_P7_liver_rep2 (0.00684609)B6_P7_liver_rep3 (0.0117711)D2_P7_liver_rep1 (0.0104208)D2_P7_liver_rep2 (0.00968561)D2_P7_liver_rep3 (0.00721649)129_P90_brain_rep1 (0.00790085)129_P90_brain_rep2 (0.00783948)129_P90_brain_rep3 (0.0121595)B6_P90_brain_rep1 (0.0141825)B6_P90_brain_rep2 (0.0125983)B6_P90_brain_rep3 (0.0146218)D2_P90_brain_rep1 (0.015038)D2_P90_brain_rep2 (0.0142093)D2_P90_brain_rep3 (0.0134139)129_P90_liver_rep1 (0.0128158)129_P90_liver_rep2 (0.0119446)129_P90_liver_rep3 (0.0210528)B6_P90_liver_rep1 (0.0172362)B6_P90_liver_rep2 (0.0163997)B6_P90_liver_rep3 (0.0152843)D2_P90_liver_rep1 (0.0159699)D2_P90_liver_rep2 (0.0137836)D2_P90_liver_rep3 (0.016901) (0.0190153) (0.0148944)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 106.3 651.5 1283.4 P ( S | Z, I ) = 1.00 Pkd2 374.6 697.6 1441.4 Mean Corr = 0.64565 Ift88 168.6 373.7 616.0 Dync2h1 200.3 595.7 950.0 Gli2 35.7 227.3 1281.8 Pkd1 156.2 372.7 818.1 Ift46 710.3 1180.3 1917.6 Pafah1b1 635.1 1879.7 4442.6 Ttc8 114.7 411.1 897.7 1110051M20Rik 165.5 1369.6 1977.3 Wdr19 72.0 270.0 423.5 Zfp354c 41.1 676.0 1402.1 Bbs1 37.8 439.8 720.0 CEM 1 + Chd6 175.3 691.5 1526.7 Top 10 Genes Glis2 83.1 515.5 905.7 Tbc1d19 97.1 896.6 1307.3 Cc2d2a 147.7 394.7 584.0 Fam115a 65.5 1142.7 1838.5

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_ (0.0555924) 12w_rep1lung_9V/null_ (0.0174661) 12w_rep2lung_9V/null_ (0.0127568) 18w_rep1lung_9V/null_ (0.0240763) 18w_rep2lung_9V/null_ (0.0254639) 28w_rep1liver_9V/null_ (0.0147736) 28w_rep2liver_9V/null_ (0.0118405) 4w_rep1liver_9V/null_ (0.00751575) 4w_rep2liver_9V/null_ (0.0262752) 12w_rep1liver_9V/null_ (0.0235401) 12w_rep2liver_9V/null_ (0.0173224) 18w_rep1liver_9V/null_ (0.0200149) 18w_rep2liver_9V/null_ (0.0236463) 28w_rep1lung_4L_ (0.0177112) 28w_rep2lung_4L_ (0.0132121)4w_rep1lung_4L_ (0.0135675)4w_rep2 (0.0142008)lung_4L_ 12w_rep1 (0.0188192)lung_4L_ 12w_rep2 (0.0251734)lung_4L_ 18w_rep1 (0.0219104)lung_4L_ 18w_rep2 (0.0435207)lung_4L_ 28w_rep1 (0.0345322)liver_4L_ 28w_rep2 (0.0650948)liver_4L_ 4w_rep1 (0.0832277)liver_4L_ 4w_rep2 (0.0157263)liver_4L_ 12w_rep1 (0.0236651)liver_4L_ 12w_rep2 (0.0285515)liver_4L_ 18w_rep1 (0.02061)liver_4L_ 18w_rep2 (0.0245816)liver_4L_ 28w_rep1 (0.0221867)lung_WT_ 28w_rep2 (0.0181777)lung_WT_ 28w_rep1 (0.0199884)lung_WT_ 28w_rep2 (0.0394726)lung_WT_ 28w_rep3 (0.0290232)liver_WT_ 28w_rep4 (0.0402389)liver_WT_ 28w_rep1 (0.0205074)liver_WT_ 28w_rep2 (0.0263517) 28w_rep3 (0.0204913) (0.0191736)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 86.9 951.7 2471.7 P ( S | Z, I ) = 1.00 Pkd2 126.4 1562.8 3443.7 Mean Corr = 0.59371 Ift88 109.1 267.2 666.7 Dync2h1 65.1 257.4 533.0 Gli2 4.1 87.2 667.3 Pkd1 74.8 410.0 1336.7 Ift46 1048.6 1705.6 2985.2 Pafah1b1 423.0 793.6 1894.7 Ttc8 110.0 218.5 507.2 1110051M20Rik 107.7 482.2 1062.5 Wdr19 44.5 204.8 674.6 Zfp354c 10.4 114.3 295.2 Bbs1 4.2 86.8 244.4 CEM 1 + Chd6 75.4 202.5 529.4 Top 10 Genes Glis2 58.1 945.4 1773.9 Tbc1d19 139.9 994.5 1493.4 Cc2d2a 96.8 356.0 733.2 Fam115a 65.1 339.0 694.5

Null module GEO Series "GSE38257" 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=GSE38257 Status: Public on Dec 21 2012 Title: A Novel Tumor suppressor network in squamous malignancies Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23145321 Summary & Design: Summary: The specific ablation of Rb1 gene in stratified epithelia (RbF/F;K14cre) promotes proliferation and altered differentiation but is insufficient to produce spontaneous tumors. The pRb relative, p107, compensates some of the functions of pRb in these tissues, however RbF/F;K14cre;p107-/- mice die postnatally. Acute pRb loss in stratified epithelia, using an inducible mouse model (RbF/F;K14creERTM), shows that p107 exerts specific tumor suppressor functions in its absence. After simultaneous absence of pRb and p107, p53 transcriptional function is impaired and Pten expression is reduced. All mutant mice develop spontaneous squamous tumors carcinomas rapidly. Gene expression analysis of mouse tumors, besides supporting the impaired p53 function and the susceptibility to Akt/mTOR inhibitors, also revealed significant overlap with human squamous carcinomas. Thus, RbF/F;K14creERTM;p107-/- may constitute a new mouse model for these malignancies. Collectively, these data demonstrate the existence of a previously unreported functional connection between pRb, Pten and p53 tumor suppressors, through p107, of a particular relevance in squamous tumor development.

Overall design: Gene expression was compared between normal mouse skin and carcinomas arising in the skin of RbF/F;K14creERTM;p107-/- mouse. All mice were treated with tamoxifen.

Background corr dist: KL-Divergence = 0.0326, L1-Distance = 0.0283, L2-Distance = 0.0009, Normal std = 0.6484

0.639 Kernel fit Pairwise Correlations Normal fit

Density 0.320

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

Skin_Normal_1Skin_Normal_2Skin_Normal_3 (0.240378)Skin_Normal_4 (0.210485)Rb_p107_carcinoma_rep1 (0.147621)Rb_p107_carcinoma_rep2 (0.0740444)Rb_p107_carcinoma_rep3Rb_p107_carcinoma_rep4 (0.0276886)Rb_p107_carcinoma_rep5 (0.00966265)Rb_p107_carcinoma_rep6 (0.0383983)Rb_p107_carcinoma_rep7 (0.0524975)Rb_p107_carcinoma_rep8 (0.0186597)Rb_p107_carcinoma_rep9 (0.0387701)Rb_p107_carcinoma_rep10 (0.0375361) (0.0259408) (0.0260523) (0.052265)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 196.7 245.8 394.6 P ( S | Z, I ) = 1.00 Pkd2 147.1 229.4 1515.0 Mean Corr = 0.62582 Ift88 251.0 278.1 330.8 Dync2h1 165.8 210.8 334.7 Gli2 261.6 389.9 793.3 Pkd1 139.3 216.4 1320.6 Ift46 1075.0 1247.4 2352.6 Pafah1b1 631.1 775.0 1258.6 Ttc8 215.9 302.8 544.7 1110051M20Rik 296.0 354.4 567.6 Wdr19 64.7 80.6 114.9 Zfp354c 49.2 64.9 262.8 Bbs1 75.6 87.8 101.7 CEM 1 + Chd6 169.1 216.7 548.9 Top 10 Genes Glis2 144.3 221.1 1013.6 Tbc1d19 86.8 139.1 654.2 Cc2d2a 232.1 303.5 518.5 Fam115a 89.0 159.7 370.9

Null module GEO Series "GSE25423" 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=GSE25423 Status: Public on Dec 31 2013 Title: LSD1 knockdown in 3T3-L1 preadipocytes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23595969 Summary & Design: Summary: Obesity is often associated with a low-grade systemic inflammation state that contributes to the development of insulin resistance and atherosclerotic complications. This is usually coupled with increased macrophage infiltration in the adipose tissue and a defect in adipocyte differentiation that results in accumulation of hypertrophic fat cells characterized by a deregulated pattern of adipokine expression. Here we show that knockdown of histone demethylase lsd1 in 3T3-L1 preadipocytes results in defective adipogenesis and derepression of an inflammatory program in these cells.

Overall design: The 24h sample groups (siC.24h and siLsd1.24h) consist of two biological replicate samples; the 48h sample groups (siC.48h and siLsd1.48h) consist of three biological replicate samples. Each sample was hybridized to a separate array, for a total of ten arrays.

Background corr dist: KL-Divergence = 0.0685, L1-Distance = 0.0356, L2-Distance = 0.0017, Normal std = 0.5250

0.795 Kernel fit Pairwise Correlations Normal fit

Density 0.397

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 siControl3T3-L1 siControl3T3-L1 24h, biologicalsiLSD13T3-L1 24h, biologicalsiLSD13T3-L124h, rep biological 1 siControl3T3-L124h, (0.0581573) rep biological 2 siControl 3T3-L1 rep(0.0641568) 48h, 1 (0.197653) biologicalsiControl 3T3-L1rep 48h, 2 (0.176717) biologicalsiLSD13T3-L1 48h,rep 1 biologicalsiLSD13T3-L148h, (0.173905) rep biological 2 siLSD148h, (0.109501) rep biological 3 48h, rep(0.0996127) 1 biological (0.0264897) rep 2 (0.014646) [rep min 3 (0.0791618) ] [ medium ] [ max ] CEM 1 Dync2li1 1004.2 1818.3 2327.2 P ( S | Z, I ) = 1.00 Pkd2 4576.3 7149.3 8277.5 Mean Corr = 0.56471 Ift88 194.9 308.1 396.7 Dync2h1 145.9 183.0 244.4 Gli2 977.3 1172.1 1261.2 Pkd1 411.9 610.4 712.2 Ift46 1144.2 1805.9 2615.6 Pafah1b1 1220.8 1573.2 1944.1 Ttc8 695.5 1048.7 1264.5 1110051M20Rik 829.6 1063.0 1361.2 Wdr19 335.0 533.4 667.8 Zfp354c 93.2 281.4 646.5 Bbs1 163.5 273.5 389.2 CEM 1 + Chd6 340.3 564.6 885.2 Top 10 Genes Glis2 1707.5 2599.1 2824.8 Tbc1d19 932.4 1234.0 1474.2 Cc2d2a 454.0 859.9 1090.8 Fam115a 602.1 890.2 1155.4

Null module GEO Series "GSE20696" 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=GSE20696 Status: Public on Sep 30 2010 Title: Expression profiling of 3T3-L1 adipogenesis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20887899 Summary & Design: Summary: 3T3-L1 pre-adipocyte cells were grown to confluence and induced to differentiate in adipogeneic media.

Overall design: Two technical replicates from four time points relative to induction of adipogenesis (day 0)

Background corr dist: KL-Divergence = 0.0408, L1-Distance = 0.0317, L2-Distance = 0.0012, Normal std = 0.6378

0.651 Kernel fit Pairwise Correlations Normal fit

Density 0.325

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_t1_rep13T3-L1_t1_rep23T3-L1_t2_rep1 (0.0427977)3T3-L1_t2_rep2 (0.00890585)3T3-L1_t3_rep1 (0.374613)3T3-L1_t3_rep2 (0.139559)3T3-L1_t4_rep1 (0.0698785)3T3-L1_t4_rep2 (0.0890308) (0.103447) (0.171769) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 502.1 1006.8 1718.3 P ( S | Z, I ) = 1.00 Pkd2 1825.4 4130.4 5381.9 Mean Corr = 0.54499 Ift88 361.9 417.4 517.7 Dync2h1 266.9 309.0 391.1 Gli2 808.7 1127.4 1763.5 Pkd1 786.7 1009.5 1353.6 Ift46 1185.0 1666.6 2092.1 Pafah1b1 784.5 965.5 1236.2 Ttc8 612.7 1308.0 1508.9 1110051M20Rik 319.0 772.7 935.0 Wdr19 108.2 291.0 488.1 Zfp354c 62.5 353.2 700.7 Bbs1 101.9 139.9 269.4 CEM 1 + Chd6 491.5 549.0 1090.1 Top 10 Genes Glis2 343.4 1635.1 1954.2 Tbc1d19 1102.7 1759.7 2064.9 Cc2d2a 224.6 728.6 1067.7 Fam115a 1455.9 2168.3 2877.5

Null module GEO Series "GSE6383" 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=GSE6383 Status: Public on Mar 12 2007 Title: Mouse small intestine epithelium vs. mesenchyme Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17299133 Summary & Design: Summary: During organogenesis of the intestine, reciprocal crosstalk between the endodermally-derived epithelium and the underlying mesenchyme is required for regional patterning and proper differentiation. Though both of these tissue layers participate in patterning, the mesenchyme is thought to play a prominant role in the determination of epithelial phenotype during development and in adult life. However, the molecular basis of this instructional dominance is unclear. In fact, surprisingly little is known about the cellular origins of many of the critical signaling molecules and the gene transcriptional events that they impact. Here, we profile genes that are expressed in separated mesenchymal and epithelial compartments of the perinatal mouse intestine. The data indicate that the vast majority of soluble modulators of signaling pathways such as Hedgehog, Bmp, Wnt, Fgf and Igf are expressed predominantly or exclusively by the mesenchyme, accounting for its ability to dominate instructional crosstalk. We also catalog the most highly enriched transcription factors in both compartments and find evidence for a major role for Hnf4alpha and Hnf4 gamma in the regulation of epithelial genes. Finally, we find that while epithelially enriched genes tend to be highly tissue-restricted in their expression, mesenchymally-enriched genes tend to be broadly expressed in multiple tissues. Thus, the unique tissue-specific signature that characterizes the intestinal epithelium is instructed and supported by a mesenchyme that itself expresses genes that are largely non-tissue specific.

Keywords: comparative genomic hybridization: epithelium vs. mesenchyme

Overall design: Mouse small intestine (E18.5) is separated to epithelium and mesenchyme. Total RNA is extracted from epithelium and mesenchyme. There are 6 samples in this microarray experiment: 3 for epithelium and 3 for mesenchyme. Samples are hybridized the affymetrix Mouse Genome 430 2.0 Array. We compare the gene expression between epithelium and mesenchyme to study the gene expression profiles in these two compartments.

Background corr dist: KL-Divergence = 0.0057, L1-Distance = 0.0149, L2-Distance = 0.0002, Normal std = 0.9832

0.414 Kernel fit Pairwise Correlations Normal fit

Density 0.207

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

small intestinesmall intestine smallEPI-MES intestine smallEPI-MES Epi intestineA small EPI-MES(0.155319) Epi intestineB small Mes(0.186226) Epi A intestineC (0.1955) Mes(0.162616) B (0.187945) Mes C (0.112393)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 421.2 654.8 801.8 P ( S | Z, I ) = 1.00 Pkd2 196.5 1852.2 2323.4 Mean Corr = 0.54295 Ift88 493.5 668.6 753.9 Dync2h1 518.5 716.6 752.2 Gli2 506.7 1496.1 1887.2 Pkd1 342.1 1057.9 1334.4 Ift46 823.1 1222.0 1430.2 Pafah1b1 656.3 921.0 992.5 Ttc8 72.8 463.0 505.6 1110051M20Rik 555.7 992.5 1083.9 Wdr19 171.0 271.0 327.4 Zfp354c 135.8 566.9 580.8 Bbs1 138.9 235.9 305.5 CEM 1 + Chd6 108.3 801.8 1011.3 Top 10 Genes Glis2 306.2 1334.4 1403.7 Tbc1d19 118.2 821.4 864.1 Cc2d2a 366.6 654.8 821.4 Fam115a 441.1 859.3 943.6

Null module GEO Series "GSE30488" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 52 -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=GSE30488 Status: Public on Aug 31 2012 Title: Expression data from E2f7/E2f8/E2f3a null placentas and embryos Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22516201 Summary & Design: Summary: To understand the underlying cause and mechanisms of embryonic lethality observed in combined loss of E2f7 and E2f8, we compared global gene expression profiles of wild type, germline deleted and sox2-Cre/Cyp19-Cre deleted embryos and placentas.

Overall design: RNA was extracted from E10.5 embryos and placentas. Gene deletion in samples confirmed by PCR genotyping of DNA isolated from each sample.

Background corr dist: KL-Divergence = 0.0427, L1-Distance = 0.0236, L2-Distance = 0.0008, Normal std = 0.5868

0.680 Kernel fit Pairwise Correlations Normal fit

Density 0.340

0.000 CEM 1

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

Pre-normalization Quantiles

E2f3a-/-;E2f7-/-;E2f8-/-E2f3a-/-;E2f7-/-;E2f8-/-E2f3a-/-;E2f7-/-;E2f8-/- E2f3a-/-;E2f7-/-;E2f8-/-embryo E2f3a-/-;E2f7-/-;E2f8-/-embryo 3a78KO E2f3a-/-;E2f7+/+;E2f8+/+embryo 3a78KO 1 (0.0118576) E2f3a-/-;E2f7+/+;E2f8+/+embryo 3a78KO 2 (0.0121506) E2f3a-/-;E2f7+/+;E2f8+/+embryo 3a78KO 3 (0.0104035)E2f3a-/-;E2f7+/+;E2f8+/+ 3a78KO 4embryo (0.0079741)E2f3a+/+;E2f7-/-;E2f8-/- 5embryo 3KO (0.0128401) E2f3a+/+;E2f7-/-;E2f8-/-1 (0.0123848)embryo 3KO E2f3a+/+;E2f7-/-;E2f8-/-2 (0.0131699)embryo 3KO E2f3a+/+;E2f7-/-;E2f8-/-3 embryo (0.0138729) 3KO Cyp19Cre+;E2f7F/F;E2f8F/F4 embryo 78KO(0.0158851) Cyp19Cre+;E2f7F/F;E2f8F/F1 embryo 78KO(0.0285336) Cyp19Cre+;E2f7F/F;E2f8F/F2 embryo 78KO(0.0416126) Sox2Cre+;E2f7F/-;E2f8F/-3 78KO(0.0310808) embryo Sox2Cre+;E2f7F/-;E2f8F/-4 (0.0388119) embryo Cyp19Sox2Cre+;E2f7F/-;E2f8F/- embryo 1Cyp19 Sox2Cre+;E2f7F/-;E2f8F/-(0.0241878) embryo 2Cyp19 E2f3a+/+;E2f7+/+;E2f8+/+(0.0193244) embryo Sox2 3 E2f3a+/+;E2f7+/+;E2f8+/+(0.0170589) 1 embryo (0.0141702)sox2E2f3a+/+;E2f7+/+;E2f8+/+ 2 embryo (0.0147061)sox2E2f3a+/+;E2f7+/+;E2f8+/+ 3 embryo (0.0166354)sox2E2f3a+/+;E2f7+/+;E2f8+/+ 4 embryo (0.0190571)WT E2f3a+/+;E2f7+/+;E2f8+/+1 (0.0248456) embryo WT E2f3a-/-;E2f7-/-;E2f8-/-2 (0.0279105) embryo WT E2f3a-/-;E2f7-/-;E2f8-/-3 (0.0156648) embryo WT E2f3a-/-;E2f7-/-;E2f8-/-4 (0.0136847) embryo WT E2f3a-/-;E2f7-/-;E2f8-/-placenta5 (0.0209657) WT E2f3a-/-;E2f7-/-;E2f8-/-placenta6 3a78KO(0.0142862) E2f3a-/-;E2f7+/+;E2f8+/+placenta 3a78KO 1 (0.022757) E2f3a-/-;E2f7+/+;E2f8+/+placenta 3a78KO 2 (0.0141531) E2f3a-/-;E2f7+/+;E2f8+/+placenta 3a78KO 3 (0.0138385)E2f3a-/-;E2f7+/+;E2f8+/+ 3a78KO placenta4 (0.0198911)E2f3a+/+;E2f7-/-;E2f8-/- placenta5 3KO (0.0184214)E2f3a+/+;E2f7-/-;E2f8-/- 1 placenta (0.0192181) 3KOE2f3a+/+;E2f7-/-;E2f8-/- 2 placenta (0.0313886) 3KOE2f3a+/+;E2f7-/-;E2f8-/- placenta3 (0.0450706) 3KOCyp19Cre+;E2f7F/F;E2f8F/F placenta4 78KO(0.0261232)Cyp19Cre+;E2f7F/F;E2f8F/F placenta1 78KO(0.0113395)Cyp19Cre+;E2f7F/F;E2f8F/F placenta2 78KO(0.0110785)Sox2Cre+;E2f7F/-;E2f8F/- 3 78KO(0.0121169) placentaSox2Cre+;E2f7F/-;E2f8F/- 4 (0.0141865) placenta Sox2Cre+;E2f7F/-;E2f8F/-cyp 19 placenta 3Sox2Cre+;E2f7F/-;E2f8F/-Cyp19 (0.0254186) placenta 1E2f3a+/+;E2f7+/+;E2f8+/+Cyp19 (0.0182749) placenta sox2 2E2f3a+/+;E2f7+/+;E2f8+/+ (0.019982) 1placenta (0.0194881)sox2E2f3a+/+;E2f7+/+;E2f8+/+ 2placenta (0.0150095)sox2E2f3a+/+;E2f7+/+;E2f8+/+ 3placenta (0.0189864)sox2E2f3a+/+;E2f7+/+;E2f8+/+ 4placenta (0.0159341)WTE2f3a+/+;E2f7+/+;E2f8+/+ 1 (0.0144068)placenta WT 2 (0.0122436)placenta WT 3 (0.0158143)placenta WT 4 (0.0177749)placenta WT[ 5 min(0.0195432) WT 6 (0.0344657) ] [ medium ] [ max ] CEM 1 Dync2li1 215.9 565.9 1262.8 P ( S | Z, I ) = 1.00 Pkd2 257.8 1163.0 1902.9 Mean Corr = 0.52697 Ift88 189.1 342.7 548.1 Dync2h1 198.3 406.2 1036.7 Gli2 55.3 1953.4 3355.0 Pkd1 277.1 350.8 803.4 Ift46 957.8 1640.7 2513.8 Pafah1b1 962.0 1834.9 3036.1 Ttc8 197.4 704.6 931.0 1110051M20Rik 241.2 805.3 1086.9 Wdr19 132.4 221.7 454.3 Zfp354c 50.7 848.7 1763.4 Bbs1 62.8 301.4 400.7 CEM 1 + Chd6 182.5 528.5 866.9 Top 10 Genes Glis2 450.1 954.7 1540.2 Tbc1d19 459.5 857.7 1354.1 Cc2d2a 107.9 369.7 619.0 Fam115a 192.5 1170.2 1839.3

Null module GEO Series "GSE21568" 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=GSE21568 Status: Public on Jan 12 2011 Title: Mouse bulge (CD34+CD200+CD49+) versus secondary hair germ (CD34-CD200+CD49+) versus interfollicular epidermis (CD34-CD200-CD49+) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21206086 Summary & Design: Summary: Mouse back skin was disassociated to single cells, sorted by cell surface markers and tested by microarrray

To compare the gene expression of mouse bulge (CD34+CD200+CD49+) versus secondary hair germ (CD34-CD200+CD49+) versus interfollicular epidermis (CD34-CD200-CD49+)

Bald scalp retains hair follicle stem cells but lacks CD200-rich and CD34-positive hair follicle progenitor cells

Androgenetic alopecia (AGA) or common baldness results from a marked decrease in hair follicle size. This miniaturization may be related to loss of hair follicle stem or progenitor cells. To test this hypothesis, we analyzed bald and non-bald scalp from the same individuals for the presence of hair follicle stem and progenitor cells using flow cytometry to quantitate cells expressing CYTOKERATIN 15 (KRT15), CD200, CD34 and ALPHA-6-INTEGRIN (ITGA6). High levels of KRT15 expression correlated with stem cell properties of small cell size and quiescence. Cells with the highest level of KRT15 expression were maintained in bald scalp; however, distinct populations of CD200high ITGA6high cells and CD34-positive cells were markedly diminished. Consistent with a progenitor cell phenotype, the diminished populations localized closely to the stem-cell rich bulge area but were larger and more proliferative than the bulge stem cells. In functional assays, analogous CD200 high /Itga6 high cells from murine hair follicles were multipotent and generated new hair follicles in skin reconstitution assays. These findings suggest that a defect in stem cell activation plays a role in the pathogenesis of AGA.

Overall design: 4 independent biologic replicates (each pooled from 3 distinct mice) were sorted for Mouse bulge (CD34+CD200+CD49+) versus secondary hair germ (CD34-CD200+CD49+) versus interfollicular epidermis (CD34-CD200-CD49+)

Background corr dist: KL-Divergence = 0.0683, L1-Distance = 0.0257, L2-Distance = 0.0012, Normal std = 0.5061

0.788 Kernel fit Pairwise Correlations Normal fit

Density 0.394

0.000 CEM 1

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

Pre-normalization Quantiles

CD34+CD200+CD49+Replicate1CD34+CD200+CD49+Replicate2CD34+CD200+CD49+Replicate3CD34+CD200+CD49+Replicate4CD34-CD200+CD49+Replicate1 (0.280285)CD34-CD200+CD49+Replicate2 (0.105775)CD34-CD200+CD49+Replicate3 (0.130376)CD34-CD200+CD49+Replicate4 (0.145981)CD34-CD200-CD49+Replicate1 (0.0579657)CD34-CD200-CD49+Replicate2 (0.0557245)CD34-CD200-CD49+Replicate3 (0.0650275)CD34-CD200-CD49+Replicate4 (0.0370841) (0.0258816) (0.0390583) (0.026801)[ (0.0300406) min ] [ medium ] [ max ] CEM 1 Dync2li1 210.7 337.7 832.0 P ( S | Z, I ) = 1.00 Pkd2 575.3 868.7 1917.0 Mean Corr = 0.54711 Ift88 260.7 339.3 438.1 Dync2h1 158.6 203.6 532.0 Gli2 74.7 1092.3 3128.6 Pkd1 444.8 512.1 1860.1 Ift46 686.2 926.7 1156.7 Pafah1b1 945.7 1397.0 1681.9 Ttc8 279.9 435.7 621.9 1110051M20Rik 711.4 1252.4 1553.7 Wdr19 300.1 334.4 595.9 Zfp354c 77.3 155.0 508.6 Bbs1 120.8 175.6 390.7 CEM 1 + Chd6 571.7 775.1 2297.7 Top 10 Genes Glis2 169.9 270.1 652.3 Tbc1d19 789.5 983.3 1895.1 Cc2d2a 487.8 1094.5 1760.8 Fam115a 199.8 265.1 574.0

Null module GEO Series "GSE45820" 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=GSE45820 Status: Public on May 19 2014 Title: Expression data from murine cardiac fibroblasts and endothelial cells following Transverse Aortic Constriction Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Accumulation of activated cardiac fibroblasts plays a key role in heart failure progression. These cells deposit excessive extracellular matrix that leads to mechanical stiffness, myocyte uncoupling and ischemia. To investigate whether two developmentally distinct cardiac fibroblast populations exhibit distinct expression profiles in response to cardiac injury, and therefore might necessitate distinct therapeutic targeting, we performed microarray analysis on FACS sorted cells. Tie2cre lineage traced CFs, non Tie2cre lineage traced cardiac fibroblasts and endothelial cells were isolated from left ventricle of SHAM operated and banded hearts at the onset of fibrosis, one week after surgery.

We used microarrays to detail the global programme of gene expression in cardiac fibroblasts and endothelium following pressure overload. Tie2cre lineage traced, non-tie2cre lineage traced fibroblasts and endothelial cells were sorted from left ventricle of 3 SHAM operated and 3 TAC operated adult male Black Swiss mice.

Overall design: Tie2cre lineage traced, non-tie2cre lineage traced fibroblasts and endothelial cells were sorted from left ventricle of 3 SHAM operated and 3 Transaortic Constriction (TAC) operated adult male Black Swiss mice for RNA extraction and Affymetrix microarray analysis. Hypertrophy in TAC animals, an lack of hypertrophy in SHAM operated animals, was evaluated by hemodynamic measurements before surgery and one week after surgery. Cells were isolated one week after surgery.

Background corr dist: KL-Divergence = 0.0132, L1-Distance = 0.0279, L2-Distance = 0.0011, Normal std = 0.8360

0.477 Kernel fit Pairwise Correlations Normal fit

Density 0.239

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

Tie2cre Tie2crelineage Tie2cre lineagetraced Tie2cre fibroblastnon-lineagetraced Endothelialfibroblastnon-lineage SHAM, tracedEndothelial BiologicalTAC, cells fibroblasttraced Biological SHAM, cellsfibroblast Replicate SHAM, BiologicalTAC, Replicate BiologicalTAC, 1 (0.0692641) ReplicateBiological 1[ (0.0929395) minReplicate 1 Replicate (0.373821) ] 1 (0.0790118)(0.240393) 1 (0.144571)[ medium ] [ max ] CEM 1 Dync2li1 158.1 761.7 812.9 P ( S | Z, I ) = 1.00 Pkd2 1911.6 3850.2 4174.0 Mean Corr = 0.51315 Ift88 129.8 357.8 426.1 Dync2h1 39.7 186.9 224.3 Gli2 36.6 1242.9 1268.0 Pkd1 628.3 2136.8 2362.9 Ift46 663.9 1485.8 1601.4 Pafah1b1 957.7 1338.0 1453.3 Ttc8 41.1 357.6 544.0 1110051M20Rik 190.1 609.3 632.6 Wdr19 93.0 183.6 338.5 Zfp354c 65.8 705.4 1013.6 Bbs1 76.5 144.7 236.2 CEM 1 + Chd6 175.2 225.3 278.6 Top 10 Genes Glis2 329.6 3668.6 4439.6 Tbc1d19 820.8 959.6 1125.5 Cc2d2a 138.2 588.6 704.7 Fam115a 439.9 1456.3 1942.5

Null module GEO Series "GSE9297" 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=GSE9297 Status: Public on Nov 01 2008 Title: Genomic profile of IL10-/- knocked out colitis model Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Objetives: study and characterization of the IL10-/- knocked out colitis model in mice at genomic level and the study of the influence of bacteria in the development of the disease.

Keywords: Differentially expressed genes analysis

Overall design: RNA was extracted from homogenized full-thickness colonic tissues in TrizolÂ® reagent (Invitrogen) and purified with RNeasy affinity columns (Qiagen), according to manufacturerÂ´s protocol. The microarray analysis was performed by Progenika Biopharma (Bilbao, Spain) on GeneChipÂ® Rat Genome 230 2.0 Array (Affymetrix). All sample labeling (biotin), hybridization, staining and scanning procedures were carried out using Affimetrix, standard protocols (www.affymetrix.com). Normalization was carried out using Bioconductor sofware (affyPLM package).

Background corr dist: KL-Divergence = 0.1442, L1-Distance = 0.0387, L2-Distance = 0.0024, Normal std = 0.3895

1.052 Kernel fit Pairwise Correlations Normal fit

Density 0.526

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

7CC, replicate7CC, replicate 17CC, (0.0297026) replicate 27SPF, (0.0154426) replicate 37SPF, (0.00859875) replicate7SPF, 1 (0.0274329) replicate7WT, 2 (0.0127772) replicate7WT, 3 (0.0072317) replicate 17WT, (0.0152439) replicate 29CC, (0.0482565) replicate 39CC, (0.0393414) replicate 19CC, (0.0797344) replicate 29SPF, (0.028736) replicate 39SPF, (0.0187606) replicate9SPF, 1 (0.0048641) replicate9WT, 2 (0.0194552) replicate9WT, 3 (0.0846625) replicate 19WT, (0.0267216) replicate 212CC, (0.0161931) replicate 312CC, (0.0313163) replicate12CC, 1 (0.0491493) replicate12SPF, 2 (0.0167038) 12SPF,replicate 3 (0.0221118) 12SPF,replicate 1 (0.118101) 12WT,replicate 2 (0.0200773) replicate12WT, 3 (0.104654) replicate12WT, 1 (0.0123586) replicate 2 (0.114875) 3 (0.027498) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 114.8 194.6 225.4 P ( S | Z, I ) = 1.00 Pkd2 312.4 616.2 739.3 Mean Corr = 0.50670 Ift88 151.8 200.1 262.8 Dync2h1 76.1 119.5 161.1 Gli2 203.0 456.9 586.8 Pkd1 231.4 400.0 581.9 Ift46 660.0 947.4 1052.1 Pafah1b1 821.2 979.2 1550.1 Ttc8 62.0 140.2 196.5 1110051M20Rik 136.7 208.1 267.1 Wdr19 82.9 113.5 148.0 Zfp354c 70.5 114.2 215.4 Bbs1 35.2 52.5 68.1 CEM 1 + Chd6 188.6 338.4 462.1 Top 10 Genes Glis2 113.5 198.9 246.4 Tbc1d19 137.9 333.3 494.6 Cc2d2a 192.6 413.8 532.8 Fam115a 224.5 358.6 450.1

Null module GEO Series "GSE37431" 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=GSE37431 Status: Public on Apr 23 2012 Title: Endothelial cell-enriched genes expression in mouse embryo Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22535667 Summary & Design: Summary: The early blood vessels of the embryo and yolk sac in mammals develop by aggregation of de novo forming angioblasts into a primitive vascular plexus, which then undergoes a complex remodeling process. Angiogenesis is also important for disease progression in the adult. However, the precise molecular mechanism of vascular development remains unclear.

It is therefore of great interest to determine which genes are specifically expressed in developing endothelial cells.Here, we utilized Flk1-deficient mouse embryos, which lack endothelial cells, to perform a genome-wide survey for genes related to vascular development.

Overall design: Wild type (WT), Flk1+/GFP and Flk1 KO embryos proper (fetuses) were dissected out at 8.5 dpc. Total RNAs from these embryos were prepared using RNeasy kit. Gene expression analysis was performed by GeneSpring software.

Background corr dist: KL-Divergence = 0.0198, L1-Distance = 0.0371, L2-Distance = 0.0015, Normal std = 0.8138

0.523 Kernel fit Pairwise Correlations Normal fit

Density 0.261

0.000 CEM 1

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

Pre-normalization Quantiles

Mouse_EC1Mouse_EC2 (0.310072)Mouse_KO1 (0.275516)Mouse_KO2 (0.0796985)Mouse_WT1 (0.0412514)Mouse_WT2 (0.170588) (0.122874) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 364.1 726.4 793.0 P ( S | Z, I ) = 1.00 Pkd2 858.0 1002.1 1149.8 Mean Corr = 0.47908 Ift88 270.8 413.3 447.0 Dync2h1 195.4 448.0 471.6 Gli2 119.3 1552.3 1832.5 Pkd1 58.2 166.2 209.9 Ift46 1083.6 1827.8 1921.8 Pafah1b1 1000.9 1533.8 1640.3 Ttc8 389.6 741.6 843.0 1110051M20Rik 343.5 557.9 594.2 Wdr19 139.4 216.5 273.7 Zfp354c 403.9 621.2 717.6 Bbs1 81.1 189.1 254.4 CEM 1 + Chd6 205.7 406.6 508.3 Top 10 Genes Glis2 501.3 653.1 754.1 Tbc1d19 769.7 958.3 1081.4 Cc2d2a 194.7 289.1 303.7 Fam115a 657.5 952.7 978.2

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 (0.181673)G-CSFCD31 cells, replicate 2 cells, (0.049306)xG-CSFCD31 5cells, days, untreated,3 cells, (0.161365)xG-CSFCD31 5replicate days, untreated, cells, x CD31replicate 5replicate days,1 untreated,(0.0612203) cells, CD31replicate replicate 1 2 (0.0243588) untreated,(0.123687) cells, CD31replicate 2 3 (0.0825805) G-CSF(0.0342334) cells, CD31replicate 3 (0.0171502)xG-CSF 5cells, CD31days, 4 (0.0450677)xG-CSF 5cells,replicate days, xG-CSF 5replicate days,1 (0.0335622) x 5replicate days,2 (0.06849) replicate [3 (0.0514742)min 4 (0.0658322) ] [ medium ] [ max ] CEM 1 Dync2li1 158.1 280.6 652.7 P ( S | Z, I ) = 1.00 Pkd2 1414.5 1741.6 4531.3 Mean Corr = 0.46156 Ift88 116.2 212.5 326.4 Dync2h1 75.0 194.4 382.3 Gli2 111.3 582.1 1359.2 Pkd1 570.3 1030.6 1432.1 Ift46 656.8 876.0 1664.6 Pafah1b1 303.6 429.7 617.7 Ttc8 126.7 198.3 504.0 1110051M20Rik 146.1 318.6 752.8 Wdr19 56.6 128.1 321.6 Zfp354c 110.4 790.1 2058.4 Bbs1 101.1 206.8 270.2 CEM 1 + Chd6 182.5 387.8 1283.4 Top 10 Genes Glis2 752.3 1390.1 3438.9 Tbc1d19 364.1 509.1 649.6 Cc2d2a 197.2 322.2 806.5 Fam115a 352.3 452.8 610.3

Null module GEO Series "GSE31013" 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=GSE31013 Status: Public on Jun 22 2012 Title: Global Differential Gene Expression Analysis of Spontaneous Lung Tumors in B6C3F1 Mice: Comparison to Human Non-Small Cell Lung Cancer Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22688403 Summary & Design: Summary: Introduction: Lung cancer is the leading cause of cancer-related death in people. There are several chemically induced and genetically modified mouse models used to study lung cancer. We hypothesized that spontaneous murine (B6C3F1) lung tumors can serve as a model to study human non-small cell lung cancer (NSCLC). Methods: RNA was extracted from untreated 2-year-old B6C3F1 mouse spontaneous lung (SL) tumors and age-matched normal lung tissue from a chronic inhalation NTP study. Global gene expression analysis was performed using Affymetrix Mouse Genome 430 2.0 GeneChipÂ® arrays. After data normalization, for each probe set, pairwise comparisons between groups were made using a bootstrap t-test while controlling the mixed directional false discovery rate (mdFDR) to generate a differential gene expression list. IPA, KEGG, and EASE software tools were used to evaluate the overrepresented cancer genes and pathways. Results: MAPK and TGF-beta pathways were overrepresented within the dataset. Almost all of the validated genes by quantitative real time RT-PCR had comparable directional fold changes with the microarray data. The candidate oncogenes included Kras, Braf, Raf1, Id2, Hmga1, Cks1b, and Foxf1. The candidate tumor suppressor genes included Rb1, Cdkn2a, Hnf4a, Tcf21, Ptprd, Hpgd, Hopx, Ogn, Id4, Hoxa5, Smad6, Smad7, Zbtb16, Cyr61, Dusp4, and Ifi16. In addition, several genes important in lung development were also differentially expressed, such as Smad6, Hopx, Sox4, Sox9 and Mycn. Conclusion: In this study, we have demonstrated that several cancer genes and signaling pathways relevant for human NSCLC were similarly altered in spontaneous murine lung tumors.

Overall design: Six spontaneous lung tumors and six normal lungs (as controls) from 2-year-old B6C3F1 mice.

Background corr dist: KL-Divergence = 0.0937, L1-Distance = 0.0321, L2-Distance = 0.0018, Normal std = 0.4603

0.871 Kernel fit Pairwise Correlations Normal fit

Density 0.436

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_normal_1Lung_normal_2Lung_normal_3 (0.0595493)Lung_normal_4 (0.0659968)Lung_normal_5 (0.0715958)Lung_normal_6 (0.0856704)Spontaneous_lung_tumor_1 (0.0797353)Spontaneous_lung_tumor_2 (0.0761277)Spontaneous_lung_tumor_3Spontaneous_lung_tumor_4 (0.0948542)Spontaneous_lung_tumor_5 (0.146924)Spontaneous_lung_tumor_6 (0.0329002) (0.0381628) (0.106851) (0.141632)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 519.3 1519.4 2005.5 P ( S | Z, I ) = 1.00 Pkd2 1045.6 2878.7 4302.6 Mean Corr = 0.45928 Ift88 291.4 411.1 582.2 Dync2h1 203.6 473.5 725.6 Gli2 7.8 81.7 122.8 Pkd1 292.1 719.7 1120.4 Ift46 939.3 1269.8 1615.2 Pafah1b1 987.9 1766.9 2132.0 Ttc8 220.1 436.6 699.6 1110051M20Rik 220.9 514.1 630.8 Wdr19 233.1 477.9 533.6 Zfp354c 37.6 189.5 267.7 Bbs1 105.0 235.9 333.6 CEM 1 + Chd6 349.3 516.1 745.4 Top 10 Genes Glis2 449.0 919.1 1351.4 Tbc1d19 610.2 1099.2 1273.7 Cc2d2a 255.0 464.9 611.2 Fam115a 281.5 429.6 551.3

Null module GEO Series "GSE20684" 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=GSE20684 Status: Public on Aug 25 2010 Title: The gene encoding the hematopoietic stem cell regulator CCN3 (NOV) is under direct cytokine control through the transcription factors STAT5a/b. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20720003 Summary & Design: Summary: Cytokines control the biology of hematopoietic stem and progenitor cells in part through the transcription factors STAT5a/b. CCN3/NOV has been reported as a positive regulator of hematopoietic stem and progenitor cells. We report microarray analyses of Lineage- Sca-1+ c-Kit+ (KSL) cells in the presence and absence of STAT5a/b. Expression of the ccn3 gene was induced over 100-fold in control, but not STAT5a/b-null cells, upon stimulation with a cocktail containing IL-3, IL-6, SCF, TPO and Flt3 ligand. Among the cytokines, IL-3 elevated ccn3 mRNA level in Lineage- c-Kit+ (KL) cells and 32D cells. ChIP assays using 32D cells revealed IL-3-induced binding of STAT5a/b to a GAS site in the ccn3 gene promoter. This is the first report to link two molecules with importance in the regulation of HSCs, CCN3 and STAT5a/b. We report that the regulation and expression of the ccn3 gene is directly controlled by IL-3 through the transcription factors STAT5a/b.

Overall design: Six Control and Six Stat5a/b-null KSL cells, including three biological replications, were unstimulated or stimulated with a cocktail containing IL-3, IL-6, SCF, TPO and FL.

Background corr dist: KL-Divergence = 0.1016, L1-Distance = 0.0325, L2-Distance = 0.0020, Normal std = 0.4373

0.912 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

KO+_BioWT+_Bio replicationKO+_Bio replication 1 WT+_Bio(0.060635) replication 1 KO+_Bio(0.0181928) replication 2 WT+_Bio(0.0555062) replication 2 KO-_Bio(0.0812006) replication 3 WT-_Bio(0.0701502) replication 3 KO-_Bio(0.0957474) replication 1 (0.0968608)WT-_Bio replication 1 (0.0591964)KO-_Bio replication 2 (0.0710273)WT-_Bio replication 2 (0.309772) replication 3 (0.0401021) 3 (0.0416096)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 35.2 127.8 277.0 P ( S | Z, I ) = 1.00 Pkd2 31.9 79.0 207.3 Mean Corr = 0.53062 Ift88 42.6 205.2 347.9 Dync2h1 63.1 100.1 172.3 Gli2 6.2 21.6 103.4 Pkd1 23.6 120.4 206.8 Ift46 255.7 474.3 772.4 Pafah1b1 944.8 1260.3 1740.0 Ttc8 34.2 159.5 462.4 1110051M20Rik 46.0 81.4 156.4 Wdr19 11.0 29.5 144.4 Zfp354c 6.6 55.5 283.7 Bbs1 12.4 50.6 115.4 CEM 1 + Chd6 317.9 951.5 2215.9 Top 10 Genes Glis2 29.7 235.8 438.7 Tbc1d19 478.0 629.5 806.0 Cc2d2a 27.3 105.2 407.9 Fam115a 19.6 31.5 42.1

Null module GEO Series "GSE14004" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14004 Status: Public on Jan 14 2009 Title: Re-expression of GATA2 Cooperates with PPAR gamma Depletion to Revert the Adipocyte Phenotype Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19136559 Summary & Design: Summary: The nuclear receptor PPAR gamma is required for adipocyte differentiation, but its role in mature adipocytes is less clear. Here we report that knockdown of PPAR gamma expression in 3T3-L1 adipocytes returned the expression of most adipocyte genes towards preadipocyte levels. Consistently, down regulated but not up regulated genes showed strong enrichment of PPAR gamma binding. Surprisingly, not all adipocyte genes were reversed and the adipocyte morphology was maintained for an extended period after PPAR gamma depletion. To explain this, we focused on transcriptional regulators whose adipogenic regulation was not reversed upon PPAR gamma depletion. We identified GATA2, a transcription factor whose down-regulation early in adipogenesis is required for preadipocyte differentiation, remaining low after PPAR gamma knockdown. Forced expression of GATA2 in mature adipocytes complemented PPAR gamma depletion and impaired adipocyte functionality with a more preadipocyte- like gene expression profile. Ectopic expression of GATA2 in adipose tissue in vivo had similar effect on adipogenic gene expression. These results suggest that PPAR gamma-independent down regulation of GATA2 prevents reversion of mature adipocytes after PPAR gamma depletion.

Keywords: cell type comparison, Gata2, PPAR gamma, adipocyte, preadipocytes, differentiation

Overall design: Technical replicates: PPAR gamma siRNA 1, PPAR gamma siRNA 2, PPAR gamma siRNA 3

Background corr dist: KL-Divergence = 0.0294, L1-Distance = 0.0232, L2-Distance = 0.0006, Normal std = 0.6966

0.586 Kernel fit Pairwise Correlations Normal fit

Density 0.293

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

preadipocytepreadipocyte rep1preadipocyte (0.130968) rep2control (0.128995) rep3 controlsiRNA (0.101048) rep1controlsiRNA (0.132499) rep2PPARsiRNA (0.153717) gamma rep3PPAR (0.187742) gammasiRNAPPAR rep1gammasiRNA (0.0274361) rep2siRNA (0.0679451) rep3 (0.0696509)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 509.8 1210.5 1955.1 P ( S | Z, I ) = 1.00 Pkd2 543.7 2640.4 4457.0 Mean Corr = 0.45281 Ift88 191.0 340.6 424.4 Dync2h1 235.0 345.2 368.2 Gli2 228.8 925.1 1297.3 Pkd1 647.7 943.7 1281.9 Ift46 1266.7 1926.9 2168.3 Pafah1b1 380.1 596.8 1098.7 Ttc8 801.0 1142.5 1779.0 1110051M20Rik 208.2 1017.8 1228.6 Wdr19 111.9 341.1 462.7 Zfp354c 61.9 310.8 864.5 Bbs1 51.5 134.2 320.9 CEM 1 + Chd6 258.6 423.9 538.1 Top 10 Genes Glis2 126.8 997.0 2116.9 Tbc1d19 875.6 1404.4 1532.8 Cc2d2a 515.9 677.2 894.7 Fam115a 1782.2 2232.3 2586.0

Null module GEO Series "GSE42548" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 29 -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=GSE42548 Status: Public on May 22 2013 Title: TH-MYCN Mice with Caspase-8 Deficiency Develop Advanced Neuroblastoma with Bone Marrow Metastasis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23536557 Summary & Design: Summary: Neuroblastoma, the most common extracranial pediatric solid tumor, is responsible for 15% of all childhood cancer deaths. Patients frequently present at diagnosis with metastatic disease, particularly to the bone marrow. Advances in therapy and understanding of the metastatic process have been limited due in part, to the lack of animal models harboring bone marrow disease. The widely employed transgenic model, the TH-MYCN mouse, exhibits limited metastasis to this site. Here we establish the first genetic immunocompetent mouse model for metastatic neuroblastoma with enhanced secondary tumors in the bone marrow. This model recapitulates two frequent alterations in metastatic neuroblasoma, over-expression of MYCN and loss of caspase-8 expression. In this model, the mouse caspase-8 gene was deleted in neural crest lineage cells by crossing a TH-Cre transgenic mouse with a caspase-8 conditional knockout mouse. This mouse was then crossed with the neuroblastoma prone TH-MYCN mouse. While over-expression of MYCN by itself rarely caused bone marrow metastasis (5% average incidence), combining MYCN overexpression and caspase-8 deletion significantly increased bone marrow metastasis (37% average incidence). Loss of caspase-8 expression did not alter the site, incidence, or latency of the primary tumors. However, secondary tumors were detected in the bone marrow of these mice as early as week 9-10. The mouse model described in this work is a valuable tool to enhance our understanding of metastatic neuroblastoma and treatment options and underscores the role of caspase-8 in neuroblastoma progression.

Overall design: Survey of spontateous 24 NB tumors and 5 bone marrow samples in wt and transgenic mice.

Background corr dist: KL-Divergence = 0.0350, L1-Distance = 0.0336, L2-Distance = 0.0021, Normal std = 0.6306

0.633 Kernel fit Pairwise Correlations Normal fit

Density 0.316

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

primaryprimary abdominalprimary abdominal NBprimary tumorabdominal NB ttt010primary tumorabdominal NB (0.00856318) ttt012primary tumorabdominal NB (0.0178049) ttt013primary tumorabdominal NB (0.00622238) ttt015primary tumorabdominal NB (0.00751164) ttt016primary tumorabdominal NB (0.0145579) ttt017primary tumorabdominal NB (0.0110509) ttt018primary tumorabdominal NB (0.00737106) ttt019primary tumorabdominal NB (0.061232) ttt020primary tumorabdominal NB (0.0420903) ttt021primary tumorabdominal NB (0.0155296) ttt100primary tumorabdominal NB (0.00632684) ttt101primary tumorabdominal NB (0.0334813) ttt102primary tumorabdominal NB (0.0518279) ttt104primary tumorabdominal NB (0.0146125) ttt105primary tumorabdominal NB (0.0349117) ttt106primary tumorabdominal NB (0.0131008) ttt107primary tumorabdominal NB (0.00847627) ttt108Total tumorabdominal NB bone(0.00863365) ttt109aTotal tumor marrow NB bone (0.0040137)ttt110primary tumor marrow ttt112 (0.0315894) ttt111primary abdominal (0.133318) ttt114a (0.0191251)primary abdominal (0.114316)NBTotal tumorabdominal NB bone ttt115Total tumor marrow NB bone(0.00341709) ttt116Total tumor marrow ttt118 bone(0.00764593) ttt117 (0.107464)marrow ttt119 (0.0131552) (0.103298) ttt120a (0.0993526)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 161.0 871.6 1317.3 P ( S | Z, I ) = 1.00 Pkd2 126.9 581.3 842.9 Mean Corr = 0.64635 Ift88 113.0 290.8 391.2 Dync2h1 190.3 589.9 739.1 Gli2 84.8 192.5 716.3 Pkd1 77.7 183.8 322.9 Ift46 415.6 1549.5 1946.1 Pafah1b1 472.0 1615.0 2271.2 Ttc8 51.8 1638.0 2706.0 1110051M20Rik 210.9 858.5 1110.5 Wdr19 83.1 107.6 173.0 Zfp354c 33.3 1149.4 1664.3 Bbs1 53.5 366.6 584.9 CEM 1 + Chd6 179.0 878.0 1197.1 Top 10 Genes Glis2 69.6 528.0 662.0 Tbc1d19 167.0 906.2 1124.6 Cc2d2a 67.6 606.8 934.7 Fam115a 51.2 1362.1 1952.5

Null module GEO Series "GSE49346" 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=GSE49346 Status: Public on Mar 07 2014 Title: Expression data from adult ATII and E18 Bipotent progenitor cells in the mouse lung Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24499815 Summary & Design: Summary: Alveoli are thin-walled sacs that serve as the gas exchange units of the lung. They are affected in devastating lung diseases including COPD, Idiopathic Pulmonary Fibrosis, and the major form (adenocarcinoma) of lung cancer, the leading cause of cancer deaths. The alveolar epithelium is composed of two morphologically distinct cell types: alveolar type (AT) 1 cells, exquisitely thin cells across which oxygen diffuses to reach the blood, and AT2 cells, specialized surfactant-secreting cells. Classical studies suggested that AT1 cells arise from AT2 cells during development and following injury, but more recent studies suggest other sources. Here we use histological and marker analysis, lineage tracing, and clonal analysis in mice to identify alveolar progenitor and stem cells and map their locations and potential in vivo. The results show that AT1 and AT2 cells arise independently during development from a bipotential progenitor. After birth, new AT1 cells derive from rare, long-lived, self-renewing AT2 cells, each producing a slowly expanding clonal focus of regenerated alveoli contiguous with the founder AT2 cell. This stem cell function of AT2 cells is broadly activated by diffuse AT1 cell injury, and AT2 self-renewal can be induced in vitro by EGF ligands and permanently activated in vivo by AT2 cell-specific targeting of the oncogenic KrasG12D allele, efficiently transforming AT2 cells into monoclonal adenomatous tumors that rapidly enlarge and prove fatal. Thus, there is a developmental switch in alveolar progenitor cells after birth, when mature AT2 cells function as facultative stem cells that contribute to local alveolar renewal, repair, and cancer. We propose that short-range signals from dying AT1 cells regulate AT2 stem cell activity: a signal transduced by EGFR-KRAS controls AT2 self-renewal and is hijacked during oncogenic transformation, and a separate signal controls reprogramming to AT1 cell fate.

Overall design: To compare expression between ATII and E18 BP populations, RNA was isolated from either population purified by FACS. Two populations are analyzed with 3 biological replicates per population.

Background corr dist: KL-Divergence = 0.0359, L1-Distance = 0.0425, L2-Distance = 0.0025, Normal std = 0.6765

0.609 Kernel fit Pairwise Correlations Normal fit

Density 0.304

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

Muc1+_Pdpn+_E18-1Muc1+_Pdpn+_E18-2Muc1+_Pdpn+_E18-3 (0.0811162)Lyz2+_EpCAM+_Adult-1 (0.110744)Lyz2+_EpCAM+_Adult-2 (0.048053)Lyz2+_EpCAM+_Adult-3 (0.183709) (0.10586) (0.470518)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 82.5 392.1 1845.6 P ( S | Z, I ) = 1.00 Pkd2 193.3 875.0 1419.3 Mean Corr = 0.36424 Ift88 110.5 536.5 1765.9 Dync2h1 122.4 247.7 870.7 Gli2 6.5 273.2 684.4 Pkd1 389.0 602.3 668.8 Ift46 595.6 730.1 2136.1 Pafah1b1 358.1 709.3 873.7 Ttc8 56.6 347.1 947.3 1110051M20Rik 172.7 415.1 675.0 Wdr19 45.1 223.5 1466.5 Zfp354c 50.4 203.6 303.1 Bbs1 56.4 206.7 663.5 CEM 1 + Chd6 405.5 672.0 1284.5 Top 10 Genes Glis2 188.6 703.4 1143.8 Tbc1d19 75.6 632.4 1176.5 Cc2d2a 165.9 745.5 867.6 Fam115a 65.2 262.0 469.3

Null module GEO Series "GSE1871" 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=GSE1871 Status: Public on Oct 26 2004 Title: SCCOR_MouseLung_Simva_LPS Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 15665042 Summary & Design: Summary: This series contain mouse lung samples treated with Simvastatin and LPS and corresponded controls.

Keywords: other

Overall design:

Background corr dist: KL-Divergence = 0.0617, L1-Distance = 0.0228, L2-Distance = 0.0006, Normal std = 0.5246

0.764 Kernel fit Pairwise Correlations Normal fit

Density 0.382

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

VehVeh1VehVeh2 (0.25539)VehVeh3 (0.0753611)VehLPS1 (0.0390814)VehLPS2 (0.0390594)VehLPS (0.0502389)SimvaVeh1 (0.080893)SimvaVeh2 (0.0381987)SimvaVeh3 (0.0720965)SimvaLPS1 (0.075928)SimvaLPS2 (0.0592581)SimvaLPS3 (0.186344) (0.0281502) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 391.0 892.2 1781.9 P ( S | Z, I ) = 1.00 Pkd2 2323.5 3348.7 4554.3 Mean Corr = 0.33138 Ift88 349.2 636.8 1240.0 Dync2h1 487.9 868.9 1181.5 Gli2 6.0 216.1 290.3 Pkd1 589.4 1191.8 1511.1 Ift46 658.0 942.1 1597.5 Pafah1b1 895.5 1145.6 1641.4 Ttc8 189.5 605.1 1130.7 1110051M20Rik 364.6 747.9 981.0 Wdr19 368.3 591.3 1168.8 Zfp354c 70.5 121.0 179.1 Bbs1 306.3 463.4 708.7 CEM 1 + Chd6 278.2 591.0 840.3 Top 10 Genes Glis2 1014.2 1353.8 1910.2 Tbc1d19 500.6 1156.4 1480.3 Cc2d2a 356.6 764.2 1093.1 Fam115a 240.9 337.4 431.7

Null module GEO Series "GSE52474" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 154 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

Details of this dataset are not shown due to large number of samples and the page size limit. Find details in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52474

Background corr dist: KL-Divergence = 0.1954, L1-Distance = 0.0793, L2-Distance = 0.0167, Normal std = 0.3721 GEO Series "GSE11898" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11898 Status: Public on Jun 27 2008 Title: Expression data from primary mesangial cells stimulated with DNA and RNA ligands Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21949095 Summary & Design: Summary: Extrarenal viral infections commonly trigger glomerulonephritis mostly in association with immune complex disease. The immunoglobulin component of immune complexes can activate glomerular cell Fc receptors but whether complexed viral nucleic acids contribute to glomerular inflammation remains unknown. Glomerular mesangial cells express TLR3 but lack TLR7-9, hence, it is unclear whether mesangial cells can recognize and respond to viral ssRNA or DNA. Here we studied the immune responses activated by 3P-RNA (5'Triphosphate RNA) and Non-CpG DNA (Double stranded DNA) in primary mesangial cells (PMC).

We used microarrays to detail the global programme of gene expression that induced by 3P-RNA and Non-CpG DNA.

Keywords: diffrent ligands

Overall design: PMC were stimulated with 3P-RNA and Non-CpG DNA for 6 hours and then total RNA was isolated for hybridization to MOE430_2 arrays.

Background corr dist: KL-Divergence = 0.0613, L1-Distance = 0.0257, L2-Distance = 0.0008, Normal std = 0.5353

0.763 Kernel fit Pairwise Correlations Normal fit

Density 0.382

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

lipofectaminelipofectamine atlipofectamine 6h-1 (0.204991)atNon-CpG 6h-2 (0.119866)atNon-CpG 6h-3 DNA (0.117431) Non-CpGat DNA6h-1 3P-RNA(0.152713)at DNA6h-2 3P-RNA(0.134563)at at 6h-3 6h-1 3P-RNA(0.0974963) (0.0695203)at 6h-2 (0.0397175)at 6h-3 (0.0637022) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 700.7 862.9 1059.9 P ( S | Z, I ) = 0.99 Pkd2 4157.0 4489.3 5149.8 Mean Corr = 0.53409 Ift88 146.6 163.1 225.2 Dync2h1 233.1 273.6 334.9 Gli2 270.4 431.9 492.3 Pkd1 669.7 761.7 1035.5 Ift46 872.1 1039.9 1314.5 Pafah1b1 959.9 1153.9 1265.2 Ttc8 382.9 567.9 872.7 1110051M20Rik 433.9 560.2 861.1 Wdr19 131.1 201.7 347.6 Zfp354c 243.2 431.9 595.2 Bbs1 117.5 134.3 219.6 CEM 1 + Chd6 184.0 246.5 408.7 Top 10 Genes Glis2 1923.4 2185.9 2638.1 Tbc1d19 1004.1 1296.0 1666.7 Cc2d2a 223.6 398.9 551.0 Fam115a 668.9 769.5 839.9

Null module GEO Series "GSE21861" 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=GSE21861 Status: Public on Nov 15 2010 Title: The transcription factors STAT5a/b negatively regulate cell proliferation through the activation of cdkn2b and cdkn1a expression Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21038417 Summary & Design: Summary: Although the cytokine-inducible transcription factors STAT5a/b promote proliferation of a wide range of cell types, there are cell- and context specific cases in which loss of STAT5a/b results in enhanced cell proliferation. Here we report that loss of STAT5a/b from mouse embryonic fibroblasts (MEFs) leads to enhanced proliferation, which was linked to reduced levels of the cell cycle inhibitor p15INK4B and p21CIP1. We further demonstrate that growth hormone through the transcription factor STAT5a/b enhances expression of the cdkn2B gene and that STAT5a binds to GAS sites within the promoter. We have recently demonstrated that ablation of STAT5a/b from liver results in hepatocellular carcinoma upon a CCl4 insult. We also established that in liver tissue, like in MEFs, STAT5a/b activates expression of the cdkn2B gene. Loss of STAT5a/b led to diminished p15INK4B and increased hepatocyte proliferation. This study for the first time demonstrates that cytokines through STAT5a/b can induce the expression of a key cell cycle inhibitor. These experiments therefore shed a light on the context-specific role of STAT5a/b as tumor suppressors.

Overall design: Control and Stat5a/b-null embryonic fibroblasts (MEFs) cells were stimulated w/o a GH including two biological replications per group (Total four groups)

Background corr dist: KL-Divergence = 0.0201, L1-Distance = 0.0466, L2-Distance = 0.0026, Normal std = 0.8018

0.546 Kernel fit Pairwise Correlations Normal fit

Density 0.273

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

KO+GH_Bio-2WT-_Bio-3 replication-05-17-10KO-_Bio-2 replication-05-17-10WT+GH_Bio-3 replication-05-17-10KO+GH_Bio-3 (0.17035) replication-05-17-10WT-_Bio-2 (0.192509) replication-5-17-10KO-_Bio-3 (0.160332) replication-05-17-10WT+GH_Bio-2 replication-05-17-10 (0.0994595) (0.083846) replication-05-17-10 (0.0478709) (0.168639)[ min (0.0769938) ] [ medium ] [ max ] CEM 1 Dync2li1 648.0 1335.6 1709.3 P ( S | Z, I ) = 0.99 Pkd2 1837.7 2140.9 2507.3 Mean Corr = 0.59139 Ift88 194.5 219.9 245.0 Dync2h1 251.0 430.1 507.9 Gli2 346.4 790.4 1206.8 Pkd1 876.7 1070.9 1494.5 Ift46 1702.8 2605.1 3373.7 Pafah1b1 1058.5 1235.0 1473.3 Ttc8 631.9 927.8 1251.8 1110051M20Rik 511.9 706.6 909.1 Wdr19 200.5 254.6 341.2 Zfp354c 173.1 539.3 721.4 Bbs1 43.1 59.1 74.0 CEM 1 + Chd6 208.3 279.7 293.9 Top 10 Genes Glis2 1089.4 1810.5 2024.2 Tbc1d19 1064.1 1128.9 1223.1 Cc2d2a 296.5 372.0 490.5 Fam115a 894.2 976.2 1227.8

Null module GEO Series "GSE31561" 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=GSE31561 Status: Public on Feb 19 2013 Title: Transcriptional analysis of organ-specific toxicity induced by a panPPAR agonist in mice: Identification of organ-specific toxicity biomarkers Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23272042 Summary & Design: Summary: In this study, we aim to identify candidate biomarkers which may be useful as surrogate indicators of toxicity for pre-clinical development of panPPAR-agonist drug candidates. Gene expression microarray, histopathology and clinical chemistry data were generated from liver, heart, kidney and skeletal muscles of three groups of mice administered with three different dosages of an experimental pan-peroxisome proliferator-activated receptor (pan-PPAR) agonist, PPM-201, for 14 days. The histopathology and clinical chemistry data were compared with the gene expression analysis and candidate biomarker genes were identified.

Overall design: Nine wild type mice (strain: C57BL/6J) were randomly divided into three groups - Group-I, II and III. PPM-201 in the vehicle base was administered daily for 14 days at 6 mg/kg body weight dose rate to each mouse in Group-II and at 20mg/kg body weight dose rate to each mouse in Group-III while the mice in Group-I received only the vehicle base. On 15th day, the mice were sacrificed to harvest blood, heart, skeletal muscle, liver and kidney tissues for clinical chemistry, microarray and histopathology analysis. In the clinical chemistry analysis, alanine aminotransferase (ALT, U/L), aspartate aminotransferase (AST, U/L), creatinine kinase (CK, U/L), blood urea nitrogen (BUN, mmol/L), creatinine (umol/L) and lactate dehydrogenase (LDH, U/L) were measured from the blood of each mouse. Two sections of liver, two sections of kidney, one or two sections of skeletal muscle, and one section of heart were prepared from each mouse, stained with hematoxylin and eosin (H&E), and examined by a veterinary pathologist. RNA was extracted and processed as per the established protocol from heart, skeletal muscle, liver and kidney tissue samples of all the 9 mice for profiling with Affymetrix Mouse Genome 430 2.0 Array and in total 36 chips were prepared. Using various quality control measures, the data was analysed for its quality. As it was found to be good in quality, the data from all the 36 chips were used for further analysis. The results from histopathology and clinical chemistry analysis were compared with the gene expression to determine if the dosages selected for the study were associated with findings in target organs.

Background corr dist: KL-Divergence = 0.0965, L1-Distance = 0.0540, L2-Distance = 0.0060, Normal std = 0.4768

0.888 Kernel fit Pairwise Correlations Normal fit

Density 0.444

0.000 CEM 1

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

Pre-normalization Quantiles

Heart vehicleHeart vehiclerep1Heart (0.0258248) vehiclerep2Heart (0.0286921) 6mgkg-1rep3Heart (0.0250217) 6mgkg-1 Heartrep1 (0.0208728) 6mgkg-1 Heartrep2 (0.0166773) 20mgkg-1 Heartrep3 (0.0155208) 20mgkg-1Heart rep1 20mgkg-1(0.0143568)Kidney rep2 (0.0126726) Kidneyvehicle rep3 (0.0160468) Kidneyvehiclerep1 (0.058451) Kidneyvehiclerep2 (0.0481549) Kidney6mgkg-1rep3 (0.0485993) Kidney6mgkg-1 rep1 (0.0636769) Kidney6mgkg-1 rep2 (0.0658896) Kidney20mgkg-1 rep3 (0.0550545) Kidney20mgkg-1 rep1 Liver 20mgkg-1(0.0427824) rep2 vehicleLiver (0.0415736) rep3 vehiclerep1Liver (0.0446951) (0.0303134) vehiclerep2Liver (0.0201993) 6mgkg-1rep3Liver (0.0279781) 6mgkg-1 rep1Liver (0.0197337) 6mgkg-1 rep2Liver (0.0220924) 20mgkg-1 rep3Liver (0.0246906) 20mgkg-1Liver rep1 20mgkg-1(0.022095)Skeletal rep2 (0.0258091)Skeletal Musclerep3 (0.0273933)Skeletal MusclevehicleSkeletal Musclevehiclerep1 (0.0102937)Skeletal Musclevehiclerep2 (0.00960719)Skeletal Muscle6mgkg-1rep3 (0.014036)Skeletal Muscle6mgkg-1 rep1Skeletal (0.0175293)Muscle6mgkg-1 rep2Skeletal (0.00786984)Muscle20mgkg-1 rep3 (0.011137)Muscle20mgkg-1 rep1 20mgkg-1(0.0251163) rep2 (0.0233118) rep3[ (0.0162309)min ] [ medium ] [ max ] CEM 1 Dync2li1 71.6 207.8 1242.7 P ( S | Z, I ) = 1.00 Pkd2 1061.0 1808.3 4673.0 Mean Corr = 0.23241 Ift88 114.2 144.1 337.5 Dync2h1 36.4 97.7 344.8 Gli2 9.1 45.3 92.0 Pkd1 185.6 357.0 538.8 Ift46 511.2 823.7 1177.8 Pafah1b1 947.4 1824.4 2328.4 Ttc8 122.0 270.5 913.5 1110051M20Rik 59.6 563.2 1099.4 Wdr19 143.1 205.6 822.4 Zfp354c 59.1 310.5 569.5 Bbs1 24.5 97.6 415.5 CEM 1 + Chd6 183.5 467.6 1061.1 Top 10 Genes Glis2 60.9 249.0 3062.7 Tbc1d19 198.5 1007.0 1779.1 Cc2d2a 166.6 575.1 900.7 Fam115a 147.6 298.7 535.6

Null module GEO Series "GSE49128" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 17 -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=GSE49128 Status: Public on Jul 23 2013 Title: Otitis Media Impact on Middle Ear Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24124478 Summary & Design: Summary: Objective: Otitis media is known to alter expression of cytokine and other genes in the mouse middle ear and inner ear. However, whole mouse genome studies of gene expression in otitis media have not previously been undertaken. Ninety-nine percent of mouse genes are shared in the human, so these studies are relevant to the human condition.

Methods: To assess inflammation-driven processes in the mouse ear, gene chip analyses were conducted on mice treated with trans-tympanic heat-killed Hemophilus influenza using untreated mice as controls. Middle and inner ear tissues were separately harvested at 6 hours, RNA extracted, and samples for each treatment processed on the Affymetrix 430 2.0 Gene Chip for expression of its 34,000 genes.

Results: Statistical analysis of gene expression compared to control mice showed significant alteration of gene expression in 2,355 genes, 11% of the genes tested and 8% of the mouse genome. Significant middle and inner ear upregulation (fold change >1.5, p<0.05) was seen in 1,081 and 599 genes respectively. Significant middle and inner ear downregulation (fold change <0.67, p<0.05) was seen in 978 and 287 genes respectively. While otitis media is widely believed to be an exclusively middle ear process with little impact on the inner ear, the inner ear changes noted in this study were numerous and discrete from the middle ear responses. This suggests that the inner ear does indeed respond to otitis media and that its response is a distinctive process. Numerous new genes, previously not studied, are found to be affected by inflammation in the ear.

Conclusion: Whole genome analysis via gene chip allows simultaneous examination of expression of hundreds of gene families influenced by inflammation in the middle ear. Discovery of new gene families affected by inflammation may lead to new approaches to the study and treatment of otitis media.

Overall design: There are 8 control samples and 9 samples trans-tympanically injected with H flu 10e9 for 6 hours. Each sample is from a single animal.

Background corr dist: KL-Divergence = 0.1073, L1-Distance = 0.0314, L2-Distance = 0.0014, Normal std = 0.4348

0.937 Kernel fit Pairwise Correlations Normal fit

Density 0.469

0.000 CEM 1

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

Pre-normalization Quantiles

ME controlME controlrep ME1 (0.13346) TTrep Hflu ME2 (0.0387687) controlrep ME1 (0.0894675) controlrep ME3 (0.0557606) TTrep Hflu ME4 (0.0182281) controlrep ME2 (0.0486102) controlrep ME5 (0.0385004) controlrep ME6 (0.0189489) TTrep Hflu ME7 (0.116437) TTrep Hflu ME3 (0.0397001) TTrep Hflu ME4 (0.0742411) controlrep ME5 (0.0318586) TTrep Hflu ME8 (0.1024) TTrep Hflu ME6 (0.0206923) TTrep Hflu ME7 (0.0305372) TTrep Hflu 8 (0.0181804) rep 9 (0.12421) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 391.6 517.6 823.6 P ( S | Z, I ) = 0.99 Pkd2 590.2 675.0 812.6 Mean Corr = 0.39569 Ift88 124.2 151.6 232.3 Dync2h1 119.9 159.8 219.7 Gli2 52.2 84.0 132.7 Pkd1 399.4 456.6 625.7 Ift46 689.9 971.1 1222.0 Pafah1b1 893.0 1097.1 1383.0 Ttc8 62.8 81.8 116.2 1110051M20Rik 611.6 750.4 1241.6 Wdr19 206.0 263.9 351.6 Zfp354c 417.8 558.7 713.6 Bbs1 96.1 131.5 172.3 CEM 1 + Chd6 310.5 379.4 456.9 Top 10 Genes Glis2 406.2 612.5 1008.4 Tbc1d19 516.3 627.0 807.9 Cc2d2a 366.6 463.3 771.8 Fam115a 221.8 291.1 384.3

Null module GEO Series "GSE11679" 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=GSE11679 Status: Public on Oct 08 2008 Title: Gene expression changes related to postnatal handling Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18836535 Summary & Design: Summary: Postnatal handling in rodents leads to decreased anxiety-like behavior in adulthood. We used microarrays to look at gene expression differences in the CA1 region of the hippocampus in female mice subjected to postnatal handling compared to controls.

Overall design: Balb c/J offspring were briefly separated from mothers for 15 minutes each morning on postnatal days 1-14 (handled group) or left undisturbed. At 8 weeks of age mice were tested in the open-field and light-dark behavioral paradigms to verify a handling-induced behavioral phenotype. 2 weeks after behavioral testing, animals were sacrificed and the CA1 region was microdissected. CA1 regions were stored at -20C in RNA later. RNA was extracted from 8 samples (4 handled and 4 non-handled) using Trizol. RNA was extracted from second group of animals (7 handled and 10 non-handled) using Qiagen RNA/DNA columns. All total RNA samples were double round amplied and labeled using standard Affymetrix protocols and hybridized to Mouse 430_2.0 arrays in parallel.

Background corr dist: KL-Divergence = 0.1846, L1-Distance = 0.0311, L2-Distance = 0.0015, Normal std = 0.3522

1.134 Kernel fit Pairwise Correlations Normal fit

Density 0.567

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

Handled:Handled: H108 Handled:(0.0180609) H109 Handled:(0.0148829) H110 Handled:(0.0231286) H116 Handled:(0.0117012) H117 Handled:(0.0277149) H118 Non-handled:(0.0191597) H123 Non-handled:(0.0187198) NH142Non-handled: (0.0313335)NH155Non-handled: (0.0268924)NH156Non-handled: (0.0326429)NH157Non-handled: (0.0156351)NH162Non-handled: (0.0419867)NH163Non-handled: (0.0205666)NH165Non-handled: (0.0305954)NH166Non-handled: (0.0546265)NH167Handled: (0.0213521)NH170Handled: H113 (0.0289583) Handled:(0.05094) H126 Handled:(0.111418) H130 Non-handled:(0.0423235) H131 Non-handled:(0.0740711) NH138Non-handled: (0.0418844)NH144Non-handled: (0.117789)NH146 (0.0870498)NH147 (0.0365667)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 376.9 648.9 894.1 P ( S | Z, I ) = 0.99 Pkd2 555.7 1008.1 1811.7 Mean Corr = 0.08027 Ift88 263.0 450.4 764.4 Dync2h1 252.1 377.0 1022.3 Gli2 42.7 169.2 276.7 Pkd1 53.8 159.9 637.2 Ift46 1071.0 1412.7 1787.8 Pafah1b1 1222.2 1757.4 2964.3 Ttc8 264.3 416.7 1472.6 1110051M20Rik 822.3 1654.7 2042.0 Wdr19 201.9 389.6 765.9 Zfp354c 908.0 1277.6 1630.0 Bbs1 258.6 493.1 641.4 CEM 1 + Chd6 946.2 1300.9 2527.2 Top 10 Genes Glis2 141.3 189.5 333.4 Tbc1d19 692.5 937.8 1691.6 Cc2d2a 262.2 368.2 1032.0 Fam115a 729.9 1332.3 1757.4

Null module GEO Series "GSE27987" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 31 -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=GSE27987 Status: Public on Aug 25 2011 Title: Differential pre-mRNA processing in Crebbp+/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21901164 Summary & Design: Summary: The presence of unspliced transcripts in hematopoietic stem cells (HSCs) and the proposed association of CREBBP with the constitutive production of unspliced RNA and with pre-mRNA processing prompted us to examine more closely an anomaly we had noted in microarray-based gene expression studies but had previously attributed to experimental noise. We noticed that more than half of the probe sets down-regulated in Crebbp+/- fetal liver HSCs (FLHSCs) relative to wild-type (WT) mapped entirely within introns, rather than detecting exonic or spliced sequences. We therefore set out to test whether this might be evidence that reduced CREBBP levels selectively alter the generation of full-length, unspliced pre-mRNA. We also asked whether this process might be associated with differentiation since self-renewal and lineage commitment are the both responses for which HSCs are primed.

Overall design: cell type comparison

Background corr dist: KL-Divergence = 0.0422, L1-Distance = 0.0924, L2-Distance = 0.0091, Normal std = 0.9341

0.496 Kernel fit Pairwise Correlations Normal fit

Density 0.248

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

Crebbp CrebbpwtHSC CrebbpsamplewtHSC Crebbp samplewtHSC1 replicate Crebbp samplewtHSC1 replicate 1 (0.0114285) Crebbp samplehetHSC2 replicate 2 (0.0140357) Crebbp hetHSC 2sample replicate 1 (0.0172366) CrebbphetHSC sample1 replicate 2 (0.0225762) Ep300hetHSC sample1 replicate 1 wtHSC(0.030805)Ep300 sample2 replicate 2 samplewtHSC(0.0170757)Ep300 2 replicate 1 samplewtHSC(0.0129201)1Ep300 replicate 2 samplewtHSC(0.015437)1Ep300 replicate 1 (0.025874) samplehetHSC2Ep300 replicate 2 (0.0152831) hetHSC 2Ep300sample replicate 1 (0.0164823) hetHSC Ep300sample1 replicate 2 (0.0277179) hetHSC Cdkn1asample1 replicate 1 (0.0203329) Cdkn1asample2wtHSC replicate 2 (0.0219859) Cdkn1a21wtHSC replicate(0.0108404) 1 (0.0299617)Cdkn1a 2wtHSC (0.0078164) 2 (0.0280599)Cdkn1a 3nullHSC (0.0112843)Cdkn1a nullHSC 1 (0.00815517)Cdkn1a nullHSC 2 (0.00896653)Crebbp nullHSC 3 (0.0121369) CrebbpwtMEF 4 (0.00610686) Crebbp1wtMEF (0.095254) Crebbp2wtMEF (0.0749315) Crebbp3wtMEF (0.0960003) Crebbp4hetMEF (0.0604985) CrebbphetMEF 1 (0.0546658) CrebbphetMEF 2 (0.0854232) hetMEF 3 (0.0841365) 4 (0.056571) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 43.5 149.8 839.2 P ( S | Z, I ) = 0.99 Pkd2 98.9 263.9 3758.5 Mean Corr = 0.50988 Ift88 49.8 78.3 177.0 Dync2h1 12.7 63.3 118.2 Gli2 6.4 14.0 626.6 Pkd1 26.4 73.9 663.5 Ift46 182.9 540.0 2076.6 Pafah1b1 978.8 1850.5 3705.0 Ttc8 18.0 59.1 895.1 1110051M20Rik 354.4 561.7 852.6 Wdr19 52.3 132.6 355.5 Zfp354c 128.2 394.2 1217.7 Bbs1 8.1 24.1 136.1 CEM 1 + Chd6 251.6 382.0 784.7 Top 10 Genes Glis2 133.3 433.9 1485.7 Tbc1d19 222.0 611.3 807.6 Cc2d2a 55.8 148.6 489.7 Fam115a 14.7 28.0 1549.7

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(0.0260607) PB_Kidney_Control_10(0.0121702) PB_Kidney_Control_8(0.0215986) PB_Kidney_Control_3(0.0367691)PB_Kidney_Control_7 (0.0320215) PB_Kidney_Control_2(0.0218836) PB_Kidney_Control_6(0.0261579) PB_Liver_Control_10(0.015993) PB_Liver_Control_9(0.0270166) PB_Liver_Control_2(0.026997) (0.0146366)PB_Liver_Control_3 (0.0258946)PB_Liver_Control_6 (0.0224356)PB_Liver_Control_5 (0.012969)PB_Liver_Control_4 (0.0213509)PB_Liver_Control_8 (0.022593)PB_Liver_Control_1 (0.037475)PB_Liver_Control_7 (0.0203447)PB_Kidney_treated_20 (0.0312048)PB_Kidney_treated_18 (0.034389)PB_Kidney_treated_12PB_Kidney_treated_11 (0.0289648)PB_Kidney_treated_17 (0.0337956)PB_Kidney_treated_16 (0.0117012)PB_Kidney_treated_14 (0.0188612)PB_Kidney_treated_15 (0.0230941)PB_Kidney_treated_13 (0.0197592)PB_Kidney_treated_19 (0.0464481)PB_Liver_treated_12 (0.0210169)PB_Liver_treated_13 (0.0207067)PB_Liver_treated_14 (0.0316414) (0.0217915)PB_Liver_treated_15 (0.0221473)PB_Liver_treated_11 (0.020686)PB_Liver_treated_16 (0.0261068)PB_Liver_treated_18 (0.0539633)PB_Liver_treated_19 (0.0212018)PB_Liver_treated_20 (0.0308892)PB_Liver_treated_17 (0.0195584) (0.0195258) (0.0181791)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 106.3 785.2 1058.3 P ( S | Z, I ) = 0.98 Pkd2 419.8 4286.0 5827.4 Mean Corr = 0.38308 Ift88 161.1 466.5 599.0 Dync2h1 169.5 325.9 559.8 Gli2 4.7 28.2 82.7 Pkd1 109.0 222.8 334.0 Ift46 947.2 1187.3 1737.8 Pafah1b1 882.2 1186.2 1619.7 Ttc8 126.1 637.2 957.7 1110051M20Rik 106.7 321.3 485.1 Wdr19 114.8 195.3 284.4 Zfp354c 3.4 113.2 190.6 Bbs1 6.4 251.6 408.0 CEM 1 + Chd6 211.7 419.7 570.0 Top 10 Genes Glis2 117.8 2461.9 3406.5 Tbc1d19 158.0 1465.8 1925.0 Cc2d2a 151.3 344.4 509.3 Fam115a 54.7 177.7 387.2

Null module GEO Series "GSE39458" 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=GSE39458 Status: Public on Dec 31 2012 Title: Differential gene expression of Kit+Sca1+Lin- (KSL) cells from arthritic versus control mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: The involvement of mature hematopoietic cells in disease pathogenesis is well recognized. However it is not clear how if and how primitive progenitors might contribute to inflammatory disease processes.

This microarray experiment is used together with data from functional assays to determine how primitive progenitors are altered in a mouse model of autoimmune arthritis and how this in turn might contribute to the disease process.

Overall design: All the mice used in this study were C57BL/6 background strain. G7 mice are congenic with C57BL/6 but with MHC II I-Ab replaced with MHC II I-Ag7.

Background corr dist: KL-Divergence = 0.0145, L1-Distance = 0.0305, L2-Distance = 0.0010, Normal std = 0.8466

0.495 Kernel fit Pairwise Correlations Normal fit

Density 0.247

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

KSL cells_B6xG7_sortedKSL cells_KRN_sortedKSL cells_KRNxG7_sortedLin+_B6xG7_sorted (0.258451)Lin+_KRN_sorted (0.13138)Lin+_KRNxG7_sorted (0.11694)(0.204736) (0.110148) (0.178344)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 83.7 166.2 218.7 P ( S | Z, I ) = 0.97 Pkd2 117.5 900.7 1128.5 Mean Corr = 0.43333 Ift88 94.6 252.9 277.1 Dync2h1 147.7 181.1 225.1 Gli2 4.2 6.2 8.2 Pkd1 177.3 553.7 600.0 Ift46 406.7 572.0 579.0 Pafah1b1 600.2 840.0 1127.6 Ttc8 22.6 218.3 356.9 1110051M20Rik 84.7 329.0 333.6 Wdr19 33.0 88.2 99.5 Zfp354c 46.7 152.4 181.5 Bbs1 28.5 138.1 196.8 CEM 1 + Chd6 535.8 1284.6 1627.0 Top 10 Genes Glis2 30.4 375.9 438.6 Tbc1d19 56.8 349.0 477.5 Cc2d2a 21.8 111.1 199.2 Fam115a 133.0 194.1 229.1

Null module GEO Series "GSE13032" 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=GSE13032 Status: Public on Oct 04 2008 Title: The Effects of Resiquimod Treatment on the Asthma Transcriptome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19491150 Summary & Design: Summary: Resiquimod is a nucleoside analog belonging to the imidazoquinoline family of compounds which is known to signal through Toll-like receptor 7. Resiquimod treatment has been demonstrated to inhibit the development of allergen induced asthma in experimental models. Despite this demonstrated effectiveness, little is known about the molecular events responsible for this effect. The aim of the present study was to elucidate the molecular processes which were altered following resiquimod treatment and antigen challenge in a mouse model of allergic asthma. Employing microarray analysis, we have characterized the asthmatic transcriptome of the murine lung and determined that it includes genes involved in: the control of cell cycle progression, airway remodelling, the complement and coagulation cascades, and chemokine signalling. We have demonstrated that systemic resiquimod administration resulted in the recruitment of NK cells to the lungs of the mice, although no causal relationship between NK cell recruitment and treatment efficacy was found. Furthermore, results of our studies demonstrated that resiquimod treatment resulted in the normalization of the expression of genes involved with airway remodelling and chemokine signalling, and in the modulation of the expression of genes including cytokines and chemokines, adhesion molecules, and B-cell related genes, involved in several aspects of immune function and antigen presentation. Overall, our findings identified several genes, important in the development of asthma pathology, that were normalized following resiquimod treatment thus improving our understanding of the molecular consequences of resiquimod treatment in the lung milieu.

Keywords: Disease and treatment state analysis

Overall design: A total of 18 samples, from 6 sets of biological replicates, were analyzed. 9 A/J and 9 C57BL/6 mice were divided into three equal groups. All animals were sensitized to ovalbumin, one group received PBS aerosol challenges, the other two received 1% ovalbumin aerosol challenges. Of the two ovalbumin challenged groups, one recieved resiquimod 24hours before each challenge.

Background corr dist: KL-Divergence = 0.1972, L1-Distance = 0.0379, L2-Distance = 0.0027, Normal std = 0.3357

1.188 Kernel fit Pairwise Correlations Normal fit

Density 0.594

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

A/J wholeA/J lung-PBS wholeA/J lung-PBS whole challenged-biologicalC57BL/6 lung-PBS challenged-biologicalC57BL/6 whole challenged-biologicalC57BL/6 lung-PBS whole rep.1A/J lung-PBS whole challenged-biological(0.0198272)whole rep.2A/J lung-PBS lung-ovalbumin challenged-biological(0.0121676)whole rep.3C57BL/6 lung-ovalbuminchallenged-biological(0.0228533)C57BL/6 whole rep.1 challenged-biologicalA/J lung-ovalbumin (0.0682289)whole rep.2 wholechallenged-biologicalA/J lung-ovalbumin(0.0951831) lung-resiquimodrep.3 wholeC57BL/6 (0.115882) challenged-biological lung-resiquimod rep.1A/J wholechallenged-biological(0.0421709) wholerep.2 treatedC57BL/6 lung-resiquimod (0.031323) lung-ovalbumin treatedandC57BL/6 whole rep.1ovalbumin and (0.037111)C57BL/6 lung-ovalbumin whole rep.2ovalbumin treated challenged-biological challenged-biological (0.0797461)A/J lung-resiquimod whole and whole challenged-biological ovalbumin lung-resiquimod challenged-biological lung-resiquimod treated challenged-biologicalrep.3 rep.1 (0.0645548)treatedand (0.0746681) treatedrep.2 ovalbumin[ rep.3 minand (0.0886984) and ovalbumin(0.0913068) ovalbumin rep.1 challenged-biological] (0.0441868) challenged-biological challenged-biological[ medium rep.2 (0.0394792) rep.3 rep.3 (0.0379879)] (0.0346252)[ max ] CEM 1 Dync2li1 948.5 1125.6 1365.7 P ( S | Z, I ) = 0.96 Pkd2 1670.5 2183.2 2762.6 Mean Corr = 0.36120 Ift88 320.4 367.3 420.0 Dync2h1 391.3 436.8 545.4 Gli2 222.4 278.1 407.3 Pkd1 895.3 1119.8 1386.4 Ift46 961.2 1113.5 1397.9 Pafah1b1 657.2 874.9 1019.7 Ttc8 277.3 371.3 459.3 1110051M20Rik 494.6 572.8 730.6 Wdr19 341.5 409.9 500.5 Zfp354c 165.6 206.7 273.1 Bbs1 110.3 141.3 150.6 CEM 1 + Chd6 242.8 324.3 435.3 Top 10 Genes Glis2 959.3 1389.0 1847.4 Tbc1d19 580.2 724.5 798.0 Cc2d2a 452.0 623.6 802.5 Fam115a 378.1 428.7 489.8

Null module GEO Series "GSE27811" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27811 Status: Public on May 12 2011 Title: Expression data from LSK WT, GMP WT and GMP NcstnKO Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21562564 Summary & Design: Summary: Notch signaling is one of the central regulators of differentiation in a variety of organisms and tissue types. Within the hematopoietic system, Notch is essential for the emergence of definitive HSC during fetal life and controls adult HSC differentiation to the T-cell lineage. Notch activation is controlled by the gamma-secretase complex complex, composed of presenilin, nicastrin (Ncstn), anterior pharynx-1 (Aph1), and presenilin enhancer-2

To determine other role of Notch signaling in HSC we designed a conditional mouse model of Nicastrin deletion. WT and KO HSC were analysed to determined genes controlled by Notch signaling.

Overall design: Bone marrow lineage negative, cKit+, Sca1+ and lineage negative, cKit+, Sca1- CD34+ FcgammaRII/III+ cells were sorted from WT and Ncstn KO littermates for RNA extraction and hybridization on Affymetrix microarrays

Background corr dist: KL-Divergence = 0.0285, L1-Distance = 0.0206, L2-Distance = 0.0006, Normal std = 0.6601

0.604 Kernel fit Pairwise Correlations Normal fit

Density 0.302

0.000 CEM 1

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

Pre-normalization Quantiles

LSK WTLSK replicate1c WTLSK replicate2c WT(0.205729)GMP replicate3c (0.296624)WTGMP replicate1 (0.0386885)WTGMP replicate2 (0.0917272) WTGMP replicate3 (0.0259065) NcstnKOGMP (0.0552558) NcstnKO GMPreplicate1 NcstnKO replicate2 (0.129595) replicate3 (0.0794994) (0.0769737)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 173.0 240.4 406.9 P ( S | Z, I ) = 0.95 Pkd2 137.7 262.1 512.0 Mean Corr = 0.60415 Ift88 98.2 138.0 154.6 Dync2h1 89.3 126.2 177.4 Gli2 9.6 11.0 20.7 Pkd1 89.2 110.5 241.5 Ift46 425.2 557.0 715.7 Pafah1b1 1046.7 1439.4 1761.8 Ttc8 140.2 204.8 336.9 1110051M20Rik 407.8 462.5 683.5 Wdr19 124.5 180.2 422.3 Zfp354c 83.3 171.5 529.7 Bbs1 25.3 42.4 216.5 CEM 1 + Chd6 169.9 338.0 631.0 Top 10 Genes Glis2 43.3 95.9 529.9 Tbc1d19 467.7 538.4 795.0 Cc2d2a 87.7 134.1 221.8 Fam115a 14.8 28.5 133.3

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 (0.12882)MouseLiver_0.05ugSe_rep2 (0.0588543)MouseLiver_0.05ugSe_rep3 (0.0492989)MouseLiver_0.2ugSe_rep1 (0.0670626)MouseLiver_0.2ugSe_rep2 (0.023504)MouseLiver_0.2ugSe_rep3 (0.0313873)MouseKidney_SeDef_rep1 (0.0566064)MouseKidney_SeDef_rep2 (0.0437096)MouseKidney_SeDef_rep3 (0.0372719)MouseKidney_0.05ugSe_rep1 (0.0387305)MouseKidney_0.05ugSe_rep2 (0.0694308)MouseKidney_0.05ugSe_rep3 (0.0451477)MouseKidney_0.2ugSe_rep1 MouseKidney_0.2ugSe_rep2(0.0421635) MouseKidney_0.2ugSe_rep3(0.0942262) (0.0483704) (0.0478451) (0.0724798) (0.0450906)[ min ] [ medium ] [ max ] CEM 1 Dync2li1 173.7 846.0 1208.3 P ( S | Z, I ) = 0.74 Pkd2 362.5 3239.5 3690.2 Mean Corr = 0.42773 Ift88 348.6 644.5 758.7 Dync2h1 574.7 801.9 912.0 Gli2 115.9 180.4 212.6 Pkd1 229.1 279.9 358.1 Ift46 1018.0 1169.9 1300.7 Pafah1b1 720.7 1108.4 1279.5 Ttc8 121.1 554.4 1168.8 1110051M20Rik 301.0 595.1 774.9 Wdr19 126.5 281.5 335.0 Zfp354c 84.2 123.7 137.5 Bbs1 100.7 323.5 398.9 CEM 1 + Chd6 124.9 258.4 364.4 Top 10 Genes Glis2 356.5 2958.2 4057.0 Tbc1d19 270.7 1698.5 2137.4 Cc2d2a 178.9 608.3 734.9 Fam115a 145.9 366.5 393.6

Null module GEO Series "GSE56777" 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=GSE56777 Status: Public on May 14 2014 Title: Expression data of E13.5 mouse Blood Brain Barrier and lung endothelial cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24828040 Summary & Design: Summary: Following the identification of a critical time window of Blood Brain Barrier formation in the mouse embryo, we aimed to identify genes important for barriergenesis. To this end, we isolated cortical and lung E13.5 endothelial cells and compared expression between the two populations.

The working hypothesis was that endothelial cells which are actively building a barrier would have a uniqe pattern of gene expression that would be detectable in comparison to a non-barrier endothelial population that is also active in vasculogenesis.

Overall design: E13.5 Tie2-GFP embryos were micro-dissected for cortex and lungs. Cortex tissue was carefully cleared of the meninges and choroid plexus. FACS purification of GFP positive cells and GeneChip analysis was applied . All material from a single litter (10-13 embryos) was pooled and considered as a biological replicate. n=4 litters.

Background corr dist: KL-Divergence = 0.0382, L1-Distance = 0.0277, L2-Distance = 0.0012, Normal std = 0.6186

0.645 Kernel fit Pairwise Correlations Normal fit

Density 0.322

0.000 CEM 1

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

Pre-normalization Quantiles

Cortex_72Lung_72 (0.199035)Lung_22 (0.0526461)Cortex_22 (0.099595)Lung_19 (0.0635542)Cortex_19 (0.0955314)Lung_18 (0.0214921)Cortex_18 (0.295583) (0.172563) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 118.6 432.0 592.3 P ( S | Z, I ) = 0.61 Pkd2 323.0 645.4 1242.8 Mean Corr = 0.32101 Ift88 148.9 197.8 260.9 Dync2h1 75.7 176.5 403.6 Gli2 22.2 286.2 827.8 Pkd1 419.2 515.5 810.1 Ift46 1020.0 1308.3 1740.7 Pafah1b1 903.7 1957.2 2497.3 Ttc8 101.2 167.0 257.5 1110051M20Rik 445.4 1292.7 2509.0 Wdr19 172.1 339.0 404.7 Zfp354c 865.2 1997.0 2602.3 Bbs1 47.5 186.4 231.9 CEM 1 + Chd6 292.3 557.8 786.0 Top 10 Genes Glis2 547.7 912.2 1188.4 Tbc1d19 625.0 1024.9 1319.8 Cc2d2a 483.6 624.2 804.0 Fam115a 1469.8 1941.3 2744.2

Null module GEO Series "GSE9061" 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=GSE9061 Status: Public on Aug 24 2011 Title: Dap12-deficient mouse brain (1 month) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy (PLOSL) is an inherited brain and bone disease. It manifests as dementia and bone fractures. The PLOSL phenotype is caused by loss-of-function mutations in one of the two genes encoding the components of the DAP12/TREM2 receptor complex. The DAP12/TREM2 complex is expressed in cells of the myeloid lineage, including microglia in the central nervous system (CNS). The molecular mechanisms producing the CNS phenotype of PLOSL remain largely unknown. To gain insight into dysfunctional CNS pathways behind PLOSL, we performed genome-wide expression analysis of Dap12 (Tyrobp)-deficient mouse brain. In Dap12-deficient mice, we observed alterations in several pathways involved in synaptic function. In agreement with the myelin loss in PLOSL patients, we also saw changes in transcript levels of genes encoding myelin components.

Keywords: knockout response

Overall design: Transcript profiles of the midbrain (diencephalon and basal ganglia) of three Dap12-knockout and three heterozygous mice were analyzed.

Background corr dist: KL-Divergence = 0.0275, L1-Distance = 0.0302, L2-Distance = 0.0012, Normal std = 0.7023

0.574 Kernel fit Pairwise Correlations Normal fit

Density 0.287

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

Dap12-koDap12-ko 68 (0.294276)Dap12-het 67 (0.202344)Dap12-het 75 (0.17426)Dap12-het 76 (0.0502762)Dap12-ko 81 (0.145295) Ko1 (0.133549) [ min ] [ medium ] [ max ] CEM 1 Dync2li1 299.4 703.9 839.6 P ( S | Z, I ) = 0.42 Pkd2 532.7 756.0 909.5 Mean Corr = 0.59832 Ift88 136.1 366.0 402.1 Dync2h1 414.5 666.9 867.4 Gli2 32.8 165.5 193.3 Pkd1 235.1 467.7 610.9 Ift46 705.1 1209.5 1379.6 Pafah1b1 1375.2 2613.0 3063.4 Ttc8 284.4 778.3 960.4 1110051M20Rik 1295.6 1676.7 1897.9 Wdr19 296.5 414.6 508.5 Zfp354c 421.8 741.0 856.5 Bbs1 419.7 513.2 697.7 CEM 1 + Chd6 763.6 1234.5 1440.0 Top 10 Genes Glis2 232.9 257.4 332.3 Tbc1d19 961.3 1161.7 1263.8 Cc2d2a 307.3 467.0 513.6 Fam115a 1034.8 1583.0 2050.5

Null module GEO Series "GSE41759" 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=GSE41759 Status: Public on Apr 19 2013 Title: Differential Gene Expression and Mitochondrial Dysfunction in Imprinting center deletion (PWS- IC del) Mouse model of Prader-Willi Syndrome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Prader-Willi syndrome (PWS) is a genetic disorder caused by deficiency of imprinted gene expression from the paternal chromosome 15q11-15q13 and clinically characterized by neonatal hypotonia, short stature, cognitive impairment, hypogonadism, hyperphagia, morbid obesity and diabetes. Previous clinical studies suggest that a defect in energy metabolism may be involved in the pathogenesis of PWS. Assessment of enzyme activities of mitochondrial oxidative phosphorylation (OXPHOS) complexes in the brain, heart, liver and muscle were assessed.

We used microarrays to detail the global programme of gene expression underlyingthe PWS and identified distinct classes of disregulated genes during this process.

Overall design: Skeletal (quadriceps) muscle Vastus Lateralis and whole brain samples from the mutant mice and their wild-type age-matched littermates were analyzed by microarray technology using the Mouse Genome 430 2.0 arrays (Affymetrix).

Background corr dist: KL-Divergence = 0.0080, L1-Distance = 0.0325, L2-Distance = 0.0010, Normal std = 0.9775

0.408 Kernel fit Pairwise Correlations Normal fit

Density 0.204

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

muscle brainVastus tissue muscleLateralis, sample, brainVastus wild tissuewild muscletypeLateralis, type sample,mice, brainVastusmice, wild biological tissuewild biological muscletypeLateralis, type sample,mice, replica brainVastusmice, replica wild biological tissue wild1biological muscletypeLateralis,(0.0502494) 1 type (0.166849) sample,mice, replica brainVastusmice, replica wild biological tissue wild2biological muscletypeLateralis,(0.0624915) 2 type (0.041924) sample,mice, replica brainVastusmice, replica mutant biological tissue mutant3biological muscleLateralis,(0.048191) 3 mice, (0.0807994) sample, mice,replica brainVastus biological replica mutant biological tissue mutant4 Lateralis,(0.051684) 4 mice, (0.082536) replicasample, mice, replica biological mutant 1biological mutant(0.0945168) 1 (0.0675527) mice, replica mice, replica[ biological min 2biological (0.0456245) 2 (0.0632425) replica] replica 3 (0.0819542) 3 (0.0623853)[ medium ] [ max ] CEM 1 Dync2li1 481.5 740.8 917.5 P ( S | Z, I ) = 0.40 Pkd2 773.6 943.6 1138.8 Mean Corr = 0.47596 Ift88 207.2 316.6 385.7 Dync2h1 88.7 452.1 523.5 Gli2 206.8 270.5 321.3 Pkd1 255.7 375.0 647.5 Ift46 563.3 817.7 1167.7 Pafah1b1 573.6 1827.4 2281.2 Ttc8 203.1 621.3 787.8 1110051M20Rik 411.5 1270.2 1802.2 Wdr19 142.3 350.5 432.7 Zfp354c 187.6 832.1 1004.3 Bbs1 41.3 442.3 545.8 CEM 1 + Chd6 221.6 769.9 1069.2 Top 10 Genes Glis2 137.4 186.1 230.1 Tbc1d19 932.8 1176.9 1611.8 Cc2d2a 334.3 440.3 540.2 Fam115a 161.3 1347.7 1630.4

Null module