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. Gatad2b Gatad2a Rbbp7 Rbbp4 Hdac2 Mbd3 Chd3 Num ofGenesinQueryGeneset:8.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Mta2

Mta2 Rbbp4 Mbd3 Chd3 Gatad2a Gatad2b Hdac2 Rbbp7 CEM 1(15datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page1 Hsp90ab1 Cdk2ap1 Snrnp40 Gatad2b Gatad2a Pip5k1c Slc16a4 Fam60a Nudcd3 Chaf1b Numa1 Thrap3 Ppm1g Dcaf15 Trim28 Hnrnpl Qrich1 G3bp1 Arid1a Rbbp7 Rbbp4 Ubap2 Nup93 Rnps1 Apex1 Casp2 Hdac2 Zbed6 Khsrp Alyref Mcm6 Stub1 Cct6a Setd3 Tfap4 Paics Snrpf Mbd3 Srsf4 Ago2 Chd3 Eif5a Dgkz Fen1 Mta2 Cct5 Phf6 Tcf3 Prr3 Ilf2 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE33308 [10] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE14004 [9] GSE50729 [6] GSE22251 [9] GSE15770 [8] GSE30083 [12] GSE21137 [16] GSE23833 [12] GSE36810 [16] GSE13805 [7] GSE18500 [35] GSE46500 [6] GSE42238 [9] GSE5037 [18] GSE35543 [6] GSE38409 [16] GSE13306 [17] GSE15741 [6] GSE51883 [30] GSE38831 [7] GSE26616 [6] GSE50687 [38] GSE12454 [13] GSE27932 [14] GSE54490 [12] GSE13104 [14] GSE21491 [9] GSE25574 [8] GSE46443 [12] GSE20100 [15] GSE46600 [44] GSE7810 [9] GSE46090 [12] GSE39458 [6] GSE20696 [8] GSE7798 [16] GSE9247 [15] GSE18800 [25] GSE5038 [9] GSE18587 [9] GSE18042 [18] GSE20954 [14] GSE11677 [8] GSE11434 [10] GSE13874 [14] GSE53986 [16] GSE20335 [8] GSE45941 [8] GSE4535 [6] GSE26023 [6] GSE36665 [6] GSE44355 [10] GSE15767 [6] GSE8322 [12] GSE11679 [25] GSE16073 [6] GSE18742 [13] GSE10525 [18] GSE5236 [8] GSE17617 [18] GSE27630 [8] GSE2527 [6] GSE32386 [13] GSE12881 [6] GSE19299 [6] GSE14499 [26] GSE41095 [6] GSE10535 [6] GSE43419 [20] GSE28025 [18] GSE27429 [8] GSE12430 [21] GSE15268 [16] GSE32103 [6] GSE9443 [24] GSE18993 [13] GSE43042 [6] GSE30767 [8] GSE9355 [51] GSE57797 [23] GSE39555 [24] GSE21670 [16] GSE21822 [12] GSE51483 [45] GSE14406 [54] GSE24276 [6] GSE31244 [6] GSE10644 [18] GSE30744 [6] GSE46209 [21] GSE24628 [16] GSE28333 [6] GSE30684 [6] GSE15173 [6] GSE21272 [44] GSE45430 [9] GSE3181 [6] GSE6957 [12] GSE56755 [13] GSE18148 [6] GSE49351 [6] GSE6837 [8] GSE54653 [6] GSE6867 [6] GSE16679 [8] GSE44162 [6] GSE6998 [32] GSE14024 [12] GSE51075 [12] GSE36530 [6] GSE1435 [27] GSE27564 [8] GSE27159 [8] GSE42688 [8] GSE20235 [6] GSE54349 [6] GSE27975 [6] GSE43928 [12] GSE32963 [6] GSE21278 [48] GSE15155 [12] GSE29045 [12] GSE21761 [43] GSE29572 [21] GSE31406 [12] GSE5582 [6] GSE32624 [6] GSE21836 [8] GSE35357 [12] GSE33101 [8] GSE29241 [6] GSE38693 [8] GSE35763 [6] GSE15433 [9] GSE30873 [6] GSE17796 [39] GSE42008 [6] GSE23040 [6] GSE39273 [6] GSE6275 [36] GSE1074 [12] GSE7897 [60] GSE22434 [8] GSE10954 [8] GSE46724 [6] GSE16002 [9] GSE14753 [6] GSE9146 [27] GSE32020 [26] GSE13364 [6] GSE5715 [10] GSE11420 [15] CEM+ CEM GSE10176 [6] GSE28389 [20] GSE48811 [20] GSE14059 [6] GSE4695 [6] GSE44339 [14] 0.0 GSE27816 [14] GSE21944 [6]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 4.21 4.22 4.26 4.26 4.26 4.28 4.28 4.29 4.34 4.36 4.38 4.44 4.44 4.47 4.57 4.63 4.75 4.84 4.86 4.98 5.03 5.07 5.12 5.19 5.24 5.25 5.27 5.30 5.30 5.58 5.68 5.73 5.80 5.85 5.85 5.92 6.10 6.25 6.67 6.78 7.14 8.82 1.0 Notes 2410016O06Rik 6030458C11Rik Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page2 Tmem194b Pafah1b3 Hnrnpab Gemin5 Ranbp3 Yae1d1 Ppp3r1 Sptbn1 Ubqln4 Irf2bp1 Ruvbl1 Scmh1 Zbtb12 Psma3 Prrc2a Dnmt1 Mex3c Ercc6l Haus4 Senp3 Usp37 Mcm2 Prmt1 Ubfd1 Atxn2 Cenpl Bccip Pcgf6 Ash1l Noc2l Dus3l Sin3a Pcm1 H2afz Prpf4 Nudc Chd8 Eif3b Rbx1 Eif4e Lmf2 Rnf8 Cdt1 Vars Slbp Mtf2 Btf3 Acd 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 3.41 3.43 3.45 3.46 3.46 3.47 3.51 3.53 3.55 3.57 3.58 3.58 3.61 3.62 3.63 3.64 3.64 3.67 3.67 3.68 3.69 3.71 3.74 3.75 3.75 3.76 3.77 3.81 3.83 3.84 3.88 3.90 3.91 3.93 3.93 3.94 3.94 3.96 3.97 3.98 3.99 4.00 4.02 4.05 4.07 4.08 4.13 4.15 4.15 4.15 1.0 Notes 3110082I17Rik Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page3 Donson Ncapg2 Rbmxl1 Topbp1 Zmym4 Ppp1r8 Mis18a Alkbh8 Rnf126 Psmd7 Lmnb1 Zfp329 Zfp326 Map1s Grwd1 Wdr46 Cops4 Wdr82 Wdr90 Nup85 Ahdc1 Lphn1 Fubp1 Tubb5 Taok1 Ap1ar Cfdp1 Rsrc2 Pnpt1 Utp15 Tra2b Nisch Nol11 Rpl12 Ptcd3 Tra2a Cse1l Etaa1 Asxl1 Nono Scrib Pcna Sbk1 Tdp2 Krit1 Hdgf Hat1 Cct2 Ipo7 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 2.67 2.70 2.71 2.71 2.71 2.72 2.75 2.76 2.76 2.77 2.81 2.83 2.85 2.85 2.86 2.88 2.89 2.90 2.90 2.93 2.95 2.96 2.96 2.96 2.97 2.98 3.00 3.01 3.03 3.06 3.08 3.09 3.12 3.12 3.13 3.15 3.15 3.19 3.20 3.21 3.24 3.25 3.29 3.29 3.29 3.32 3.35 3.38 3.38 3.39 1.0 Notes 2410002F23Rik Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page4 Fam199x Csnk1g2 Tubgcp4 Tomm40 Tamm41 Ankrd10 Champ1 Ncaph2 Nup153 Hnrnpu Hnrnpd Exosc2 Tuba1a Setd1b Dnaaf2 Wdhd1 Hs2st1 Ube2j2 Dnajc9 Kansl3 Eefsec Zfp251 Cand1 Haus5 Akap8 Eif2b5 Ddx20 Rps20 Ncoa7 Vps16 Hirip3 Parp1 Ptbp2 Sf3b4 Palb2 Lsm2 Srsf7 Rhoa Nop9 Hypk Eif3d Ppil1 Tcp1 Ola1 Cct7 Ipo9 Ipo5 Tia1 Eif5 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 2.19 2.19 2.20 2.20 2.20 2.21 2.23 2.23 2.23 2.24 2.26 2.27 2.29 2.29 2.31 2.34 2.35 2.36 2.37 2.37 2.39 2.39 2.39 2.41 2.43 2.44 2.45 2.46 2.47 2.48 2.50 2.51 2.54 2.54 2.55 2.56 2.56 2.59 2.59 2.60 2.62 2.62 2.63 2.63 2.64 2.65 2.65 2.66 2.66 2.66 1.0 Notes Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page5 Mapk1ip1l Tmem201 Zc3hav1l Znf512b Hnrnpm Ranbp1 Nup155 Ogfod3 Tada2a Eef1b2 Cntrob Med12 Mex3b Copg1 Dtymk Haus8 Ddx18 Enkd1 Cxxc1 Pds5a Ndor1 Mcm4 Srpk1 Acer2 Ercc6 Phf13 H2afx U2af1 Uspl1 Smu1 Smc5 Taf1d Lta4h Gpn1 Prpf8 Sart1 Srsf3 Srsf1 Nelfa Cdc7 Rcc2 Phc1 Bcl9l Ints3 Ints7 Grk6 Bora Brd2 Ttc5 Fus 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 1.74 1.76 1.78 1.80 1.80 1.82 1.83 1.84 1.86 1.86 1.87 1.87 1.88 1.88 1.88 1.90 1.90 1.91 1.91 1.92 1.92 1.92 1.93 1.94 1.96 1.96 1.97 1.98 1.99 1.99 2.00 2.00 2.01 2.01 2.01 2.01 2.03 2.04 2.04 2.05 2.06 2.07 2.09 2.09 2.10 2.13 2.14 2.17 2.18 2.18 1.0 Notes Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page6 Smarca4 S100pbp Hnrnph1 Gprasp1 Khdrbs1 Hnrnpa1 Ppp2r5d Ctdnep1 Pabpc4 Dazap1 Rbm48 Ruvbl2 Mrpl15 Zfp383 Gtf3c4 Srebf1 Polr2a Kif18b Bend3 Rps13 Basp1 Rps10 Eif2s1 Elavl1 Fance Ints10 Mast2 Nudt3 Btbd2 Pold3 Ifnar1 Ube2i Pms2 Zfp53 Zfp12 Cirbp Prpf3 Msh6 Ago1 Cnn3 Wdr6 Dph7 Ddb1 Rpa2 Rcc1 Ldb1 Gtf2i Prcc Zzz3 Hn1 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 1.33 1.34 1.34 1.35 1.35 1.36 1.37 1.38 1.38 1.39 1.39 1.41 1.44 1.45 1.46 1.46 1.47 1.47 1.47 1.50 1.50 1.51 1.51 1.51 1.53 1.53 1.54 1.54 1.56 1.56 1.56 1.56 1.57 1.58 1.58 1.60 1.60 1.62 1.62 1.63 1.64 1.64 1.65 1.65 1.66 1.68 1.72 1.72 1.73 1.73 1.0 Notes Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page7 Ppp2r1b Zmym3 Coro1c Ampd2 Kdm2b Atp2b1 Topors Rbm8a Kdm1a Papola Pnpla6 Zfp574 Zfp512 Slc7a6 Cdan1 Ssbp2 Ssbp3 Dhx57 Pa2g4 Snx27 Thoc3 Snrpg Rrbp1 Cpsf1 U2af2 Safb2 Pold1 Smg5 Phf5a Pola1 Patz1 Prr12 Msh2 Pmf1 Midn Tial1 Mcat Gnl1 Prcp Ostc Dctd Rfx1 Ttll4 Gart Ubtf Bptf Isy1 Ctcf Atic Dck 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 0.95 0.96 0.96 0.96 0.98 0.98 0.99 0.99 1.00 1.01 1.01 1.02 1.02 1.04 1.05 1.05 1.08 1.08 1.08 1.09 1.09 1.09 1.09 1.09 1.10 1.14 1.14 1.14 1.17 1.17 1.18 1.19 1.19 1.22 1.22 1.23 1.24 1.24 1.24 1.24 1.25 1.26 1.26 1.27 1.29 1.30 1.31 1.32 1.32 1.32 1.0 Notes 4933427D14Rik Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page8 Ccdc102a Tmem39b Trp53bp1 Fam168b Fam126a Msantd2 Gpatch4 Twistnb Cops7b Zmym1 Raver1 Dnajb1 Gas2l3 Smad4 Atpaf2 Spire1 N4bp2 Stmn1 Casp3 Eif4g3 Pmm2 Ddx11 Dmwd Sec62 Tusc3 Mcm7 Aamp Rbm5 Ptov1 Sf3b1 Ttyh3 Zfp74 Htra2 Gps1 Uba2 Cbx5 Rbak Edc4 Crlf3 Gle1 Rfc2 Rfc5 Hsf1 Rpl6 Rpl8 Mri1 Nbn Fxn Srrt 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 0.61 0.61 0.64 0.64 0.65 0.66 0.66 0.67 0.67 0.67 0.68 0.69 0.70 0.71 0.71 0.73 0.73 0.74 0.74 0.74 0.75 0.75 0.76 0.76 0.77 0.77 0.78 0.78 0.78 0.81 0.82 0.83 0.84 0.85 0.88 0.88 0.88 0.89 0.89 0.89 0.89 0.90 0.90 0.90 0.91 0.91 0.91 0.92 0.94 0.94 1.0 Notes Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page9 Mphosph9 Fam216a Suv39h2 Zdhhc20 Exosc10 Ncapd2 Nucks1 Akap12 Snrpd3 Hmgn5 Supt16 Nap1l1 Trim39 Zfp207 Bmpr2 Polr1c Lrrc45 Rqcd1 Ubxn1 Cdk10 Dhx30 Casc3 Fkbp4 Top3a Fads2 Rrp1b Prmt2 Mcm5 Agbl5 H3f3a Larp7 Bcl7a Lsm7 Lsm3 Nop2 Rpa1 Klf16 Oaz1 Nav1 Pogz Pex2 Ppig Cul7 Adsl Bcl9 Ift74 Gan Clta Cic Dtl 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 0.36 0.37 0.37 0.38 0.38 0.39 0.39 0.39 0.39 0.39 0.39 0.40 0.41 0.41 0.41 0.41 0.41 0.41 0.42 0.42 0.43 0.43 0.44 0.45 0.45 0.46 0.46 0.48 0.48 0.48 0.50 0.51 0.51 0.53 0.53 0.53 0.54 0.54 0.54 0.54 0.55 0.55 0.56 0.56 0.56 0.57 0.59 0.60 0.60 0.61 1.0 Notes 2310036O22Rik 4930422G04Rik 2510002D24Rik Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page10 Casp8ap2 Thumpd2 Zmynd19 Mybbp1a Zkscan1 Zcchc11 Ankrd32 Pom121 Hdgfrp2 Hnrnpdl Cbfa2t3 Anapc5 Poldip3 Snapc2 Ctnnb1 Polr2m Gnb2l1 Alkbh4 Wbp11 Zfp428 Zfp687 Isyna1 Prrc2c Mecp2 Wdr18 Nop16 Ddx56 Usp10 Ddx49 Eif4a1 Foxp4 Cnot6 Agfg2 Pprc1 Efnb2 Rnf26 Galk1 Ptch1 Plcg1 Stk25 Fut11 Uhrf1 Naca Sfpq Polb Hn1l Csk 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE11723 [9] Scale ofaveragePearsoncorrelations GSE21996 [14] GSE28731 [10] GSE44260 [10] GSE1871 [12] GSE40660 [6] GSE14415 [31] 0.2 GSE14354 [6] GSE20562 [20] GSE21380 [7] GSE33156 [18] GSE36237 [64] GSE18660 [10] GSE16100 [6] GSE17112 [8] GSE42877 [14] 0.4 GSE27546 [51] GSE6674 [15] GSE10344 [6] GSE27901 [23] GSE30868 [8] GSE9130 [6] GSE2557 [6] GSE24813 [10] GSE15379 [12] 0.6 GSE22140 [13] GSE10113 [12] GSE9013 [12] GSE34324 [12] GSE17462 [8] GSE23738 [17] GSE17879 [6] GSE29458 [23] GSE6675 [8] 0.8 GSE21143 [6] GSE26461 [6] GSE28895 [6] GSE37676 [6] Score 0.08 0.09 0.09 0.09 0.09 0.09 0.11 0.11 0.11 0.11 0.11 0.12 0.12 0.13 0.14 0.16 0.17 0.18 0.18 0.19 0.20 0.21 0.22 0.22 0.23 0.23 0.23 0.25 0.25 0.25 0.26 0.26 0.27 0.27 0.27 0.28 0.28 0.29 0.29 0.30 0.31 0.32 0.32 0.32 0.33 0.33 0.34 0.35 0.35 0.36 1.0 Notes Symbol Num ofCEMGenes:8.Predicted506.SelectedDatasets:15.Strength:0.1 CEM 1,Geneset"[C]HDAC2-asscociatedcorecomplex",Page11 Nsmce4a Hnrnpa0 Mrps27 Snrpa1 Rnf219 Mrpl38 Slc9a5 Prdm2 Ddx23 Pebp1 Ubtd2 Cstf3 Aida Rai1 0.0 1.0

GSE20390 [6] GSE28830 [9]

GSE33308 [10] Only showingfirst200datasets-Seetxtoutputforfulldetails . GSE14004 [9] GSE50729 [6] GSE22251 [9] GSE15770 [8] GSE30083 [12] GSE21137 [16] GSE23833 [12] GSE36810 [16] GSE13805 [7] GSE18500 [35] GSE46500 [6] GSE42238 [9] GSE5037 [18] GSE35543 [6] GSE38409 [16] GSE13306 [17] GSE15741 [6] GSE51883 [30] GSE38831 [7] GSE26616 [6] GSE50687 [38] GSE12454 [13] GSE27932 [14] GSE54490 [12] GSE13104 [14] GSE21491 [9] GSE25574 [8] GSE46443 [12] GSE20100 [15] GSE46600 [44] GSE7810 [9] GSE46090 [12] GSE39458 [6] GSE20696 [8] GSE7798 [16] GSE9247 [15] GSE18800 [25] GSE5038 [9] GSE18587 [9] GSE18042 [18] GSE20954 [14] GSE11677 [8] GSE11434 [10] GSE13874 [14] GSE53986 [16] GSE20335 [8] GSE45941 [8] GSE4535 [6] GSE26023 [6] GSE36665 [6] GSE44355 [10] GSE15767 [6] GSE8322 [12] GSE11679 [25] GSE16073 [6] GSE18742 [13] GSE10525 [18] GSE5236 [8] GSE17617 [18] GSE27630 [8] GSE2527 [6] GSE32386 [13] GSE12881 [6] GSE19299 [6] GSE14499 [26] GSE41095 [6] GSE10535 [6] GSE43419 [20] GSE28025 [18] GSE27429 [8] GSE12430 [21] GSE15268 [16] GSE32103 [6] GSE9443 [24] GSE18993 [13] GSE43042 [6] GSE30767 [8] GSE9355 [51] GSE57797 [23] GSE39555 [24] GSE21670 [16] GSE21822 [12] GSE51483 [45] GSE14406 [54] GSE24276 [6] GSE31244 [6] GSE10644 [18] GSE30744 [6] GSE46209 [21] GSE24628 [16] GSE28333 [6] GSE30684 [6] GSE15173 [6] GSE21272 [44] GSE45430 [9] GSE3181 [6] GSE6957 [12] GSE56755 [13] GSE18148 [6] GSE49351 [6] GSE6837 [8] GSE54653 [6] GSE6867 [6] GSE16679 [8] GSE44162 [6] GSE6998 [32] GSE14024 [12] GSE51075 [12] GSE36530 [6] GSE1435 [27] GSE27564 [8] GSE27159 [8] GSE42688 [8] GSE20235 [6] GSE54349 [6] GSE27975 [6] GSE43928 [12] GSE32963 [6] GSE21278 [48] GSE15155 [12] GSE29045 [12] GSE21761 [43] GSE29572 [21] GSE31406 [12] GSE5582 [6] GSE32624 [6] GSE21836 [8] GSE35357 [12] GSE33101 [8] GSE29241 [6] GSE38693 [8] GSE35763 [6] GSE15433 [9] GSE30873 [6] GSE17796 [39] GSE42008 [6] GSE23040 [6] GSE39273 [6] GSE6275 [36] GSE1074 [12] GSE7897 [60] GSE22434 [8] GSE10954 [8] GSE46724 [6] GSE16002 [9] GSE14753 [6] GSE9146 [27] GSE32020 [26] GSE13364 [6] GSE5715 [10] GSE11420 [15] CEM+ CEM GSE10176 [6] GSE28389 [20] GSE48811 [20] GSE14059 [6] GSE4695 [6] GSE44339 [14] 0.0 GSE27816 [14] GSE21944 [6]

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20390 Status: Public on Jul 07 2010 Title: Deficiency in the 15 kDa Selenoprotein Inhibits Tumorigenicity and Metastasis of Colon Cancer Cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20388823 Summary & Design: Summary: Selenium has cancer preventive activity that is mediated, in part, through selenoproteins. The role of the 15 kDa selenoprotein (Sep15) in colon cancer was assessed by preparing and using mouse colon CT26 cells stably transfected with shRNA constructs targeting Sep15. Metabolic 75Se-labeling and Northern and Western blot analyses revealed that more than 90% of Sep15 was knocked down. Growth of the resulting Sep15-deficient CT26 cells was reduced (p<0.01) and cells formed significantly (p<0.001) fewer colonies in soft agar compared to control CT26 cells. Whereas most (14/15) BALB/c mice injected with control cells developed tumors, few (3/30) mice injected with Sep15 knockdown cells developed tumors (p<0.0001). The ability to form pulmonary metastases had similar results. Mice injected with the plasmid-transfected control cells had >250 lung metastases/mouse; however, mice injected with the Sep15 knockdown cells only had 7.8 +/- 5.4 metastases. To investigate molecular targets affected by Sep15 status, gene expression patterns between control and knockdown CT26 cells were compared. Ingenuity Pathways Analysis was used to analyze the 1045 genes that were significantly (p<0.001) affected by Sep15 deficiency. The highest scored biological functions were cancer and cellular growth and proliferation. Consistent with these observations, subsequent analyses revealed a G2/M cell cycle arrest in Sep15 CT26 knockdown cells. In contrast, to CT26 cells Sep15 knockdown in Lewis Lung Carcinoma (LLC1) cells did not affect anchorage-dependent or independent cell growth. These data suggest tissue specificity in the cancer protective effects of Sep15 knockdown, which are mediated, at least in part, by influencing the cell cycle.

Overall design: mRNA was isolated from plasmid-transfected control and shSep15 knockdown CT26 cells (three replicates of each). Microarray analysis was performed on Affymetrix Mouse 430_2 gene chips. Three arrays were analyzed from different mRNA samples for each construct.

Background corr dist: KL-Divergence = 0.0254, L1-Distance = 0.0347, L2-Distance = 0.0013, Normal std = 0.7444

0.566 Kernel fit Pairwise Correlations Normal fit

Density 0.283

0.000 CEM 1

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

Pre-normalization Quantiles

ControlControl - repeatControl - 1repeat - mAdbID:101315shSep15 - 2repeat - mAdbID:101316shSep15 3- repeat- mAdbID:101317 (0.17736)shSep15 - 1repeat - mAdbID:101321(0.119958) - 2repeat - mAdbID:101322(0.151187) 3 - mAdbID:101323 (0.183129) (0.182864)[ min (0.185502) ] [ medium ] [ max ] CEM 1 Mta2 842.3 1588.3 1645.1 P ( S | Z, I ) = 1.00 Rbbp4 129.6 212.3 249.3 Mean Corr = 0.74442 Mbd3 593.6 830.0 918.0 Chd3 1075.8 1500.3 1915.2 Gatad2a 3316.2 4045.2 4733.7 Gatad2b 580.5 780.5 957.9 Hdac2 54.1 61.6 89.8 Rbbp7 8080.9 9528.3 10385.6 Hnrnpl 1443.4 2594.1 2936.3 Tcf3 740.0 1154.5 1207.9 Rnps1 177.1 466.2 545.1 Snrnp40 1376.8 1802.5 1902.0 Ppm1g 4375.7 6565.8 6970.3 CEM 1 + Srsf4 1716.6 2810.8 3027.7 Top 10 Genes Arid1a 1119.9 1465.1 1828.3 Prr3 264.1 360.3 388.2 Alyref 2560.7 3904.7 4201.7 Trim28 4357.1 6803.2 8036.2

Null module GEO Series "GSE28830" 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=GSE28830 Status: Public on Dec 01 2013 Title: Differential gene expression in CD11b+ splenocytes from mice subject to social threat vs. control (II) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Gene expression profiling was carried out on splenocyte mRNA samples collected from 6 animals subject to repeated social threat and 6 animals subject to non-threatening control conditions (pooled into 3 groups of 2). The primary research question is whether gene expression differs in CD11b+ splenocytes from animals exposed to social threat vs non-threatening control conditions.

Keywords: Risk prediction

Overall design: This study provides an additional body of data from the same general protocol used in Series GSE16661, and will support more extensive analyses than the original study.

Background corr dist: KL-Divergence = 0.0554, L1-Distance = 0.0377, L2-Distance = 0.0018, Normal std = 0.5796

0.732 Kernel fit Pairwise Correlations Normal fit

Density 0.366

0.000 CEM 1

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

Pre-normalization Quantiles

ControlControl pool 1-2Control pool (0.221208) 3-4Threat pool (0.141855) 5-6 1Threat (0.0879381)(0.251615) 2Threat (0.0319181) 3Threat (0.133232) 4Threat (0.034694) 5Threat (0.0306072) 6 (0.0669333) [ min ] [ medium ] [ max ] CEM 1 Mta2 1420.9 1622.5 1796.5 P ( S | Z, I ) = 1.00 Rbbp4 86.6 95.8 161.3 Mean Corr = 0.63094 Mbd3 345.7 391.5 483.4 Chd3 420.3 486.1 994.7 Gatad2a 2314.7 2497.1 3465.8 Gatad2b 525.2 1202.0 1941.5 Hdac2 44.4 51.4 59.1 Rbbp7 3578.2 3830.7 6467.4 Hnrnpl 692.5 807.3 991.2 Tcf3 189.0 209.8 381.9 Rnps1 122.7 168.7 337.8 Snrnp40 687.4 710.3 756.4 Ppm1g 1864.1 1938.3 2497.0 CEM 1 + Srsf4 1992.5 2100.1 2186.0 Top 10 Genes Arid1a 1141.1 1395.6 1686.8 Prr3 175.6 195.0 279.2 Alyref 1942.9 2052.8 2294.7 Trim28 793.0 878.0 1663.5

Null module GEO Series "GSE33308" 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=GSE33308 Status: Public on Jan 01 2013 Title: Keratinocyte Growth Factor and Dexamethasone Plus Elevated cAMP Levels Synergistically Support Pluripotent Stem Cell Differentiation into Alveolar Epithelial Type II Cells. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23176317 Summary & Design: Summary: Alveolar epithelial type II (ATII)-like cells can be generated from murine embryonic stem cells (ESCs), although to date, no robust protocols applying specific differentiation factors are established. We hypothesized that the keratinocyte growth factor (KGF), an important mediator of lung organogenesis and primary ATII cell maturation and proliferation, together with dexamethasone, 8-bromoadenosine-cAMP, and isobutylmethylxanthine (DCI), which induce maturation of primary fetal ATII cells, also support the alveolar differentiation of murine ESCs. Here we demonstrate that the above stimuli synergistically potentiate the alveolar differentiation of ESCs as indicated by increased expression of the surfactant proteins (SP-) C and SP-B. This effect is most profound if KGF is supplied not only in the late stage, but at least also during the intermediate stage of differentiation. Our results indicate that KGF most likely does not enhance the generation of (mes)endodermal or NK2 homeobox 1 (Nkx2.1) expressing progenitor cells but rather, supported by DCI, accelerates further differentiation/maturation of respiratory progeny in the intermediate phase and maturation/proliferation of emerging ATII cells in the late stage of differentiation. Ultrastructural analyses confirmed the presence of ATII-like cells with intracellular composite and lamellar bodies. Finally, induced pluripotent stem cells (iPSCs) were generated from transgenic mice with ATII cell-specific lacZ reporter expression. Again, KGF and DCI synergistically increased SP-C and SP-B expression in iPSC cultures, and lacZ expressing ATII-like cells developed. In conclusion, ATII cell-specific reporter expression enabled the first reliable proof for the generation of murine iPSC-derived ATII cells. In addition, we have shown KGF and DCI to synergistically support the generation of ATII-like cells from ESCs and iPSCs. Combined application of these factors will facilitate more efficient generation of stem cell-derived ATII cells for future basic research and potential therapeutic application.

Overall design: mESCs at d24 of differentiation with KGF and DCI treatment

Background corr dist: KL-Divergence = 0.0344, L1-Distance = 0.0193, L2-Distance = 0.0005, Normal std = 0.6401

0.623 Kernel fit Pairwise Correlations Normal fit

Density 0.312

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

mESCs mESCsat d8 of mESCsat differentiation d8 of mESCsat differentiation d17 of mESCs at(Control) differentiation d17 of mESCs atwith differentiation (0.27148)d17 KGF of mESCsat (Control)differentiation d17treatment of mESCsat withdifferentiation d24 (0.0163216) (0.295072) KGFof mESCsat withdifferentiation d24 treatment DCIof mESCsat withdifferentiation d24 treatment KGF(0.016954)of at (Control)differentiation d24 and (0.054784) of DCI withdifferentiation (0.0714906) treatment KGF with treatment DCI[ (0.0612343) withmin treatment KGF(0.0582149) and] (0.0883732) DCI treatment[ medium (0.0660747) ] [ max ] CEM 1 Mta2 806.4 949.2 1079.7 P ( S | Z, I ) = 1.00 Rbbp4 270.9 559.2 1065.6 Mean Corr = 0.58307 Mbd3 568.3 925.3 1431.1 Chd3 540.5 723.0 1065.3 Gatad2a 1770.7 1896.7 2694.7 Gatad2b 216.4 239.2 477.0 Hdac2 50.0 63.4 120.2 Rbbp7 12042.8 14358.7 17053.7 Hnrnpl 2481.4 3233.0 4796.6 Tcf3 776.3 1462.9 2549.6 Rnps1 134.6 223.6 368.2 Snrnp40 660.4 926.3 1653.0 Ppm1g 1144.9 1357.9 2024.9 CEM 1 + Srsf4 1502.5 1841.5 2618.2 Top 10 Genes Arid1a 286.5 353.6 606.3 Prr3 254.9 307.6 447.1 Alyref 1457.0 2477.1 4149.9 Trim28 2415.4 3248.8 5401.4

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 (0.252944) rep2control (0.122186) rep3 controlsiRNA (0.200993) rep1controlsiRNA (0.126231) rep2PPARsiRNA (0.0945626) gamma rep3PPAR (0.129136) gammasiRNAPPAR rep1gammasiRNA (0.0307868) rep2siRNA (0.0214444) rep3 (0.0217157)[ min ] [ medium ] [ max ] CEM 1 Mta2 654.5 1237.2 2242.2 P ( S | Z, I ) = 1.00 Rbbp4 59.8 69.6 140.8 Mean Corr = 0.42594 Mbd3 743.8 819.7 1086.1 Chd3 369.1 398.8 1574.4 Gatad2a 2031.5 2769.1 4616.0 Gatad2b 438.7 528.2 785.8 Hdac2 31.0 41.5 61.9 Rbbp7 6394.8 10598.0 13110.9 Hnrnpl 456.0 823.5 2386.0 Tcf3 323.0 948.1 2576.8 Rnps1 100.6 133.8 198.0 Snrnp40 549.2 630.1 742.2 Ppm1g 1799.2 2434.7 3357.3 CEM 1 + Srsf4 1070.2 1178.2 1690.8 Top 10 Genes Arid1a 408.8 749.7 925.3 Prr3 112.5 253.5 680.1 Alyref 267.9 365.9 763.4 Trim28 1825.9 4532.0 5985.0

Null module GEO Series "GSE50729" 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=GSE50729 Status: Public on Sep 11 2013 Title: The polycomb protein Ezh2 regulates differentiation and plasticity of CD4 T helper type-1 and type-2 cells. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24238339 Summary & Design: Summary: Following antigen encounter by CD4 T cells, polarizing cytokines induce the expression of master regulators that control differentiation. Inactivation of the histone methyltransferase Ezh2 was found to specifically enhance T-helper (Th)1 and Th2 cell differentiation and plasticity. Ezh2 directly bound and facilitated correct expression of Tbx21 and Gata3 in differentiating Th1 and Th2 cells, accompanied by substantial tri-methylation at lysine 27 of histone 3 (H3K27-Me3). In addition, Ezh2 deficiency resulted in spontaneous generation of discrete IFN-Î³ and Th2 cytokine-producing populations in non-polarizing cultures, and under these conditions IFN-Î³ expression was largely dependent on enhanced expression of the transcription factor Eomesodermin. In vivo, Loss of Ezh2 caused increased pathology in a model of allergic asthma and resulted in progressive accumulation of memory phenotype Th2 cells. This study establishes a functional link between Ezh2 and transcriptional regulation of lineage-specifying genes in terminally differentiated CD4 T cells.

Overall design: Wild type and Ezh2 knock out unpolarized Th cells, Th1 cells and Th2 cells are profiled for mRNA expression

Background corr dist: KL-Divergence = 0.0344, L1-Distance = 0.0254, L2-Distance = 0.0007, Normal std = 0.6569

0.623 Kernel fit Pairwise Correlations Normal fit

Density 0.312

0.000 CEM 1

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

Pre-normalization Quantiles

Wild typeEzh2 unpolarized KOWild unpolarized type Ezh2Th Th1 cells KO ThcellsWild (0.190013) Th1 cells (0.109669)type cells Ezh2(0.0877565) Th2 (0.155027) KO cells Th2 (0.209592) cells (0.247942) [ min ] [ medium ] [ max ] CEM 1 Mta2 659.6 882.9 1001.0 P ( S | Z, I ) = 1.00 Rbbp4 594.6 862.4 1065.1 Mean Corr = 0.40862 Mbd3 626.4 775.0 922.2 Chd3 417.1 885.5 1207.8 Gatad2a 1271.7 1505.2 1833.9 Gatad2b 289.5 390.1 551.3 Hdac2 32.8 61.3 76.5 Rbbp7 13758.9 16970.7 19262.8 Hnrnpl 2292.2 2868.2 3395.3 Tcf3 948.0 1056.6 1127.9 Rnps1 451.9 630.8 803.6 Snrnp40 2053.9 2388.0 2618.4 Ppm1g 1822.2 1963.1 1968.3 CEM 1 + Srsf4 2991.4 3525.3 3987.8 Top 10 Genes Arid1a 199.4 252.4 284.4 Prr3 142.5 203.2 216.3 Alyref 6825.8 7414.0 7818.9 Trim28 1360.9 2275.3 2477.5

Null module GEO Series "GSE22251" 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=GSE22251 Status: Public on Sep 09 2011 Title: Necdin, a Negative Growth Regulator, is a Novel STAT3 Target Gene Down-Regulated in Human Cancer Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22046235 Summary & Design: Summary: We took a broad approach to identify novel STAT3 regulated genes by examining changes in the genome-wide gene expression profile by microarray, using cells expressing constitutively-activated STAT3. Using computational analysis, we were able to define the gene expression profiles of cells containing activated STAT3 and identify candidate target genes with a wide range of biological functions.

We demonstrated that STAT3 has an important role in regulating, both positively and negatively, a diverse array of cellular processes, including cell adhesion, cytoskeletal remodeling, nucleotide, lipid and protein metabolism, as well as signal transduction. This suggest that STAT3 coordinates expression of genes involved in multiple metabolic and biosynthetic pathways, integrating signals that lead to global transcriptional changes and oncogenesis.

Overall design: Balb/c-3T3 mouse fibroblasts, v-Src 3T3 cells and STAT3-C 3T3 cells were grown in DMEM/10% bovine calf serum supplemented with 1% penicillin and streptomycin. At each of 3 passages, cells from the five dishes were pooled and total RNA was extracted.

Background corr dist: KL-Divergence = 0.0448, L1-Distance = 0.0153, L2-Distance = 0.0002, Normal std = 0.5807

0.687 Kernel fit Pairwise Correlations Normal fit

Density 0.344

0.000 CEM 1

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

Pre-normalization Quantiles

BALB_VSRC__1BALB_VSRC__5BALB_VSRC__6 (0.0837103)Balb_Control_1 (0.0530666)Balb_Control_2 (0.054919)Balb_Control_3 (0.186457)STAT3_C_1 (0.111057)STAT3_C_2 (0.111528) (0.15611)STAT3_C_3 (0.123698) (0.119454) [ min ] [ medium ] [ max ] CEM 1 Mta2 794.9 1305.3 2112.5 P ( S | Z, I ) = 1.00 Rbbp4 140.5 182.7 227.6 Mean Corr = 0.37414 Mbd3 471.4 631.5 846.1 Chd3 952.0 1352.2 2175.4 Gatad2a 1840.2 3211.8 4859.6 Gatad2b 567.2 871.9 1499.6 Hdac2 57.1 72.3 88.5 Rbbp7 6626.6 9406.3 11152.3 Hnrnpl 689.4 956.1 1189.9 Tcf3 722.0 1128.2 1711.7 Rnps1 199.8 217.1 227.3 Snrnp40 1037.1 1260.5 1969.6 Ppm1g 2687.3 4125.0 4873.7 CEM 1 + Srsf4 1353.0 1617.0 2373.4 Top 10 Genes Arid1a 298.9 330.7 1116.2 Prr3 323.9 404.5 620.3 Alyref 3007.3 4522.9 6540.0 Trim28 2993.3 4111.7 6894.3

Null module GEO Series "GSE15770" 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=GSE15770 Status: Public on May 20 2009 Title: WT and Get1 +/- Bladder Time Course Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19494835 Summary & Design: Summary: Skin and bladder epithelia form effective permeability barriers through the activation of distinct differentiation gene programs. Employing a genome-wide gene expression study, we identified transcription regulators whose expression correlates highly with that of differentiation markers both in bladder and skin, including the Grainyhead factor Get1/Grhl3, already known to be important for epidermal barrier formation. In the bladder, Get1 is most highly expressed in the differentiated umbrella cells and its mutation in mice leads to a defective bladder epithelial barrier formation due to failure of apical membrane specialization. Genes encoding components of the specialized urothelial membrane, the uroplakins, were downregulated in Get1-/- mice. At least one of these genes, Uroplakin II, is a direct target of Get1. The urothelial-specific activation of the Uroplakin II gene is due to selective binding of Get1 to the Uroplakin II promoter in urothelial cells, most likely regulated by histone modifications. These results demonstrate a key role for Get1 in urothelial differentiation and barrier formation.

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

Background corr dist: KL-Divergence = 0.0667, L1-Distance = 0.0219, L2-Distance = 0.0008, Normal std = 0.5100

0.782 Kernel fit Pairwise Correlations Normal fit

Density 0.391

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

E18.5 Get1E18.5 +/- Get1 BladderE18.5 +/- Get1 Bladder E14.52-4 +/-(0.133209) WT Bladder E16.52-5 Bladder (0.0795622) WT E16.52-6 Bladder 1-3 (0.313083) WT (0.12562)E16.5 Bladder 1-1 WT (0.046541)E14.5 Bladder 1-2 WT (0.045426) Bladder 1-3 (0.045943) 1-6 (0.210615)[ min ] [ medium ] [ max ] CEM 1 Mta2 84.4 188.9 284.5 P ( S | Z, I ) = 1.00 Rbbp4 355.2 1209.2 1569.5 Mean Corr = 0.40493 Mbd3 108.5 208.8 258.4 Chd3 370.8 476.8 633.9 Gatad2a 4849.2 8523.0 9688.7 Gatad2b 78.5 112.5 167.4 Hdac2 2.8 249.6 437.0 Rbbp7 11473.3 15978.0 20748.2 Hnrnpl 33.7 223.2 445.3 Tcf3 79.7 167.3 324.4 Rnps1 23.1 65.6 169.4 Snrnp40 183.2 422.9 614.0 Ppm1g 543.9 770.7 880.6 CEM 1 + Srsf4 170.3 282.9 446.7 Top 10 Genes Arid1a 131.4 189.1 296.4 Prr3 759.5 978.9 1547.3 Alyref 51.6 477.5 819.3 Trim28 2243.8 3558.3 5096.6

Null module GEO Series "GSE30083" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

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

0.840 Kernel fit Pairwise Correlations Normal fit

Density 0.420

0.000 CEM 1

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

Pre-normalization Quantiles

SP1, biologicalSP2, biologicalSP3, rep1 biological(0.0659289)SP4, rep1 biological(0.0268684)SP1, rep1 biological(0.099327)SP2, rep1 biological(0.0441695)SP3, rep2 biological(0.067875)SP4, rep2 biological(0.0893871)SP1, rep2 biological(0.0369232)SP2, rep2 biological(0.0388524)SP3, rep3 biological(0.133075)SP4, rep3 biological(0.147116) rep3 (0.119903) rep3 (0.130574)[ min ] [ medium ] [ max ] CEM 1 Mta2 1149.3 2892.9 3695.5 P ( S | Z, I ) = 1.00 Rbbp4 397.5 601.9 1529.1 Mean Corr = -0.09553 Mbd3 532.0 743.4 960.3 Chd3 1959.6 2856.0 4213.8 Gatad2a 1655.0 2867.9 3351.3 Gatad2b 747.6 932.7 2070.4 Hdac2 75.5 108.8 212.9 Rbbp7 7839.2 10609.0 13199.8 Hnrnpl 2306.9 4653.5 6700.0 Tcf3 1190.5 1645.5 2086.7 Rnps1 582.2 746.9 1059.7 Snrnp40 1234.2 1905.1 2139.9 Ppm1g 2015.6 4505.0 5382.1 CEM 1 + Srsf4 2959.7 3211.7 3994.6 Top 10 Genes Arid1a 1097.7 2438.9 3620.8 Prr3 539.4 687.1 798.1 Alyref 2002.0 2909.9 5592.8 Trim28 2845.6 5480.7 6709.8

Null module GEO Series "GSE21137" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21137 Status: Public on Apr 20 2010 Title: Ultrastructural and transcriptional profiling of neuropathological misregulation of CREB function Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20395962 Summary & Design: Summary: We compare here the neurodegenerative processes observed in the hippocampus of bitransgenic mice with chronically altered levels of cAMP-response element-binding protein (CREB) function. The combination of genome-wide transcriptional profiling of degenerating hippocampal tissue with microscopy analyses reveals that the sustained inhibition of CREB function in A-CREB mice is associated with dark neuron degeneration, whereas its strong chronic activation in VP16-CREB mice primarily causes excitotoxic cell death and inflammation. Furthermore, the meta-analysis with gene expression profiles available in public databases identifies relevant common markers to other neurodegenerative processes and highlights the importance of the immune response in neurodegeneration. Overall, these analyses define the ultrastructural and transcriptional signatures associated with these two forms of hippocampal neurodegeneration, confirm the importance of fine-tuned regulation of CREBdependent gene expression for CA1 neuron survival and function, and provide novel insight into the function of CREB in the etiology of neurodegenerative processes.

Overall design: For each mouse genome 430 2.0 gene expression array (Affymetrix, Santa Clara, CA, USA), total RNA was extracted from the hippocampi of three to four mice with the same age, sex, and genotype to produce one pooled sample. We analyzed three late A-CREB pooled samples (6-week-old mice) and three late VP16-CREB pooled samples (3-week-off dox) with their corresponding control littermate samples (three pooled samples for each strain). To compare with early changes, we included two pooled A-CREB early samples (3-week-old mice) and two pooled VP16-CREB early samples (1-week-off dox) with their corresponding control littermate samples. In the case of A-CREB mice, we used the dataset GSE14320. We prepared new samples from bitransgenic mice and control littermates 1 week after transgene induction and hybridized them to mouse genome 430 2.0 genechips. The arrays were hybridized, washed, and screened for quality according to the manufacturers protocol.

Background corr dist: KL-Divergence = 0.1496, L1-Distance = 0.0345, L2-Distance = 0.0023, Normal std = 0.3737

1.067 Kernel fit Pairwise Correlations Normal fit

Density 0.534

0.000 CEM 1

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

Pre-normalization Quantiles

ControlControl littermateControl littermate for VP16-CREBVP16-CREB littermate for VP16-CREBVP16-CREB for 3 3 weeks-induction VP16-CREBweeks-inducedVP16-CREB 3 3 weeks-induction weeks-inducedControl 3 3 weeks-induction weeks-induced Control samplelittermatesample VP16-CREBsample1 littermatesample1 (0.104323) (0.0855404)for VP16-CREB VP16-CREBsample2 sample2 (0.110359) (0.081133)for 1 VP16-CREBweek-induced Control3 3 (0.0691763) (0.103362) 1 1 week-induction week-inducedControl littermate 1 week-inductionsampleControl littermate for sampleA-CREB1sampleA-CREB littermate(0.0645349) for A-CREB2 sample1 A-CREB 6(0.0322724) 6(0.0363769) weeks-old weeks-oldfor A-CREB 2 A-CREB6 6(0.0498875) weeks-old weeks-old sample sample 6 6 weeks-old weeks-old sample 1 sample1 (0.0278824) (0.022278) sample 2 sample2 (0.0162526) (0.0202051) 3 3 [(0.0327611) (0.143656) min ] [ medium ] [ max ] CEM 1 Mta2 157.3 461.9 651.5 P ( S | Z, I ) = 0.96 Rbbp4 23.8 87.0 239.9 Mean Corr = 0.25143 Mbd3 384.5 703.7 1087.8 Chd3 2131.0 2659.3 4100.9 Gatad2a 460.3 715.0 921.2 Gatad2b 116.9 294.4 1467.0 Hdac2 11.4 63.6 219.4 Rbbp7 6620.0 7959.1 10617.8 Hnrnpl 145.6 379.9 695.1 Tcf3 109.9 201.8 308.1 Rnps1 85.4 239.9 625.5 Snrnp40 491.7 588.9 721.7 Ppm1g 1162.9 1396.6 2123.2 CEM 1 + Srsf4 1234.8 1369.2 2115.3 Top 10 Genes Arid1a 844.3 1171.4 1603.4 Prr3 240.4 332.0 424.7 Alyref 270.6 492.8 916.2 Trim28 1728.9 1978.3 3045.4

Null module GEO Series "GSE23833" 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=GSE23833 Status: Public on Sep 01 2010 Title: The Forkhead factor FoxQ1 influences epithelial differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20717954 Summary & Design: Summary: The Forkhead family of transcription factors comprises numerous members and is implicated in various cellular functions, including cell growth, apoptosis, migration and differentiation.In this study we identified the Forkhead factor FoxQ1 as increased in expression during TGF-beta1 induced changes in epithelial differentiation, suggesting functional roles of FoxQ1 for epithelial plasticity.The repression of FoxQ1 in mammary epithelial cells led to a change in cell morphology characterized by an increase in cell size, pronounced cell-cell contacts and an increased expression of several junction proteins (e.g. E-cadherin). In addition, FoxQ1 knock-down cells revealed rearrangements in the actin-cytoskeleton and slowed down cell cycle G1-phase progression.Furthermore, repression of FoxQ1 enhanced the migratory capacity of coherent mammary epithelial cells.Gene expression profiling of NM18 cells indicated that FoxQ1 is a relevant downstream mediator of TGF-beta1 induced gene expression changes. This included the differential expression of transcription factors involved in epithelial plasticity, e.g. Ets-1, Zeb1 and Zeb2.In summary, this study has elucidated the functional impact of FoxQ1 on epithelial differentiation

Overall design:

Background corr dist: KL-Divergence = 0.0453, L1-Distance = 0.0772, L2-Distance = 0.0080, Normal std = 0.6930

0.668 Kernel fit Pairwise Correlations Normal fit

Density 0.334

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

2h_co._enriched12h_co._enriched22h_co._enriched3 (0.136873)2h_co._total1 (0.0613694)2h_co._total2 (0.0645816) (0.069203)2h_co._total3 (0.0702577)2h_TGFbeta_enriched1 (0.096129)2h_TGFbeta_enriched22h_TGFbeta_enriched32h_TGFbeta_total1 (0.150406)2h_TGFbeta_total2 (0.0647477)2h_TGFbeta_total3 (0.0594509) (0.0742851) (0.0746643) (0.0780316)[ min ] [ medium ] [ max ] CEM 1 Mta2 773.7 1830.2 2042.3 P ( S | Z, I ) = 0.95 Rbbp4 146.9 554.0 1923.9 Mean Corr = -0.03612 Mbd3 139.1 401.8 582.5 Chd3 944.2 2613.0 3018.5 Gatad2a 721.2 1383.0 1536.9 Gatad2b 665.6 1982.8 6378.0 Hdac2 76.8 370.9 489.5 Rbbp7 7219.8 15505.9 18475.6 Hnrnpl 170.7 368.8 437.5 Tcf3 405.4 1132.1 1272.0 Rnps1 112.8 319.1 475.0 Snrnp40 668.9 858.9 1263.3 Ppm1g 1953.8 3305.1 3704.4 CEM 1 + Srsf4 1770.6 1959.1 2303.0 Top 10 Genes Arid1a 340.8 603.9 1223.6 Prr3 279.8 431.9 615.4 Alyref 370.4 1082.7 1356.9 Trim28 3740.9 8760.4 10098.7

Null module GEO Series "GSE36810" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE36810 Status: Public on Mar 27 2012 Title: Expression data from mouse lungs exposed in-utero and/or as an adult to second-hand smoke (SHS) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22962063 Summary & Design: Summary: Second-hand smoke (SHS) exposure during pregnancy has adverse effects on offspring. We used microarrays to characterize the gene expression changes caused by in-utero exposure and adult exposure to SHS in adult mouse lungs.

Overall design: Left lungs from Balb/c male mice were collected at 15 weeks of age for RNA extraction and hybridization on Affymetrix mouse 430 2.0 microarrays. Based on their smoke exposure status, there are 4 groups of mice, each exposed in-utero to filtered-air or SHS and as an adult to filtered-air or SHS. We extracted RNA from 4 animals from each group for microarray analysis (N = 16 samples).

Background corr dist: KL-Divergence = 0.0998, L1-Distance = 0.0238, L2-Distance = 0.0008, Normal std = 0.4416

0.903 Kernel fit Pairwise Correlations Normal fit

Density 0.452

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_AA_biologicalLung_AA_biologicalLung_AA_biological rep1Lung_AA_biological (0.0111569) rep2Lung_AS_biological (0.0834357) rep3Lung_AS_biological (0.0423959) rep4Lung_AS_biological (0.0328373) rep1Lung_AS_biological (0.0291889) rep2Lung_SA_biological (0.0609954) rep3Lung_SA_biological (0.251666) rep4Lung_SA_biological (0.289593) rep1Lung_SA_biological (0.0225801) rep2Lung_SS_biological (0.0261806) rep3Lung_SS_biological (0.0223905) rep4Lung_SS_biological (0.0312291) rep1Lung_SS_biological (0.0269703) rep2 (0.0191919) rep3 (0.0152827) rep4 (0.0349058)[ min ] [ medium ] [ max ] CEM 1 Mta2 993.9 1121.4 1379.2 P ( S | Z, I ) = 0.95 Rbbp4 174.4 307.0 381.0 Mean Corr = -0.01356 Mbd3 296.4 333.2 562.6 Chd3 555.3 587.9 885.1 Gatad2a 1769.5 2082.5 3305.5 Gatad2b 297.0 363.7 534.3 Hdac2 147.8 297.3 367.2 Rbbp7 4507.7 5462.9 5727.2 Hnrnpl 602.9 745.8 1044.2 Tcf3 433.9 542.5 729.7 Rnps1 393.3 433.9 493.1 Snrnp40 423.2 459.5 507.3 Ppm1g 1463.2 1584.3 2263.6 CEM 1 + Srsf4 2038.9 2158.5 2249.0 Top 10 Genes Arid1a 1158.1 1426.1 2202.1 Prr3 212.8 227.0 283.8 Alyref 616.0 708.1 815.3 Trim28 1482.0 1699.4 2429.0

Null module GEO Series "GSE13805" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 7 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13805 Status: Public on Dec 02 2009 Title: Expression data from wild type and calreticulin deficient murine embryonic stem cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20506533 Summary & Design: Summary: Primordial genomic challenge compromises embryonic development and survival, and surveillance of deployed transcriptional programs may provide an early opportunity to forecast phenotype abnormalities. Here, comparisons between wild-type and calreticulin-ablated embryonic stem cells revealed transcriptome shifts precipitated by calreticulin loss. Bioinformatic analysis identified down and up-regulation in 1187 and 418 genes, respectively. Cardiovascular development precedes other organogenic programs, and examination of cardiogenic genes revealed a map of calreticulin-calibrated expression profiles that encompass the developmental regulators, Ccnd1, Ccnd2 and Notch1. Interrogation of primary function in the resolved network forecasted abnormalities during myocardial development. Whole embryo magnetic resonance imaging, verified by pathoanatomical analysis, diagnosed prominent ventricular septal defect. Correlation clustering and network resolution of probesets associated with protein folding/chaperoning and calcium handling demonstrated 14 and 19 genes, respectively, modulated by calreticulin deficiency. Calreticulin deletion provoked ontological re-prioritization of gene expression, molecular transport and protein trafficking that translated into multiple subcellular functional outcomes. Individual stem cell-derived cardiomyocytes lacking calreticulin demonstrated a disorganized contractile apparatus with mitochondrial paucity and architectural aberrations. Thus, bioinformatic deconvolution of primordial embryonic stem cell transcriptomes enables predictive phenotyping of defective developmental networks that coalesce from complex systems biology hierarchies.

Keywords: Comparison of embryonic stem cell genomes between wild type and calreticulin knockouts

Overall design: Stem cells cultured in triplicate (or more) were pooled to provide raw material per sample. Each sample represents material collected from three technical replicates or more. In this manner, two wild type samples, and five derived from calreticulin knockout samples, were obtained. Although sample content contains material from three or more technical replicates harvested contemporaneously, each sample is a distinct biological replicate. Total RNA was extracted from each of the samples and RNA pools were profiled on Affymetrix Mouse 430 2.0 Arrays to identify global gene expression changes invoked by genomic ablation of calreticulin.

Background corr dist: KL-Divergence = 0.0370, L1-Distance = 0.0281, L2-Distance = 0.0009, Normal std = 0.6423

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

Wild typeWild mouse typeCRT embryonicmouse knockoutCRT embryonic knockout stem mouseCRT cell, knockout stem embryonicmouseCRT biological cell, knockout embryonicmouseCRT biological stem rep1knockout embryonicmouse cell,(0.350452) stem rep2 biological embryonicmouse cell,(0.0534754) stem biological embryonic cell,rep1 stem biological(0.132307)[ cell,rep2min stem biological(0.154663) cell,rep3 ] biological(0.210998) rep4 (0.0648118) rep5[ medium (0.0332937) ] [ max ] CEM 1 Mta2 825.0 1552.0 2547.0 P ( S | Z, I ) = 0.93 Rbbp4 97.0 158.4 216.2 Mean Corr = 0.32156 Mbd3 534.2 732.8 1380.5 Chd3 314.0 345.9 438.5 Gatad2a 3497.7 6129.1 8699.8 Gatad2b 263.5 499.2 730.2 Hdac2 31.4 51.0 66.4 Rbbp7 6983.4 9725.7 10703.5 Hnrnpl 1183.1 2632.6 5592.1 Tcf3 739.4 1187.3 2223.8 Rnps1 363.3 469.2 691.7 Snrnp40 1972.6 2825.4 4921.3 Ppm1g 2704.6 4644.8 11231.0 CEM 1 + Srsf4 1543.8 2400.0 3307.4 Top 10 Genes Arid1a 1154.3 2875.7 5447.3 Prr3 278.4 408.2 770.7 Alyref 1219.5 5057.1 9605.0 Trim28 10484.1 13753.0 18789.4

Null module GEO Series "GSE18500" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 35 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18500 Status: Public on Dec 31 2009 Title: Mast cells in response to some pathogens elicit a transcriptional program devoid of type I IFN response Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20421474 Summary & Design: Summary: Although mast cells elicit proinflammatory and type I IFN responses upon VSV infection, in response to L.monocytogenes (L.m) or S. Typhimurium (S.t), such cells elicit a transcriptional program devoid of type I IFN response.

Balanced induction of proinflamatory and type I interferon (IFN) responses upon activation of Toll like receptors (TLRs) determines the outcome of microbial infections and the pathogenesis of autoimmune and other inflammatory diseases. Mast cells, key components of the innate immune system, are known for their debilitating role in allergy and autoimmune syndromes. However, their potential role in anti-microbial host defenses is increasingly being acknowledged. How mast cells interact with microbes and the nature of responses triggered thereof is not well characterized. Here we show that in response to TLR activation by Gram-positive and negative bacteria or their components like LPS, unlike macrophages, mast cells elicit pro-inflammatory but not type I IFN responses. We demonstrate that in mast cells, the bound bacteria and TLR ligands remain trapped at the cell surface and do not undergo internalization - a prerequisite for type I IFN induction. Such cells could, however, elicit type I IFNs in response to vesicular stomatitis virus (VSV), which accesses the cytosolic RIG-I receptor. Although important for anti-viral immunity, a strong type I IFN response is known to contribute to pathogenesis during bacterial infection. Thus, while endowed with the capacity to elicit type I IFNs in response to viral infection, the fact that mast cells only elicit pro-inflammatory responses upon bacterial infection illustrates that mast cells, key effector cells of the innate immune system, are well adjusted for optimal anti-bacterial and anti-viral responses.

Overall design: Gene Expression levels were determined by the Affymetrix MOE 430 2.0 GeneChips. Signal Intensities were calculated using the RMA algorithm and for statistical analysis we applied GeneSpring GX 10 software suite (Agilent Technologies, Waldbronn, Germany). MultiExperiment Viewer (MEV) software version 4.4 of the Institute for Genomic Research was used for clustering algorithm data analysis and visualization.

Background corr dist: KL-Divergence = 0.1240, L1-Distance = 0.0285, L2-Distance = 0.0012, Normal std = 0.4128

0.981 Kernel fit Pairwise Correlations Normal fit

Density 0.490

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 O cntrwt (0.0383554) O L.m.wt (0.0121378)O S.t.wt (0.0144579) O VSV-AV2MC cntr (0.0236974)MC (0.0176755) L.m.MC (0.0329147) S.t. MC(0.105392) VSV-AV2IFNAR (0.0217004) OIFNAR cntr (0.0245996) L.m.IFNAR (0.0170401) S.t.MC (0.0277689)cntr_1MC (0.0244998)L.m._1MC (0.030207)S.t._1wt (0.0518117)MACwt cntr_1 MAC wt (0.0115255)L.m._1 MACwt (0.0227129)S.t._1 MAC (0.0235736)wt cntr_2 MAC wt (0.0407095)L.m._2 MACwt (0.0136094)S.t._2 MAC (0.013756)MC VSV-AV2_1 cntr_2MC (0.0148742)L.m._2 (0.0207129)MC (0.0373889)S.t._2MC (0.0964556) VSV-AV2_1IFNAR MACIFNAR (0.0184872) cntr_1 MACIFNAR (0.0213747)L.m._1 MACwt MAC (0.0140604)S.t._1wt cntr_3 MAC (0.0346323) MC (0.0143434)VSV-AV2_2 cntr_3MC (0.0261141)VSV-AV2_2 (0.0498069)IFNAR MACIFNAR (0.0479623) cntr_2 MACIFNAR (0.0115918)L.m._2 MAC (0.0125288)S.t._2 (0.0115213)[ min ] [ medium ] [ max ] CEM 1 Mta2 822.2 1034.2 2305.4 P ( S | Z, I ) = 0.89 Rbbp4 112.2 230.9 1844.6 Mean Corr = 0.16439 Mbd3 425.5 856.0 1476.7 Chd3 324.1 592.3 2847.5 Gatad2a 1715.7 3354.1 6450.4 Gatad2b 135.7 327.9 801.8 Hdac2 25.2 34.9 44.5 Rbbp7 4534.8 6762.7 9383.6 Hnrnpl 905.5 1497.9 5638.4 Tcf3 249.0 519.7 1122.5 Rnps1 62.8 125.2 330.8 Snrnp40 532.3 911.4 1525.9 Ppm1g 848.7 952.3 1555.6 CEM 1 + Srsf4 859.5 1189.0 3224.7 Top 10 Genes Arid1a 140.1 333.1 972.5 Prr3 113.5 183.8 580.8 Alyref 1767.2 3212.2 6205.0 Trim28 1035.0 1891.5 3193.6

Null module GEO Series "GSE46500" 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=GSE46500 Status: Public on May 01 2013 Title: Gene expression data for three mouse auditory brainstem nuclei at two times of development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23708139 Summary & Design: Summary: Genome-wide gene expression was obtained in three auditory brainstem nuclei (defined below), at two different ages in mice, postnatal day (P)3 and P14. The primary aim was to identify genes which are differentially expressed between the medial nucleus of the trapezoid body (MNTB) and the superior olive (LSO), at both age groups.

Overall design: Tissue samples from the ventral cochlear nucleus (VCN), the medial nucleus of the trapezoid body (MNTB) and the lateral superior olive (LSO) were collected from 200 Î¼m thick fresh transverse mouse brainstem slices prepared with a vibratome tissue slicer. Individual brainstem nuclei were dissected out with fine forceps under optical control with a binocular. For each nucleus (VCN, MNTB, and LSO), the tissue from six male C57Bl6 mice at postnatal day (P) 3, and from three male C57Bl6 mice at P14 was pooled. The RNA was isolated with the RNeasy Micro kit (Qiagen); RNA samples were amplified using a WT ovation Pico RNA amplification (Nugen, CA, USA). The cDNA was hybridized onto mouse Affymetrix microarrays 430 2.0 (Affymetrix, Santa Clara, USA).

Background corr dist: KL-Divergence = 0.0190, L1-Distance = 0.0101, L2-Distance = 0.0001, Normal std = 0.7487

0.533 Kernel fit Pairwise Correlations Normal fit

Density 0.266

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

VCN_P14LSO_P14 (0.160589)MNTB_P14 (0.146889)VCN_P3 (0.0978475)LSO_P3 (0.252204)MNTB_P3 (0.0961169) (0.246354) [ min ] [ medium ] [ max ] CEM 1 Mta2 466.7 526.6 566.6 P ( S | Z, I ) = 0.75 Rbbp4 50.2 78.4 133.9 Mean Corr = 0.61487 Mbd3 477.3 544.1 674.4 Chd3 513.6 848.4 1012.1 Gatad2a 5707.4 6331.7 7138.8 Gatad2b 1073.7 1277.3 1426.6 Hdac2 66.6 82.8 127.2 Rbbp7 2455.3 3097.0 3253.2 Hnrnpl 876.9 1089.0 1256.7 Tcf3 350.3 491.5 596.8 Rnps1 54.0 88.9 107.5 Snrnp40 453.1 564.6 591.8 Ppm1g 946.1 1575.4 1778.7 CEM 1 + Srsf4 3130.7 3414.4 3934.3 Top 10 Genes Arid1a 733.1 1006.7 1162.1 Prr3 810.0 1206.9 1350.8 Alyref 989.0 1159.7 1445.2 Trim28 1198.2 1786.5 1895.9

Null module GEO Series "GSE42238" 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=GSE42238 Status: Public on Feb 19 2013 Title: The C-terminus of CBFˆ-SMMHC is required to induce embryonic hematopoietic defects and leukemogenesis. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23152542 Summary & Design: Summary: The C-terminus of CBFˆ-SMMHC, the fusion protein produced by a chromosome 16 inversion in acute myeloid leukemia subtype M4Eo, contains domains for self-mulimerization and transcriptional repression, both of which have been proposed to be important for leukemogenesis by CBFˆ-SMMHC. To test the role of the fusion protein’s C-terminus in vivo, we generated knock-in mice expressing a C-terminally truncated CBFˆ-SMMHC (CBFˆ-SMMHC˛C95). Embryos with a single copy of CBFˆ-SMMHCDC95 were viable and showed no defects in hematopoiesis, while embryos homozygous for the CBFˆ-SMMHC˛C95 allele had hematopoietic defects and died in mid-gestation, similar to embryos with a single-copy of the full-length CBFˆ-SMMHC˛C95.

To identify gene expression changes induced by CBFˆ-SMMHCDC95, we compared the gene expression profile in the blood cells of Cbfb+/+, Cbfb+/˛C95, and Cbfb˛C95/˛C95 embryonic day 12.5 (E12.5) mice.

Overall design: Cbfb+/˛C95 were mated together to generate Cbfb+/+, Cbfb+/˛C95, and Cbfb˛C95/˛C95 embryos. Blood from 8-10 E12.5 embryos of the same genotype was pooled, and RNA was isolated, labeled, and hybridized to Affymetrix Genechip mouse microarray (430 2.0) chips. 3 chips were used for each genotype.

Background corr dist: KL-Divergence = 0.0484, L1-Distance = 0.0351, L2-Distance = 0.0021, Normal std = 0.5825

0.685 Kernel fit Pairwise Correlations Normal fit

Density 0.342

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

Cbfb˛C95/˛C95Cbfb˛C95/˛C95Cbfb˛C95/˛C95 peripheralCbfb+/˛C95 peripheral blood,Cbfb+/˛C95 peripheral replicateblood,peripheralCbfb+/˛C95 replicateblood,peripheral 1 Cbfb+/+ (0.0959675)blood, replicate peripheral 2 Cbfb+/+ replicate(0.332034)blood,peripheral 3 Cbfb+/+ replicate(0.110284)blood,peripheral 1 (0.0398035)blood, replicate peripheral 2 replicate(0.0831139)blood, 3 replicate(0.0407204)blood, 1 (0.0661195) replicate 2 (0.1218)[ min 3 (0.110157) ] [ medium ] [ max ] CEM 1 Mta2 819.2 901.9 1046.7 P ( S | Z, I ) = 0.54 Rbbp4 185.4 194.6 219.2 Mean Corr = 0.62526 Mbd3 1281.2 1379.3 1847.0 Chd3 397.7 406.1 461.8 Gatad2a 4211.8 4925.6 6087.4 Gatad2b 1022.2 1041.9 1159.9 Hdac2 109.1 117.8 149.7 Rbbp7 5883.1 7213.0 7497.6 Hnrnpl 4223.1 4989.2 5576.9 Tcf3 768.9 853.0 1076.0 Rnps1 191.7 238.5 270.9 Snrnp40 1256.0 1348.2 1634.4 Ppm1g 4131.2 5002.3 5652.7 CEM 1 + Srsf4 1061.8 1395.7 1756.9 Top 10 Genes Arid1a 663.0 779.2 866.0 Prr3 331.8 389.4 476.4 Alyref 2003.8 2692.8 4209.3 Trim28 2936.5 4054.5 4400.8

Null module GEO Series "GSE5037" 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=GSE5037 Status: Public on Jun 09 2006 Title: zhang-affy-mouse-217286 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: In our original grant we proposed to use the NR3B-null mouse model to study the role of NR3B subunit in motor neuron function. We have now successfully generated NR3B null mice. Interestingly, NR3B-null mice invariably die at age P4-P8. Our preliminary examination indicates that the motor strength of these mice is severely impaired prior to death. As we continue to explore the cause of death in NR3B null mice, we propose to conduct gene profiling experiments to search for transcription changes in the brain related to ablation of the NR3B gene. We have used the facility provided by the NINDS/NIMH Microarray Consortium to identify genes that show abnormal expression patterns in these mice. We would like to compare these changes with that opccured in SOD1 mice, a mouse model of motor neuron diseases. Analysis of these genes will help to identify changes in networks and pathways that may cause the death of NR3B-null mice. These studies will further help to elucidate the functional role of NR3B in motor neurons.

We will compare samples from motor neurons of wild type and SOD1 mice to identify genes that show abnormal expression patterns, which may be implicated in the death of SOD1 mice and shared with the same changes in NR3B-null mice.

We hypothesize that genes with their transcription level changing significantly by ablation of NR3B will be associated with the molecular mechanism underlying the death of motor neurons in NR3B null mice.

As NR3B is expressed primarily in the motor neurons of hindbrain and spinal cord, we have first collected and analyzed the spinal cord samples from NR3B null mice and wild-type controls in P4, an age of disease onset. We like to compare motor neuron and spinal cord smaples from SOD1 mice at the age prior to the disease onset. Total RNA from total 12 samples will be purified from ~200 motor neurons obtained by Laser Capture Microdissection and the total spinal cord. Extracted RNAs will be subjected to one or two rounds of amplification and the obtained cRNA will be biotinylated. The purified cRNA will be sent to the NINDS/NIMH Microarray Consortium be used to hybridize the GeneChip Mouse Genome 430 2.0 Array. The hybridization, scanning, and initial data analysis of these GeneChips will be conducted by the Consortium staff. We will analyze the collected data further after data collection. We will first identify genes that show significant changes between wild-type and SOD1 mice and then compare that with the result from NR3B null mice.

Keywords: dose response

Overall design:

Background corr dist: KL-Divergence = 0.0803, L1-Distance = 0.0825, L2-Distance = 0.0124, Normal std = 0.5517

0.841 Kernel fit Pairwise Correlations Normal fit

Density 0.420

0.000 CEM 1

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

Pre-normalization Quantiles

spinal cord,spinal ventral cord,spinal ventralspinal cord,spinal cord: ventralspinal cord,spinal D60WTSP1_e1_le1 cord: ventralspinal cord,spinal D60WTSP2_e1_le1 cord: ventralspinal cord,spinal D60WTSP3_e1_le1 cord: ventralspinal cord,(0.0692686)spinal D60SODSP1_e1_le1 cord: ventralspinal cord,(0.085991)spinal D60SODSP2_e1_le1 cord: ventralspinal cord,(0.0912867)spinal D60SODSP3_e1_le1 cord: ventralspinal cord,spinal (0.0672389) D60WTSPMN1_e1_le1 cord: ventralspinal cord,spinal (0.0812084) D60WTSPMN2_e1_le1 cord: ventralspinal cord,brain, (0.077169) D60WTSPMN3_e1_le1 cord: ventralspinal brainstem:brain, D60SODSPMN1_e1_le1(0.062299) cord: spinal brainstem:brain, D60SODSPMN2_e1_le1D60WTFNMN1_e1_le1(0.0421385) cord: brainstem:brain, D60SODSPMN3_e1_le1D60WTFNMN2_e1_le1(0.0509009) brainstem:brain, D60WTFNMN3_e1_le1 (0.026145) brainstem:brain, D60SODFNMN1_e1_le1(0.0263641) (0.0189269) brainstem: D60SODFNMN2_e1_le1(0.088616) (0.0310762) D60SODFNMN3_e1_le1(0.0827111) (0.0124301)[ min (0.0392191) (0.0470106)] [ medium ] [ max ] CEM 1 Mta2 3.5 33.6 367.6 P ( S | Z, I ) = 0.38 Rbbp4 7.2 95.2 210.3 Mean Corr = 0.09011 Mbd3 31.7 90.9 770.5 Chd3 72.6 363.2 1317.3 Gatad2a 201.8 407.5 1047.0 Gatad2b 171.8 244.9 434.7 Hdac2 28.1 56.4 85.3 Rbbp7 4411.1 9227.1 11734.2 Hnrnpl 107.4 246.7 1822.1 Tcf3 4.7 147.2 325.7 Rnps1 3.9 73.6 236.5 Snrnp40 257.4 402.8 547.3 Ppm1g 765.4 1436.3 1979.2 CEM 1 + Srsf4 634.6 1378.7 2118.8 Top 10 Genes Arid1a 46.4 108.7 833.4 Prr3 86.0 302.9 527.6 Alyref 502.9 886.2 1317.0 Trim28 1252.4 1946.3 2438.4

Null module GEO Series "GSE35543" 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=GSE35543 Status: Public on Dec 06 2012 Title: Gene expression profiling of in vitro derived induced and natural FOXP3+ regulatory T cells and ex-iTreg cells in the mouse Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23125413 Summary & Design: Summary: Induced Treg (iTreg) cells are essential for tolerance and can be used therapeutically, yet their stability in vivo and mechanisms of suppression are unresolved. Here, we used a treatment model of colitis to examine the role of autologous IL-10 in iTreg cell function. Mice treated with IL-10+/+ iTreg cells in combination with IL-10/ natural Treg (nTreg) cells survived and gained weight, even though iTreg cells were numerically disadvantaged and comprised just ~20% of all Treg cells in treated mice. Notably, ~85% of the transferred iTreg cells lost Foxp3 expression (ex-iTreg) but retained a portion of the iTreg transcriptome which failed to limit their pathogenic potential. The TCR repertoires of iTreg and ex-iTreg cells exhibited almost no overlap, which indicates that the two populations are clonally unrelated and maintained by different selective pressures. These data demonstrate a potent and critical role for iTreg cell produced IL-10 that can supplant the IL-10 produced by nTreg cells and compensate for the inherent instability of the iTreg population.

Overall design: BALB/c Rag1-/- mice were treated with 500,00 WT nTreg cells plus 500,000 WT in-vitro-derived iTreg cells. After 125 days cells were sorted by flow cytometry from spleens and mesenteric lymph nodes from 14 treated mice. EGFP+ Thy1.1+ iTreg cells, EGFP+ Thy1.1 nTreg cells, and EGFPThy1.1+ ex-iTreg cells were pooled and used to generate total RNA for each iTreg, nTreg, and ex-iTreg array set, which was labeled and hybridized to Affymetrix 430 2.0 GeneChips in accordance to the manufacturers protocol. Two sets of arrays were performed, and the results were averaged. Both iTreg and nTreg array sets were compared to a) naˆﬂve CD4+EGFP Tconv cells from Foxp3EGFP. The subset of probe sets whose expression increased or decreased by twofold or more relative to Tconv cells as a common standard was identified and used for further analysis.

Background corr dist: KL-Divergence = 0.0351, L1-Distance = 0.0306, L2-Distance = 0.0010, Normal std = 0.6659

0.630 Kernel fit Pairwise Correlations Normal fit

Density 0.315

0.000 CEM 1

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

Pre-normalization Quantiles

Mouse invivoMouse nTreg invivoMouse cells, nTreg stableMouse replicate cells, invitro stableMouse replicate pool iTreginvitro ex-iTregMouse 1 cells, (0.0885096) pooliTreg ex-iTreg cells, replicate2 cells, (0.104725) replicate cells, replicate pool replicate pool 1 (0.213564) pool 1 [(0.188576) pool 2min (0.246507) 2 (0.158118) ] [ medium ] [ max ] CEM 1 Mta2 872.5 958.8 1159.6 P ( S | Z, I ) = 0.16 Rbbp4 1527.1 1648.6 1909.1 Mean Corr = 0.16231 Mbd3 454.5 561.6 598.4 Chd3 1831.6 2627.6 2744.3 Gatad2a 2338.8 2456.0 2973.7 Gatad2b 300.2 357.7 510.2 Hdac2 165.9 191.5 271.7 Rbbp7 6156.3 7078.8 7270.8 Hnrnpl 1732.1 2018.0 2905.5 Tcf3 1024.6 1162.1 1233.7 Rnps1 693.1 763.7 815.7 Snrnp40 1333.6 1402.4 1502.8 Ppm1g 1007.6 1140.3 1399.7 CEM 1 + Srsf4 2655.6 2785.7 2868.3 Top 10 Genes Arid1a 495.8 662.4 789.2 Prr3 297.8 385.5 434.2 Alyref 2370.2 2442.6 2480.0 Trim28 1265.4 1561.1 2025.1

Null module GEO Series "GSE38409" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38409 Status: Public on Jun 02 2012 Title: Expression data from mouse lungs, exposed in-utero to second-hand smoke (SHS) and challenged with ovalbumin (OVA) as adults. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23898987 Summary & Design: Summary: SHS exposure during pregnancy has adverse effects on offspring.

We used microarrays to characterize the gene expression changes caused by in-utero SHS exposure and adult (19-23 weeks) OVA challenge in 23-week mouse lungs.

Overall design: Left lungs from Balb/c male and female mice were collected at 23 weeks of age for RNA extraction and hybridization on Affymetrix mouse 430 2.0 microarrays. Based on the gender differences and in-utero exposure status, there are 4 groups of mice, females and males, exposed in-utero to filtered-air or SHS. All were exposure to OVA (19-23 weeks). We extracted RNA from 4 animals from each group for microarray analysis (total N = 16 samples).

Background corr dist: KL-Divergence = 0.0488, L1-Distance = 0.0396, L2-Distance = 0.0021, Normal std = 0.5850

0.726 Kernel fit Pairwise Correlations Normal fit

Density 0.363

0.000 CEM 1

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

Pre-normalization Quantiles

Lung_AF_biologicalLung_AF_biologicalLung_AF_biological rep1Lung_AF_biological (0.108299) rep2Lung_AM_biological (0.0673302) rep3Lung_AM_biological (0.0406988) rep4Lung_AM_biological (0.0482984) rep1Lung_AM_biological (0.048756) rep2Lung_EF_biological (0.0662373) rep3Lung_EF_biological (0.0549732) rep4Lung_EF_biological (0.0818127) rep1Lung_EF_biological (0.0326041) rep2Lung_EM_biological (0.0600286) rep3Lung_EM_biological (0.0577302) rep4Lung_EM_biological (0.0717503) rep1Lung_EM_biological (0.0835033) rep2 (0.0682215) rep3 (0.0598251) rep4 (0.0499309)[ min ] [ medium ] [ max ] CEM 1 Mta2 580.9 1730.3 2015.0 P ( S | Z, I ) = 0.11 Rbbp4 341.0 614.7 694.8 Mean Corr = -0.08531 Mbd3 424.5 504.0 584.9 Chd3 541.2 645.7 869.1 Gatad2a 1466.1 2458.2 2962.7 Gatad2b 500.4 841.1 961.1 Hdac2 70.3 223.1 356.2 Rbbp7 4700.5 5192.7 6102.8 Hnrnpl 559.5 1273.5 1601.0 Tcf3 636.8 723.6 919.9 Rnps1 238.5 323.6 458.2 Snrnp40 430.4 560.3 639.3 Ppm1g 778.9 1201.7 1895.7 CEM 1 + Srsf4 1515.3 1876.0 2133.2 Top 10 Genes Arid1a 208.3 1209.3 1911.2 Prr3 169.9 246.4 295.0 Alyref 674.6 1322.1 1749.0 Trim28 1065.4 1940.9 2239.9

Null module GEO Series "GSE13306" 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=GSE13306 Status: Public on Nov 16 2008 Title: Retinoic Acid Enhances Foxp3 Induction Indirectly by Relieving Inhibition from CD4(+)CD44(hi) Cells. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19006694 Summary & Design: Summary: CD4(+)Foxp3(+) regulatory T (Treg) cells originate primarily from thymic differentiation, but conversion of mature T lymphocytes to Foxp3 positivity can be elicited by several means, including in vitro activation in the presence of TGF-beta. Retinoic acid (RA) increases TGF-beta-induced expression of Foxp3, through unknown molecular mechanisms. We showed here that, rather than enhancing TGF-beta signaling directly in naive CD4(+) T cells, RA negatively regulated an accompanying population of CD4(+) T cells with a CD44(hi) memory and effector phenotype. These memory cells actively inhibited the TGF-beta-induced conversion of naive CD4(+) T cells through the synthesis of a set of cytokines (IL-4, IL-21, IFN-gamma) whose expression was coordinately curtailed by RA. This indirect effect was evident in vivo and required the expression of the RA receptor alpha. Thus, cytokine-producing CD44(hi) cells actively restrain TGF-beta-mediated Foxp3 expression in naive T cells, and this balance can be shifted or fine-tuned by RA.

Overall design: All gene expression profiles were obtained from highly purified T cell populations sorted by flow cytometry. To reduce variability, cells from multiple mice were pooled for sorting, and replicates were generated for essentially all groups. RNA from 0.5-3 x 105 cells was amplified, labeled, and hybridized to Affymetrix M430v2 microarrays. Raw data were preprocessed with the RMA algorithm in GenePattern, and averaged expression values were used for analysis.

Background corr dist: KL-Divergence = 0.0519, L1-Distance = 0.0522, L2-Distance = 0.0058, Normal std = 0.5629

0.709 Kernel fit Pairwise Correlations Normal fit

Density 0.354

0.000 CEM 1

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

Pre-normalization Quantiles

LPFoxp3-no1LPFoxp3-no2 (0.0418456)LPFoxp3+no1 (0.023543)LPFoxp3+no2 (0.0442162)SpRAFoxp3-no2 (0.023888)SpRAFoxp3+no1SpRAFoxp3+no2 (0.0440505)SpFoxp3-no1 (0.0243011)SpFoxp3-no2 (0.0521507) (0.0316877)SpFoxp3+no1 (0.0546891)SpFoxp3+no2 (0.0537096)CD4+Memoryno1 (0.0322632)CD4+Memoryno2CD4+Memoryno3 (0.0655654)CD4+MemoryRAno1 (0.0680424)CD4+MemoryRAno2 (0.0903321)CD4+MemoryRAno3 (0.0903939) (0.0916303) (0.167691)[ min ] [ medium ] [ max ] CEM 1 Mta2 326.1 399.5 718.7 P ( S | Z, I ) = 0.07 Rbbp4 250.4 344.4 609.5 Mean Corr = 0.50459 Mbd3 73.8 125.7 256.0 Chd3 1131.6 1793.8 3170.9 Gatad2a 511.6 601.7 972.7 Gatad2b 228.5 355.9 625.9 Hdac2 51.8 69.3 103.2 Rbbp7 13967.8 19692.9 39850.8 Hnrnpl 194.8 319.7 531.1 Tcf3 159.2 189.9 313.2 Rnps1 149.1 411.3 455.7 Snrnp40 375.7 498.5 1442.9 Ppm1g 2291.8 3079.7 7574.3 CEM 1 + Srsf4 1582.9 2958.8 3607.9 Top 10 Genes Arid1a 105.0 125.0 320.4 Prr3 152.4 313.4 449.4 Alyref 215.6 583.8 995.8 Trim28 1660.0 2608.8 4273.2

Null module GEO Series "GSE15741" 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=GSE15741 Status: Public on Nov 10 2009 Title: Gene expression profiles of forced miR-200 expression in 344SQ lung adenocarcinoma cells with high metastatic potential Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19759262 Summary & Design: Summary: Metastatic disease is a primary cause of cancer-related death, and factors governing tumor cell metastasis have not been fully elucidated. Here we addressed this question by using tumor cell lines derived from mice that develop metastatic lung adenocarcinoma owing to expression of mutant K-ras and p53. A feature of metastasis-prone tumor cells that distinguished them from metastasis-incompetent tumor cells was plasticity in response to changes in their microenvironment. They transited reversibly between epithelial and mesenchymal states, forming highly polarized epithelial spheres in 3-dimensional culture that underwent epithelial-mesenchymal transition (EMT) following treatment with transforming growth factor-beta or injection into syngeneic mice. This plasticity was entirely dependent upon the microRNA-200 family, which decreased during EMT. Forced expression of miR-200 abrogated the capacity of these tumor cells to undergo EMT, invade, and metastasize and conferred transcriptional features of metastasis-incompetent tumor cells. We conclude that microenvironmental cues direct tumor metastasis by regulating miR-200 expression.

Overall design: Cell lines from p53R172Hg/+ K-rasLA1/+ mice were derived from tumor tissues removed at autopsy from two different mice (#344 and #393). The tissues were minced, placed in culture, and passed serially in RPMI 1640 supplemented with 10% fetal bovine serum (FBS), which yielded mass populations of tumor cells derived from primary lung tumors (344P and 393P), mediastinal lymph nodes (344LN and 393LN), and a subcutaneous site (344SQ). Stable 344SQ cell lines expressing the miR-200b-200a-429 cluster or control vector were generated by transduction with lentivirus vectors. GFP positive transfectant pools were selected by growth in RPMI 1640 with 10% FBS and puromycin. RNA samples of miR-200b-200a-429 knockup versus control (from triplicate cultures of each) were processed and analyzed on Affymetrix Mouse Expression Array 430A 2.0 chips.

Background corr dist: KL-Divergence = 0.0327, L1-Distance = 0.0246, L2-Distance = 0.0007, Normal std = 0.6647

0.624 Kernel fit Pairwise Correlations Normal fit

Density 0.312

0.000 CEM 1

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

Pre-normalization Quantiles

ControlControl A (0.0553977)Control B (0.16492)429 C (0.0591237) B (0.19404)429 A (0.190711)429 C (0.335807) [ min ] [ medium ] [ max ] CEM 1 Mta2 692.5 874.3 1296.9 P ( S | Z, I ) = 0.06 Rbbp4 180.8 324.5 648.0 Mean Corr = 0.38983 Mbd3 263.7 377.2 633.5 Chd3 75.2 189.3 219.9 Gatad2a 1199.6 1431.3 2588.1 Gatad2b 200.0 347.0 425.2 Hdac2 53.9 58.1 73.9 Rbbp7 6287.9 7723.5 7985.4 Hnrnpl 2260.2 3604.7 4965.6 Tcf3 452.5 539.9 874.8 Rnps1 156.0 260.0 285.4 Snrnp40 548.0 892.9 1234.3 Ppm1g 1975.4 2425.1 3703.2 CEM 1 + Srsf4 975.1 1302.6 1807.5 Top 10 Genes Arid1a 1186.4 1588.7 1934.0 Prr3 161.9 208.3 243.2 Alyref 6326.1 9729.1 9967.8 Trim28 943.9 1223.5 1569.3

Null module GEO Series "GSE51883" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 30 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51883 Status: Public on Jan 28 2014 Title: Effect of Mirn378 overexpression on gene expression during C2C12 myogenic and BMP2-induced osteogenic differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Background: MicroRNAs (miRNAs) are a family of small, non-coding single-stranded RNA molecules involved in post-transcriptional regulation of gene expression. As such, they are believed to play a role in regulating the step-wise changes in gene expression patterns that occur during cell fate specification of multipotent stem cells. Here, we have studied whether terminal differentiation of C2C12 myoblasts is indeed controlled by lineage-specific changes in miRNA expression.

Results: Using a previously generated RNA polymerase II (Pol-II) ChIP-on-chip dataset, we show differential Pol-II occupancy at the promoter regions of six miRNAs during C2C12 myogenic versus BMP2-induced osteogenic differentiation. Overexpression of one of these miRNAs, miR-378, enhances Alp activity, calcium deposition and mRNA expression of osteogenic marker genes in the presence of BMP2.

Conclusions: Our results demonstrate a previously unknown role for miR-378 in promoting BMP2-induced osteogenic differentiation. #!#

Overall design: Stable C2C12 cell lines C2C12-pMirn0 and C2C12-pMirn378 were generated by lentiviral transduction of C2C12 myoblasts with a Mirn378-overexpression construct and its parent vector, respectively. C2C12-pMirn0 and C2C12-pMirn378 cells were plated at 2.5 x 10^4 cells/cm2 (day -1), cultured for 1 day in DMEM 10%NCS, then (d0) treated with or without 300 ng/ml bone morphogenetic protein 2 (BMP2) for 6 days. RNA was extracted on d0, d3 and d6 and hybridized to GeneChip Mouse Genome 430 2.0 array (Affymetrix).

Background corr dist: KL-Divergence = 0.1521, L1-Distance = 0.0728, L2-Distance = 0.0106, Normal std = 0.4058

1.104 Kernel fit Pairwise Correlations Normal fit

Density 0.552

0.000 CEM 1

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

Pre-normalization Quantiles

C2C12-pMirn0_d0_rep1C2C12-pMirn0_d0_rep2C2C12-pMirn0_d0_rep3C2C12-pMirn0_day (0.0559424)C2C12-pMirn0_day (0.0609134)C2C12-pMirn0_day (0.0798642) 3_untreated_rep1C2C12-pMirn0_day 3_untreated_rep2C2C12-pMirn0_day 3_untreated_rep3 C2C12-pMirn0_day(0.0309937) 6_untreated_rep1 C2C12-pMirn0_day(0.0222859) 6_untreated_rep2 C2C12-pMirn0_day(0.0318531) 6_untreated_rep3 C2C12-pMirn0_day(0.0396277) 3_BMP2 C2C12-pMirn0_day(0.0160267) 3_BMP2 treated_rep1 C2C12-pMirn0_day(0.0448417) 3_BMP2 treated_rep2C2C12-pMirn0_day (0.0194839)6_BMP2 treated_rep3C2C12-pMirn378_d0_rep1 (0.018767)6_BMP2 treated_rep1C2C12-pMirn378_d0_rep2 (0.0156578)6_BMP2 treated_rep2C2C12-pMirn378_d0_rep3 (0.0233088) treated_rep3C2C12-pMirn378_day (0.0736218)(0.0252077)C2C12-pMirn378_day (0.0874799)(0.0193551)C2C12-pMirn378_day (0.117895) 3_untreated_rep1C2C12-pMirn378_day 3_untreated_rep2C2C12-pMirn378_day 3_untreated_rep3C2C12-pMirn378_day (0.0260557) 6_untreated_rep1C2C12-pMirn378_day (0.00736071) 6_untreated_rep2C2C12-pMirn378_day (0.0180133) 6_untreated_rep3C2C12-pMirn378_day (0.0196111) 3_BMP2C2C12-pMirn378_day (0.0176698) 3_BMP2C2C12-pMirn378_day treated_rep1 (0.0229865) 3_BMP2C2C12-pMirn378_day treated_rep2 (0.00688841)6_BMP2 treated_rep3 (0.0141437)6_BMP2 treated_rep1 (0.0261247)6_BMP2 treated_rep2 (0.0179371)[ treated_rep3 min (0.0195496) ] (0.0205341)[ medium ] [ max ] CEM 1 Mta2 228.0 349.1 505.0 P ( S | Z, I ) = 0.06 Rbbp4 231.2 384.3 617.8 Mean Corr = 0.31403 Mbd3 715.1 883.8 1600.2 Chd3 527.2 878.6 1380.0 Gatad2a 1425.4 1837.2 3650.5 Gatad2b 425.4 614.7 917.0 Hdac2 46.0 82.5 117.9 Rbbp7 5842.9 7047.2 12463.5 Hnrnpl 1551.2 2017.3 4158.2 Tcf3 761.3 1206.9 2138.0 Rnps1 152.2 231.3 348.7 Snrnp40 583.1 719.1 1422.5 Ppm1g 832.7 1083.1 2328.7 CEM 1 + Srsf4 1011.4 1412.7 2399.2 Top 10 Genes Arid1a 123.1 218.0 320.9 Prr3 169.7 292.4 443.5 Alyref 1909.3 2396.6 6498.4 Trim28 1347.7 1778.5 4294.3

Null module GEO Series "GSE38831" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 7 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.606 Kernel fit Pairwise Correlations Normal fit

Density 0.303

0.000 CEM 1

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

Pre-normalization Quantiles

C57BL/6JE13.5C57BL/6JE14.5C57BL/6JE15.5 (0.130222)C57BL/6JE16.5 (0.0490066)C57BL/6JE17.5 (0.248712)C57BL/6JE18.5 (0.0260854)C57BL/6JADULT (0.0508202) (0.0806694) COLON (0.414484)[ min ] [ medium ] [ max ] CEM 1 Mta2 130.0 162.2 244.8 P ( S | Z, I ) = 0.04 Rbbp4 221.5 635.7 826.1 Mean Corr = 0.60792 Mbd3 423.8 454.6 509.7 Chd3 335.1 510.1 622.3 Gatad2a 3670.6 4517.6 5293.7 Gatad2b 120.3 150.2 189.5 Hdac2 349.2 472.2 659.2 Rbbp7 3095.6 6135.7 7508.3 Hnrnpl 379.3 493.5 616.7 Tcf3 203.4 242.4 304.7 Rnps1 78.7 101.2 147.7 Snrnp40 511.3 773.2 1080.4 Ppm1g 602.4 697.7 892.8 CEM 1 + Srsf4 320.0 360.4 500.8 Top 10 Genes Arid1a 196.1 268.3 366.4 Prr3 390.0 772.3 990.9 Alyref 498.0 736.5 814.9 Trim28 1829.6 2244.0 3569.4

Null module GEO Series "GSE26616" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.652 Kernel fit Pairwise Correlations Normal fit

Density 0.326

0.000 CEM 1

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

Pre-normalization Quantiles

Ezh1/2 2KOEzh1/2 FACS 2KOEzh1/2 purified FACS 2KOEzh1/2 purified basalFACS WTEzh1/2 epidermal purifiedFACS matrix WTEzh1/2 purified FACS cellsORS cells WT (0.303327) cellspurified basalFACS(0.131411) (0.0956672) epidermal purified matrix cellsORS cells [ (0.261091)cells (0.139024)min (0.0694798) ] [ medium ] [ max ] CEM 1 Mta2 1054.6 1959.9 2240.8 P ( S | Z, I ) = 0.02 Rbbp4 265.0 451.8 719.2 Mean Corr = 0.50460 Mbd3 985.2 1292.1 2191.3 Chd3 640.5 827.1 1266.3 Gatad2a 2186.1 2844.0 4404.0 Gatad2b 314.2 459.9 623.9 Hdac2 32.3 63.3 91.6 Rbbp7 8005.4 8643.9 9810.3 Hnrnpl 2979.9 3580.1 5479.2 Tcf3 1006.3 1491.1 1760.3 Rnps1 420.5 685.8 911.6 Snrnp40 910.2 1198.5 2047.7 Ppm1g 1361.2 1949.6 2375.5 CEM 1 + Srsf4 1925.4 2695.4 3634.7 Top 10 Genes Arid1a 463.3 696.4 985.7 Prr3 211.1 317.2 542.8 Alyref 4066.3 5539.9 8289.7 Trim28 2992.2 4421.2 6620.9

Null module GEO Series "GSE50687" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 38 -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=GSE50687 Status: Public on Jan 31 2014 Title: Expression data from testes of the mouse X-chromosome substitution strains Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24743563 Summary & Design: Summary: To investigate the evolutionary divergence of transcriptional regulation between the mouse subspecies, we performed transcriptome analysis by microarray on testes from the X-chromosome substitution strain, which carries different subspecies-derived X chromosome on the host subspecies genome. Transcription profiling showed that large-scale aberrations in gene expression were occurred on the introgressed X chromosome. This improper expression was restored by introducing chromosome 1 from the same donor strain as the X chromosome, suggesting that the genetic incompatibility between trans-acting regulatory gene(s) on chromosome 1 and X-linked downstream genes might be a cause of the misregulation.

Overall design: Testes were collected from 5- and 7-day-old males for RNA extraction and the microarray experiments were performed by using Affymetrix microarrays. Testes from three different males for each strain were tested independently. Tested males are from control C57BL/6J (B6) strain, MSM strain, X-chromosome substitution strain (B6-ChrXMSM), partial X-chromosome substitution strain 1 (B6-ChrXTMSM), partial X-chromosome substitution strain 2 (XS39-tel), and restored (B6-ChrXTMSM X B6-Chr1MSM) F1.

Background corr dist: KL-Divergence = 0.1752, L1-Distance = 0.0398, L2-Distance = 0.0028, Normal std = 0.3593

1.136 Kernel fit Pairwise Correlations Normal fit

Density 0.568

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

B6 testesB6 at testes 5dpp,B6 at testesbiological 5dpp,MSM at biological 5dpp,testes rep1MSM biological (0.0225687)at testes rep25dpp,MSM (0.0262419)at testesbiological rep35dpp,B6-ChrXMSM (0.0113275)at biological 5dpp,B6-ChrXMSM rep1 biologicaltestes(0.174727)B6-ChrXMSM rep2 at testes(0.128457)B6-ChrXTMSM 5dpp, rep3 at testes(0.180385)biologicalB6-ChrXTMSM 5dpp, at biological B6-ChrXTMSM testes5dpp, rep1 biologicalatXS39-tel(0.00779775)testes 5dpp,rep2 atXS39-tel(0.00557254) testesbiological testes 5dpp,rep3 atXS39-tel(0.013433) atbiological testes5dpp, 5dpp, rep1(B6-ChrXTMSM at biological (0.0108174)testesbiological 5dpp, rep2(B6-ChrXTMSM at (0.00744813)biological 5dpp, rep3 rep1(B6-ChrXTMSM x (0.0111345) biological (0.0108649)B6-Chr1MSM)F1 rep2B6 x (0.0200056) B6-Chr1MSM)F1testes rep3B6 x (0.0506599)at B6-Chr1MSM)F1testes testes7dpp,B6 at testes biologicalat testes7dpp, 5dpp,MSM at biologicalat testes 7dpp,biologicaltestes 5dpp,rep1MSM biologicalat (0.0203376) at biologicaltestes 5dpp, rep27dpp,MSM rep1 (0.0169872) at biologicaltestes(0.00482194)biological rep37dpp,B6-ChrXMSM rep2 (0.0122606)at (0.014316)biological 7dpp,B6-ChrXMSM rep3 rep1 (0.0267761) biologicaltestes(0.0168158)B6-ChrXMSM rep2 at testes(0.0216217)B6-ChrXTMSM 7dpp, rep3 at testes(0.0370327)biologicalB6-ChrXTMSM 7dpp, at biological B6-ChrXTMSM testes7dpp, rep1 biologicalat(B6-ChrXTMSM(0.0257743)testes 7dpp,rep2 at(B6-ChrXTMSM(0.00580268) testesbiological 7dpp,rep3 at(B6-ChrXTMSM(0.00758805) biologicalx 7dpp, B6-Chr1MSM)F1 rep1(B6-ChrXTMSM biologicalx(0.0141973) B6-Chr1MSM)F1 rep2(B6-ChrXTMSM x(0.00495556) B6-Chr1MSM)F1 rep3 testes(B6-ChrXTMSM x(0.00661155) B6-Chr1MSM)F1 at testes 7dpp,(B6-ChrXTMSM x B6-Chr1MSM)F1 at testesbiological 7dpp,(B6-ChrXTMSM x B6-Chr1MSM)F1 at testesbiological 7dpp, rep1x B6-Chr1MSM)F1 at testes biological(0.0111799) 7dpp, rep2x B6-Chr1MSM)F1 at testes biological(0.0134914) 7dpp, rep3 at testes biological(0.0103748) 7dpp, [rep4 min at testes biological(0.00453872) 7dpp, rep5 at ] biological(0.0193694) 7dpp, rep6 biological(0.0070069) rep7[ (0.00688426)medium rep8 (0.0098146) ] [ max ] CEM 1 Mta2 405.0 465.3 900.8 P ( S | Z, I ) = 0.01 Rbbp4 1112.3 1649.3 2044.1 Mean Corr = 0.01020 Mbd3 499.9 590.1 815.2 Chd3 685.1 775.0 1257.7 Gatad2a 1091.9 1330.1 3523.1 Gatad2b 292.4 694.6 1095.9 Hdac2 64.2 150.8 216.9 Rbbp7 17174.9 20316.1 23181.1 Hnrnpl 1637.7 1986.7 5806.2 Tcf3 1213.8 1407.3 2752.9 Rnps1 403.4 580.2 672.3 Snrnp40 1323.6 1502.4 1849.2 Ppm1g 558.1 760.5 1383.7 CEM 1 + Srsf4 2623.7 2924.3 3558.7 Top 10 Genes Arid1a 165.1 226.9 452.7 Prr3 286.4 365.3 684.9 Alyref 3224.7 3783.2 5234.9 Trim28 2826.4 3264.1 7554.6

Null module GEO Series "GSE12454" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 13 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12454 Status: Public on Aug 01 2009 Title: The SWI/SNF protein ATRX co-regulates pseudoautosomal genes that have translocated to autosomes in the mouse genome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18842153 Summary & Design: Summary: Pseudoautosomal regions (PAR1 and PAR2) in eutherians retain homologous regions between the X and Y chromosomes that play a critical role in the obligatory X-Y crossover during male meiosis. Genes that reside in the PAR1 are exceptional in that they are rich in repetitive sequences and undergo a very high rate of recombination. Remarkably, murine PAR1 homologs have translocated to various autosomes, reflecting the complex recombination history during the evolution of the mammalian X chromosome. We now report that the SNF2-type chromatin remodeling protein ATRX controls the expression of eutherians ancestral PAR1 genes that have translocated to autosomes in the mouse. In addition, we have identified two potentially novel mouse PAR1 orthologs. We propose that the ancestral PAR1 genes share a common epigenetic environment that allows ATRX to control their expression.

Overall design: At P0.5, n = 4 biological replicates of littermate-matched wt/ko pairs (for pair #2 there is one wt and 2 Atrx-null samples (2A & 2B) and we count this as 2 pairs).

Background corr dist: KL-Divergence = 0.0342, L1-Distance = 0.0308, L2-Distance = 0.0011, Normal std = 0.6463

0.648 Kernel fit Pairwise Correlations Normal fit

Density 0.324

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

E13.5 wildE13.5 type wildE13.5 #1 type(0.114902) wildE13.5 #2 type(0.0824295) Atrx-nullE13.5 #3 (0.0611068) Atrx-null E13.5#1 (0.0941831) Atrx-null P0.5#2 (0.0600889) wild P0.5#3 type (0.129699) wild #1P0.5 type(0.0734892) wild #2P0.5 type(0.0553501) Atrx-null #3P0.5 (0.0787002) Atrx-null #1P0.5 (0.0570239) Atrx-null #2AP0.5 (0.0240172) Atrx-null #2B (0.0668933) #3 (0.102117) [ min ] [ medium ] [ max ] CEM 1 Mta2 1115.9 1717.4 2466.5 P ( S | Z, I ) = 0.01 Rbbp4 185.2 306.7 568.4 Mean Corr = 0.34988 Mbd3 620.7 886.2 1727.1 Chd3 2735.0 3326.9 4424.9 Gatad2a 1884.8 2425.9 4279.7 Gatad2b 515.6 807.9 1211.4 Hdac2 270.1 374.8 744.3 Rbbp7 3597.8 4103.6 5026.4 Hnrnpl 734.2 2366.1 3838.0 Tcf3 852.0 1088.3 3995.8 Rnps1 207.3 340.4 628.2 Snrnp40 533.7 1225.9 1996.2 Ppm1g 3567.8 4309.5 5009.6 CEM 1 + Srsf4 2068.4 2591.4 4506.5 Top 10 Genes Arid1a 1688.8 3212.8 4434.8 Prr3 1111.0 1483.4 1806.0 Alyref 933.8 1435.7 5382.5 Trim28 4243.5 6324.3 9267.9

Null module GEO Series "GSE27932" 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=GSE27932 Status: Public on Mar 16 2011 Title: FoxOs are lineage-restricted redundant tumor suppressors and regulate endothelial cell homeostasis. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17254969 Summary & Design: Summary: Activated phosphoinositide 3-kinase (PI3K)-AKT signaling appears to be an obligate event in the development of cancer. The highly related members of the mammalian FoxO transcription factor family, FoxO1, FoxO3, and FoxO4, represent one of several effector arms of PI3K-AKT signaling, prompting genetic analysis of the role of FoxOs in the neoplastic phenotypes linked to PI3K-AKT activation. While germline or somatic deletion of up to five FoxO alleles produced remarkably modest neoplastic phenotypes, broad somatic deletion of all FoxOs engendered a progressive cancer-prone condition characterized by thymic lymphomas and hemangiomas, demonstrating that the mammalian FoxOs are indeed bona fide tumor suppressors. Transcriptome and promoter analyses of differentially affected endothelium identified direct FoxO targets and revealed that FoxO regulation of these targets in vivo is highly context-specific, even in the same cell type. Functional studies validated Sprouty2 and PBX1, among others, as FoxO-regulated mediators of endothelial cell morphogenesis and vascular homeostasis.

Overall design: Mice were engineered with negative control (MxCre- Fk1 L/L Fk2 L/L Afx L/L) and experimental (MxCre+ Fk1 L/L Fk2 L/L Afx L/L) genotypes. RNAs were isolated from Lung endothelial cells (2 negative controls, 2 experimental), liver sinusoidal endothelial cells (3 negative controls, 3 experimental) and thymus cells (2 negative controls, 2 experimental), and profiled on Affymetrix Mouse Genome 430 2.0 Array.

Background corr dist: KL-Divergence = 0.0486, L1-Distance = 0.0400, L2-Distance = 0.0023, Normal std = 0.5970

0.712 Kernel fit Pairwise Correlations Normal fit

Density 0.356

0.000 CEM 1

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

Pre-normalization Quantiles

Lung EC,Lung control, EC,Lung control, rep1 EC,Lung (0.0331975) experimental, rep2 EC,Liver (0.0402684) experimental, sinusoidalLiver rep1 sinusoidal (0.0596358)Liver rep2EC, sinusoidalcontrol, (0.0187645)Liver EC, sinusoidalcontrol, rep1Liver EC, (0.0640398) sinusoidalcontrol, rep2Liver EC, (0.101289) sinusoidalexperimental, rep3Thymus, EC, (0.0706746) experimental,Thymus, EC,control, rep1 experimental,Thymus, control, rep1(0.0615867) rep2 Thymus,(0.137857) experimental, rep2(0.0234109) rep3 (0.125894) experimental, (0.0514091) rep1 (0.110928) rep2 (0.101045)[ min ] [ medium ] [ max ] CEM 1 Mta2 677.6 1440.2 3092.2 P ( S | Z, I ) = 0.01 Rbbp4 209.4 294.8 1600.9 Mean Corr = 0.33313 Mbd3 363.1 532.5 713.5 Chd3 316.3 965.5 1888.9 Gatad2a 2302.7 2591.4 2811.9 Gatad2b 365.1 675.4 1070.5 Hdac2 425.7 654.4 736.7 Rbbp7 3814.9 4800.2 5382.0 Hnrnpl 575.4 2871.8 3709.3 Tcf3 267.2 885.2 2237.8 Rnps1 100.0 194.4 746.3 Snrnp40 559.1 715.3 1042.3 Ppm1g 1839.0 2155.5 2734.3 CEM 1 + Srsf4 866.7 1308.5 2559.5 Top 10 Genes Arid1a 942.4 1263.1 4855.7 Prr3 233.0 325.9 502.0 Alyref 2758.1 3268.6 4885.6 Trim28 2045.5 2578.6 5139.2

Null module GEO Series "GSE54490" 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=GSE54490 Status: Public on Feb 16 2014 Title: FoxA1 directs the lineage and immunosuppressive properties of FoxA1+ regulatory T cells in EAE and MS Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24531377 Summary & Design: Summary: Affymetrix gene expression analysis was carried out to investigate the differences in gene profile of MBP89-101-reactive encephalitogenic T cells before and after co-culture with cerebellar granular neurons (CGNs). Co-culture of MBP89-101-reactive encephalitogenic T cells with CGNs leads to generation of T cells with regulatory T cells phenotype (CD4+CD25+membrane bound TGF-b+ T cells) or a new regulatory phenotype (CD4highPD-L1high T cells). CGN-induced CD4+CD25+membrane bound TGF-b+ T regulatory cells, CD4highPD-L1high T cells were purified by FACSAria. IFN-beta induced T lymphocytes (CD4highPD-L1high T cells) were also FACSAria purified. All these populations were compared to MBP89-101-reactive encephalitogenic T cells. Samples were prepared from biological triplicates for each FACSAria sorted population.

Overall design: There are four different cell types, as determined by cell surface markers, in triplicate in the experiment.

Background corr dist: KL-Divergence = 0.0239, L1-Distance = 0.0546, L2-Distance = 0.0040, Normal std = 0.7910

0.572 Kernel fit Pairwise Correlations Normal fit

Density 0.286

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

EncephalitogenicEncephalitogenicEncephalitogenic Tcellsneuron rep1 Tcells (0.0387884)neuroninduced rep2 Tcells (0.0561224)neuroninduced FoxA1Treg rep3 (0.0167066)Treginduced FoxA1Treg rep1rep1Treg FoxA1Treg (0.0702728)(0.0683183) rep2rep2Treg (0.0357418)(0.0501319) rep3rep3IFN-beta (0.0362354)(0.0350431)IFN-beta inducedIFN-beta induced FoxA1Treg induced FoxA1Treg rep1 FoxA1Treg (0.211904) rep2 (0.188464) rep3[ min (0.192271) ] [ medium ] [ max ] CEM 1 Mta2 491.6 1779.9 2043.0 P ( S | Z, I ) = 0.01 Rbbp4 264.8 852.7 1146.7 Mean Corr = 0.34366 Mbd3 392.4 491.7 699.7 Chd3 1342.7 2996.4 4112.4 Gatad2a 1416.2 2931.7 3293.8 Gatad2b 573.6 1653.2 1917.7 Hdac2 45.3 86.1 140.5 Rbbp7 6968.3 14321.0 16010.3 Hnrnpl 1728.6 2203.4 3008.9 Tcf3 832.0 939.8 1311.4 Rnps1 156.6 538.5 627.8 Snrnp40 1081.0 1403.0 1601.6 Ppm1g 1305.7 5249.5 5813.6 CEM 1 + Srsf4 2549.0 3098.7 3329.4 Top 10 Genes Arid1a 298.2 2913.5 3485.0 Prr3 175.3 214.8 248.9 Alyref 5676.3 7490.0 8470.8 Trim28 1496.3 4264.1 4811.3

Null module GEO Series "GSE13104" 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=GSE13104 Status: Public on Oct 10 2008 Title: p53+/- mouse osteosarcoma RNA array (with mc3T3 and one RS control) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: RNA expression profiles from 12 (twelve) osteosarcomas arisen from p53+/- mouse were compared with a mc3T3 osteoblast control, and a rhabdomyosarcoma expression profile which was from a mouse with the same genetic background.

Overall design: Total RNA was extracted from 12 osteosarcomas and 1 rhabdomyosarcoma, both arisen from p53+/- mice. Total RNA was also extracted from a cultured mc3T3 osteoblast cell line as control. RNA microarray was performed on the 14 samples, and expression profiles were compared.

Background corr dist: KL-Divergence = 0.1999, L1-Distance = 0.0504, L2-Distance = 0.0061, Normal std = 0.3348

1.192 Kernel fit Pairwise Correlations Normal fit

Density 0.596

0.000 CEM 1

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

Pre-normalization Quantiles

mc3T3 osteoblastc2846-(1)c2984 osteosarcoma control osteosracomao19 (0.317083)osteosarcomao7-1 (0.0559964) osteosarcoma (0.0972625)m710 (0.0203781) osteosarcomam525 (0.0481866) osteosarcomac3193 (0.0514625)osteosarcomam849 (0.058086)osteosarcomam824 osteosarcoma(0.0301369)m825 (0.0913519)osteosarcomac3261 (0.056461)osteosarcomam718 (0.0351269)rhabdomyosarcomam520 osteosarcoma(0.0599528) (0.0458613) (0.0326544)[ min ] [ medium ] [ max ] CEM 1 Mta2 505.3 781.4 1205.6 P ( S | Z, I ) = 0.00 Rbbp4 11.2 80.2 160.7 Mean Corr = 0.41859 Mbd3 450.6 698.1 1123.3 Chd3 202.7 371.2 1677.0 Gatad2a 1070.3 1609.2 2672.2 Gatad2b 117.2 196.1 296.5 Hdac2 8.3 55.8 120.9 Rbbp7 8158.1 11925.3 18277.7 Hnrnpl 86.6 379.5 1527.3 Tcf3 285.7 488.5 1014.6 Rnps1 49.2 157.6 685.2 Snrnp40 974.8 1197.4 1573.8 Ppm1g 1632.0 2236.5 2971.1 CEM 1 + Srsf4 977.5 1572.6 1981.0 Top 10 Genes Arid1a 469.1 797.2 1415.0 Prr3 147.8 258.4 361.5 Alyref 721.0 2041.5 2927.9 Trim28 1574.0 2802.9 4092.9

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

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

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

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

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

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

0.774 Kernel fit Pairwise Correlations Normal fit

Density 0.387

0.000 CEM 1

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

Pre-normalization Quantiles

activatedactivated CD8alphaactivated CD8alpha cDCs,activated CD11b replicate cDCs,activated cDCs,CD11b replicate 1 activated(0.0631491) replicate cDCs,pDCs, 2 activated(0.0326346) replicatereplicate pDCs, 1 (0.0596013)activated replicate NK 21 (0.0218815)(0.074497) cells,activated NK 2 replicate (0.106565) cells, B replicatelymphocytes, 1 (0.204519) 2 (0.207667) replicate[ min 1 (0.229486) ] [ medium ] [ max ] CEM 1 Mta2 382.9 612.9 1335.3 P ( S | Z, I ) = 0.00 Rbbp4 135.7 259.6 1135.4 Mean Corr = 0.45655 Mbd3 373.6 742.6 1535.2 Chd3 355.0 794.7 1551.1 Gatad2a 432.0 618.8 1329.3 Gatad2b 362.9 454.8 931.4 Hdac2 43.4 57.7 76.4 Rbbp7 6829.0 11375.6 22295.1 Hnrnpl 211.1 261.0 828.4 Tcf3 379.3 561.1 2855.6 Rnps1 115.7 138.9 272.9 Snrnp40 1227.3 1790.4 4040.0 Ppm1g 1817.3 2069.1 7322.3 CEM 1 + Srsf4 2017.2 3045.5 5036.7 Top 10 Genes Arid1a 235.7 373.2 732.4 Prr3 94.5 153.9 364.6 Alyref 744.5 890.7 3461.5 Trim28 1561.3 1969.0 5422.3

Null module GEO Series "GSE25574" 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=GSE25574 Status: Public on Nov 29 2010 Title: Hypothalamic transcriptome plasticity in two rodent species reveals divergent differential gene expression but conserved pathways Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21070396 Summary & Design: Summary: We have addressed the question of how different rodent species cope with the life-threatening homeostatic challenge of dehydration at the level of transcriptome modulation in the supraoptic nucleus (SON), a specialised hypothalamic neurosecretory apparatus responsible for the production of the antidiuretic peptide hormone arginine vasopressin (AVP). AVP maintains water balance by promoting water conservation at the level of the kidney. Dehydration evokes a massive increase in the regulated release of AVP from SON axon terminals located in the posterior pituitary, and this is accompanied by a plethora of changes in the morphology, electrophysiological properties, biosynthetic and secretory activity of this structure. Microarray analysis was used to generate a definitive catalogue of the genes expressed in the mouse SON, and to describe how the gene expression profile changes in response to dehydration. Comparison of the genes differentially expressed in the mouse SON as a consequence of dehydration with those of the rat has revealed many similarities, pointing to common processes underlying the function-related plasticity in this nucleus. In addition we have identified many genes that are differentially expressed in a species-specific manner. However, in many cases, we have found that the hyperosmotic cue can induce species-specific alterations in the expression of different genes in the same pathway. The same functional end can be served by different means, via differential modulation, in different species, of different molecules in the same pathway. We suggest that pathways, rather than specific genes, should be the focus of integrative physiological studies based on transcriptome data.

Overall design: Microarray analysis. Separate microarrays (n=4) were probed using independently generated target. For each completely independent replicate, tissue from 1 mouse was used for RNA extraction.

Background corr dist: KL-Divergence = 0.0641, L1-Distance = 0.0211, L2-Distance = 0.0008, Normal std = 0.5165

0.772 Kernel fit Pairwise Correlations Normal fit

Density 0.386

0.000 CEM 1

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

Pre-normalization Quantiles

SON MouseSON ControlMouseSON Control Mouse1 (0.193506)SON Control Mouse2 (0.0666238)SON Control Mouse3 (0.0487661)SON Dehydrated Mouse4 (0.060352)SON DehydratedMouseSON (48hrs) DehydratedMouse (48hrs)1 (0.293212) Dehydrated (48hrs)2 (0.124727) (48hrs)3 (0.121478)[ 4min (0.0913354) ] [ medium ] [ max ] CEM 1 Mta2 73.5 412.5 519.3 P ( S | Z, I ) = 0.00 Rbbp4 72.2 122.7 237.7 Mean Corr = 0.20560 Mbd3 102.9 344.1 461.5 Chd3 439.8 1329.3 1355.3 Gatad2a 3400.0 5222.1 7154.7 Gatad2b 508.8 1070.7 1300.4 Hdac2 25.3 52.3 154.2 Rbbp7 4053.9 4856.0 6836.7 Hnrnpl 362.3 902.1 1056.3 Tcf3 40.7 298.7 385.4 Rnps1 20.7 75.4 112.9 Snrnp40 291.9 373.7 496.6 Ppm1g 764.1 2117.4 2320.9 CEM 1 + Srsf4 1544.1 2342.6 5252.0 Top 10 Genes Arid1a 444.9 827.9 1006.0 Prr3 772.0 866.5 1098.5 Alyref 248.2 730.3 1255.7 Trim28 1077.3 1241.5 1567.1

Null module GEO Series "GSE46443" 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=GSE46443 Status: Public on Oct 21 2013 Title: Expression data from mouse cerebral cortex Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23800850 Summary & Design: Summary: Differential gene expression of cerebral cortex might be responsible for distinct neurovascular developments between different mouse strains

We used Affymetrix microarray to explore the global gene expression patterns of mouse cerebral cortex of different mouse strains at two developmental stages

Overall design: Cerebral cortex from two mouse strains [C57BL/6J(B6) and C3H/J (C3H)] at post-natal day 1 (p1) and post-natal 11 weeks (11 wk) were harvested for microarray experiments

Background corr dist: KL-Divergence = 0.0145, L1-Distance = 0.0214, L2-Distance = 0.0004, Normal std = 0.8048

0.506 Kernel fit Pairwise Correlations Normal fit

Density 0.253

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

p1 B6 cerebralp1 B6 cerebral p1cortex, B6 cerebral p1cortex,rep1 C3H (0.0625583) p1cortex,rep2cerebral C3H (0.0519236) p1rep3cerebral cortex, C3H (0.0870232) 11cerebral cortex,rep1 wk B6(0.0550204)11 cortex,rep2cerebral wk B6(0.110258)11 rep3cerebral wkcortex, B6(0.0642879)11 cerebral wkcortex,rep1 C3H11 (0.0686212) wkcortex,rep2cerebral C3H11 (0.0897692) wk rep3cerebral cortex,rep1 C3H (0.137788) cerebral cortex, (0.122371) cortex,rep2 (0.0895153) rep3[ (0.0608644)min ] [ medium ] [ max ] CEM 1 Mta2 293.1 586.8 711.4 P ( S | Z, I ) = 0.00 Rbbp4 335.2 608.0 764.3 Mean Corr = 0.44264 Mbd3 624.8 741.0 869.8 Chd3 2308.5 2914.0 3376.0 Gatad2a 843.3 1290.5 1444.1 Gatad2b 716.1 884.8 1049.5 Hdac2 86.6 146.2 175.2 Rbbp7 6230.1 6796.0 7194.7 Hnrnpl 1846.3 2888.6 3214.2 Tcf3 366.6 850.9 1076.4 Rnps1 127.5 269.5 499.3 Snrnp40 465.2 934.6 1136.5 Ppm1g 1386.6 2781.7 2900.4 CEM 1 + Srsf4 1595.1 2228.1 2713.2 Top 10 Genes Arid1a 665.8 909.3 1054.4 Prr3 421.5 1134.8 1216.6 Alyref 603.3 1208.5 1401.4 Trim28 1932.3 4396.3 4845.2

Null module GEO Series "GSE20100" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20100 Status: Public on Jul 01 2010 Title: Expression data from primary MEF lacking either HDAC1, HDAC2 or both Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20194438 Summary & Design: Summary: Previously published data suggested some redundant functions between HDAC1 and HDAC2 in mouse. To test this hypothesis, we used microarrays to have a genome wide analysis at the transcription level of primary MEFs lacking HDAC1, HDAC2.

Overall design: MEF HDAC1 F/F were were transduced with two different retroviruses: one virus expresses the Tamoxifen-inducible cre recombinase Cre-ERT2 and the second virus expresses either a small hairpin micro-RNA against HDAC2 or a scrambled version. HDAC1F/F MEFs expressing either a scrambled micro-RNA or a micro-RNA against HDAC2 can be induced by addition of Tamoxifen to delete HDAC1, thereby generating four different genotypes: WT, HDAC1 KO, HDAC2 knockdown (Kd) and HDAC1/2 KO/Kd.

Background corr dist: KL-Divergence = 0.0906, L1-Distance = 0.0823, L2-Distance = 0.0115, Normal std = 0.5232

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

MEF HDAC1MEF HDAC1+/+MEF + Tamoxien HDAC1+/+MEF + Tamoxien HDAC1+/+ rep1MEF + Tamoxien(0.0772108) HDAC1fl/fl rep2MEF + siRNA(0.0294448) HDAC1fl/fl rep3MEF + scrambled siRNA(0.0667696) HDAC1fl/flMEF + scrambledsiRNA HDAC1fl/fl +MEF EtOH + scrambledsiRNA HDAC1fl/fl +rep1MEF EtOH + scrambledsiRNA (0.119472) HDAC1fl/fl +rep2MEF EtOH + scrambledsiRNA (0.0518427) HDAC1fl/fl +rep3MEF Tamoxifen + scrambledsiRNA (0.0441677) HDAC1fl/fl +MEF Tamoxifen + +siRNA rep1EtOH HDAC1fl/fl +MEF Tamoxifen +(0.0183958) +rep1siRNA rep2EtOH HDAC1fl/flMEF (0.0485859) +(0.0209391) +rep2siRNA rep3EtOH HDAC1fl/fl (0.0311379) +(0.0213881) +rep3siRNA Tamoxifen fl/fl (0.0374271) + +siRNA Tamoxifen rep1 + Tamoxifen (0.147654)[ rep2 min (0.116557) rep3 ] (0.169008) [ medium ] [ max ] CEM 1 Mta2 696.9 973.9 1162.0 P ( S | Z, I ) = 0.00 Rbbp4 28.7 44.0 77.8 Mean Corr = 0.31756 Mbd3 734.5 1258.3 1522.4 Chd3 235.7 751.3 877.8 Gatad2a 1822.4 2274.2 2554.7 Gatad2b 603.5 1191.7 1536.6 Hdac2 13.7 19.0 23.1 Rbbp7 8205.4 10274.3 11120.0 Hnrnpl 587.8 1054.7 1298.7 Tcf3 361.1 564.4 624.3 Rnps1 85.0 195.7 249.0 Snrnp40 593.4 1594.5 1820.5 Ppm1g 1841.0 2114.2 2476.0 CEM 1 + Srsf4 817.7 1304.4 1547.8 Top 10 Genes Arid1a 348.0 766.2 997.8 Prr3 159.6 224.6 280.5 Alyref 1086.8 3020.9 3898.1 Trim28 3410.2 4966.9 5387.2

Null module GEO Series "GSE46600" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 44 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46600 Status: Public on Jun 20 2014 Title: Transcriptome and Molecular Pathways Analysis of CD4 T-Cells from Young NOD Mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24918037 Summary & Design: Summary: Type 1 diabetes is a multigenic disease caused by T-cell mediated destruction of the insulin producing Î²-cells. Although conventional (targeted) approaches of identifying causative genes have advanced our knowledge of this disease, many questions remain unanswered. Using a whole molecular systems study, we unraveled the genes/molecular pathways that are altered in CD4 T-cells from young NOD mice prior to insulitis (lymphocytic infiltration into the pancreas). Many of the CD4 T-cell altered genes lie within known diabetes susceptibility regions (Idd), including several genes in the diabetes resistance region Idd13 and two genes (Khdrbs1 and Ptp4a2) in the CD4 T-cell diabetogenic activity region Idd9/11. Alterations involved apoptosis/cell proliferation and metabolic pathways (predominant at 2 weeks), inflammation and cell signaling/activation (predominant at 3 weeks), and innate and adaptive immune responses (predominant at 4 weeks). We identified several factors that may regulate these abnormalities: IRF-1, HNF4A, TP53, BCL2L1 (lies within Idd13), IFNG, IL4, IL15, and prostaglandin E2, which were common to all 3 ages; AR and IL6 to 2 and 4 weeks; and Interferon (IFN-I) and IRF-7 to 3 and 4 weeks. Others were unique to the various ages (e. g. MYC, JUN, and APP to 2 weeks; TNF, TGFB1, NFKB, ERK, and p38MAPK to 3 weeks; and IL12 and STAT4 to 4 weeks). Our data suggest that diabetes resistance genes in Idd13 and Idd9/11, and BCL2L1, IL6-AR and IFNG-IRF-1-IFN-I/IRF-7-IL12 pathways play an important role in CD4 T-cells in the early pathogenesis of autoimmune diabetes. Thus, the alternative approach of investigation at the molecular systems level has captured new information, which combined with validation studies, offers the opportunity to test hypotheses on the role played by the genes/molecular pathways identified in this study, to understand better the mechanisms of autoimmune diabetes in CD4 T-cells, and to develop new therapeutic strategies for the disease.

Overall design: CD4 T-cells were purified from spleen leukocytes collected from 2-, 3- and 4-week old NOD mice and two age-matched control strains, NOR, and C57BL/6, (n=5 for each strain and each age group; except NOD2wk). NOR is an insulitis- and diabetes-free control strain that shares shares ~88% of its genome with NOD mice, including the diabetogenic H2g7 MHC haplotype and several important non-MHC T1D susceptibility loci. C57BL/6 is also a diabetes-resitant strain, but it is more genetically distantly related to NOD.

Background corr dist: KL-Divergence = 0.4129, L1-Distance = 0.0601, L2-Distance = 0.0093, Normal std = 0.2468

1.617 Kernel fit Pairwise Correlations Normal fit

Density 0.808

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

CD4T-cells_NODCD4T-cells_NODCD4T-cells_NOD mice_2wk_repCD4T-cells_NOD mice_2wk_repCD4T-cells_NOR mice_2wk_rep1 (0.0240803)CD4T-cells_NOR mice_2wk_rep2 (0.02909)CD4T-cells_NOR mice_2wk_rep3 (0.0481752)CD4T-cells_NOR mice_2wk_rep4 (0.0142095)CD4T-cells_NOR mice_2wk_rep1 (0.0405664)CD4T-cells_C57BL/6 mice_2wk_rep2 (0.0202149)CD4T-cells_C57BL/6 mice_2wk_rep3 (0.0110608)CD4T-cells_C57BL/6 4 (0.0383874) mice_2wk_repCD4T-cells_C57BL/6 5 (0.0314591) mice_2wk_repCD4T-cells_C57BL/6 mice_2wk_rep1 CD4T-cells_NOD(0.00438198) mice_2wk_rep2 CD4T-cells_NOD(0.00846549) mice_2wk_rep3 CD4T-cells_NOD(0.0227573) mice_3wk_rep 4 CD4T-cells_NOD(0.037032) mice_3wk_rep 5 CD4T-cells_NOD(0.0206639) mice_3wk_rep1 (0.00264451)CD4T-cells_NOR mice_3wk_rep2 (0.0431761)CD4T-cells_NOR mice_3wk_rep3 (0.0112157)CD4T-cells_NOR mice_3wk_rep4 (0.041402)CD4T-cells_NOR mice_3wk_rep5 (0.00776967)CD4T-cells_NOR mice_3wk_rep1 (0.026471)CD4T-cells_C57BL/6 mice_3wk_rep2 (0.0643663)CD4T-cells_C57BL/6 mice_3wk_rep3 (0.0228289)CD4T-cells_C57BL/6 4 (0.00563446) mice_3wk_repCD4T-cells_C57BL/6 5 (0.00620736) mice_3wk_repCD4T-cells_C57BL/6 mice_3wk_rep1 CD4T-cells_NOD(0.00474153) mice_3wk_rep2 CD4T-cells_NOD(0.036347) mice_3wk_rep3 CD4T-cells_NOD(0.00849797) mice_4wk_rep 4 CD4T-cells_NOD(0.0352187) mice_4wk_rep 5 CD4T-cells_NOD(0.0205956) mice_4wk_rep1 (0.0195947)CD4T-cells_NOR mice_4wk_rep2 (0.0100498)CD4T-cells_NOR mice_4wk_rep3 (0.00453175)CD4T-cells_NOR mice_4wk_rep4 (0.027062)CD4T-cells_NOR mice_4wk_rep5 (0.0414563)CD4T-cells_NOR mice_4wk_rep1 (0.0538695)CD4T-cells_C57BL/6 mice_4wk_rep2 (0.0119712)CD4T-cells_C57BL/6 mice_4wk_rep3 (0.00739144)CD4T-cells_C57BL/6 4 (0.0229725) mice_4wk_repCD4T-cells_C57BL/6 5 (0.0254277) mice_4wk_repCD4T-cells_C57BL/6 mice_4wk_rep1 (0.0362356) mice_4wk_rep2 (0.0107576) mice_4wk_rep3 (0.015534) 4 [(0.0119875) min 5 (0.0134971) ] [ medium ] [ max ] CEM 1 Mta2 1109.7 2577.1 4145.0 P ( S | Z, I ) = 0.00 Rbbp4 186.3 433.6 1473.5 Mean Corr = 0.06710 Mbd3 200.8 994.1 2229.8 Chd3 447.6 1585.5 3522.5 Gatad2a 1400.6 2739.3 5905.4 Gatad2b 137.0 344.2 2254.3 Hdac2 30.1 175.7 412.4 Rbbp7 8997.6 13519.6 20256.4 Hnrnpl 304.5 1363.5 4646.6 Tcf3 672.8 1279.5 3738.7 Rnps1 226.9 405.4 864.9 Snrnp40 1457.0 1876.9 2472.8 Ppm1g 3009.3 5908.2 10591.1 CEM 1 + Srsf4 1787.7 3046.1 4170.9 Top 10 Genes Arid1a 2154.9 3818.1 10040.1 Prr3 185.4 297.5 571.3 Alyref 964.2 3680.9 5860.5 Trim28 2422.7 5001.7 8848.9

Null module GEO Series "GSE7810" 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=GSE7810 Status: Public on May 18 2007 Title: Comparative analysis of gene expression WT and Nrf2-/- mice Type II cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17895394 Summary & Design: Summary: We hypothesize that gene expression in the Type II cells of Nrf2+/+ and Nrf2-/- mice are divergent thus contributing the cell growth. More specifically, type II cells from Nrf2-/- mice have increased reactive oxygen species that cause the impaired cell growth. In order to test these hypotheses at the gene expression level, we utilized microarray analysis to examine transcriptional differences between Nrf2+/+ and Nrf2-/- cells.

Keywords: comparative expression profiling

Overall design: . This study utilizes microarray analysis to test these hypotheses. Three sets of type II cells were isolated from lungs from both Nrf2+/+ and Nrf2-/- mice and grown for 5 days. RNA was isolated and used for global gene expression profiling (Affymetrix Mouse 430 2.0 array). Statistically significant gene expression was determined as a minimum 6 counts of 9 pairwise comparisons, minimum 1.5-fold change, and p < 0.05. Further, Absolute | FC - FC SEM | >= 1.5.

Background corr dist: KL-Divergence = 0.0624, L1-Distance = 0.0171, L2-Distance = 0.0003, Normal std = 0.5241

0.761 Kernel fit Pairwise Correlations Normal fit

Density 0.381

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

MNR 1-2MNR WT 2-23 (0.114207)MNR WT 5-24 (0.065156)MNR KO 26-2 (0.101222)MNR KO 37-2 (0.0808116)MNR KO Treated8-2MNR KO Treated1-3 2 MNR(0.120387) WT 2-35 3 (0.110603) MNR(0.0901175) KO 43-3 (0.160662) KO Treated 4 (0.156833)[ min ] [ medium ] [ max ] CEM 1 Mta2 1176.8 1635.6 1930.3 P ( S | Z, I ) = 0.00 Rbbp4 64.7 179.1 257.4 Mean Corr = 0.37119 Mbd3 489.5 712.6 939.8 Chd3 804.4 1141.6 1408.4 Gatad2a 4299.1 4699.1 5279.2 Gatad2b 320.2 383.1 480.0 Hdac2 56.2 130.9 144.9 Rbbp7 5178.6 6549.3 7209.1 Hnrnpl 391.9 1210.5 1742.2 Tcf3 714.8 760.0 1147.3 Rnps1 176.1 222.2 289.0 Snrnp40 637.6 896.5 941.7 Ppm1g 2819.4 3275.3 4178.5 CEM 1 + Srsf4 1112.2 1398.9 1740.5 Top 10 Genes Arid1a 1077.0 1433.0 1898.9 Prr3 330.4 390.7 459.9 Alyref 1799.4 2456.4 3228.6 Trim28 3404.3 4245.3 5057.6

Null module GEO Series "GSE46090" 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=GSE46090 Status: Public on Apr 17 2013 Title: Gene expression in WT and Ikaros-deficient DN3, DN4 and DP thymocyte populations Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24643801 Summary & Design: Summary: DN3, DN4 and DP cells were sorted from 3-4 week old WT and mice and subjected to transcriptome analysis

Overall design: Cells from 3 mice were pooled for sorting.

Background corr dist: KL-Divergence = 0.0692, L1-Distance = 0.0334, L2-Distance = 0.0015, Normal std = 0.5233

0.791 Kernel fit Pairwise Correlations Normal fit

Density 0.396

0.000 CEM 1

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

Pre-normalization Quantiles

WT DN3WT cells DN3 repWT cells 1 DN4 (0.0583216) repWT cells 2 DN4 (0.073955) repWT cells 1 DP (0.0603873) rep cellsWT 2 DP (0.0823442)rep cellsDN3 1 (0.271155) cellsrepDN3 2 rep (0.0870964) cells 1DN4 (0.067494) rep cells 2DN4 (0.0327103) rep cells 1DP (0.0131031) rep cells 2DP (0.083191)rep cells 1 (0.0852339) rep 2 (0.0850087) [ min ] [ medium ] [ max ] CEM 1 Mta2 1374.6 2629.9 3880.4 P ( S | Z, I ) = 0.00 Rbbp4 139.8 341.8 746.9 Mean Corr = 0.10314 Mbd3 322.2 809.2 1078.6 Chd3 770.1 2247.9 3209.0 Gatad2a 541.9 961.8 1130.4 Gatad2b 1422.3 1802.6 2793.9 Hdac2 83.4 135.6 259.8 Rbbp7 7571.1 17706.9 21188.5 Hnrnpl 229.7 455.5 697.5 Tcf3 909.6 1673.1 1999.4 Rnps1 228.8 380.0 738.7 Snrnp40 894.0 1652.4 2376.2 Ppm1g 2368.7 5340.5 6014.4 CEM 1 + Srsf4 3943.7 4826.2 5708.8 Top 10 Genes Arid1a 1882.9 2952.1 3191.7 Prr3 204.2 279.8 399.3 Alyref 389.0 1192.8 1763.0 Trim28 7562.2 14054.1 16473.6

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 (0.109334)Lin+_KRN_sorted (0.164419)Lin+_KRNxG7_sorted (0.172526)(0.167488) (0.199191) (0.187041)[ min ] [ medium ] [ max ] CEM 1 Mta2 604.1 990.1 1368.2 P ( S | Z, I ) = 0.00 Rbbp4 561.8 1023.1 1272.4 Mean Corr = 0.27868 Mbd3 83.0 256.8 279.9 Chd3 134.1 457.9 489.2 Gatad2a 751.0 779.4 830.4 Gatad2b 351.8 481.6 865.9 Hdac2 220.0 287.1 319.4 Rbbp7 7050.0 10613.8 11406.9 Hnrnpl 234.2 415.6 890.4 Tcf3 226.6 378.8 500.9 Rnps1 126.0 162.9 232.5 Snrnp40 481.5 721.6 866.3 Ppm1g 3872.2 4907.8 5154.3 CEM 1 + Srsf4 5723.3 6003.7 6258.0 Top 10 Genes Arid1a 981.6 1659.9 1828.6 Prr3 281.7 881.8 1316.7 Alyref 2413.2 3571.9 4482.6 Trim28 1583.3 4210.1 5081.1

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 (0.129612)3T3-L1_t2_rep2 (0.0632256)3T3-L1_t3_rep1 (0.0523403)3T3-L1_t3_rep2 (0.185554)3T3-L1_t4_rep1 (0.10451)3T3-L1_t4_rep2 (0.0869763) (0.201583) (0.176199) [ min ] [ medium ] [ max ] CEM 1 Mta2 838.3 1163.6 1288.4 P ( S | Z, I ) = 0.00 Rbbp4 277.3 352.1 562.7 Mean Corr = 0.43750 Mbd3 668.8 1060.6 1497.9 Chd3 247.2 382.5 595.7 Gatad2a 1320.6 2453.2 3047.2 Gatad2b 973.1 1231.5 1558.1 Hdac2 126.9 226.7 283.0 Rbbp7 7529.2 12948.9 14951.7 Hnrnpl 271.5 438.8 685.9 Tcf3 264.2 1068.9 1266.6 Rnps1 272.7 496.5 536.4 Snrnp40 345.2 1059.7 1164.5 Ppm1g 2283.3 3623.5 6474.7 CEM 1 + Srsf4 1244.4 1928.5 2171.5 Top 10 Genes Arid1a 680.5 820.0 1029.8 Prr3 117.5 251.1 319.0 Alyref 571.4 1197.6 2182.0 Trim28 2072.0 3862.7 4724.4

Null module GEO Series "GSE7798" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7798 Status: Public on Jun 01 2007 Title: Osteoclastic estrogen receptor alpha mediates the osteoprotective estrogen action through Fas ligand signaling Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17803905 Summary & Design: Summary: Estrogen clearly prevents osteoporotic bone loss by attenuating bone resorption. The molecular basis of how this is accomplished, however, remains elusive. Here we report a critical role of osteoclastic ERa in mediating estrogen action on bone in females. We selectively ablated ERa in differentiated osteoclasts (ERa dOc/dOc). ERa dOc/dOc females, but not males, exhibited clear trabecular bone loss, similar to the osteoporotic bone phenotype in post-menopausal women. Recovery of bone loss by estrogen treatment of the ovariectomized ERa dOc/dOc females was ineffective in the trabecular areas of the long bones and lumbar vertebral bodies. Osteoclastic apoptosis, induced by estrogen, occurred simultaneously with up-regulation of Fas ligand (FasL) expression in intact trabecular bones of ERa +/+mice, but not in ERa dOc/dOc mice. ERa was also required for similar effects of estrogen and tamoxifen in cultured osteoclasts. These findings suggest that the osteoprotective actions of estrogen and SERMS are mediated at least in part through osteoclastic ERa in trabecular bone; and the life span of mature osteoclasts is regulated through activation of the Fas/FasL system.

Keywords: Study about estrogen response of osteoclast-specific estrogen receptor alpha mice

Overall design: Wild type and osteoclast-specific Estrogen Receptor alpha knock-out mice were ovariectomized. The number of both genotypes of mice was eight. The mice of each genotypes were divided to vehicle control and estrogen treated group. Four hours after chemical treatment, the distal 5 mm of the left femurs were harvested after sacrificing by cervical dislocation and total RNAs were purified for Affymetix GeneChip microarray analysis without pooling. Therefore, this experiment consists of four groups with four replicates per group.

Background corr dist: KL-Divergence = 0.1510, L1-Distance = 0.0385, L2-Distance = 0.0031, Normal std = 0.3730

1.070 Kernel fit Pairwise Correlations Normal fit

Density 0.535

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-OVX-1WT-OVX-2 (0.0444464)WT-OVX-3 (0.15732)WT-OVX-4 (0.0575747)WT-E2-4hr-1 (0.0216003)WT-E2-4hr-2 (0.014454)WT-E2-4hr-3 (0.0646892)WT-E2-4hr-4 (0.102204)ERaKO-OVX-1 (0.156925)ERaKO-OVX-2 (0.0193855)ERaKO-OVX-3 (0.0560059)ERaKO-OVX-4 (0.0113786)ERaKO-E2-4hr-1 (0.0267642)ERaKO-E2-4hr-2ERaKO-E2-4hr-3 (0.116338)ERaKO-E2-4hr-4 (0.0403822) (0.041091) (0.0694408) [ min ] [ medium ] [ max ] CEM 1 Mta2 648.3 1776.0 2214.1 P ( S | Z, I ) = 0.00 Rbbp4 518.5 1030.8 1446.7 Mean Corr = 0.27169 Mbd3 256.7 372.2 532.8 Chd3 720.9 859.8 1156.3 Gatad2a 1164.6 2646.0 3173.4 Gatad2b 110.6 518.1 847.5 Hdac2 208.3 285.0 467.1 Rbbp7 3176.3 4369.8 5500.1 Hnrnpl 487.3 1082.6 1591.9 Tcf3 632.3 950.2 1430.4 Rnps1 204.9 425.8 549.2 Snrnp40 566.0 883.7 1056.6 Ppm1g 1831.7 3868.9 4851.1 CEM 1 + Srsf4 2466.9 3286.2 3755.0 Top 10 Genes Arid1a 1054.6 2192.9 3005.6 Prr3 107.9 406.6 654.1 Alyref 974.4 2234.2 2962.5 Trim28 1944.4 4018.6 4901.8

Null module GEO Series "GSE9247" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9247 Status: Public on Oct 06 2007 Title: Effect of histone deacetylase inhibitors on osteoblast gene expression Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17925016 Summary & Design: Summary: Background:

Osteoblast differentiation requires the coordinated stepwise expression of multiple genes. Histone deacetylase inhibitors (HDIs) accelerate the osteoblast differentiation process by blocking the activity of histone deacetylases (HDACs), which alter gene expression by modifying chromatin structure. We previously demonstrated that HDIs and HDAC3 shRNAs accelerate matrix mineralization and the expression of osteoblast maturation genes (e.g. alkaline phosphatase, osteocalcin). Identifying other genes that are differentially regulated by HDIs might identify new pathways that contribute to osteoblast differentiation.

Results:

To identify other osteoblast genes that are altered early by HDIs, we incubated MC3T3-E1 preosteoblasts with HDIs (trichostatin A, MS-275, or valproic acid) for 18 hours in osteogenic conditions. The promotion of osteoblast differentiation by HDIs in this experiment was confirmed by osteogenic assays. Gene expression profiles relative to vehicle-treated cells were assessed by microarray analysis with Affymetrix GeneChip 430 2.0 arrays. The regulation of several genes by HDIs in MC3T3-E1 cells and primary osteoblasts was verified by quantitative real-time PCR. Nine genes were differentially regulated by at least two-fold after exposure to each of the three HDIs and six were verified by PCR in osteoblasts. Four of the verified genes (solute carrier family 9 isoform 3 regulator 1 (Slc9a3r1), sorbitol dehydrogenase 1, a kinase anchor protein, and glutathione S-transferase alpha 4) were induced. Two genes (proteasome subunit, beta type 10 and adaptor-related protein complex AP-4 sigma 1) were suppressed. We also identified eight growth factors and growth factor receptor genes that are significantly altered by each of the HDIs, including Frizzled related proteins 1 and 4, which modulate the Wnt signaling pathway.

Conclusions: This study identifies osteoblast genes that are regulated early by HDIs and indicates pathways that might promote osteoblast maturation following HDI exposure. One gene whose upregulation following HDI treatment is consistent with this notion is Slc9a3r1. Also known as NHERF1, Slc9a3r1 is required for optimal bone density. Similarly, the regulation of Wnt receptor genes indicates that this crucial pathway in osteoblast development is also affected by HDIs. These data support the hypothesis that HDIs regulate the expression of genes that promote osteoblast differentiation and maturation.

Keywords: gene expression

Overall design: To identify other osteoblast genes that are altered early by HDIs, we incubated MC3T3-E1 preosteoblasts with HDIs (trichostatin A, MS-275, or valproic acid) or the vehicle control (DMSO) for 18 hours in osteogenic conditions. Gene expression profiles relative to vehicle-treated cells were assessed in triplicate (in some cases quadruplicate) samples by microarray analysis with Affymetrix GeneChip 430 2.0 arrays.

Background corr dist: KL-Divergence = 0.1049, L1-Distance = 0.0636, L2-Distance = 0.0067, Normal std = 0.4730

0.936 Kernel fit Pairwise Correlations Normal fit

Density 0.468

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

DMSO TreatedDMSO Treated DMSOControl Treated DMSOControl 1 (0.0638583) Treated MS-275Control 2 (0.0554032) MS-275Control Treated3 (0.060144) MS-275 Treated 4Rep1 (0.0641027) (0.0913572) MS-275Treated Rep2 (0.0212127) TSATreated Rep3 Treated (0.0524407)TSA Rep4 Treated Rep (0.0239926)TSA 1 (0.183933)Treated RepVPA 2 (0.120064)Treated RepVPA 3 (0.148257)Treated RepVPA 1 (0.0195032)Treated RepVPA 2 (0.0776735)Treated Rep 3 (0.0142759) Rep 4 (0.00378271)[ min ] [ medium ] [ max ] CEM 1 Mta2 711.0 1082.4 1224.3 P ( S | Z, I ) = 0.00 Rbbp4 185.9 272.5 387.9 Mean Corr = 0.09733 Mbd3 428.4 830.2 1201.1 Chd3 241.6 994.0 1471.3 Gatad2a 2050.7 2248.3 2617.7 Gatad2b 401.7 634.4 1275.4 Hdac2 115.3 196.6 234.6 Rbbp7 8535.4 11102.3 12417.5 Hnrnpl 665.4 1034.3 1347.6 Tcf3 1358.8 1496.5 1669.2 Rnps1 454.7 528.2 636.2 Snrnp40 606.4 998.2 1155.5 Ppm1g 4594.0 4921.9 5251.2 CEM 1 + Srsf4 1289.4 2107.8 2331.5 Top 10 Genes Arid1a 494.0 813.8 1080.8 Prr3 354.4 457.1 785.9 Alyref 1777.9 3609.5 5145.8 Trim28 2712.6 3870.6 4311.1

Null module GEO Series "GSE18800" 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=GSE18800 Status: Public on Oct 30 2009 Title: Effect of PGF receptor FP on bleomycin-induced pulmonary fibrosis in mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19966781 Summary & Design: Summary: We purposed to examine the effect of PGF receptor FP in development of

bleomycin-induced pulmonary fibrosis in mice. We performed gene

expression analysis in the lung of WT and FP-KO mice on Days 0, 7 and

14. We found out that fibrosis-related genes such as various isoforms

of collagen, which were induced on Day 7 and continued to increase or

remained unchanged on Day 14, were induced to less extent in FP-KO

mice. In contrast, expression of inflammation-related genes peaked on

Day 7 similarly in WT and FP-KO mice. These results suggest that FP

functions in fibrosis-phase, not in peak inflammation phase, and

facilitates fibrogenesis by enhancing expression of fibrosis-related

genes.

Overall design: compared with those in WT mice.

Background corr dist: KL-Divergence = 0.2049, L1-Distance = 0.0359, L2-Distance = 0.0021, Normal std = 0.3323

1.201 Kernel fit Pairwise Correlations Normal fit

Density 0.600

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

FP-KO mouseFP-KO onmouseFP-KO Day onmouse0,FP-KO No.1 Day onmouse0,(0.0359076)FP-KO No.2 Day onmouse0,(0.0368865)FP-KO No.3 Day onmouse0,(0.0234176)FP-KO No.4 Day onmouse7,(0.0214975)FP-KO No.1 Day onmouse7,(0.0439309)FP-KO No.2 Day onmouse7,(0.0528535)FP-KO No.3 Day onmouse7,(0.0142508)FP-KO No.4 Day onmouse14,(0.0258526)FP-KO DayNo.1 onmouse14,WT (0.121372) Day No.2mouse on14,WT (0.0626911) Day No.3onmouse Day14,WT (0.0168521) No.4onmouse0, No.1 DayWT (0.0139348) onmouse0,(0.0568512) No.2 DayWT onmouse0,(0.0257151) No.3 DayWT onmouse0,(0.0430186) No.4 DayWT onmouse7,(0.00808195) No.1 DayWT onmouse7,(0.0150593) No.2 DayWT onmouse7,(0.0192053) No.3 DayWT onmouse7,(0.0136087) No.4 DayWT onmouse14,(0.0208694) DayWTNo.1 onmouse14, (0.0894829) DayWTNo.2 onmouse14, (0.125058) DayNo.3 on14, (0.101327) DayNo.4 14, (0.00663959) No.5 (0.00563606)[ min ] [ medium ] [ max ] CEM 1 Mta2 726.1 986.1 1482.9 P ( S | Z, I ) = 0.00 Rbbp4 119.4 334.1 458.2 Mean Corr = -0.09746 Mbd3 277.4 424.5 581.3 Chd3 403.6 651.3 1038.6 Gatad2a 1874.1 2215.9 3277.2 Gatad2b 194.1 1138.8 1896.2 Hdac2 56.0 130.8 233.7 Rbbp7 5739.6 6988.7 9216.5 Hnrnpl 177.7 289.7 715.7 Tcf3 245.5 439.8 853.0 Rnps1 192.8 325.1 459.5 Snrnp40 438.8 573.3 750.9 Ppm1g 1499.1 1747.2 2133.6 CEM 1 + Srsf4 1288.8 1578.2 2022.1 Top 10 Genes Arid1a 560.3 1291.1 2547.6 Prr3 83.3 141.1 263.9 Alyref 305.8 588.8 1158.0 Trim28 1531.4 1743.3 2206.4

Null module GEO Series "GSE5038" 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=GSE5038 Status: Public on Jun 09 2006 Title: zhang-affy-mouse-308606 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: In our original grant we proposed to use the NR3B-null mouse model to study the role of NR3B subunit in motor neuron function. We have now successfully generated NR3B null mice. Interestingly, NR3B-null mice invariably die at age P4-P8. Our preliminary examination indicates that the motor strength of these mice is severely impaired prior to death. As we continue to explore the cause of death in NR3B null mice, we propose to conduct gene profiling experiments to search for transcription changes in the brain related to ablation of the NR3B gene. We have used the facility provided by the NINDS/NIMH Microarray Consortium to identify genes that show abnormal expression patterns in these mice. We would like to compare these changes with that opccured in SOD1 mice, a mouse model of motor neuron diseases. Analysis of these genes will help to identify changes in networks and pathways that may cause the death of NR3B-null mice. These studies will further help to elucidate the functional role of NR3B in motor neurons.

We hypothesize that genes with their transcription level changing significantly in SOD1 mutant mice will be associated with the molecular mechanism underlying the death of motor neurons.

We like to compare motor neuron and spinal cord smaples from SOD1 mice at the age prior to the disease onset. Total RNA from total 9 samples will be purified, each from ~200 motor neurons obtained by Laser Capture Microdissection and the total spinal cord. Extracted RNAs will be subjected to one or two rounds of amplification and the obtained cRNA will be biotinylated. The purified cRNA will be sent to the NINDS/NIMH Microarray Consortium be used to hybridize the GeneChip Mouse Genome 430 2.0 Array. The hybridization, scanning, and initial data analysis of these GeneChips will be conducted by the Consortium staff. We will analyze the collected data further after data collection. We will first identify genes that show significant changes between wild-type and SOD1 mice and then compare that with the result from NR3B null mice.

Keywords: other

Overall design:

Background corr dist: KL-Divergence = 0.0309, L1-Distance = 0.0667, L2-Distance = 0.0062, Normal std = 0.7668

0.589 Kernel fit Pairwise Correlations Normal fit

Density 0.294

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

spinal cord,spinal ventral cord,spinal ventralspinal cord,spinal cord: ventralspinal cord,spinal D28WTSP1 cord: ventralspinal cord,spinal D28WTSP2 cord: ventralspinal cord,e1spinal le1D28WTSP3_e1_le1 cord: ventralspinal (0.193958) cord,e1_le1spinal D28WTMN1_e1_le1 cord: ventralspinal (0.162865)cord,spinal D28WTMN2_e1_le1 cord: ventralspinal cord,(0.149183) D28WTMN3_e1_le1 cord: ventralspinal (0.0870472) D28SDMN1_e1_le1 cord: spinal (0.102118) D28SDMN2_e1_le1 cord: (0.0407837)[ D28SDMN3_e1_le1min (0.0702831) ] (0.155816) (0.0379458)[ medium ] [ max ] CEM 1 Mta2 11.4 73.1 397.9 P ( S | Z, I ) = 0.00 Rbbp4 6.0 59.3 113.6 Mean Corr = 0.20240 Mbd3 19.9 136.2 528.1 Chd3 195.3 282.3 1136.5 Gatad2a 301.9 499.8 1184.1 Gatad2b 45.0 177.6 299.9 Hdac2 3.1 38.7 56.9 Rbbp7 4270.6 9757.7 15503.7 Hnrnpl 181.5 317.8 1882.2 Tcf3 12.0 93.4 322.7 Rnps1 27.5 129.6 277.4 Snrnp40 273.8 387.9 511.7 Ppm1g 1242.4 2188.0 2405.5 CEM 1 + Srsf4 805.5 1494.5 1918.8 Top 10 Genes Arid1a 11.7 104.2 956.9 Prr3 214.0 356.5 476.1 Alyref 723.0 943.8 1291.4 Trim28 1129.1 1628.0 2305.3

Null module GEO Series "GSE18587" 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=GSE18587 Status: Public on Sep 21 2011 Title: Specific modulation of mucosal immune response, tolerance and proliferation in mice colonized with A. muciniphila Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21904534 Summary & Design: Summary: Epithelial cells of the mammalian intestine are covered with a mucus layer that prevents direct contact with intestinal microbes but also constitutes a substrate for mucus-degrading bacteria. To study the effect of mucus degradation on the host response, germ-free mice were colonized with Akkermansia muciniphila. This anaerobic bacterium belonging to the Verrucomicrobia is specialized in the degradation of mucin, the glycoprotein present in mucus, and found in high numbers in the intestinal tract of human and other mammalian species. Efficient colonization of A. muciniphila was observed with highest numbers in the cecum, where most mucin is produced. In contrast, following colonization by Lactobacillus plantarum, a facultative anaerobe belonging to the Firmicutes that ferments carbohydrates, similar cell-numbers were found at all intestinal sites. Whereas A. muciniphila was located closely associated with the intestinal cells, L. plantarum was exclusively found in the lumen. The global transcriptional host response was determined in intestinal biopsies and revealed a consistent, site-specific, and unique modulation of about 750 genes in mice colonized by A. muciniphila and over 1500 genes after colonization by L. plantarum. Pathway reconstructions showed that colonization by A. muciniphila altered mucosal gene expression profiles toward increased expression of genes involved in immune responses and cell fate determination, while colonization by L. plantarum led to up-regulation of lipid metabolism. These indicate that the colonizers induce host responses that are specific per intestinal location. In conclusion, we propose that A. muciniphila modulates pathways involved in establishing homeostasis for basal metabolism and immune tolerance toward commensal microbiota.

Keywords: Analysis of target gene regulation by using microarrays

Overall design: Adult germ-free female NMRI-KI mice (45 65 days) were used for bacterial mono-association. Two bacterial strains were used in this study, A. muciniphila MucT (ATTC BAA-835) and L. plantarum WCFS1 (NCIMB 8826). A. muciniphila was grown anaerobically in a basal mucin based medium and L. plantarum was grown anaerobically at 37´C in Man-Rogosa-Sharpe broth (MRS; Le Pont de Claix, France). After 7 days of colonization, mice were killed by cervical dislocation and terminal ileum, cecum and ascending colon specimens were sampled.

Background corr dist: KL-Divergence = 0.0560, L1-Distance = 0.0627, L2-Distance = 0.0089, Normal std = 0.5753

0.855 Kernel fit Pairwise Correlations Normal fit

Density 0.427

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

ileum_germ_free_non_inoculated_(pool)ileum_germ_free_inoculated_A.muciniphila_(pool)ileum_germ_free_inoculated_L.plantarum_(pool)caecum_germ_free_non_inoculated_(pool)caecum_germ_free_inoculated_A.muciniphila_(pool)caecum_germ_free_inoculated_L.plantarum_(pool) (0.164581)colon_germ_free_non_inoculated_(pool)colon_germ_free_inoculated_A.muciniphila_(pool) (0.158552)colon_germ_free_inoculated_L.plantarum_(pool) (0.204766) (0.062737) (0.134062) (0.0166373) (0.10447)[ min ] (0.115363) (0.0388325)[ medium ] [ max ] CEM 1 Mta2 543.7 612.9 754.1 P ( S | Z, I ) = 0.00 Rbbp4 147.4 278.7 375.5 Mean Corr = 0.49066 Mbd3 287.9 332.4 477.9 Chd3 488.7 702.2 954.2 Gatad2a 1286.3 1640.0 2339.0 Gatad2b 50.4 69.2 127.3 Hdac2 124.4 176.5 275.2 Rbbp7 5343.7 5474.6 6164.6 Hnrnpl 263.8 452.1 492.0 Tcf3 99.3 261.7 401.8 Rnps1 31.4 157.6 215.4 Snrnp40 894.0 1045.8 1178.2 Ppm1g 1531.0 1673.1 2090.6 CEM 1 + Srsf4 929.2 1138.2 1380.8 Top 10 Genes Arid1a 491.2 918.8 1066.3 Prr3 24.4 40.4 75.9 Alyref 1518.1 2024.9 2719.7 Trim28 1396.2 1653.3 2177.7

Null module GEO Series "GSE18042" 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=GSE18042 Status: Public on Sep 10 2009 Title: Erythroid differentiation: G1E model Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19887574 Summary & Design: Summary: Analysis of erythroid differentiation using Gata1 gene-disrupted G1E ER4 clone cells. Estradiol addition activates an ectopically expressed Gata-1-estrogen receptor fusion protein, triggering synchronous differentiation. 30 hour time course corresponds roughly to late burst-forming unit-erythroid stage (t=0 hrs) through orthochromatic erythroblast stage (t=30 hrs).

Overall design: G1E ER4 cells cultured in G1E medium were treated at 6 time points with estradiol to initiate erythroid differentiation by activating Gata1 transcription factor and total RNAs from treated cells were extracted for microarray experiment. The erythroid differentiation status was confirmed by cell pellet color and expression of microRNA miR451. The design was similar to an earlier studies (Welch, J. J., Watts, J. A., Vakoc, C. R., Yao, Y., Wang, H., Hardison, R. C., Blobel, G. A., Chodosh, L. A., and Weiss, M. J. (2004)). Global regulation of erythroid gene expression by transcription factor GATA-1. Blood 104, 3136-3147), except that a more recent version of Affymetric chip was used to acheive greater transcriptome coverage.

Background corr dist: KL-Divergence = 0.0901, L1-Distance = 0.0663, L2-Distance = 0.0070, Normal std = 0.5071

0.884 Kernel fit Pairwise Correlations Normal fit

Density 0.442

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

pre-estradiol,pre-estradiol, biologicalpre-estradiol, biological3 hrep1 post-estradiol,biological biological(0.0896386)3 hrep2 post-estradiol,biological (0.143067)3 hrep3 post-estradiol,biological (0.101251)7 h post-estradiol,biological rep17 h post-estradiol,biological(0.029752) rep27 h post-estradiol,biological(0.0203811) rep314 h (0.0218297) post-estradiol,biological rep114 h (0.0277466) post-estradiol,biological rep214 h (0.0111794) post-estradiol,biological rep321 h (0.0207712) post-estradiol,biological rep121 h post-estradiol,biological(0.0210388) rep221 h post-estradiol,biological(0.0235148) rep330 h post-estradiol,biological(0.0187062) rep130 h post-estradiol,biological(0.101083) rep230 h post-estradiol,biological(0.0410468) rep3 (0.0148174) rep1 (0.104444) rep2 (0.116209) rep3[ min (0.0935239) ] [ medium ] [ max ] CEM 1 Mta2 522.1 797.7 909.7 P ( S | Z, I ) = 0.00 Rbbp4 776.7 1206.6 1980.3 Mean Corr = 0.30794 Mbd3 141.8 318.2 418.7 Chd3 207.2 291.8 477.8 Gatad2a 7077.1 7946.3 9002.9 Gatad2b 436.7 548.6 651.3 Hdac2 40.3 107.5 178.4 Rbbp7 2906.5 7298.0 8852.4 Hnrnpl 843.3 1669.5 2044.3 Tcf3 259.5 524.7 912.6 Rnps1 70.1 140.1 182.5 Snrnp40 788.9 1702.8 1966.2 Ppm1g 2957.9 4574.8 5604.2 CEM 1 + Srsf4 1986.0 2071.3 2290.6 Top 10 Genes Arid1a 753.3 967.0 1364.3 Prr3 454.9 736.7 1219.6 Alyref 864.5 2315.6 2982.0 Trim28 4924.3 10156.7 12241.9

Null module GEO Series "GSE20954" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20954 Status: Public on Aug 17 2010 Title: mRNA expression profile in mouse lung development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20520778 Summary & Design: Summary: We performed miRNA and mRNA profiling over a 7-point time course, encompassing all recognized stages of lung development and explore dynamically regulated miRNAs and potential miRNA-mRNA interaction networks specific to mouse lung development

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

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

0.551 Kernel fit Pairwise Correlations Normal fit

Density 0.275

0.000 CEM 1

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

Pre-normalization Quantiles

Mouse lung-embryoMouse lung-embryoMouse day lung-embryoMouse 12-rep1 day lung-embryoMouse 12-rep2 (0.0915585) day lung-embryoMouse 14-rep1 (0.159767) day lung-embryoMouse 14-rep2 (0.0861087) day lung-embryoMouse 16-rep1 (0.0838463) day lung-embryoMouse 16-rep2 (0.0484783) day lung-postnatalMouse 18-rep1 (0.0427588) day lung-postnatalMouse 18-rep2 (0.0665546) lung-postnatalMouseday (0.0350976) 2-rep1 lung-postnatalMouseday (0.0223864)2-rep2 lung-postnatalMouseday (0.0215381)10-rep1 lung-postnatalday 10-rep2 (0.0453177) day 30-rep1 (0.0445226) day 30-rep2 (0.129555)[ min (0.122511) ] [ medium ] [ max ] CEM 1 Mta2 953.0 1335.0 1937.8 P ( S | Z, I ) = 0.00 Rbbp4 352.4 425.3 736.4 Mean Corr = 0.32573 Mbd3 563.9 664.7 1552.5 Chd3 1116.1 1544.2 1878.7 Gatad2a 1792.3 2315.2 2686.4 Gatad2b 428.4 515.7 579.1 Hdac2 123.1 189.1 318.2 Rbbp7 4364.8 8585.8 11674.1 Hnrnpl 485.4 711.3 1048.9 Tcf3 424.4 745.2 1693.5 Rnps1 296.3 572.3 1042.9 Snrnp40 527.4 809.1 2530.0 Ppm1g 1934.1 2117.8 3230.2 CEM 1 + Srsf4 1578.5 1776.9 2405.4 Top 10 Genes Arid1a 1401.4 1976.6 2467.8 Prr3 229.8 341.2 520.2 Alyref 347.6 503.3 1832.9 Trim28 1813.5 2857.3 7563.0

Null module GEO Series "GSE11677" 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=GSE11677 Status: Public on Aug 15 2008 Title: Gene expression profiles of age-associated clonal expansions of CD8 memory T cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18728183 Summary & Design: Summary: Many aged individuals develop monoclonal expansions of CD8 T cells. These expansions are derived from a CD8 memory T cell that outcompetes neighboring CD8 T cells. The molecular alterations within clonal expansions that confer this competitive advantage relative to other CD8 T cells remains unknown. These microarray experiments were designed to identify genes differentially expressed in age-associated expansions of CD8 memory T cells relative to polyclonal CD8 memory T cells found in the same aged mice.

Subsequent analysis of these data identified two major types of clonal expansions, distinguished by expression level of integrin a4 mRNA and protein. Based on this classification, Expansion_rep1 belongs to the integrin a4 high subtype of clonal expansions. In contrast, reps 2, 4, and 5 belong to the integrin a4 low subtype of clonal expansions. Given the divergent biological properties of these two subtypes of clonal expansions, we have focused genes differentially expressed between Expansion_rep 2, 4, and 5 and their paired PolyclonalAged samples.

Keywords: Cell type comparison of gene expression

Overall design: A total of 8 samples were analyzed for gene expression using the Affymetrix mouse genome 430 2.0 microarray platform. The experimental samples of interest were age-associated clonal expansions of CD8 memory T cells. We purified four clonal expansions from four independent, aged mice (indicated as ""Expansion"" rep1 2, 3, 4). For each clonal expansion of CD8 memory T cells that was purified, there was a paired control in which polyclonal CD8 memory T cells were harvested from the same aged mouse (denoted as ""PolyclonalAged"" rep1, 2, 3, 4). These paired samples allow one to consider gene expression changes from mice which have undergone the same age-associated changes in biology. The predominant comparison this study focused on was changes in gene expression between age-associated clonal expansions of CD8 memory T cells and their paired, polyclonal CD8 memory T cells. A total of 4 of these pairs were collected.

Background corr dist: KL-Divergence = 0.0783, L1-Distance = 0.0370, L2-Distance = 0.0026, Normal std = 0.4898

0.814 Kernel fit Pairwise Correlations Normal fit

Density 0.407

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

CD8 memoryCD8 memory T CD8cell_Expansion_rep1 memory T CD8cell_PolyclonalAged_rep1 memory T CD8cell_Expansion_rep2 memory T (0.0613828) CD8cell_PolyclonalAged_rep2 memory T CD8cell_Expansion_rep3 memory(0.0489308) T (0.0682406) CD8cell_PolyclonalAged_rep3 memory T cell_Expansion_rep4 (0.457882) T (0.213957) cell_PolyclonalAged_rep4 (0.0354937) (0.0493978)[ min ](0.0647152) [ medium ] [ max ] CEM 1 Mta2 31.4 94.2 292.9 P ( S | Z, I ) = 0.00 Rbbp4 230.5 752.9 1365.4 Mean Corr = 0.23118 Mbd3 3.0 6.9 135.5 Chd3 105.3 181.3 418.2 Gatad2a 118.5 154.7 356.1 Gatad2b 76.0 104.0 216.8 Hdac2 52.3 86.9 120.9 Rbbp7 21533.6 32304.8 39229.0 Hnrnpl 3.4 26.5 99.6 Tcf3 41.2 124.1 150.7 Rnps1 205.1 504.6 724.6 Snrnp40 199.7 298.1 617.2 Ppm1g 131.6 426.6 1377.0 CEM 1 + Srsf4 821.1 1168.5 1677.7 Top 10 Genes Arid1a 53.5 104.2 184.7 Prr3 40.8 83.9 157.3 Alyref 79.9 240.7 523.9 Trim28 219.1 368.1 929.9

Null module GEO Series "GSE11434" 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=GSE11434 Status: Public on May 15 2008 Title: Ventilator-induced lung injury in C57BL\6 mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19447895 Summary & Design: Summary: This study was undertaken to examine differential gene expression across the whole genome during short-term ventilator-induced lung injury in mice, a commonly used model of acute lung injury, as compared with spontaneous ventilation.

Keywords: Disease state analysis

Overall design: Mice were anesthetized with isoflurane followed by ketamine/xylaxine. Saline (0.25 ml) was given every hour ip. A tracheotomy tube was placed and the mice were ventilated with an initial peak airway pressure of 20 cmH2O approximating a tidal volume of 20 ml/kg and without end-expiratory pressure. Ventilation was continued for 3h. Tidal volume was not adjusted. Body temperature was monitored with a digital rectal thermometer and maintained at 37C with a heating table and external heating lamp. Control mice were treated identically, but were not mechanically ventilated (i.e. breathed spontaneously). There were 5 biological relicates in each group.

Background corr dist: KL-Divergence = 0.1024, L1-Distance = 0.0264, L2-Distance = 0.0012, Normal std = 0.4335

0.920 Kernel fit Pairwise Correlations Normal fit

Density 0.460

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

HVT1 (0.0954048)HVT2 (0.240149)HVT3 (0.100362)HVT4 (0.0828721)HVT5 (0.0382518)NV1 (0.096889)NV2 (0.114377)NV3 (0.141091)NV4 (0.0169045)NV5 (0.0736978) [ min ] [ medium ] [ max ] CEM 1 Mta2 130.9 297.2 640.4 P ( S | Z, I ) = 0.00 Rbbp4 62.7 254.8 384.1 Mean Corr = 0.21675 Mbd3 55.8 151.8 275.0 Chd3 335.4 911.8 1206.6 Gatad2a 1949.8 2384.1 3677.3 Gatad2b 392.9 536.7 932.2 Hdac2 118.0 190.1 247.7 Rbbp7 4314.2 5456.5 6362.5 Hnrnpl 924.4 1787.1 2269.5 Tcf3 253.0 413.0 648.9 Rnps1 27.3 149.1 308.6 Snrnp40 355.1 440.2 520.0 Ppm1g 1019.8 1831.0 2574.6 CEM 1 + Srsf4 1410.6 2248.9 3281.5 Top 10 Genes Arid1a 529.2 760.0 1433.7 Prr3 121.0 263.5 335.5 Alyref 873.4 1305.2 1775.3 Trim28 877.2 1702.0 3054.5

Null module GEO Series "GSE13874" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.482 Kernel fit Pairwise Correlations Normal fit

Density 0.241

0.000 CEM 1

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

Pre-normalization Quantiles

NTg, biologicalNTg, biologicalNTg, replicate biologicalNTg, replicate 1 (Affymetrix) biologicalCalcineurin replicate 2 (Affymetrix)Calcineurin replicate (0.0262265) 3 (Affymetrix)Tg,Calcineurin biological (0.0226415) 4 (Affymetrix)Tg,Calcineurin biological (0.0359343) replicate Tg,Differentiating biological (0.0233714) replicate Tg, 1 (Affymetrix)Differentiating biological replicate 2 P19CL6(Affymetrix)Differentiating replicate (0.0439291) 3 P19CL6(Affymetrix)Differentiating cells (0.0670879) 4at P19CL6(Affymetrix)Differentiating cellsday (0.0344495)6 at afterP19CL6Differentiating cellsday DMSO(0.0427135)6 at afterP19CL6 cellsday treatment, DMSO6 at afterP19CL6 cellsday treatment, DMSO10 at replicate aftercellsday treatment, 10 DMSOat replicate[ afterday 1min (Affymetrix) 10 treatment,DMSO replicate after 2 (Affymetrix)] treatment,DMSO (0.0531311)replicate 3 (Affymetrix) treatment, (0.0841485)replicate [1 (Affymetrix)medium (0.142978)replicate 2 (Affymetrix) (0.206504) 3 (Affymetrix) ] (0.117931) (0.0989538)[ max ] CEM 1 Mta2 531.0 681.1 1426.7 P ( S | Z, I ) = 0.00 Rbbp4 83.1 210.1 649.7 Mean Corr = 0.36373 Mbd3 272.1 354.5 1559.1 Chd3 313.6 436.6 762.4 Gatad2a 1103.4 1333.5 3248.7 Gatad2b 173.0 285.4 374.3 Hdac2 45.9 254.2 375.6 Rbbp7 5250.6 7399.8 15801.0 Hnrnpl 698.2 901.2 2769.7 Tcf3 163.7 273.9 2047.7 Rnps1 106.3 163.6 449.7 Snrnp40 331.9 391.2 1500.1 Ppm1g 1785.8 2071.3 4552.0 CEM 1 + Srsf4 1169.7 1426.6 3452.2 Top 10 Genes Arid1a 751.9 909.6 3615.9 Prr3 49.3 95.0 744.1 Alyref 914.2 1125.3 5087.4 Trim28 1222.5 1615.9 10880.4

Null module GEO Series "GSE53986" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53986 Status: Public on Mar 31 2014 Title: NRROS negatively regulates ROS in phagocytes during host defense and autoimmunity Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24739962 Summary & Design: Summary: Production of reactive oxygen species (ROS) is one of the important antimicrobial mechanisms of phagocytic cells. Enhanced oxidative burst requires these cells to be primed with agents such as IFNg and LPS with a synergistic effect of these agents on the level of the burst. However, excessive ROS generation will lead to tissue damage and has been implicated in a variety of inflammatory and autoimmune disease. Therefore, this process needs to be tightly regulated. In order to understand the genes regulating this process, we will treat bone marrow derived macrophages with above mentioned priming agents and study the gene expression.

We used microarrays to determine the changes in gene expression that occur in bone marrow derived macrophages after treatment with IFNg, LPS, or a combination of IFNg and LPS

Overall design: Four condition experiment; Biological replicates: four replicates per condition

Background corr dist: KL-Divergence = 0.1364, L1-Distance = 0.0322, L2-Distance = 0.0018, Normal std = 0.3981

1.009 Kernel fit Pairwise Correlations Normal fit

Density 0.504

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

BMDM, BMDM,untreated, BMDM,untreated, 1 (0.0935846) BMDM,untreated, 2 (0.0576218) BMDM,untreated, 3 (0.0335526) BMDM,IFNg, 4 (0.137314) 1 BMDM,IFNg,(0.0471159) 2 BMDM,IFNg,(0.0236424) 3 BMDM,IFNg,(0.0315712) 4 BMDM,LPS,(0.0395914) 1 (0.111861)BMDM,LPS, 2 (0.0327157)BMDM,LPS, 3 (0.0465999)BMDM,LPS, 4 (0.0176174)BMDM,IFNg+LPS, BMDM,IFNg+LPS, 1 (0.126549) BMDM,IFNg+LPS, 2 (0.0345592) IFNg+LPS, 3 (0.0734794) 4 (0.0926242)[ min ] [ medium ] [ max ] CEM 1 Mta2 682.3 802.6 1176.7 P ( S | Z, I ) = 0.00 Rbbp4 92.5 202.7 294.3 Mean Corr = 0.07429 Mbd3 199.5 581.3 848.5 Chd3 187.8 494.7 792.0 Gatad2a 1097.1 1520.1 2378.1 Gatad2b 147.5 219.8 352.0 Hdac2 2.7 37.3 52.9 Rbbp7 2865.6 5403.4 7397.1 Hnrnpl 1356.8 1867.6 2359.0 Tcf3 276.3 447.6 592.0 Rnps1 44.9 166.5 218.9 Snrnp40 566.1 691.1 778.3 Ppm1g 1113.1 1562.4 1867.5 CEM 1 + Srsf4 1355.7 1579.7 1900.3 Top 10 Genes Arid1a 281.4 407.1 529.2 Prr3 83.6 167.4 234.5 Alyref 1294.7 1721.4 2254.4 Trim28 1020.0 1332.3 1938.3

Null module GEO Series "GSE20335" 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=GSE20335 Status: Public on Apr 17 2010 Title: Expression analysis data from large T antigen-immortalized murine embryonic fibroblasts (MEFs) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20399150 Summary & Design: Summary: Microarrays were used to examine the genome-wide expression in FIH null, VHL null and VHL/FIH double null MEFs.

We used these data to analyze how deletion of FIH or VHL alone affects gene expression and if VHL and FIH have synergistic effects and differential selectivity on regulating gene expression.

Overall design: To assess how deletion of FIH, VHL or both VHL and FIH affect gene expression genome-wide, we generated FIH null, VHL null and VHL/FIH double null MEFs after adeno-cre virus infection on large T-immortalized FIHdf, VHLdf, and VHLdf/FIHdf MEFs. These MEFs were cultured under normoxia (21% O2) with complete culture medium before RNA extraction. Total RNA were isolated by using the Qiagen RNeasy kit and treated with on-column DNase digestion. Affymetrix GeneChip Mouse Genome 430 2.0 Array was used.

Background corr dist: KL-Divergence = 0.0547, L1-Distance = 0.0269, L2-Distance = 0.0009, Normal std = 0.5587

0.729 Kernel fit Pairwise Correlations Normal fit

Density 0.365

0.000 CEM 1

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

Pre-normalization Quantiles

Wild-typeWild-type MEFs,FIH biological MEFs, nullFIH MEFs, biological null rep1 VHLbiological MEFs, (0.131999) nullrep2 VHLbiological MEFs, (0.116072) rep1 nullVHL/FIH (0.113956)biological MEFs, rep2VHL/FIH (0.119763)biologicalnull rep1 MEFs, null(0.18935) rep2 biological MEFs, (0.128474) biological rep1 (0.0673471) [rep2 min (0.13304) ] [ medium ] [ max ] CEM 1 Mta2 1527.6 2392.7 2708.5 P ( S | Z, I ) = 0.00 Rbbp4 109.5 138.6 188.9 Mean Corr = 0.08923 Mbd3 1543.3 1685.9 1958.7 Chd3 558.4 1285.3 1475.9 Gatad2a 2594.3 4099.9 4483.7 Gatad2b 289.0 381.5 480.9 Hdac2 8.8 35.1 48.4 Rbbp7 9573.8 10535.3 11610.8 Hnrnpl 856.6 1773.9 2109.6 Tcf3 1068.9 1723.4 1956.6 Rnps1 308.1 415.2 522.1 Snrnp40 1746.6 2167.2 2281.9 Ppm1g 3997.6 5611.0 6077.7 CEM 1 + Srsf4 1851.0 2036.3 2315.4 Top 10 Genes Arid1a 918.6 1284.8 1490.3 Prr3 311.6 369.3 406.5 Alyref 3470.9 5062.2 5447.4 Trim28 3263.6 3906.3 4279.7

Null module GEO Series "GSE45941" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.740 Kernel fit Pairwise Correlations Normal fit

Density 0.370

0.000 CEM 1

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

Pre-normalization Quantiles

Ctrl ESCCtrl rep1 ESC (0.10935)KO rep2 ESC (0.137443)KO rep1 ESC (0.187088)Ctrl rep2 PGC (0.0227345)Ctrl rep1 PGC (0.167481)KO rep2 PGC (0.179242)KO rep1 PGC (0.0742782) rep2 (0.122383) [ min ] [ medium ] [ max ] CEM 1 Mta2 293.3 430.4 511.3 P ( S | Z, I ) = 0.00 Rbbp4 271.0 625.0 1164.2 Mean Corr = 0.21988 Mbd3 746.9 1101.3 1853.1 Chd3 224.9 350.2 718.8 Gatad2a 1565.0 2292.4 2629.0 Gatad2b 259.1 611.6 876.2 Hdac2 90.8 110.9 124.4 Rbbp7 13850.2 19387.2 22935.1 Hnrnpl 3099.9 3380.7 3746.0 Tcf3 1237.1 1480.7 2657.7 Rnps1 173.7 370.6 646.8 Snrnp40 2588.0 3252.1 3598.6 Ppm1g 1001.9 1714.7 1990.7 CEM 1 + Srsf4 3040.1 3394.7 4022.0 Top 10 Genes Arid1a 170.3 282.9 378.4 Prr3 164.7 213.3 242.7 Alyref 7382.2 7766.2 9373.0 Trim28 4755.0 7955.7 11862.2

Null module