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

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

Dataset: Num of genes in input gene set: 7 Total number of genes: 16493

CLIC PDF output has three sections:

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

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

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

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

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

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

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

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

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

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

Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Med23 Med10 Med21 Med14 Med6 Num ofGenesinQueryGeneset:7.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Ccnc Cdk8

Med14 Med21 Med6 Cdk8 Ccnc Med10 Med23 CEM 1(46datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 0610009D07Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page1 Smarcad1 Smarca5 Smchd1 Trmt10c Magohb Prpf40a Nudcd2 Ncapg2 Rbmxl1 Ccdc58 Cep192 Trmt11 Rbm12 Dcaf13 Dnajc9 Psma1 Magoh Prpf4b Polr2d Med23 Med10 Med21 Med14 Srsf10 Nup54 Cks1b Caap1 Ddx21 Haus3 Pbdc1 Rad17 Abce1 Pfdn4 Asf1a Tfdp1 Cse1l Txnl1 Med6 Wdr3 Rpa3 Pno1 Ccnc Cdk8 Tipin Orc6 Hat1 Dis3 Ltv1 Ssb 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE7275 [8] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE48935 [12] GSE47694 [10] GSE49237 [8] GSE50813 [24] GSE21836 [8] GSE42601 [6] GSE12993 [6] GSE24243 [6] GSE38831 [7] GSE29458 [23] GSE18135 [18] GSE44175 [18] GSE58368 [15] GSE14406 [54] GSE12454 [13] GSE27708 [9] GSE25286 [10] GSE27114 [6] GSE11201 [18] GSE9533 [35] GSE13235 [9] GSE19512 [6] GSE38693 [8] GSE37546 [20] GSE7863 [16] GSE6837 [8] GSE57797 [23] GSE13874 [14] GSE11356 [9] GSE21711 [6] GSE15330 [27] GSE51628 [15] GSE31028 [6] GSE11258 [24] GSE15794 [6] GSE26616 [6] GSE32277 [33] GSE45820 [6] GSE16874 [12] GSE5861 [6] GSE8322 [12] GSE6998 [32] GSE36513 [8] GSE27605 [8] GSE43373 [130] GSE10210 [16] GSE15325 [23] GSE36415 [14] GSE13106 [10] GSE29485 [12] GSE10644 [18] GSE24276 [6] GSE19204 [6] GSE4230 [8] GSE38257 [14] GSE12498 [12] GSE11862 [6] GSE4308 [16] GSE9913 [9] GSE36665 [6] GSE35219 [6] GSE2557 [6] GSE13693 [9] GSE7430 [12] GSE14478 [7] GSE28093 [6] GSE27261 [8] GSE10776 [15] GSE21278 [48] GSE51804 [10] GSE35366 [78] GSE27516 [17] GSE4734 [61] GSE33942 [12] GSE7424 [8] GSE30176 [12] GSE40368 [10] GSE9297 [27] GSE49346 [6] GSE38048 [20] GSE59672 [12] GSE13611 [8] GSE7764 [10] GSE24489 [14] GSE27848 [16] GSE27720 [6] GSE48204 [6] GSE28389 [20] GSE27195 [6] GSE23002 [8] GSE43825 [31] GSE23895 [18] GSE27309 [10] GSE26461 [6] GSE27378 [8] GSE44084 [8] GSE41084 [6] GSE8025 [21] GSE7225 [9] GSE6196 [9] GSE37975 [8] GSE19657 [21] GSE20944 [18] GSE49283 [12] GSE10813 [12] GSE30498 [12] GSE49248 [12] GSE6223 [13] GSE52022 [8] GSE7759 [112] GSE28664 [17] GSE30083 [12] GSE13129 [12] GSE21224 [16] GSE5333 [16] GSE8684 [10] GSE35044 [9] GSE30868 [8] GSE13553 [10] GSE46091 [8] GSE13692 [8] GSE17383 [6] GSE33471 [12] GSE45619 [6] GSE24203 [8] GSE6065 [100] GSE55809 [8] GSE10904 [6] GSE12465 [14] GSE17112 [8] GSE14415 [31] GSE30160 [6] GSE41925 [8] GSE35435 [6] GSE11982 [6] GSE14753 [6] GSE13707 [20] GSE26076 [12] GSE40296 [6] GSE51385 [8] GSE11382 [10] GSE39233 [40] GSE4749 [6] GSE26476 [6] GSE46606 [30] GSE12518 [6] GSE36810 [16] GSE18567 [24] GSE18925 [6] GSE20152 [8] GSE16992 [48] CEM+ CEM GSE16110 [16] GSE18326 [8] GSE11990 [20] GSE15433 [9] GSE15871 [18] GSE13149 [25] 0.0 GSE38574 [32] GSE7810 [9]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 34.05 34.07 34.22 34.22 34.28 34.42 34.66 34.85 35.37 35.42 35.43 35.54 35.84 36.11 36.13 36.56 36.78 36.86 37.00 37.16 37.20 37.83 38.37 38.62 38.84 38.89 39.37 39.44 39.55 39.63 39.90 40.00 40.08 40.22 40.23 40.29 40.62 40.64 40.85 41.45 42.29 43.30 48.42 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page2 Mphosph6 Casp8ap2 Smndc1 Armc10 Prps1l3 Anp32e Nup160 Topbp1 Exosc9 Tsen15 Dnttip2 Pgam5 Psma4 Psma2 Gtf2h2 Mak16 Nop58 Cenpk Rnpc3 Ccne2 Naa15 Tex30 Snrpe Gspt1 Mcm4 Sarnp Mis12 Atad2 Trmt6 Nol11 Lin54 Pwp1 Srsf1 Pcna Exo5 Leo1 Ints2 Dbr1 Rrs1 Gnl3 Utp6 Anln Rnf4 Nip7 Ect2 Tsr1 Taf2 Eri1 Itpa Set 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 29.68 29.70 29.72 29.75 29.91 29.99 30.00 30.21 30.25 30.28 30.31 30.38 30.53 30.59 30.60 30.73 30.80 30.82 31.09 31.11 31.26 31.30 31.31 31.35 31.43 31.48 31.56 31.57 31.58 31.62 31.64 31.64 31.98 32.05 32.19 32.34 32.38 32.44 32.46 32.59 32.69 33.16 33.16 33.23 33.35 33.59 33.74 33.83 33.87 33.96 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page3 Arhgap11a Commd2 Cenpc1 Skiv2l2 Zc3h15 Isg20l2 Rbm34 Rbmx2 Rsl1d1 Tcerg1 Eef1e1 Zfp131 Med17 Gtf2e2 Gtf2e1 Kpnb1 Lrrc40 Wdr77 Ncbp2 Actl6a Dhx15 Rad51 Kif18a Ckap2 Cdc73 Mcm6 Ccar1 Parp2 Yars2 Spdl1 Hbs1l Sf3a3 Snrpf Msh6 Bub1 G2e3 Xpo5 Fmr1 Uba2 Skp2 Hells Tfam Fen1 Rars Sfpq Npat Rfc4 Ctcf Eed Ttf2 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 26.75 26.82 26.83 26.93 26.94 26.95 26.95 26.96 27.00 27.05 27.12 27.15 27.29 27.30 27.33 27.35 27.36 27.39 27.54 27.57 27.73 27.74 27.80 27.85 28.03 28.03 28.11 28.27 28.28 28.29 28.56 28.58 28.60 28.61 28.68 28.71 28.72 28.73 28.77 28.86 28.88 28.97 29.14 29.23 29.24 29.37 29.38 29.49 29.53 29.58 1.0 Notes Mphosph10 Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page4 Tmem167 Racgap1 Rnaseh1 Hnrnpab Snrnp40 Dnajc24 Fastkd5 Fam98b Map3k7 Syncrip Anapc4 Zmym1 Hnrnpk Mettl10 Trdmt1 Nudt21 Mis18a Ruvbl1 Trim59 Spata5 Kdelc1 Nufip1 Polr3k Polr1e Kpna2 Ncbp1 Nup93 Fubp3 Qtrtd1 Tmtc3 Rrp15 Cnot6 Prim2 Prim1 Nme1 Larp7 Pola1 Lsm1 Brix1 Hus1 Eif4e Orc2 Rnf2 Rbl1 Hn1l Api5 Rfc3 Krr1 Taf5 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 23.66 23.69 23.81 23.82 23.94 23.95 23.95 24.09 24.10 24.12 24.16 24.23 24.32 24.38 24.49 24.49 24.55 24.57 24.60 24.63 24.72 24.75 24.93 24.95 24.97 25.11 25.15 25.30 25.33 25.39 25.53 25.60 25.63 25.65 25.69 25.69 25.72 25.84 25.93 25.95 26.09 26.11 26.21 26.35 26.35 26.39 26.58 26.62 26.63 26.74 1.0 Notes 9430016H08Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page5 BC016423 BC055324 Depdc1a Eif4enif1 Psmd12 Smim15 Rwdd4a Ranbp2 Ranbp1 Ormdl1 Arl6ip6 Rbm26 Katna1 Cbwd1 Psmc6 Ergic2 Nup35 Rpp30 Ccna2 Usp14 Znhit6 Naa20 Tex10 Mcm2 Prmt3 Gmps Cfdp1 Dimt1 Cenpi Sgol1 Pole2 Etaa1 Mob4 Med4 Srsf3 Rad1 Cdc7 Vbp1 Eif3a Tdp2 Mtbp Ezh2 Rrn3 Ctps Naf1 Rlim Cdyl Nifk Atr 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 21.43 21.59 21.65 21.69 21.76 21.92 21.93 21.98 21.99 22.01 22.06 22.10 22.10 22.13 22.18 22.22 22.37 22.46 22.60 22.63 22.72 22.75 22.79 22.79 22.85 22.93 22.95 23.01 23.01 23.03 23.05 23.07 23.08 23.13 23.14 23.18 23.19 23.20 23.23 23.24 23.26 23.31 23.34 23.42 23.43 23.46 23.46 23.51 23.53 23.63 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page6 Ebna1bp2 Ccdc115 Zfp280c Gemin2 Prpf38a Anp32b Nup107 Zcchc9 Rbm8a Wdhd1 Psma7 Psma6 Mrpl13 Zfp330 Cwc22 Srfbp1 Zwilch Heatr1 Prdm4 Ncapg Nup43 Rqcd1 Cenpe Cep44 Ddx20 Ddx18 Ssbp1 Rfwd3 Naa50 Esco2 Fancb Brca1 Aspm Atad5 Utp20 Bms1 Sf3b3 Smc3 Bzw1 Eif5b Cdc6 Nfxl1 Xpo1 Ftsj3 Urb2 Dbf4 Zzz3 Esf1 Plk4 Taf9 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 19.22 19.25 19.32 19.34 19.45 19.47 19.50 19.52 19.54 19.57 19.63 19.67 19.76 19.76 19.78 19.81 19.85 19.88 19.95 19.98 20.02 20.08 20.13 20.13 20.14 20.15 20.16 20.31 20.36 20.52 20.62 20.64 20.68 20.71 20.73 20.74 20.77 20.82 20.84 20.86 20.89 20.95 21.01 21.04 21.10 21.22 21.33 21.33 21.34 21.40 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page7 Tmem168 Anapc10 Psmd14 Ppip5k2 Cacybp Exosc3 Ppp4r2 Hmgb3 Cnot11 Rbm27 Kansl2 Zfp472 Zfp958 Polr2h Cenpq Rbbp8 Rbbp7 Nop16 Nup88 Nup50 Ube2c Hspa4 Cep57 Rap2c Usp38 Apex1 Trip13 Fubp1 Pspc1 Fignl1 Aurkb Alyref Srp19 Cpsf2 Pcgf6 Rpl14 Zbtb1 Rrm2 Cdk1 Uba6 Pus7 Exo1 Tpx2 Mtx2 Iws1 Cul1 Pfas Lyar Pnn Ncl 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 16.90 16.95 17.01 17.01 17.07 17.08 17.14 17.15 17.18 17.21 17.23 17.29 17.41 17.51 17.53 17.55 17.57 17.59 17.64 17.67 17.91 18.01 18.12 18.14 18.16 18.24 18.27 18.30 18.31 18.34 18.34 18.35 18.41 18.46 18.50 18.56 18.64 18.66 18.70 18.75 18.79 18.83 18.87 18.93 18.95 19.01 19.04 19.13 19.14 19.19 1.0 Notes 2700029M09Rik 1110037F02Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page8 Mis18bp1 Thumpd1 Ankrd32 Hnrnpm Mms22l Heatr5a Shcbp1 Nup155 Cdc123 Mrps17 Mrps22 Hnrnpc Hnrnpll Snrpd3 Psmd5 Nap1l1 Mrpl32 Cenph Cand1 Ercc6l Eif4g2 Dpy30 Ddx46 Ddx42 Ube2k Tnpo1 Spcs3 Snrpg Jade3 U2af1 Nol10 Mtrf1l Eme1 Ttc27 Vwa9 Prpf3 Plrg1 Nhp2 Snx5 Ireb2 Dkc1 Ska3 Denr Lin9 Nkrf Blm Yy1 Lbr 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 15.51 15.54 15.56 15.59 15.61 15.63 15.67 15.67 15.72 15.77 15.81 15.86 15.89 15.90 15.94 15.97 15.98 15.98 16.10 16.19 16.27 16.27 16.27 16.34 16.37 16.38 16.45 16.47 16.51 16.52 16.52 16.53 16.56 16.56 16.58 16.64 16.68 16.70 16.70 16.73 16.76 16.76 16.81 16.81 16.82 16.83 16.83 16.86 16.89 16.89 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page9 Zmynd19 Fam133b Zdhhc13 Capza1 Ppp1r8 Rnf219 Sumo1 Prkaa1 Ier3ip1 Ppwd1 Mrpl18 Slc4a7 Pitrm1 Med30 Polr2g Srsf11 Cops3 Rad21 Ddx27 Cdca7 Dhx33 Haus6 Cdca4 Gorab Mettl9 Gstcd Prmt6 Mki67 Cenpl Xrcc6 Scaf8 Taf11 Lsm6 Mitd1 Rrm1 Srsf9 Terf1 Ppil1 Cks2 Phax Ska2 Ofd1 Melk Hars Nuf2 Piga Nbn Rif1 Pigf Zfx 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 13.72 13.73 13.74 13.83 13.84 13.93 13.94 13.98 13.99 14.02 14.05 14.07 14.14 14.18 14.29 14.34 14.34 14.34 14.38 14.46 14.46 14.46 14.48 14.48 14.51 14.58 14.62 14.63 14.64 14.68 14.69 14.88 14.90 14.95 14.96 15.02 15.07 15.09 15.10 15.14 15.18 15.20 15.21 15.23 15.28 15.32 15.33 15.33 15.36 15.44 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page10 Rnaseh2b Rad51ap1 B3galnt2 Tomm20 Rabggtb Snrnp27 Sephs1 Ccdc43 Rnf168 Rbm22 Psmd1 Rps27l Cenpw Gabpa Nsun2 Bend3 Rpap3 Cops5 Ddx39 Senp5 Ddx52 Dhx36 Fbxo5 Cenpj Cetn3 Noc2l Riok1 Alg13 Cct6a Strap Tyw3 Srsf7 Birc5 Bdp1 Pigm Rpa2 Kif11 Nae1 Mtap Cbfb Gnl2 Xpot Utp3 Alg6 Lars Tars Elp2 Eri2 Iars Dr1 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 11.92 11.93 11.94 11.97 12.03 12.05 12.08 12.09 12.10 12.13 12.15 12.18 12.19 12.26 12.29 12.31 12.47 12.49 12.50 12.55 12.61 12.63 12.65 12.70 12.74 12.80 12.81 12.83 12.84 12.84 12.89 12.97 12.99 12.99 13.00 13.13 13.13 13.14 13.17 13.25 13.29 13.39 13.39 13.43 13.48 13.50 13.52 13.54 13.56 13.64 1.0 Notes 2700097O09Rik E430025E21Rik 1200014J11Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page11 Tmem199 Hnrnpa0 Hmgxb4 Nsmce2 Fam49b Katnbl1 Nucks1 Ccdc34 Atad2b Alkbh1 Txnrd1 Psmd6 Cwc27 Gtf3c3 Prpf31 Polr2b Copb1 Hddc2 Nup85 Trpm7 Cep78 Ddx31 Bbs12 Rpl7l1 Ndc80 Cebpz Ints12 Tasp1 Vprbp Gins1 Gnai3 Cul4b Pomp Xrcc5 Bccip Lsm3 Mastl Dhx9 Pop4 Rae1 Tbca Gin1 Dars Ssr1 Cct2 Pole Ipo9 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 10.58 10.60 10.71 10.73 10.75 10.77 10.77 10.78 10.78 10.85 10.87 10.88 10.89 10.92 10.93 10.93 10.96 11.04 11.04 11.05 11.05 11.06 11.11 11.13 11.16 11.21 11.25 11.26 11.28 11.29 11.33 11.44 11.45 11.46 11.51 11.52 11.61 11.61 11.62 11.64 11.64 11.66 11.67 11.70 11.72 11.73 11.73 11.78 11.85 11.91 1.0 Notes 4930503L19Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page12 Tmem128 Aasdhppt Slc7a6os Fam111a Hnrnph2 Txndc17 Tamm41 Dnajc13 Appbp2 Dclre1b Rpusd4 Nup133 Anapc1 Ccp110 Snapc3 Hnrnpu Mcmbp Mettl18 Snrpa1 Hmgb2 Papolg Nop56 Eif2b3 Slmo2 Rps25 Cdc26 Dtwd1 Mettl3 Gtf2f2 Gmnn Mnat1 Mcm8 Pprc1 Ube2t Asf1b Smu1 Phf5a Eif3m Psip1 Ccnh Ufm1 Bmi1 Kif22 Ppil4 Rcc1 Tgds Rtca E2f5 Ift74 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 9.33 9.35 9.37 9.37 9.39 9.41 9.41 9.41 9.42 9.43 9.46 9.53 9.54 9.57 9.64 9.65 9.66 9.68 9.70 9.74 9.75 9.77 9.77 9.83 9.83 9.89 9.89 9.96 9.96 10.00 10.01 10.01 10.05 10.08 10.20 10.21 10.22 10.24 10.27 10.29 10.29 10.30 10.33 10.37 10.38 10.43 10.46 10.47 10.51 10.56 1.0 Notes 9130401M01Rik 1700123O20Rik 1110004F10Rik 2410127L17Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page13 BC018507 Fam179b Ankrd49 Timm21 Twistnb Ncapd2 Nusap1 Prkrip1 Mettl14 Ythdc2 Supt16 Lmnb1 Psmc4 Mrpl22 Zfp664 G3bp2 Cirh1a Knop1 Pacrgl Nedd8 Ncaph Sdad1 Kif20a Cdc45 Vps29 Fkbp3 Thoc3 Impa1 Mcm5 Ercc3 Sgol2 Uchl5 Riok2 Mrpl3 Ttc37 Surf6 Med7 Btaf1 Dph6 Blmh Noa1 Aaas Rrp8 Msl3 Slirp Far1 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 8.10 8.12 8.17 8.24 8.29 8.30 8.31 8.31 8.37 8.38 8.39 8.39 8.39 8.46 8.47 8.51 8.55 8.55 8.60 8.61 8.66 8.67 8.68 8.68 8.68 8.71 8.73 8.73 8.75 8.83 8.85 8.88 8.92 8.92 8.93 8.94 9.00 9.02 9.03 9.07 9.09 9.09 9.13 9.19 9.22 9.22 9.26 9.27 9.29 9.32 1.0 Notes 2310057M21Rik D030056L22Rik A130010J15Rik 4921524J17Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page14 Tmem165 Fam122b Wbscr22 Suv39h2 Psmd10 Chchd1 Rad54b Ddx19a Pdcd10 Yae1d1 Sec11a Ppp4r1 Chaf1b Cmss1 Zfp770 Mmgt1 G3bp1 Apitd1 Ythdf2 Dtymk Haus1 Cep55 Cep76 Papd4 Bclaf1 Znhit3 Tnpo3 Sap30 Sec13 Mettl5 Cenpf Ssrp1 Clint1 l7Rn6 Pms2 Uhrf1 Gnl3l Dph2 Nde1 Rps9 Pdk3 Taf5l Toe1 Mtf2 Lzic Pbk 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 6.77 6.77 6.77 6.78 6.81 6.82 6.83 6.91 6.92 6.97 6.97 6.98 6.99 7.00 7.00 7.01 7.03 7.04 7.04 7.06 7.06 7.17 7.20 7.28 7.28 7.34 7.36 7.38 7.41 7.41 7.51 7.54 7.55 7.55 7.55 7.66 7.66 7.69 7.72 7.78 7.78 7.78 7.80 7.86 7.90 7.92 8.07 8.08 8.09 8.09 1.0 Notes 4930579G24Rik 2700094K13Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page15 Fra10ac1 Tubgcp3 Cnep1r1 Ppp2r1b Pwwp2a Pak1ip1 Fam98a Gabpb1 Donson Prdm15 Phf20l1 Morf4l2 Mthfd1l Sec23b Mapre1 Pdzd11 Ap3m1 Kdm5a Ckap2l Gtf3c2 Nufip2 Dnmt1 Dicer1 Nup98 Wdr36 Cdca8 Pus10 Prmt1 Ctbp2 Cnih4 Psrc1 Recql Pgm3 Nif3l1 Pus7l Fancl Mnd1 Mogs Gen1 Ddx1 Acn9 Ints7 Yrdc Rfc1 Cct4 Ttll4 Rtf1 Tpr 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 5.27 5.29 5.31 5.32 5.35 5.38 5.40 5.45 5.47 5.47 5.49 5.53 5.54 5.56 5.62 5.63 5.66 5.67 5.67 5.68 5.78 5.80 5.84 5.94 6.01 6.03 6.06 6.07 6.14 6.14 6.20 6.20 6.22 6.23 6.23 6.25 6.28 6.29 6.30 6.38 6.44 6.46 6.52 6.60 6.63 6.65 6.70 6.71 6.71 6.76 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page16 BC003965 Thumpd3 Cdk2ap1 Mrps18c Nfatc2ip Zfp518a Zdhhc6 Exosc1 Gtpbp4 Metap2 Kdm1a Whsc1 Fbxl14 Gtf2h5 Tceal8 Mapk1 Pbrm1 Atpaf1 Wdr55 Wdr26 Pdap1 Chek2 Cdca5 Usp42 Dhx29 Usp45 Srpk1 Trmt5 Rbm7 Snip1 Ptcd3 Pole3 Pinx1 Siva1 Tcf19 Crls1 Nob1 Ppil3 Ppa1 Tefm Orc5 Mlh1 Mzt1 Ppat Nxt1 Adsl E2f7 Pdcl Lig4 Arl6 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 3.93 4.01 4.01 4.04 4.05 4.14 4.15 4.15 4.18 4.19 4.19 4.20 4.22 4.24 4.24 4.26 4.26 4.33 4.35 4.36 4.36 4.36 4.46 4.50 4.50 4.53 4.57 4.57 4.63 4.65 4.74 4.74 4.75 4.75 4.77 4.80 4.83 4.85 4.85 4.88 4.91 4.95 4.96 4.98 5.06 5.09 5.09 5.10 5.24 5.26 1.0 Notes 2810403A07Rik 2810417H13Rik 0610010F05Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page17 BC027231 Tomm70a Tmem39a Pafah1b2 Commd6 Chordc1 Fam96a Enoph1 Cdc25c U2surp Arpp19 Dlgap5 Zfp617 Med19 C1qbp Rbbp5 Cops2 Hsph1 Hspe1 Spag5 Pds5b Syce2 Mbnl3 Myef2 Hirip3 Apool Upf3b Aggf1 Dmtf1 Prps1 Nupl1 Kntc1 Nme7 Smc5 Scyl2 Odf2l Kti12 Stam Diexf Naca Cdt1 Rtcb Prc1 Setx Lig1 Dhfr Dck 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 2.85 2.88 2.88 2.89 2.94 2.97 2.99 3.01 3.02 3.03 3.07 3.09 3.11 3.14 3.16 3.17 3.18 3.22 3.28 3.31 3.32 3.36 3.37 3.38 3.42 3.54 3.57 3.57 3.58 3.61 3.61 3.61 3.66 3.67 3.68 3.70 3.70 3.70 3.72 3.73 3.75 3.75 3.76 3.79 3.81 3.84 3.88 3.89 3.92 3.93 1.0 Notes 2410016O06Rik 4930422G04Rik Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page18 BC026590 Trappc13 Slc4a1ap Timeless Tmem70 Gnpnat1 Ankrd28 Bloc1s2 Caprin1 Pdcd11 Mrps33 Stoml2 Zfp386 Zfp317 Ahctf1 Cenpu Wdr46 Cops4 Cnpy4 Eif1ad Chsy1 Eif4a1 Naa30 Gins2 Gtse1 Polr2j Cnih1 Trub1 Setd8 Emg1 Smn1 Smc4 H2afz Tstd2 Brip1 Strn3 Shq1 Dsn1 Eapp Qtrt1 Top1 Nras Rfx7 Sfr1 Ung Ado Kif4 Tsn 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 2.00 2.01 2.03 2.03 2.05 2.07 2.08 2.08 2.08 2.08 2.10 2.10 2.15 2.16 2.16 2.18 2.19 2.20 2.24 2.26 2.28 2.28 2.34 2.37 2.48 2.49 2.50 2.53 2.55 2.57 2.58 2.58 2.61 2.61 2.63 2.69 2.69 2.69 2.72 2.73 2.73 2.74 2.76 2.78 2.79 2.81 2.82 2.83 2.84 2.84 1.0 Notes A830080D01Rik 1110059E24Rik 3110001I22Rik D15Ertd621e Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page19 Tmem55a Nsmce4a Timm17a Rsl24d1 Sec23ip Fam76b Fam72a Ndufaf2 Cep290 Tnfaip8 Otud6b Mettl25 Pphln1 Efcab7 Psmg1 Hnrnpf Zfp143 Polr3c Wdr43 Aimp1 Casp2 Naa10 Spc24 Gtf2f1 Rars2 Ptpn9 Spopl Srek1 Pms1 Pdcl3 Pdia6 Ngdn Chuk Nanp Xpo7 Rcc2 Pes1 Tcp1 Parg Ccnf Rfc5 Yaf2 Isy1 Rpe C1d Aqr 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 0.98 0.99 0.99 1.00 1.02 1.04 1.05 1.05 1.07 1.09 1.11 1.11 1.17 1.18 1.18 1.19 1.19 1.21 1.22 1.25 1.26 1.27 1.28 1.31 1.32 1.34 1.34 1.38 1.42 1.44 1.46 1.48 1.48 1.48 1.54 1.64 1.64 1.70 1.72 1.74 1.74 1.79 1.80 1.90 1.95 1.96 1.96 1.98 1.98 1.98 1.0 Notes Symbol Num ofCEMGenes:7.Predicted989.SelectedDatasets:46.Strength:0.2 CEM 1,Geneset"[C]NATcomplex",Page20 Slc39a10 Depdc1b Csnk1g1 Hnrnph1 Hnrnpa3 Trmt10a Map4k4 N6amt2 Rbm45 Psmg3 Pgam1 Trim37 Zbtb26 Mrpl40 Incenp Zfp281 Zfp566 Slc7a6 Cwc15 Med31 Gtf3c4 Grwd1 Bub1b Polr2c Wdr82 Wdr73 Reps1 Ebag9 Rgs19 Rasa1 Eif2s2 Prmt5 Dars2 Prdx4 Kctd5 Phf10 Gpn1 Nudc Nop2 Chd1 Ppan Bivm Iars2 Ints3 Tsr2 Aen 0.0 1.0

GSE20954 [14] GSE15155 [12]

GSE16751 [6] Scale ofaveragePearsoncorrelations GSE18745 [6] GSE4786 [9] GSE31702 [10] GSE44162 [6] GSE44101 [6] GSE31406 [12] 0.2 GSE22291 [16] GSE48004 [6] GSE37000 [47] GSE27159 [8] GSE28593 [9] GSE9146 [27] GSE43381 [26] GSE12810 [6] GSE18148 [6] 0.4 GSE7683 [12] GSE18587 [9] GSE15772 [8] GSE21063 [24] GSE10113 [12] GSE46723 [6] GSE57469 [6] GSE4193 [8] GSE28408 [6] 0.6 GSE36826 [12] GSE18993 [13] GSE17728 [12] GSE10290 [24] GSE28333 [6] GSE18669 [12] GSE19369 [8] GSE30980 [6] GSE6526 [16] 0.8 GSE7762 [36] GSE4928 [8] GSE37676 [6] GSE6482 [9] Score 0.00 0.01 0.02 0.02 0.03 0.03 0.04 0.06 0.07 0.09 0.18 0.21 0.27 0.28 0.32 0.32 0.36 0.41 0.41 0.43 0.49 0.51 0.55 0.55 0.56 0.56 0.57 0.57 0.58 0.62 0.66 0.70 0.70 0.70 0.71 0.72 0.72 0.76 0.81 0.83 0.83 0.86 0.88 0.95 0.97 0.97 1.0 Notes 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 (0.154396) day lung-embryoMouse 14-rep1 (0.126264) day lung-embryoMouse 14-rep2 (0.071136) day lung-embryoMouse 16-rep1 (0.0569644) day lung-embryoMouse 16-rep2 (0.0826795) day lung-postnatalMouse 18-rep1 (0.0655672) day lung-postnatalMouse 18-rep2 (0.0709924) lung-postnatalMouseday (0.046249) 2-rep1 lung-postnatalMouseday (0.0227081)2-rep2 lung-postnatalMouseday (0.0290273)10-rep1 lung-postnatalday 10-rep2 (0.031688) day 30-rep1 (0.0370005) day 30-rep2 (0.10098)[ min (0.104348) ] [ medium ] [ max ] CEM 1 Med14 651.2 862.3 1315.7 P ( S | Z, I ) = 1.00 Med21 675.5 911.6 1388.1 Mean Corr = 0.83376 Med6 247.0 344.0 818.9 Cdk8 1089.8 1414.1 2325.2 Ccnc 208.3 263.8 328.8 Med10 1504.2 1876.5 2446.4 Med23 610.2 877.6 1492.1 Prpf40a 432.8 606.6 1331.4 Rbm12 658.1 1073.6 2109.9 0610009D07Rik 2892.1 4075.7 6116.7 Srsf10 613.7 807.2 1154.5 Ccdc58 310.8 626.7 1580.3 CEM 1 + Pfdn4 847.1 1321.1 2817.9 Top 10 Genes Pno1 638.6 1095.1 2723.5 Orc6 318.8 562.1 1976.5 Abce1 855.4 1345.0 3146.9 Magoh 2513.4 3952.4 7993.6

Null module GEO Series "GSE15155" 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=GSE15155 Status: Public on Jan 04 2010 Title: Gene profiling of quiescent and activated skeletal muscle satellite cells by an in vivo approach Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19962952 Summary & Design: Summary: The satellite cell of skeletal muscle provides a paradigm for quiescent and activated tissue stem cell states. We have carried out transcriptome analyses by comparing satellite cells from adult skeletal muscles, where they are mainly quiescent, with cells from growing muscles, regenerating (mdx) muscles, or with cells in culture, where they are activated. Our study gives new insights into the satellite cell biology during activation and in respect with its niche.

We used microarrays to study the global programme of gene expression underlying adult satellite cell quiescence compared to activation states and to identify distinct classes of up-regulated genes in these two different states

Overall design: Skeletal muscle satellite cells were isolated by flow cytrometry using the GFP fluorescence marker from Pax3GFP/+ mice skeletal muscle. The transcriptome of quiescent satellite cells from adult Pax3GFP/+ muscle was compared to the transcriptome of activated satellite cells obtained from three different samples: 1) regenerating Pax3GFP/+:mdx/mdx muscle (Ad.mdx) , 2) growing 1 week old Pax3GFP/+ muscle (1wk), and 3) adult Pax3GFP/+ cells after 3 days in culture (Ad.cult).

Background corr dist: KL-Divergence = 0.0419, L1-Distance = 0.0196, L2-Distance = 0.0005, Normal std = 0.5936

0.672 Kernel fit Pairwise Correlations Normal fit

Density 0.336

0.000 CEM 1

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

Pre-normalization Quantiles

quiescentquiescent satellitequiescent satellite cell_adultactivated satellite cell_adult muscle_rep1activated satellite cell_adult muscle_rep2activated satellite cell_adult (0.124338) muscle_rep3activated satellite cell_adult (0.085065) regeneratingactivated satellite cell_adult (0.0640332) regeneratingactivated satellite cell_1wk mdx regeneratingactivated muscle_rep1satellite cell_1wk mdxoldactivated growing muscle_rep2satellite cell_1wk mdxoldactivated (0.044547) growing muscle_rep3 satellite muscle_rep1cell_cultured old (0.0316789) growing satellite muscle_rep2cell_cultured (0.0373885) (0.0115539) 3days_rep1 muscle_rep3cell_cultured (0.00624195) 3days_rep2 (0.173982)[ (0.0268949) 3days_rep3min (0.27965) ] (0.114627) [ medium ] [ max ] CEM 1 Med14 545.4 1711.5 3013.7 P ( S | Z, I ) = 1.00 Med21 188.8 587.5 981.6 Mean Corr = 0.81931 Med6 181.8 250.6 428.0 Cdk8 1565.5 2379.3 4529.1 Ccnc 61.4 131.1 219.9 Med10 1626.7 1920.7 2650.1 Med23 612.1 813.6 1088.6 Prpf40a 290.6 460.3 1143.0 Rbm12 1256.5 2245.7 3016.0 0610009D07Rik 1193.8 2160.1 3015.9 Srsf10 458.3 701.9 1009.0 Ccdc58 265.2 741.5 2125.2 CEM 1 + Pfdn4 655.6 1273.8 3424.3 Top 10 Genes Pno1 883.9 1636.4 5047.9 Orc6 519.6 1002.2 2783.3 Abce1 1378.4 2156.1 6197.2 Magoh 3083.8 3894.0 7164.0

Null module GEO Series "GSE7275" 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=GSE7275 Status: Public on Sep 05 2007 Title: Evaluation of murine mast cells derived exosomal RNA versus their parental cells MC/9. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17486113 Summary & Design: Summary: Exosomes are vesicles of endocytic origin released by many types of cells into the extracellular environment. In an attempt to further examine the exosome-mediated cellular communication, we show that exosomes from a mouse mast cell line (MC/9), exosomes from primary bone marrow derived mast cells, and exosomes from a human mast cell line (HMC-1) contain RNA but not DNA.

Microarray assessments of exosome-derived RNA revealed that these vesicles contain mRNA from approximately 1200 genes, many of which are unique and not present in the cytoplasmic RNA pool in the donor cell.

Keywords: Exosomal RNA versus their parental cells, MC/9

Overall design: Exosomes were prepared from the supernatant of MC/9 cells by differential centrifugations and filtration. RNA was isolated from the exosomes and their parental cells using Trizo. The microarray experiments were performed by SweGene (www.swegene.org/) according to Affymetrix microarray DNA chip analysis. The experiment was performed in quadruple samples. ExoRNA1, ExoRNA2, ExoRNA3, and ExoRNA4 for the exosomes samples and Mast_cells1, Mast_cells2, Mast_cells3, and Mast_cells4 for the MC/9 cells.

Background corr dist: KL-Divergence = 0.0228, L1-Distance = 0.0688, L2-Distance = 0.0086, Normal std = 0.8711

0.458 Kernel fit Pairwise Correlations Normal fit

Density 0.229

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

ExosomalExosomal RNA,Exosomal biological RNA,Exosomal biological RNA, rep1Mast biological(0.153066) RNA, rep2 cellsMast biological(0.086081) RNA, rep3 cellsMast biological(0.132357) RNA, rep4 cellsMast biological(0.133295) RNA, rep1 cells biological(0.0756729) RNA, rep2 biological(0.0574909) rep3 (0.153471) rep4[ (0.208566)min ] [ medium ] [ max ] CEM 1 Med14 139.8 1189.3 2271.0 P ( S | Z, I ) = 1.00 Med21 100.2 1575.9 2379.8 Mean Corr = 0.81093 Med6 25.8 304.6 451.2 Cdk8 682.7 1875.3 2410.9 Ccnc 12.1 346.0 464.0 Med10 330.5 2882.5 4571.9 Med23 37.0 632.5 929.8 Prpf40a 277.5 831.9 889.7 Rbm12 257.3 1525.0 2818.3 0610009D07Rik 56.7 4794.5 8725.2 Srsf10 86.8 804.4 1536.9 Ccdc58 386.3 1166.1 1505.4 CEM 1 + Pfdn4 38.0 1353.1 1921.1 Top 10 Genes Pno1 31.1 1427.5 1835.7 Orc6 115.5 1554.9 2124.5 Abce1 207.9 1262.1 1857.9 Magoh 35.6 6320.9 10091.8

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

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

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

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

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

0.806 Kernel fit Pairwise Correlations Normal fit

Density 0.403

0.000 CEM 1

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

Pre-normalization Quantiles

wild-typewild-type vehiclewild-type vehicleanimalAtf6a-/- vehicle1animal (34h) Atf6a-/-vehicle (0.0797983)2animal (34h) Atf6a-/-vehicleanimal (0.0450097)3 (34h) wild-typevehicle1animal (34h)(0.0223032) wild-type(0.0182142)2animal (34h)TM animal wild-type(0.0431016)3 (34h)TM 1animal Atf6a-/-(34h)(0.0369673) TM (0.0796135)2animal Atf6a-/-(34h)TM animal (0.0670872)3 Atf6a-/-(34h)TM 1animal (34h)(0.0353223) TM (0.179801)2animal (34h) (0.241434)3 (34h) (0.151347)[ min ] [ medium ] [ max ] CEM 1 Med14 403.9 462.9 674.6 P ( S | Z, I ) = 1.00 Med21 445.2 519.2 1053.2 Mean Corr = 0.72816 Med6 119.0 142.5 172.9 Cdk8 1225.3 1527.6 2005.5 Ccnc 110.8 134.7 197.0 Med10 1472.6 1658.0 4216.2 Med23 201.2 269.7 420.8 Prpf40a 158.1 203.4 299.6 Rbm12 111.5 152.0 274.4 0610009D07Rik 2078.3 2440.6 5713.5 Srsf10 166.1 247.4 472.1 Ccdc58 1092.2 1282.2 1709.1 CEM 1 + Pfdn4 472.7 563.2 1128.2 Top 10 Genes Pno1 968.0 1366.1 4102.8 Orc6 128.3 192.8 240.4 Abce1 970.0 1480.4 2956.4 Magoh 1394.7 1933.1 5373.3

Null module GEO Series "GSE47694" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 10 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE47694 Status: Public on Jul 01 2013 Title: Regulation of Mouse Lens Development and Gene Expression by KrÃ¼ppel-Like Factor 4 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Conditional disruption of Klf4 in the ectoderm-derived tissues of the eye results in defective cornea, conjunctiva and the lens.

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

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

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

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

0.605 Kernel fit Pairwise Correlations Normal fit

Density 0.303

0.000 CEM 1

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

Pre-normalization Quantiles

E16.5_WT_sample_1E16.5_WT_sample_2E16.5_WT_sample_3 (0.129787)E16.5_Klf4CN_sample_1 (0.0519895)E16.5_Klf4CN_sample_2 (0.063322)E16.5_Klf4CN_sample_3PN56_WT_sample_1 (0.0792505)PN56_WT_sample_2 (0.0683098)PN56_Klf4CN_sample_1 (0.0509204) (0.205658)PN56_Klf4CN_sample_2 (0.108847) (0.137698) (0.104218)[ min ] [ medium ] [ max ] CEM 1 Med14 636.5 1171.1 1426.4 P ( S | Z, I ) = 1.00 Med21 1242.9 3455.7 4336.8 Mean Corr = 0.72815 Med6 205.1 708.4 937.8 Cdk8 1040.2 2740.9 3182.2 Ccnc 96.4 214.6 273.0 Med10 3226.2 4008.2 5097.0 Med23 324.7 451.0 545.2 Prpf40a 441.4 716.8 770.8 Rbm12 382.1 1090.5 1182.6 0610009D07Rik 3639.2 6460.3 7244.4 Srsf10 607.4 1283.3 1376.3 Ccdc58 750.9 1373.4 1670.1 CEM 1 + Pfdn4 523.9 1234.8 1503.4 Top 10 Genes Pno1 2137.0 2647.3 3119.8 Orc6 415.0 560.5 695.5 Abce1 897.7 1912.6 2154.8 Magoh 1490.8 5250.3 6818.3

Null module GEO Series "GSE49237" 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=GSE49237 Status: Public on Dec 31 2013 Title: Analysis of TBR1 downnstream target genes in embryonic forebrains Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24441682 Summary & Design: Summary: TBR1 is a forebrain specific T-box transcription factor. Tbr1-/- mice have been characterized by defective axonal projections from cerebral cortex and abnormal neuronal migration of cerebral cortex and amygdala.

To investigate how TBR1 regulates neural development, the gene expression profile of Tbr1-/- brains was compared with WT littermates.

Overall design: Total RNAs purified from forebrains at embryonic day 16.5 were hybridized on Affymetrix microarrays

Background corr dist: KL-Divergence = 0.0472, L1-Distance = 0.0231, L2-Distance = 0.0006, Normal std = 0.5812

0.697 Kernel fit Pairwise Correlations Normal fit

Density 0.349

0.000 CEM 1

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

Pre-normalization Quantiles

WT #1 (0.0691965)WT#2 (0.034766)WT#3 (0.0506321)WT#4 (0.133776)Tbr1-/-#1Tbr1-/-#2 (0.155471)Tbr1-/-#3 (0.0425807)Tbr1-/-#4 (0.0222928) (0.491285) [ min ] [ medium ] [ max ] CEM 1 Med14 686.7 811.2 1326.5 P ( S | Z, I ) = 1.00 Med21 327.2 490.4 727.5 Mean Corr = 0.72149 Med6 196.1 274.7 514.0 Cdk8 967.4 1374.5 1816.3 Ccnc 98.0 210.1 275.4 Med10 2205.5 2429.9 2913.3 Med23 1010.8 1081.8 1306.9 Prpf40a 348.8 468.6 759.6 Rbm12 994.0 1187.7 1554.0 0610009D07Rik 2740.0 3566.9 5221.2 Srsf10 559.0 743.8 962.9 Ccdc58 364.7 436.4 522.1 CEM 1 + Pfdn4 2716.7 3476.0 4249.5 Top 10 Genes Pno1 607.8 964.8 1092.2 Orc6 894.6 977.2 1349.6 Abce1 581.6 1000.2 1151.4 Magoh 3800.6 4036.6 5187.6

Null module GEO Series "GSE50813" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50813 Status: Public on Dec 31 2013 Title: Prevention of mammary tumor progression by silencing HoxA1 via intraductal injection of nanoparticle-formulated siRNA Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24382894 Summary & Design: Summary: Silencing HoxA1 in vivo by intraductal delivery of nanoparticle-formulated siRNA reduced mammary tumor incidence by 75% , reduced cell proliferation, and prevented loss of ER and PR expression.

Overall design: 8 week wild type FVB mouse whole mammary gland and 8week to 20 week transgenic FVB C3(1)-SV40Tag mouse whole mammary gland

Background corr dist: KL-Divergence = 0.1026, L1-Distance = 0.0245, L2-Distance = 0.0008, Normal std = 0.4380

0.911 Kernel fit Pairwise Correlations Normal fit

Density 0.455

0.000 CEM 1

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

Pre-normalization Quantiles

8 weeks8 wildweeks type8 wildweeks Mammary33 type8 wildweeks Mammary34 type8 wild(0.00835009)weeks Mammary35 type8 wild(0.0116767)weeks Mammary36 type8 tumor(0.0659836)weeks Mammary37 8Mammary1 tumor(0.015239)weeks 8Mammary2 tumor(0.012554)weeks (0.0344641) 8Mammary3 tumorweeks (0.00481327) 12Mammary4 tumor weeks (0.0113324) 12Mammary5 tumorweeks (0.0229968)12 Mammary6 tumorweeks (0.0137052)12 Mammary7 tumorweeks (0.00559551)12 Mammary8 tumorweeks (0.00818076)16 Mammary9 tumorweeks (0.00562167)16 Mammary10 tumorweeks (0.0111977)16 Mammary11 tumorweeks (0.0103372)16 Mammary13 tumorweeks (0.013619)16 Mammary14 tumorweeks (0.0061262)20 Mammary15 tumorweeks (0.0107143)20 Mammary32 tumorweeks (0.0121981)20 Mammary22 tumorweeks (0.0123788)20 Mammary23 tumorweeks (0.0986603) Mammary24 tumor (0.0628761) Mammary31 (0.34596) (0.195419)[ min ] [ medium ] [ max ] CEM 1 Med14 734.1 1301.0 4030.6 P ( S | Z, I ) = 1.00 Med21 769.0 945.4 15224.9 Mean Corr = 0.70090 Med6 207.8 334.0 797.8 Cdk8 1138.8 1497.4 2613.5 Ccnc 88.1 123.0 195.5 Med10 1893.9 2208.7 3324.3 Med23 356.0 479.4 671.9 Prpf40a 325.3 423.0 821.2 Rbm12 398.8 673.1 1598.4 0610009D07Rik 3124.0 3943.5 6809.3 Srsf10 508.3 917.0 1603.9 Ccdc58 513.5 636.0 1017.7 CEM 1 + Pfdn4 870.5 1059.1 2541.0 Top 10 Genes Pno1 1515.7 1900.0 2205.8 Orc6 339.9 527.6 1878.4 Abce1 723.7 1103.6 1506.0 Magoh 2460.3 4133.4 8578.1

Null module GEO Series "GSE21836" 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=GSE21836 Status: Public on May 15 2010 Title: Tob1 is a Constitutively Expressed Repressor of Liver Regeneration Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20513747 Summary & Design: Summary: How proliferative and inhibitory cell signals integrate to control liver regeneration remains poorly understood. A screen for antiproliferative factors repressed after liver injury identified Tob1, a member of the PC3/BTG1 family of mitoinhibitory molecules as a target for further evaluation. Tob1 protein decreases after 2/3 hepatectomy in mice secondary to post-transcriptional mechanisms. Deletion of Tob1 increases hepatocyte proliferation and accelerates restoration of liver mass after hepatectomy. Down-regulation of Tob1 is required for normal liver regeneration and Tob1 controls hepatocyte proliferation in a dose-dependent fashion. Tob1 associates directly with both Caf1 and the Cyclin/cdk complex to modulate kinase activity. In addition, Tob1 has significant effects on the transcription of critical cell cycle components, including E2F targets and genes involved in p53 signaling. These studies provide direct evidence that levels of an inhibitory factor control the rate of liver regeneration. Our data identify Tob1 as a crucial check-point molecule that acts by by modulating levels and activity of cell cycle proteins.

Overall design: Samples from wild type and Tob1 null mice as normal adults and 24 hours after 2/3 hepatectomy are used. Each experimental point used data from two chips, each having a different set of three pooled animals. In summary we had 8 chips: 2 for WT time 0, 2 for WT time 24, 2 for KO time 0, 2 for KO time 24.

Background corr dist: KL-Divergence = 0.0565, L1-Distance = 0.0213, L2-Distance = 0.0005, Normal std = 0.5474

0.737 Kernel fit Pairwise Correlations Normal fit

Density 0.368

0.000 CEM 1

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

Pre-normalization Quantiles

Liver_normal_0hr_rep1Liver_normal_0hr_rep2Liver_normal_24hr_rep1Liver_normal_24hr_rep2 (0.140254)Liver_Tob1KO_0hr_rep1 (0.0513315)Liver_Tob1KO_0hr_rep2 (0.144782)Liver_Tob1KO_24hr_rep1 (0.0132302)Liver_Tob1KO_24hr_rep2 (0.116591) (0.0816535) (0.248402) (0.203755)[ min ] [ medium ] [ max ] CEM 1 Med14 668.2 801.0 1164.0 P ( S | Z, I ) = 1.00 Med21 743.4 1092.2 1377.2 Mean Corr = 0.69919 Med6 467.9 553.5 719.0 Cdk8 1484.2 1637.2 2159.0 Ccnc 538.6 645.9 717.4 Med10 1077.8 1598.5 2100.3 Med23 292.6 331.2 398.1 Prpf40a 398.4 616.1 708.9 Rbm12 261.3 297.4 356.3 0610009D07Rik 2407.5 3082.3 4338.1 Srsf10 543.6 784.2 1043.5 Ccdc58 1882.5 2265.0 2594.9 CEM 1 + Pfdn4 672.9 1030.3 1696.4 Top 10 Genes Pno1 2006.3 3618.8 4122.0 Orc6 164.5 281.7 702.9 Abce1 1103.0 1699.7 2165.9 Magoh 1855.4 2351.6 3511.2

Null module GEO Series "GSE42601" 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=GSE42601 Status: Public on Jun 01 2013 Title: Expression data from wild-type and Dazap1 mutant mouse testes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23965306 Summary & Design: Summary: Deleted in Azoospermia Associated Protein 1 (DAZAP1) is a ubiquitous RNA-binding protein that is highly expressed in the testis. It is a component of the hnRNP particles and shuttles between the nucleus and the cytoplasm. Mice expressing the DAZAP1-Fn mutant protein manifest both growth retardation and spermatogenic arrest before meiosis I. To elucidate the biological function(s) of DAZAP1 and to search for its natural RNA substrates, we compared the expression profiles of wild-type and Dazap1 mutant testes by cDNA microarrays.

Overall design: We used wild-type and Dazap1 mutant mouse testes. Each genotype has three replicates. 6 total samples were analyzed.

Background corr dist: KL-Divergence = 0.0070, L1-Distance = 0.0271, L2-Distance = 0.0008, Normal std = 0.9770

0.430 Kernel fit Pairwise Correlations Normal fit

Density 0.215

0.000 CEM 1

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

Pre-normalization Quantiles

Wild-typeMutant testes Wild-typetestes at P21, atMutant P21,biological testes biological Wild-typetestes at P21,rep1 atMutant P21,biological rep1(0.142697)testes biological(0.168165)testes at P21,rep2 at P21,biologicalrep2(0.217306) biological(0.165619) rep3[ rep3(0.156697)min (0.149515) ] [ medium ] [ max ] CEM 1 Med14 129.7 283.3 345.4 P ( S | Z, I ) = 1.00 Med21 1273.1 2063.8 2460.0 Mean Corr = 0.73542 Med6 408.5 811.3 907.8 Cdk8 1867.9 2087.7 2154.9 Ccnc 93.0 114.6 134.2 Med10 6846.3 8532.5 10037.9 Med23 1353.3 1554.2 1621.8 Prpf40a 762.1 1108.6 1189.0 Rbm12 1107.8 1656.2 2108.9 0610009D07Rik 2070.9 3379.8 3387.3 Srsf10 1065.6 1582.1 1809.8 Ccdc58 1148.3 1361.4 1534.9 CEM 1 + Pfdn4 2115.0 2342.0 2587.2 Top 10 Genes Pno1 2079.5 2601.3 2866.2 Orc6 775.8 1386.5 1446.6 Abce1 797.4 1181.9 1409.4 Magoh 3992.8 6679.8 7154.8

Null module GEO Series "GSE12993" 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=GSE12993 Status: Public on Jul 31 2009 Title: C2C12 culture: myogenesis timecourse and shRp58 treatment Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: To predict Rp58-regulated gene involved in myogenesis, RNA profiling experiments were performed, comparing RNA derived from C2C12 with or without expressing shRNA for Rp58. As a result, 271 genes were upregulated in C2C12 stably expressing shRNA-Rp58 cells compared with control C2C12 cells. As Rp58 is repressor in C2C12, we hypothesized that Rp58 regulates gene cluster which expression is downregulated in accordance with Rp58 expression and myogenesis progression. In this regard, we also characterized dynamic gene expression patterns during myogenesis by microarray at 4 different stage (GM, day 0, 2, 4) of C2C12 myogenesis assays and found that 399 genes expression is characterized as downregulation pattern during myogenesis. Importantly, this down regulation gene set and upregulated genes by shRNA for Rp58 were highly overlapped.

Keywords: time course, shRNA

Overall design: MAPPFinder (www.genmapp.org) was used to integrate expression data with known pathways.

Background corr dist: KL-Divergence = 0.0165, L1-Distance = 0.0127, L2-Distance = 0.0002, Normal std = 0.7749

0.515 Kernel fit Pairwise Correlations Normal fit

Density 0.257

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-GMC2C12-day0 (0.438878)C2C12-day2 (0.107752)C2C12-day4 (0.0343026)C2C12-control-day0 (0.133929)C2C12-shRp58-day0 (0.161831) (0.123308)[ min ] [ medium ] [ max ] CEM 1 Med14 744.3 1009.9 1386.5 P ( S | Z, I ) = 1.00 Med21 971.7 1354.6 1764.3 Mean Corr = 0.71024 Med6 625.3 888.6 1175.6 Cdk8 869.7 1136.3 1520.0 Ccnc 209.2 267.8 391.7 Med10 2063.7 2431.6 3010.0 Med23 655.7 771.8 830.6 Prpf40a 481.8 516.3 756.3 Rbm12 757.6 817.6 1160.6 0610009D07Rik 3145.1 3785.4 4238.7 Srsf10 374.6 418.0 737.3 Ccdc58 652.6 870.4 1432.8 CEM 1 + Pfdn4 1262.3 2208.1 2853.1 Top 10 Genes Pno1 1925.2 2193.0 3529.7 Orc6 611.9 829.6 1759.8 Abce1 1250.3 1510.5 2318.8 Magoh 2596.0 2924.0 5247.5

Null module GEO Series "GSE24243" 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=GSE24243 Status: Public on May 09 2011 Title: Murine skin gene expression analysis of skin-specific Scd1-deficient and control mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21573029 Summary & Design: Summary: To help elucidate the metabolic changes in the skin that contribute to the obesity resistance and skin pathology in mice lacking Scd1, we performed microarray analysis of skin gene expression in male skin Scd1 knockout (SKO) and Scd1 flox/flox control (Lox) mice fed a standard rodent diet.

We identified an extraordinary number of differentially expressed genes that support the previously documented histological observations of sebocyte atrophy, inflammation and epidermal hyperplasia in SKO mice. Additionally, transcript levels were reduced in skin of SKO mice for genes involved in fatty acid synthesis, elongation and desaturation, which may be attributed to decreased abundance of key transcription factors including SREBP1c, ChREBP and LXRÎ±. Conversely, genes involved in cholesterol synthesis were increased, suggesting an imbalance between skin fatty acid and cholesterol synthesis. Unexpectedly, we observed a robust elevation in skin retinol, retinoic acid and retinoic acid-induced genes in SKO mice. These results highlight the importance of monounsaturated fatty acid synthesis for maintaining retinol homeostasis and point to disturbed retinol metabolism as a novel contributor to the Scd1 deficiency-induced skin pathology.

Overall design: We analyzed dorsal skin gene expression in non-fasted 8-9 week old male skin Scd1 knockout (SKO) mice (n=3) and Scd1flox/flox (Lox) control mice (n=3)on a C57BL/6J background using Affymetrix 430 2.0 microarrays.

Background corr dist: KL-Divergence = 0.0198, L1-Distance = 0.0107, L2-Distance = 0.0001, Normal std = 0.7416

0.538 Kernel fit Pairwise Correlations Normal fit

Density 0.269

0.000 CEM 1

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

Pre-normalization Quantiles

Skin_Lox_Control_Rep1Skin_Lox_Control_Rep2Skin_Lox_Control_Rep3Skin_SKO_Rep1 (0.106736)Skin_SKO_Rep2 (0.455396)Skin_SKO_Rep3 (0.0945456)(0.0549529) (0.215577) (0.0727922) [ min ] [ medium ] [ max ] CEM 1 Med14 727.6 1065.3 1134.6 P ( S | Z, I ) = 1.00 Med21 136.6 297.0 366.2 Mean Corr = 0.68613 Med6 46.9 60.6 71.4 Cdk8 154.7 403.7 469.3 Ccnc 22.9 44.6 51.4 Med10 1198.5 2056.7 2151.9 Med23 418.2 527.5 574.2 Prpf40a 96.5 147.9 209.7 Rbm12 329.2 623.4 738.0 0610009D07Rik 1600.1 2481.5 2802.3 Srsf10 145.3 312.4 361.4 Ccdc58 141.4 221.1 270.9 CEM 1 + Pfdn4 192.3 416.5 482.5 Top 10 Genes Pno1 179.4 273.6 412.3 Orc6 105.3 221.0 240.9 Abce1 118.5 210.4 345.5 Magoh 1390.1 2307.8 2701.2

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 (0.277547)C57BL/6JE16.5 (0.164117)C57BL/6JE17.5 (0.109467)C57BL/6JE18.5 (0.0208924)C57BL/6JADULT (0.0308872) (0.0671654) COLON (0.329924)[ min ] [ medium ] [ max ] CEM 1 Med14 420.9 531.0 832.8 P ( S | Z, I ) = 1.00 Med21 1564.3 1926.8 2467.4 Mean Corr = 0.65300 Med6 775.4 931.7 1763.9 Cdk8 2395.6 3815.5 4859.9 Ccnc 246.0 289.8 348.4 Med10 1448.2 2302.9 2649.5 Med23 316.3 374.7 578.9 Prpf40a 75.8 84.1 137.7 Rbm12 482.5 1044.4 1545.8 0610009D07Rik 1296.2 1846.8 2637.3 Srsf10 326.0 426.8 639.2 Ccdc58 1409.0 1991.6 2217.2 CEM 1 + Pfdn4 428.4 659.3 1024.2 Top 10 Genes Pno1 314.4 338.5 555.9 Orc6 418.7 1404.8 2169.6 Abce1 2965.1 6672.8 8624.6 Magoh 1045.1 2654.9 3645.1

Null module GEO Series "GSE29458" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 23 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29458 Status: Public on May 23 2011 Title: Expression data from PDGF driven mouse tumors Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21625383 Summary & Design: Summary: Background

Tumor heterogeneity is a major obstacle for finding effective treatment of Glioblastoma (GBM). Based on global expression analysis, GBM can be classified into distinct subtypes: Proneural, Neural, Classical and Mesenchymal. The signatures of these different tumor subtypes may reflect the phenotypes of cells giving rise to them.

However, the experimental evidence connecting any specific subtype of GBM to particular cells of origin is lacking. In addition, it is unclear how different genetic alterations interact with cells of origin in determining tumor heterogeneity. This issue cannot be addressed by studying end-stage human tumors.

Methodology/Principal Findings

To address this issue, we used retroviruses to deliver transforming genetic lesions to glial progenitors in adult mouse brain. We compared the resulting tumors to human GBM. We found that different initiating genetic lesions gave rise to tumors with different growth rates.

However all mouse tumors closely resembled the human Proneural GBM.

Comparative analysis of these mouse tumors allowed us to identify a set of genes whose expression in humans with Proneural GBM correlates with survival.

Conclusions/Significance

This study offers insights into the relationship between adult glial progenitors and Proneural GBM, and allows us to identify molecular alterations that lead to more aggressive tumor growth. In addition, we present a new preclinical model that can be used to test treatments directed at a specific type of GBM in future studies.

Overall design: Gene expression profiling was performed on 20 tumors (12 Ptenf/f and 8 Ptenf/f; p53f/f) and 3 normal brains from mice. End stage tumors were used for expression array analysis. The platform used was Affymetrix GeneChip Mouse Genome 430A 2.0 Array. The microarray labeling, hybridization and quality controls were performed by following Affymetrix protocol.

Background corr dist: KL-Divergence = 0.0721, L1-Distance = 0.0373, L2-Distance = 0.0027, Normal std = 0.4903

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

Tumor inTumor Ptenf/f inTumor micePtenf/f in(1ptenTumor micePtenf/f 1)in(1ptenTumor (0.0278153)micePtenf/f 2)in(1ptenTumor (0.0118231)micePtenf/f 3)in(1ptenTumor (0.0114304)micePtenf/f 4)in(1ptenTumor (0.00989067)micePtenf/f; 5)in(1ptenTumor (0.0367733) Ptenf/f;p53f/f 6)inTumor mice (0.0263018) Ptenf/f;p53f/f (1ptenp53inTumor mice Ptenf/f;p53f/f (1ptenp53inTumor mice Ptenf/f;7)p53f/f (0.0622163) (1ptenp53inTumor mice Ptenf/f8)p53f/f (0.0474197) (1ptenp53inTumor mice micePtenf/f9) (0.0302135) (1ptenp53in(2ptenTumor micePtenf/f10) (0.0516985) 5F)in(2ptenTumor micePtenf/f11) (0.0324389) (0.07304) F7)in(2ptenTumor micePtenf/f (0.0131513) F9)in(2ptenTumor micePtenf/f (0.0558435) JM3)in(2ptenTumor micePtenf/f; (0.0283862) M11)in(2ptenTumor Ptenf/f;p53f/f (0.0320352) YFP1)inNormal mice Ptenf/f;p53f/f (0.0438823) (2ptenp53 Normalbrain mice p53f/f (2NB1F)(2ptenp53 Normalbrain mice F1S) (2NB2F)(2ptenp53 (0.0918414)(0.0237628)brain M1) (2NB3F)(0.0543689) (0.074084) R3F) (0.128132)(0.0334509)[ min ] [ medium ] [ max ] CEM 1 Med14 369.8 1637.4 2619.7 P ( S | Z, I ) = 1.00 Med21 572.2 1091.2 1412.6 Mean Corr = 0.67908 Med6 220.3 377.6 641.0 Cdk8 548.1 1262.4 2147.5 Ccnc 118.3 342.5 535.4 Med10 884.0 1660.9 2083.3 Med23 324.8 540.9 729.4 Prpf40a 287.0 686.1 934.5 Rbm12 1380.4 2323.7 2978.4 0610009D07Rik 782.2 1360.0 1962.9 Srsf10 136.7 400.8 624.9 Ccdc58 956.3 2285.9 2797.7 CEM 1 + Pfdn4 842.9 1426.5 1857.1 Top 10 Genes Pno1 124.8 511.6 862.4 Orc6 775.2 1859.1 2836.4 Abce1 700.8 1855.2 2271.5 Magoh 497.6 1324.9 2037.7

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

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

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

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

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

0.862 Kernel fit Pairwise Correlations Normal fit

Density 0.431

0.000 CEM 1

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

Pre-normalization Quantiles

FlutamideFlutamide treatedFlutamide treatedmaleVehicule at treatedmaleGD 17,Vehicule at (control) malebiologicalGD 17,Vehicule at (control) biologicalfemaleGD rep1 17,Vehicule (control) at biologicalfemale(0.0136578) GD rep2Vehicule (control)17, at female(0.0354166) biologicalGD rep3Vehicule (control)17, at male(0.0222059) biologicalGDFlutamide rep1 at(control)17, maleGD biological(0.0967024) Flutamide17, rep2at treated malebiologicalGD (0.0536183) Flutamide17, rep3at treated malebiologicalGD (0.0859931)rep1 Vehicule17, at treatedmaleGD biological(0.0872246) rep2 18,Vehicule at (control) malebiologicalGD (0.0381503) rep3 18,Vehicule at (control) biologicalfemaleGD (0.0220091) rep1 18,Vehicule (control) at biologicalfemale(0.0654324) GD rep2Vehicule (control)18, at female(0.0319502) biologicalGD rep3Vehicule (control)18, at male(0.0518303) biologicalGD rep1 at(control)18, maleGD biological(0.111919) 18, rep2at malebiologicalGD (0.0531784) 18, rep3at biologicalGD (0.0521969)rep1 [18, min biological(0.00122681) rep2 (0.0426463)] rep3 (0.134641)[ medium ] [ max ] CEM 1 Med14 888.8 1201.3 1364.4 P ( S | Z, I ) = 1.00 Med21 593.0 778.5 926.5 Mean Corr = 0.64273 Med6 610.5 788.8 894.7 Cdk8 856.2 1057.5 1357.9 Ccnc 102.5 140.7 181.6 Med10 1298.9 1536.0 1772.7 Med23 561.4 778.5 879.2 Prpf40a 359.1 580.8 731.2 Rbm12 971.5 1714.0 1960.4 0610009D07Rik 3232.1 4431.3 5288.8 Srsf10 702.2 1147.9 1370.3 Ccdc58 662.5 897.8 1152.6 CEM 1 + Pfdn4 914.8 1274.9 1569.5 Top 10 Genes Pno1 582.9 1404.2 1798.4 Orc6 463.8 786.4 963.8 Abce1 824.3 1397.3 1735.5 Magoh 3235.5 5351.6 5693.0

Null module GEO Series "GSE44175" 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=GSE44175 Status: Public on Feb 09 2013 Title: Expression data from mouse embyonic stem cell, neural progenitor and neuron Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23775126 Summary & Design: Summary: The effect of HMGN1 protein on gene expression of mouse ESC, NP and Neurons were investigated by comparing the transcriptome between Hmgn1+/+ and Hmgn1 -/- cells.

Overall design: three cell types, two genotypes, three reps per sample type

Background corr dist: KL-Divergence = 0.0123, L1-Distance = 0.0320, L2-Distance = 0.0019, Normal std = 0.8462

0.471 Kernel fit Pairwise Correlations Normal fit

Density 0.236

0.000 CEM 1

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

Pre-normalization Quantiles

EmbyonicEmbyonic stemEmbyonic cell, stem Hmgn1+/+,Neural cell, stem Hmgn1+/+, progenitor,Neural cell, biological Hmgn1+/+, progenitor,Neural biological Hmgn1+/+, rep1 progenitor,Neuron, biological (0.0310348) Hmgn1+/+, rep2Neuron, biological Hmgn1+/+, (0.0362588) Hmgn1+/+, rep3Neuron, biological Hmgn1+/+, (0.0219556)rep1 biologicalEmbyonic biological(0.0286081)Hmgn1+/+, rep2 biologicalEmbyonic rep1(0.0191282) stem rep3 biological(0.0974747)Embyonic rep2cell,(0.0361391) stem (0.0847545)Hmgn1-/-,Neural rep3cell, stem (0.0663268)Hmgn1-/-, progenitor,Neural cell, biological Hmgn1-/-, progenitor,Neural biological Hmgn1-/-,rep1 progenitor,Neuron, biological(0.0493603) Hmgn1-/-,rep2 biologicalNeuron, Hmgn1-/-, (0.0800928) Hmgn1-/-,rep3 biologicalNeuron, Hmgn1-/-, (0.0697805)rep1 biological biological(0.0359683) Hmgn1-/-, rep2 biological rep1(0.0437259) rep3 biological(0.111415) rep2(0.0432737) (0.0777935) rep3[ min (0.0669098) ] [ medium ] [ max ] CEM 1 Med14 1049.6 2208.7 2585.8 P ( S | Z, I ) = 1.00 Med21 701.5 1007.0 1101.6 Mean Corr = 0.62114 Med6 297.4 760.4 1336.7 Cdk8 2836.5 3961.6 4416.0 Ccnc 133.7 230.3 271.3 Med10 2176.2 2737.0 4035.0 Med23 675.0 725.3 753.9 Prpf40a 634.2 1155.8 1604.5 Rbm12 768.9 2245.0 3036.1 0610009D07Rik 5533.4 6182.4 6423.8 Srsf10 673.7 1354.4 1577.5 Ccdc58 711.7 1740.5 4078.4 CEM 1 + Pfdn4 2822.1 3675.5 4220.2 Top 10 Genes Pno1 594.6 3367.8 5643.4 Orc6 829.4 2251.9 3201.3 Abce1 1009.3 2293.7 4130.9 Magoh 4507.5 8765.0 9994.6

Null module GEO Series "GSE58368" 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=GSE58368 Status: Public on Jun 11 2014 Title: Linking Notch signaling to ischemic stroke Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Using a hitherto uncharacterized knockout mouse model of Notch 3, a Notch signaling receptor paralogue highly expressed in vascular SMCs, we uncover a striking susceptibility to ischemic stroke upon challenge. Cellular and molecular analyses of vascular SMCs derived from these animals associate Notch 3 activity to the expression of specific gene targets, whereas genetic rescue experiments unambiguously link Notch 3 function in vessels to the ischemic phenotype.

Overall design: Microarray Studies. Biotinylated cRNA samples from freshly sorted brain SMCs (four Notch 3 +/ mice and five Notch 3 / mice) were fragmented before hybridization (15 Î¼g each) onto mouse 430 2.0 Affymetrix chips. The chips were washed, stained by using strepavidin-phycoerytrin, and scanned the next day as described in ref. 24. For data normalization, all probe sets were scaled to a target intensity of 150. Microarray data analysis was performed by using Rosetta Resolver. All cells were from 10- to 12-week-old male mice. Gene Ontology Analyses. PANTHER software was used to define over- and underrepresented functions in the list of signature genes found by microarray analysis (25). P values were calculated by using binomial statistics.

Background corr dist: KL-Divergence = 0.0540, L1-Distance = 0.0336, L2-Distance = 0.0015, Normal std = 0.5673

0.733 Kernel fit Pairwise Correlations Normal fit

Density 0.367

0.000 CEM 1

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

Pre-normalization Quantiles

E NOTCH3G NOTCH3 +/- (brain)I NOTCH3 +/- (0.0346414)(brain)H NOTCH3 +/- (brain) (0.0742561)A NOTCH3 +/- (0.0383965) (brain)B NOTCH3 -/- (brain)(0.0823709)C NOTCH3 -/- (0.0475863)(brain)D NOTCH3 -/- (0.0491028)(brain)F NOTCH3 -/- (0.0255118)(brain)5556 -/- NOTCH3 (0.0674923)(brain)5561 NOTCH3 (0.0601613) +/-6166 (aorta) NOTCH3 +/-5558 (0.0598244)(aorta) NOTCH3 +/-5559 (0.110795)(aorta) NOTCH3 -/-6167 (aorta)(0.0775343) NOTCH3 -/- (0.0982158)(aorta) -/- (0.0926967)(aorta) (0.081415)[ min ] [ medium ] [ max ] CEM 1 Med14 458.6 611.4 1355.8 P ( S | Z, I ) = 1.00 Med21 5.5 65.5 662.1 Mean Corr = 0.50393 Med6 98.5 196.1 512.4 Cdk8 524.2 945.6 1218.4 Ccnc 13.4 105.5 300.9 Med10 1485.7 1954.5 2315.5 Med23 347.6 504.2 833.8 Prpf40a 60.5 252.1 375.7 Rbm12 331.2 655.5 1137.5 0610009D07Rik 528.6 710.0 2044.3 Srsf10 129.8 341.4 635.6 Ccdc58 57.5 109.2 216.4 CEM 1 + Pfdn4 217.2 334.6 1232.0 Top 10 Genes Pno1 304.4 448.4 1110.3 Orc6 346.4 544.6 759.9 Abce1 172.7 458.2 1196.7 Magoh 275.9 553.3 1533.6

Null module GEO Series "GSE14406" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 54 -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=GSE14406 Status: Public on Jan 31 2009 Title: Oligodendroglial precursor cell line [Oli-neu] undergoing differentiation into myelin basic protein-producing cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19139271 Summary & Design: Summary: Inadequate remyelination of brain white matter lesions has been associated with a failure of oligodendrocyte precursors to differentiate into mature, myelin-producing cells. In order to better understand which genes play a specific role in oligodendrocyte differentiation we performed time dependent, genome-wide gene expression studies of mouse Oli-neu cells as they differentiate into myelin basic protein-producing cells, following treatment with three different agents. Our data indicate that different inducers activate distinct pathways that ultimately converge into the differentiated state where regulated gene sets overlap maximally.

In order to also gain insight into the functional role of genes that are regulated in this process, we silenced 88 of these genes using siRNA, and identified multiple repressors of spontaneous differentiation of Oli-neu, most of which were confirmed in rat primary oligodendrocyte precursors cells. Among these repressors were CNPase, a well-known myelin constituent, and three phosphatases, each known to negatively control MAP kinase cascades. We show that a novel inhibitor for one of the identified genes, dual-specificity phosphatase DUSP10/MKP5, was also capable of inducing oligodendrocyte differentiation in primary oligodendrocyte precursors. Oligodendrocytic differentiation feedback loops may therefore yield pharmacological targets to treat disease related to dysfunctional myelin deposition

Keywords: time course

Overall design: triplicates for 3 times points 10h, 24h, 72h in 6 conditions, Forskolin, Insulin, Dexamethasone, Retinoic Acid, PD174265, Untreated. Arrays were done in two distinct experiments 1 and 2. Some replicates are missing because of lab operating issues

Background corr dist: KL-Divergence = 0.3521, L1-Distance = 0.0454, L2-Distance = 0.0041, Normal std = 0.2629

1.518 Kernel fit Pairwise Correlations Normal fit

Density 0.759

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

DexamethasoneDexamethasoneDexamethasone at 10 h,Dexamethasone atbiol. 10 rep1h,Dexamethasone atbiol. 10in rep2Exp1h,Dexamethasone atbiol. 24in (0.00706203) rep3Exp1h,Dexamethasone atbiol. 24in (0.0128962) rep1Exp1h,Dexamethasone atbiol. 24in (0.00358745) rep2Exp1h,Dexamethasone atbiol. 72in (0.0119147) rep3Exp1h,Forskolin atbiol. 72in (0.0150073) rep1Exp1h,Forskolin at biol.at 72 in10(0.0188428) rep2Exp1h, Forskolinh, biol. atbiol. in10(0.0172916) rep3Exp1 Forskolinrep1h, atbiol. in 24(0.0252446)in Exp1 Forskolinrep2Exp2h, atbiol. 24(0.0153938)in (0.041424) Forskolinrep1Exp2h, atbiol. 72in (0.0480372) Forskolinrep2Exp2h, atbiol. 72in (0.0293179) Insulinrep1Exp2h, atbiol. 72in (0.0190063) atInsulinrep2Exp2h, 10 biol. h,in (0.0108601) atInsulinbiol.rep3Exp2 10 rep1h,in (0.0119033) atInsulinbiol.Exp2 24in rep2Exp2h, (0.0223445) atInsulinbiol. 24in (0.037692) rep1Exp2h, atInsulinbiol. 72in (0.0990011) rep2Exp2h, atPD174265biol. 72in (0.0454559) rep1Exp2h, PD174265biol. in at(0.0242463) rep2Exp210PD174265 h, in at(0.0102838)biol. Exp210PD174265 rep1h, at(0.00579828)biol. 10inPD174265 rep2Exp1h, atbiol. 24in (0.0155306)PD174265 rep3Exp1h, atbiol. 24in (0.0122977)PD174265 rep1Exp1h, atbiol. 24in (0.0209196)PD174265 rep2Exp1h, atbiol. 72in (0.0135337)PD174265 rep3Exp1h, atbiol. 72in (0.0103165)RetinoicAcid rep1Exp1h, atbiol. 72in (0.0139712)RetinoicAcid rep2Exp1h, biol. inat (0.0131422)RetinoicAcid rep3Exp110 h, inatbiol.(0.0173057)RetinoicAcid Exp110 rep1h, atbiol.(0.0156609)RetinoicAcid 10in rep2Exp1h, atbiol.RetinoicAcid 24in (0.0056193) rep3Exp1h, atbiol.RetinoicAcid 24in (0.0102821) rep1Exp1h, atbiol.RetinoicAcid 24in (0.00733242) rep2Exp1h, atbiol.RetinoicAcid 72in (0.0108661) rep3Exp1h, atbiol.Untreated 72in (0.00458876) rep1Exp1h, atbiol.Untreated 72in (0.0111928) at rep2Exp1h, 10 biol.Untreated h,in (0.0134334) at biol.rep3Exp1 10Untreated rep1 h,in (0.0175283) at biol.Exp1 10inUntreated rep2Exp1h, (0.00436131) atbiol. 10in (0.00827136)Untreated rep1Exp1h, atbiol. 24in (0.00836517)Untreated rep2Exp2h, atbiol. 24in (0.054386)Untreated rep1Exp2h, atbiol. 24in (0.0552638)Untreated rep2Exp1h, atbiol. 24in (0.00525093)Untreated rep3Exp1h, atbiol. 72in (0.00937949)Untreated rep1Exp1h, atbiol. 72in (0.0155951)Untreated rep1Exp2h, atbiol. 72in (0.0233381)Untreated rep2Exp1h, atbiol. 72in (0.0256914)Untreated rep3Exp1h, atbiol. 72in (0.00907017) rep1Exp1h, atbiol. 72in (0.00550905) rep2Exp2h, biol. in (0.0140437) rep3Exp2 in (0.0101769)[ Exp2 min (0.0051652) ] [ medium ] [ max ] CEM 1 Med14 613.8 936.6 1605.4 P ( S | Z, I ) = 1.00 Med21 362.6 570.5 858.7 Mean Corr = 0.50372 Med6 125.5 238.0 566.1 Cdk8 1724.3 2904.4 4680.4 Ccnc 166.1 315.6 559.5 Med10 1462.5 1661.0 2072.3 Med23 578.6 752.1 994.2 Prpf40a 722.5 984.9 1418.2 Rbm12 748.8 1143.9 1770.9 0610009D07Rik 2327.2 3353.4 5712.1 Srsf10 654.5 981.5 1428.3 Ccdc58 291.2 423.0 769.2 CEM 1 + Pfdn4 1830.1 2675.4 5457.8 Top 10 Genes Pno1 1860.1 2749.6 5279.8 Orc6 527.3 955.6 1916.9 Abce1 1361.7 1992.5 3343.6 Magoh 2774.6 4317.0 6765.7

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(0.0983453) wildE13.5 #2 type(0.0862516) Atrx-nullE13.5 #3 (0.100461) Atrx-null E13.5#1 (0.128834) Atrx-null P0.5#2 (0.115634) wild P0.5#3 type (0.0460176) wild #1P0.5 type(0.0403737) wild #2P0.5 type(0.068983) Atrx-null #3P0.5 (0.0596787) Atrx-null #1P0.5 (0.0745049) Atrx-null #2AP0.5 (0.0819932) Atrx-null #2B (0.0603942) #3 (0.038529) [ min ] [ medium ] [ max ] CEM 1 Med14 903.1 1074.8 1876.8 P ( S | Z, I ) = 1.00 Med21 179.4 420.6 641.7 Mean Corr = 0.60796 Med6 263.5 447.7 692.4 Cdk8 833.6 1328.3 2329.6 Ccnc 274.7 344.9 458.6 Med10 1883.0 2038.1 2159.0 Med23 703.8 911.5 1237.7 Prpf40a 482.7 660.7 1501.5 Rbm12 1305.0 2177.4 2574.8 0610009D07Rik 1704.9 2940.5 4159.3 Srsf10 532.5 872.2 1543.2 Ccdc58 272.2 366.1 857.0 CEM 1 + Pfdn4 1206.4 1747.2 2418.0 Top 10 Genes Pno1 1038.1 1191.5 1347.2 Orc6 568.0 807.0 1256.8 Abce1 912.1 1109.0 1687.1 Magoh 2099.9 3294.2 5573.7

Null module GEO Series "GSE27708" 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=GSE27708 Status: Public on Aug 01 2011 Title: esBAF facilitates pluripotency by conditioning the genome for LIF/STAT3 signaling and by regulating Polycomb function Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21785422 Summary & Design: Summary: Signaling by the cytokine LIF and its downstream transcription factor, STAT3, prevents differentiation of pluripotent embryonic stem cells (ESCs) by opposing MAP kinase signaling. This contrasts with most cell types where STAT3 signaling induces differentiation. We find that STAT3 binding across the pluripotent genome is dependent upon Brg, the ATPase subunit of a specialized chromatin remodeling complex (esBAF) found in ESCs. Brg is required to establish chromatin accessibility at STAT3 binding targets, in essence preparing these sites to respond to LIF signaling. Moreover, Brg deletion leads to rapid Polycomb (PcG) binding and H3K27me3-mediated silencing of many Brg-activated targets genome-wide, including the target genes of the LIF signaling pathway. Hence, one crucial role of Brg in ESCs involves its ability to potentiate LIF signaling by opposing PcG. Contrary to expectations, Brg also facilitates PcG function at classical PcG target including all four Hox loci, reinforcing their repression in ESCs. These findings reveal that esBAF does not simply antagonize PcG, but rather, the two chromatin regulators act both antagonistically and synergistically with the common goal of supporting pluripotency.

Overall design: ChIP-Seq was used to detect and measure STAT3 occupancy and levels of H3K27me3 in the genome before and after the removal of the SWI/SNF ATPase Brg in mouse ESCs. Total of 4 samples (WT and KO STAT3; WT and KO H3K27me3). Input DNA was sequenced as control.

Background corr dist: KL-Divergence = 0.0417, L1-Distance = 0.0209, L2-Distance = 0.0005, Normal std = 0.6028

0.674 Kernel fit Pairwise Correlations Normal fit

Density 0.337

0.000 CEM 1

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

Pre-normalization Quantiles

WT ES cells,WT ES rep1 cells,WT (0.144571) ES rep2 cells,Brg-KO (0.0748007) rep3Brg-KO ES (0.237141) cells,Brg-KO ES rep1 cells, Lif-WD(0.0872255) ES rep2 cells, ESLif-WD(0.0808102) rep3 cells, ESLif-WD(0.133725) rep1 cells, (0.0764549) ES rep2 cells, (0.0789097) rep3 (0.0863619)[ min ] [ medium ] [ max ] CEM 1 Med14 725.1 1431.4 2352.2 P ( S | Z, I ) = 1.00 Med21 786.0 1046.8 1826.2 Mean Corr = 0.58823 Med6 885.2 1591.0 1856.1 Cdk8 2113.2 2541.9 3049.9 Ccnc 182.2 237.6 314.0 Med10 2117.7 2780.4 3048.3 Med23 825.8 932.0 1130.4 Prpf40a 969.9 1299.2 1432.2 Rbm12 1874.9 2501.9 3308.2 0610009D07Rik 7005.4 8990.4 9409.3 Srsf10 795.9 995.9 1139.2 Ccdc58 2981.8 4947.8 5593.0 CEM 1 + Pfdn4 3206.5 3449.9 5513.8 Top 10 Genes Pno1 4428.5 5399.2 6665.7 Orc6 3141.3 4641.3 5226.7 Abce1 4053.7 4511.6 6461.1 Magoh 9920.4 11203.4 13189.1

Null module GEO Series "GSE25286" 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=GSE25286 Status: Public on May 01 2012 Title: mRNA expression profile in a murine model of hyperoxia-induced bronchopulmonary dysplasia Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: We performed miRNA and mRNA profiling at postnatal day 14 and day 29 to compare hyperoxia-induced bronchopulmonary dysplasia and wild type. We built potential miRNA-mRNA interaction networks specific to brochopulmonary dysplasia.

Overall design: Replicated time course of mouse lung development at 2 time points (P14, P29). Three replicates per time point for bronchopulmonary dysplasia induced by hyperoxia mouse lung, and two replicates per time point for wild type mouse lung. This dataset represents the mRNA expression profiling component of the study.

Background corr dist: KL-Divergence = 0.0273, L1-Distance = 0.0359, L2-Distance = 0.0021, Normal std = 0.6782

0.588 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

P14-WT-lung1P14-WT-lung2 (0.0441247)P14-BPD-lung1 (0.0397987)P14-BPD-lung2P14-BPD-lung3 (0.0822817)P29-WT-lung1 (0.0727012)P29-WT-lung2 (0.152928) (0.230813)P29-BPD-lung1 (0.184197)P29-BPD-lung2P29-BPD-lung3 (0.0691614) (0.0649426) (0.0590514) [ min ] [ medium ] [ max ] CEM 1 Med14 667.3 1113.9 1288.1 P ( S | Z, I ) = 1.00 Med21 590.6 713.8 791.2 Mean Corr = 0.64676 Med6 247.9 316.8 397.6 Cdk8 1109.6 1636.2 1776.1 Ccnc 212.5 279.2 334.9 Med10 1376.0 1717.5 1978.2 Med23 574.3 703.5 860.4 Prpf40a 373.9 664.3 768.1 Rbm12 699.9 1082.0 1304.8 0610009D07Rik 2467.9 2971.5 3382.9 Srsf10 609.9 831.2 893.5 Ccdc58 327.4 463.4 557.1 CEM 1 + Pfdn4 815.0 1086.8 1215.7 Top 10 Genes Pno1 707.2 1060.7 1224.7 Orc6 313.0 573.8 820.3 Abce1 993.4 1325.2 1485.9 Magoh 2872.5 3716.0 4011.8

Null module GEO Series "GSE27114" 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=GSE27114 Status: Public on Sep 04 2012 Title: Expression data from REST knock-out versus REST wild type cells during in vitro neurogenesis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22964890 Summary & Design: Summary: While changes in chromatin are integral to transcriptional reprogramming during cellular differentiation, it is currently unclear how chromatin modifications are targeted to specific loci. We developed a computational model on the premise that transcription factors (TFs) direct dynamic chromatin changes during cell fate decisions. When applied to a neurogenesis paradigm, this approach predicted the TF REST as a determinant of gain of Polycomb-mediated H3K27me3 in neuronal progenitor cells. We prove this prediction experimentally by showing that the absence of REST causes loss of H3K27me3 at target promoters in trans at the same cellular state. Moreover, promoter fragments containing a REST binding site are sufficient to recruit H3K27me3 in cis, while deletion of their REST site results in loss of H3K27me3. These findings illustrate that computational modeling can systematically identify TFs that regulate chromatin dynamics genome-wide. Local determination of Polycomb activity by REST exemplifies such TF based regulation of chromatin.

Overall design: Expression profiling of REST knock-out (RESTko) versus REST wildtype (RESTwt) or REST heterozygous knock-out (RESThet) cells at three stages of in vitro neuronal differentiation. RESTko and RESTwt/RESThet embryonic stem (ES) cells were differentiated to terminal neurons (TN) via a defined neuronal progenitor (NP) state. Three biological replicates (suffixes a to c).

Background corr dist: KL-Divergence = 0.0155, L1-Distance = 0.0419, L2-Distance = 0.0020, Normal std = 0.8997

0.478 Kernel fit Pairwise Correlations Normal fit

Density 0.239

0.000 CEM 1

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

Pre-normalization Quantiles

2_ESwt_a2_ESwt_b (0.104864)2_NPwt_a (0.0835582)2_NPwt_b (0.150812)2_TNwt_a (0.1162)2_TNwt_b (0.188407) (0.356159) [ min ] [ medium ] [ max ] CEM 1 Med14 335.7 768.7 815.2 P ( S | Z, I ) = 0.99 Med21 450.3 1506.0 1690.6 Mean Corr = 0.68715 Med6 382.5 883.2 1065.2 Cdk8 1451.2 2580.5 3567.8 Ccnc 67.4 115.5 131.6 Med10 2053.0 2271.3 2363.3 Med23 938.3 1211.0 1350.8 Prpf40a 195.0 740.9 877.6 Rbm12 728.9 1500.7 1812.1 0610009D07Rik 3335.1 7037.8 7888.5 Srsf10 667.4 1356.0 1494.1 Ccdc58 176.6 3330.5 4439.8 CEM 1 + Pfdn4 3685.3 5910.7 7225.0 Top 10 Genes Pno1 495.1 1841.2 3693.6 Orc6 976.1 2607.1 3409.8 Abce1 2029.4 4136.3 6100.2 Magoh 2361.0 9060.4 9446.5

Null module GEO Series "GSE11201" 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=GSE11201 Status: Public on Apr 18 2008 Title: Coordinated Regulation of Signaling Pathways and Biological Processes during Liver Development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Understanding congenital liver disease requires elucidation of the signaling pathways and transcriptional events in the developing liver. Comprehensive assessment of gene expression between 10.5 and 16.5 dpc in the developing mouse liver and comparison with adult liver and non-hepatic embryonic tissue was validated with real-time PCR and in situ hybridization. The broad nature of the analysis provides insights into patterns of genetic control of hepatogenesis. Pathways implicated in human disease are highly regulated at the transcriptional level. Rather than activating or inhibiting a pathway or biological process by altering the expression of a single signaling molecule, transcriptional changes in large numbers of genes in a pathway or process are regulated in a coordinated manner. For example, both TGF-beta and Notch signaling is inhibited during hepatogenesis not just by decreasing transcription of multiple pathway members, but also with a complementary increase in the transcription of a pathway inhibitor. Similarly, genes related to specific biological processes exhibit strong temporal synchronization in which multiple members of the pathway have similar transcriptional regulation over time. Global coordination of signaling or functional families at the transcriptional level may be a mechanism to produce robustness of the desired outcomes. In addition, this comprehensive analysis provides a database for the further study of transcriptional events during liver development by identifying liver-specific, highly regulated genes.

Keywords: time course

Overall design: In order to provide transcriptional profile of the developing liver compared both to normal adult liver and non-hepatic embryonic tissueswe performed high-density microarray analysis using Affymetrix MG 430 2.0 chips for embryonic liver samples at 10.5, 11.5, 12.5, 13.5, 14.5, and 16.5 days post conception (dpc), embryo-minus liver tissues at 10.5, 11.5, 12.5, and 14.5 dpc, and normal 10-week-old adult mouse liver. Each sample consisted of at least five embryos.

Background corr dist: KL-Divergence = 0.0374, L1-Distance = 0.0354, L2-Distance = 0.0018, Normal std = 0.6265

0.637 Kernel fit Pairwise Correlations Normal fit

Density 0.318

0.000 CEM 1

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

Pre-normalization Quantiles

baselinebaseline liver sampledevelopmental liver sampleatdevelopmental T0, biological at developmentalliver T0, samplebiological developmentalliver rep1 sample at(0.143597) developmental liver T105,rep2 sample at(0.192668) biological developmental liverT105, sampleat biological developmental liverT115, rep1 sampleat biological(0.00701165) developmental liverT115, rep2 sampleat biological(0.0241536) developmental liverT125, rep1 sampleat biological(0.003009) developmental liverT125, rep2 sampleat biological(0.016984) developmental liverT135, rep1 sampleat biological(0.00491466) developmental liverT135, rep2 sampleat biological(0.00927612) embryonic liverT145, rep1 sampleat biological(0.0169387) embryonic liverT145, rep2 liver sampleat biological(0.019575)embryonic T165,sample rep1 liver at biological(0.0179514)embryonic T165, sampleat rep2 liver105, biological(0.0280866) samplebiologicalat rep1 liver115, (0.0222389) samplebiologicalat rep2 125,rep1 (0.0267292) biologicalat(0.134386) 145,rep1[ biological (0.169801)min rep1 (0.0998957) rep1] (0.0627835)[ medium ] [ max ] CEM 1 Med14 363.4 843.4 1713.3 P ( S | Z, I ) = 1.00 Med21 132.2 536.7 1253.7 Mean Corr = 0.34671 Med6 441.3 632.3 1112.2 Cdk8 497.2 1889.7 2425.1 Ccnc 189.0 314.0 453.7 Med10 761.1 1821.6 2581.4 Med23 206.6 634.6 1033.7 Prpf40a 200.1 673.3 1075.1 Rbm12 139.5 995.3 1836.9 0610009D07Rik 1055.3 3292.0 5839.4 Srsf10 297.0 941.4 1416.6 Ccdc58 694.5 1102.9 1823.7 CEM 1 + Pfdn4 552.6 1852.3 2888.6 Top 10 Genes Pno1 804.6 1708.3 2572.1 Orc6 60.9 1164.3 1993.3 Abce1 849.5 1478.1 2026.3 Magoh 1035.0 4671.5 8605.0

Null module GEO Series "GSE9533" 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=GSE9533 Status: Public on May 22 2008 Title: PPARalpha-mediated effects of dietary lipids on intestinal barrier gene expression Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18489776 Summary & Design: Summary: Background: The selective absorption of nutrients and other food constituents in the small intestine is mediated by a group of transport proteins and metabolic enzymes, often collectively called intestinal barrier proteins. An important receptor that mediates the effects of dietary lipids on gene expression is the peroxisome proliferator-activated receptor alpha (PPARÎ±), which is abundantly expressed in enterocytes. In this study we examined the effects of acute nutritional activation of PPARÎ± on expression of genes encoding intestinal barrier proteins. To this end we used triacylglycerols composed of identical fatty acids in combination with gene expression profiling in wild-type and PPARÎ±-null mice. Treatment with the synthetic PPARÎ± agonist WY14643 served as reference.

Results: We identified 74 barrier genes that were PPARÎ±-dependently regulated 6 hours after activation with WY14643. For eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and oleic acid (OA) these numbers were 46, 41, and 19, respectively. The overlap between EPA-, DHA-, and WY14643-regulated genes was considerable, whereas OA treatment showed limited overlap. Functional implications inferred form our data suggested that nutrient-activated PPARÎ± regulated transporters and phase I/II metabolic enzymes were involved in a) fatty acid oxidation, b) cholesterol, glucose, and amino acid transport and metabolism, c) intestinal motility, and d) oxidative stress defense.

Conclusion: We identified intestinal barrier genes that were PPARÎ±-dependently regulated after acute activation by fatty acids.This knowledge provides a better understanding of the impact dietary fat has on the barrier function of the gut, identifies PPARÎ± as an important factor controlling this key function, and underscores the importance of PPARÎ± for nutrient-mediated gene regulation in intestine.

Keywords: metabolic state analysis

Overall design: Pure bred wild-type (129S1/SvImJ) and PPARÎ±-null (129S4/SvJae) mice were treated for 6 hours with the synthetic triacylglycerols triolein [oleic acid (OA, C18:1)], trieicosapentaenoin [eicosapentaenoic acid (EPA, C20:5)] or tridocosahexaenoin [ocosahexaenoic acid (DHA, C22:6)], or the potent PPARÎ± agonist WY14,643. Two weeks before the start of the experiment, mice were put on a modified AIN76A diet, in which corn oil was replaced by olive oil. At the day of the experiment mice were fasted for four hours. At 9 AM mice were dosed by oral gavage with 400 ´l of a 0.1% WY14643 suspension in 0.5% carboxymethyl cellulose, or 400 ´l of the synthetic triacylglycerols. Six hours after the gavage the mice were anaesthetized, small intestines were removed, flushed with ice-cold PBS and remaining fat and pancreatic tissue was carefully removed. Total RNA was then isolated. RNA of 4-5 biological replicates was hybridized to Affymetrix 430-2.0 plus arrays. Five microgram total RNA was labelled according to the ENZO-protocol, fragmented and hybridized according to Affymetrix's protocols.

Background corr dist: KL-Divergence = 0.3720, L1-Distance = 0.0584, L2-Distance = 0.0087, Normal std = 0.2574

1.550 Kernel fit Pairwise Correlations Normal fit

Density 0.775

0.000 CEM 1

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

Pre-normalization Quantiles

intestine_WT_triolein_6hr_rep1intestine_WT_triolein_6hr_rep2intestine_WT_triolein_6hr_rep3intestine_WT_triolein_6hr_rep4intestine_PPARaKO_triolein_6hr_rep1 (0.01073)intestine_PPARaKO_triolein_6hr_rep2 (0.00696132)intestine_PPARaKO_triolein_6hr_rep3 (0.00770199)intestine_PPARaKO_triolein_6hr_rep4 (0.00517458)intestine_PPARaKO_trieicosapentaenoin_6hr_rep5intestine_WT_trieicosapentaenoin_6hr_rep1 (0.044115)intestine_WT_trieicosapentaenoin_6hr_rep2 (0.006986)intestine_WT_trieicosapentaenoin_6hr_rep3 (0.0135266)intestine_WT_trieicosapentaenoin_6hr_rep4 (0.0260226)intestine_WT_trieicosapentaenoin_6hr_rep5intestine_PPARaKO_trieicosapentaenoin_6hr_rep1 (0.0144695)intestine_PPARaKO_trieicosapentaenoin_6hr_rep2(0.0417068) intestine_PPARaKO_trieicosapentaenoin_6hr_rep3(0.0527252) intestine_PPARaKO_trieicosapentaenoin_6hr_rep4(0.0200881) intestine_WT_tridocosahexaenoin_6hr_rep1(0.148986) intestine_WT_tridocosahexaenoin_6hr_rep2(0.00391992)intestine_WT_tridocosahexaenoin_6hr_rep3 (0.0216533)intestine_WT_tridocosahexaenoin_6hr_rep4 (0.0504564)intestine_WT_tridocosahexaenoin_6hr_rep5 (0.0293774)intestine_PPARaKO_tridocosahexaenoin_6hr_rep1 (0.0217232)intestine_PPARaKO_tridocosahexaenoin_6hr_rep2(0.00451045) intestine_PPARaKO_tridocosahexaenoin_6hr_rep3(0.00985294) intestine_PPARaKO_tridocosahexaenoin_6hr_rep4(0.0121323) intestine_WT_WY_6hr_rep1(0.0433698) intestine_WT_WY_6hr_rep2(0.0323948)intestine_WT_WY_6hr_rep3 (0.01671)intestine_WT_WY_6hr_rep4 (0.0307542) (0.00815559)intestine_PPARaKO_WY_6hr_rep1 (0.0240009) (0.0520552)intestine_PPARaKO_WY_6hr_rep2 (0.0296938) (0.0147165)intestine_PPARaKO_WY_6hr_rep3 (0.0195746)intestine_PPARaKO_WY_6hr_rep4 (0.0371591) (0.0662405) (0.051121)[ min (0.0212346) ] [ medium ] [ max ] CEM 1 Med14 781.8 1023.6 1305.6 P ( S | Z, I ) = 1.00 Med21 342.6 507.4 713.0 Mean Corr = 0.27502 Med6 319.5 549.4 806.4 Cdk8 1925.2 2288.8 2813.7 Ccnc 209.1 404.6 770.8 Med10 892.6 1192.1 1555.6 Med23 289.5 401.9 519.3 Prpf40a 442.2 641.6 790.0 Rbm12 499.9 693.0 970.1 0610009D07Rik 5847.7 7173.3 9031.1 Srsf10 622.4 1047.4 1425.3 Ccdc58 1108.7 1654.1 2694.7 CEM 1 + Pfdn4 580.7 1065.7 1688.5 Top 10 Genes Pno1 808.5 1532.5 1979.3 Orc6 83.7 149.7 199.3 Abce1 389.8 916.7 1458.6 Magoh 3374.6 4768.0 6244.2

Null module GEO Series "GSE13235" 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=GSE13235 Status: Public on Oct 17 2008 Title: Gene expression profile of mouse embryonic stem cells (D3-pOCT-mESC) grown in low concentrations of nitric oxide Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: In order to identify the genes regulated in mouse embryonic stem cells (mESC) by the effect of low concentrations of nitric oxide (NO), we analysed the transcriptome of cells treated with NO and compared it to those of cells cultured in the absence of leukemia inhibitory factor (LIF), and in the presence of LIF. We used the cell line D3-pOct4, which carries the enhanced Green Fluorescence Protein gene (eGFP) under the control of the Oct-4 promotor. This line is continuously maintained in the undifferentiated state in the presence of LIF, in comparison with the wild type line .

Overall design: D3-pOct4 cells cultured in the presence of 1000 U/ml of LIF, in the absence of LIF, and in the absence of LIF supplemented with 2uM of diethylenetriamine nitric oxide adduct (DETA)/NO (Sigma) used as donor of nitric oxide. Treatments were maintained for seven days. RNA was extracted and analyzed by Bioanalyzer of Agilent. The cDNA microarray chip used was Mouse Genome 430_2.0 (Affymetrix) and the data were analyzed with GeneChip Operating System v1.4.0.036 using global scaling as the normalization method.

Background corr dist: KL-Divergence = 0.0684, L1-Distance = 0.0302, L2-Distance = 0.0016, Normal std = 0.5120

0.779 Kernel fit Pairwise Correlations Normal fit

Density 0.390

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

D3-pOct4D3-pOct4 (passD3-pOct4 31) (pass withD3-pOct4 31) LIF(pass without (0.0927172)D3-pOct4 31) (pass without LIFD3-pOct4 33)(0.311017) (pass with LIFD3-pOct4 33) plus LIF(pass without (0.0505191) NOD3-pOct4 33) (pass(0.0979539) without LIFD3-pOct4 34)(0.10022) (pass with LIF 34) plus LIF(pass without (0.0427423) NO 34) (0.072618) without LIF (0.0676003) LIF[ plusmin NO (0.164612) ] [ medium ] [ max ] CEM 1 Med14 197.6 583.1 1626.3 P ( S | Z, I ) = 1.00 Med21 272.0 775.7 1041.3 Mean Corr = 0.37058 Med6 175.9 386.3 1320.4 Cdk8 1238.9 1791.9 3760.6 Ccnc 65.2 123.4 213.4 Med10 916.3 1618.4 3081.9 Med23 874.6 1145.2 1363.8 Prpf40a 244.1 433.7 1274.8 Rbm12 556.3 1144.5 3038.1 0610009D07Rik 1718.2 3558.8 6875.3 Srsf10 290.9 371.6 1454.5 Ccdc58 825.7 2081.4 5457.6 CEM 1 + Pfdn4 951.1 2347.3 3922.0 Top 10 Genes Pno1 1297.0 2397.1 5932.6 Orc6 543.0 1412.8 3280.0 Abce1 1496.1 2311.4 3777.1 Magoh 1664.2 4282.4 13027.8

Null module GEO Series "GSE19512" 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=GSE19512 Status: Public on Jun 30 2011 Title: Gene expression profiling of in vivo derived induced and natural FOXP3+ regulatory T cells in the mouse Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21723159 Summary & Design: Summary: The relative contribution of induced and natural Foxp3+ regulatory T cells (iTreg and nTreg cells, respectively) to the maintenance of tolerance is unknown. We examined their respective roles by in vivo adoptive transfer immunotherapy of newborn Foxp3-deficient BALB/c mice. Survival, weight gain, tissue infiltration, T cell activation, and the concentration of proinflammatory cytokines were used as outcome measurements. Treatment with iTreg cells alone was not successful. While effective in preventing death, treatment with nTreg cells alone was associated with chronic inflammation and autoimmunity. Outcomes markedly improved when conventional T (Tconv) cells were transferred together with the nTreg cells, where 10% of the peripheral Treg cell pool was derived by in-situ conversion. This enhancement depended upon the capacity of Tconv cells to express Foxp3.

The gene expression profile of in vivo derived iTreg cells was similar to the established nTreg cell genetic signature. These results identify iTreg cells as an essential regulatory subset that supplements tolerance maintained by nTreg cells.

Overall design: In vitro derived iTreg cells 72 hours after Foxp3 induction: GSM360147 - GSM360151

Background corr dist: KL-Divergence = 0.0200, L1-Distance = 0.0212, L2-Distance = 0.0007, Normal std = 0.7342

0.543 Kernel fit Pairwise Correlations Normal fit

Density 0.272

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 inMouse vivo nTreginMouse vivo cells, nTreginMouse vivo replicate cells, nTreginMouse vivo replicate cells,pool iTreginMouse vivo 1 replicate cells,(0.093382) pool iTregin vivo replicate2 cells,(0.0632165) pool iTreg replicate3 cells,pool(0.0858315) 1 replicate (0.293989) pool[ min2 (0.420651) pool 3 ](0.0429293) [ medium ] [ max ] CEM 1 Med14 1133.7 1729.9 1868.9 P ( S | Z, I ) = 0.99 Med21 187.0 357.7 676.8 Mean Corr = 0.69015 Med6 232.9 282.7 360.1 Cdk8 1184.6 1764.8 1830.2 Ccnc 127.6 227.0 285.2 Med10 2074.2 2659.5 3161.3 Med23 685.0 905.9 1210.1 Prpf40a 181.5 332.9 609.9 Rbm12 1824.0 2493.2 2751.6 0610009D07Rik 1382.3 1958.6 3384.6 Srsf10 749.9 905.0 1048.6 Ccdc58 141.2 204.6 327.2 CEM 1 + Pfdn4 336.0 577.4 978.6 Top 10 Genes Pno1 461.5 758.1 923.3 Orc6 320.2 386.0 465.5 Abce1 806.6 1114.1 1382.9 Magoh 2262.5 2552.2 3189.3

Null module GEO Series "GSE38693" 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=GSE38693 Status: Public on Jun 14 2012 Title: c-JUN REPROGRAMS SCHWANN CELLS OF INJURED NERVES TO GENERATE A REPAIR CELL ESSENTIAL FOR REGENERATION Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: The striking PNS regenerative response to injury rests on the plasticity of adult Schwann cells and their ability to transit between differentiation states, a highly unusual feature in mammals. Using mice with inactivation of Schwann cell c-Jun, we show that the injury response involves c-Jun dependent natural reprograming of differentiated cells to generate a distinct Schwann cell state specialized to promote regeneration. Transected distal stumps of c-Jun mutants show 172 disregulated genes, resulting in abnormal expression of growth factors, adhesion molecules and cytoskeletal changes that lead to neuronal death, inhibition of axon growth and striking failures of functional repair after injury. These observations provide a molecular basis for understanding Schwann cell plasticity and nerve regeneration. They offer conclusive support for the notion that Schwann cells control repair in the PNS, using dedicated transcriptional controls to generate a distinct repair cell, a transition that shows similarities to transdifferentiation seen in other systems.

Overall design: Total RNA was purified from a 10mm segment of the distal stump and uninjured contralateral nerve from c-Jun mutants and control mice 7 days after nerve cut. For each condition (injured/uninjured) and genotype (control/ knock-out) 2 independent samples (replicates) were generated from pooled nerves of 4/6 mice resulting in a total of 8 samples: CTRL.cut.R1, CTRL.cut.R2, CTRL.uncut.R1, CTRL.uncut.R2, KO.cut.R1, KO.cut.R2, KO.uncut.R1,KO.uncut.R2.

Background corr dist: KL-Divergence = 0.0320, L1-Distance = 0.0284, L2-Distance = 0.0009, Normal std = 0.6626

0.628 Kernel fit Pairwise Correlations Normal fit

Density 0.314

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.cut.R1CTRL.cut.R2 (0.231424)CTRL.uncut.R1 (0.150816)CTRL.uncut.R2KO.cut.R1 (0.0480991)KO.cut.R2 (0.150639) (0.0832569)KO.uncut.R1 (0.0467563)KO.uncut.R2 (0.114362) (0.174647) [ min ] [ medium ] [ max ] CEM 1 Med14 523.2 830.8 924.5 P ( S | Z, I ) = 0.99 Med21 470.2 620.6 732.2 Mean Corr = 0.58015 Med6 172.1 276.5 295.2 Cdk8 779.3 974.2 1024.9 Ccnc 139.7 150.1 195.8 Med10 1155.0 1342.5 1438.3 Med23 497.1 511.2 546.7 Prpf40a 445.5 506.0 579.4 Rbm12 573.3 678.1 779.2 0610009D07Rik 1763.5 2364.6 2946.9 Srsf10 601.6 696.9 775.3 Ccdc58 325.5 463.0 524.7 CEM 1 + Pfdn4 603.2 722.3 905.3 Top 10 Genes Pno1 689.0 1215.9 1528.8 Orc6 329.7 403.4 479.4 Abce1 889.3 971.0 1116.9 Magoh 1998.0 2351.4 2611.0

Null module GEO Series "GSE37546" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 20 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37546 Status: Public on Apr 26 2012 Title: Disturbed Hepatic Carbohydrate Management During High Metabolic Demand in Medium-Chain Acyl-CoA Dehydrogenase (MCAD)-deficient Mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18459129 Summary & Design: Summary: Medium-chain acyl-coenzyme A (CoA) dehydrogenase (MCAD) catalyzes crucial steps in mitochondrial fatty acid oxidation, a process that is of key relevance for maintenance of energy homeostasis, especially during high metabolic demand. To gain insight into the metabolic consequences of MCAD deficiency under these conditions, we compared hepatic carbohydrate metabolism in vivo in wild-type and MCAD-/- mice during fasting and during a lipopolysaccharide (LPS)-induced acute phase response (APR). MCAD-/- mice did not become more hypoglycemic on fasting or during the APR than wild-type mice did. Nevertheless, microarray analyses revealed increased hepatic peroxisome proliferator-activated receptor gamma coactivator-1a (Pgc-1a) and decreased peroxisome proliferator-activated receptor alpha (Ppar a) and pyruvate dehydrogenase kinase 4 (Pdk4) expression in MCAD-/- mice in both conditions,suggesting altered control of hepatic glucose metabolism. Quantitative flux measurements revealed that the de novo synthesis of glucose-6-phosphate (G6P) was not affected on fasting in MCAD-/- mice. During the APR, however, this flux was significantly decreased (-20%) in MCAD-/- mice compared with wild-type mice. Remarkably, newly formed G6P was preferentially directed toward glycogen in MCAD-/- mice under both conditions. Together with diminished de novo synthesis of G6P, this led to a decreased hepatic glucose output during the APR in MCAD-/- mice; de novo synthesis of G6P and hepatic glucose output were maintained in wild-type mice under both conditions. APR-associated hypoglycemia, which was observed in wild-type mice as well as MCAD-/- mice, was mainly due to enhanced peripheral glucose uptake. Conclusion: Our data demonstrate that MCAD deficiency in mice leads to specific changes in hepatic carbohydrate management on exposure to metabolic stress. This deficiency, however, does not lead to reduced de novo synthesis of G6P during fasting alone, which may be due to the existence of compensatory mechanisms or limited rate control of MCAD in murine mitochondrial fatty acid oxidation.

Overall design: Total RNA obtained from Liver ( 20 samples) , where comparing 4 groups, consisting out of 5 biological replicates, all groups where fasted for 12 hrs, and half of them where injected with LPS ( 100ug/20gr BW) or vehicle

Background corr dist: KL-Divergence = 0.1254, L1-Distance = 0.0278, L2-Distance = 0.0011, Normal std = 0.4081

0.979 Kernel fit Pairwise Correlations Normal fit

Density 0.489

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 1 (0.0304442)Control 2 (0.0249102)Control 3 (0.0346892)Control 4 (0.0346721)Control 5 (0.0347366)Control + LPS 1Control + (0.10861) LPS 2Control + (0.0523652) LPS 3Control + (0.0299796) LPS 4MCAD + (0.0382925) LPS 15MCAD (0.0731018)(0.0211024) 2MCAD (0.0454087) 3MCAD (0.0597946) 4MCAD (0.0729157) 5MCAD (0.0730185) +MCAD LPS 1 + MCAD(0.0354248) LPS 2 + MCAD(0.0845169) LPS 3 + MCAD(0.0686514) LPS 4 + (0.0225725) LPS 5 (0.0547931) [ min ] [ medium ] [ max ] CEM 1 Med14 229.7 472.5 895.5 P ( S | Z, I ) = 0.99 Med21 486.8 879.0 1721.8 Mean Corr = 0.14254 Med6 210.0 290.6 549.0 Cdk8 783.0 1050.0 1462.1 Ccnc 275.6 481.9 659.3 Med10 1012.1 1825.3 2551.1 Med23 142.0 213.8 422.5 Prpf40a 290.5 603.3 846.0 Rbm12 215.0 392.9 1626.9 0610009D07Rik 4927.1 6554.5 9921.6 Srsf10 180.0 327.7 528.4 Ccdc58 2869.3 3447.5 4321.7 CEM 1 + Pfdn4 446.7 1088.0 1678.4 Top 10 Genes Pno1 2487.0 3455.9 6283.6 Orc6 65.7 100.0 232.6 Abce1 1117.8 1520.3 2129.3 Magoh 2021.7 3433.8 4836.7

Null module GEO Series "GSE7863" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

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

0.795 Kernel fit Pairwise Correlations Normal fit

Density 0.398

0.000 CEM 1

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

Pre-normalization Quantiles

GastrocnemiusGastrocnemiusGastrocnemius MuscleGastrocnemius MuscleWT rep1Gastrocnemius MuscleWT (0.0446844) rep2Gastrocnemius Musclemdx (0.0140399) rep1Gastrocnemius Musclemdx (0.0240778) rep2Gastrocnemius MuscleGalgt2 (0.1506)Gastrocnemius TransgenicMuscleGalgt2Gastrocnemius TransgenicMuscleGalgt2 rep1Gastrocnemius TransgenicMuscleGalgt2 (0.030218) rep2Gastrocnemius TransgenicMusclemdx (0.0241562) mdx AAV-Galgt2-TreatedMyoblast Musclemdx rep1 mdx AAV-Galgt2-Treated Myoblast(0.0263294) Musclemdx Cellrep2 PBS-TreatedLine Myoblast(0.0305893) mdx Cell rep1 PBS-TreatedLineMyoblast (0.125728)(0.0186051)Cell Differentiatedrep2rep1 Line (0.0238759)(0.107536)Cell Stablyrep2 Line (0.0276266) rep1 TransfectedStably (0.121784) Transfected[ with min Galgt2 with ] rep1Galgt2 (0.114886) Differentiated[ medium rep1 (0.115264) ] [ max ] CEM 1 Med14 929.5 1338.7 2192.3 P ( S | Z, I ) = 0.98 Med21 1511.8 3145.5 5122.2 Mean Corr = 0.61446 Med6 329.2 694.3 1659.5 Cdk8 1583.9 2800.2 3634.0 Ccnc 151.9 767.8 1227.5 Med10 827.2 1076.8 1548.5 Med23 185.0 280.2 428.6 Prpf40a 49.4 115.7 253.3 Rbm12 257.6 466.7 1340.5 0610009D07Rik 878.1 1874.5 3010.4 Srsf10 102.1 406.8 739.6 Ccdc58 1248.1 1757.9 2405.1 CEM 1 + Pfdn4 531.1 763.2 1596.1 Top 10 Genes Pno1 420.8 881.1 1200.6 Orc6 293.9 563.9 1940.5 Abce1 3387.5 9437.4 12373.4 Magoh 530.4 1467.6 2837.0

Null module GEO Series "GSE6837" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6837 Status: Public on Jan 31 2007 Title: Expression data from wild type (wt) and Ikbke knockout (Ikke) embryonic fibroblasts (EF) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17332413 Summary & Design: Summary: WT and Ikbke-/- EF cells were stimulated with recombinant interferon beta for 6 hours. Cells lacking IKKe kinase show a defect in a subset of interferon stimulated gene transcription

Keywords: comparative study

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

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

0.536 Kernel fit Pairwise Correlations Normal fit

Density 0.268

0.000 CEM 1

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

Pre-normalization Quantiles

unstimulatedunstimulated embryonicstimulated embryonicstimulated fibroblasts embryonicstimulated fibroblasts embryonic WT, stimulatedfibroblasts biologicalembryonic KO, stimulatedfibroblasts biologicalembryonicWT, rep1 stimulatedfibroblasts biological embryonicWT,(0.06445) rep1 fibroblasts biological embryonicrep1WT,(0.0835034) fibroblasts biological(0.0712539) rep2KO, fibroblasts biological (0.0559292) rep3KO,[ biological (0.0568334) min rep1KO, biological(0.367384) rep2] (0.0780766) rep3 (0.222569)[ medium ] [ max ] CEM 1 Med14 609.6 2345.1 2851.8 P ( S | Z, I ) = 0.97 Med21 352.9 1657.5 1881.7 Mean Corr = 0.68076 Med6 222.7 626.3 750.7 Cdk8 990.7 2410.8 2821.3 Ccnc 200.1 251.3 356.6 Med10 1668.2 3026.8 4000.0 Med23 418.9 677.6 730.6 Prpf40a 332.6 1334.8 1487.5 Rbm12 504.3 1404.2 1561.4 0610009D07Rik 1647.4 3336.1 5721.3 Srsf10 571.8 1091.7 1704.1 Ccdc58 325.7 1412.4 1950.7 CEM 1 + Pfdn4 820.4 4729.3 6345.6 Top 10 Genes Pno1 735.1 4863.9 5845.9 Orc6 284.6 2853.8 3006.5 Abce1 798.3 6464.8 7009.1 Magoh 2841.0 9147.6 14186.8

Null module GEO Series "GSE57797" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 23 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57797 Status: Public on Jul 13 2014 Title: Expression data from the subclones of Lewis Lung Carcinoma (LLC) cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Medium conditioned by LLC cells stimulates thermogenic gene expression when added onto primary adipocytes. We generated single cell colonies from parental LLC cells. Media conditioned by the subclones stimulated thermogenic gene expression in primary adipocytes at varying degrees.

Subclones 2, 3, 6 and 28 produce significantly larger amount of thermogenic activity than the subclones 18, 19, 23 and 24. We compared gene expression profiles of these subclones to identify secreted factors enriched in the more thermogenic clones.

Overall design: LLC subclones were cultured under conditioned medium preparation conditiones and total RNA was extracted from biological replicates.

Background corr dist: KL-Divergence = 0.2154, L1-Distance = 0.0344, L2-Distance = 0.0019, Normal std = 0.3269

1.220 Kernel fit Pairwise Correlations Normal fit

Density 0.610

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

LLC-subclone-2,LLC-subclone-2,LLC-subclone-2, biologicalLLC-subclone-3, biological rep1LLC-subclone-3, biological(0.0521468) rep2LLC-subclone-3, biological(0.0407018) rep3LLC-subclone-6, biological(0.0372389) rep1LLC-subclone-6, biological(0.0527097) rep2LLC-subclone-28, biological(0.0435734) rep3LLC-subclone-28, biological(0.0523652) rep1LLC-subclone-28, (0.00876123) biological rep2LLC-subclone-18, (0.0076956) biological rep1LLC-subclone-18, biological(0.0224693) rep2LLC-subclone-18, biological(0.0273385) rep3LLC-subclone-19, biological(0.0274671) rep1LLC-subclone-19, biological(0.123387) rep2LLC-subclone-19, biological(0.100244) rep3LLC-subclone-23, biological(0.0893247) rep1LLC-subclone-23, biological(0.0527653) rep2LLC-subclone-23, biological(0.0905661) rep3LLC-subclone-24, biological(0.0610273) rep1LLC-subclone-24, biological(0.0112964) rep2LLC-subclone-24, biological(0.0180491) rep3 biological(0.0205) rep1 biological(0.0213033) rep2 (0.022479) rep3[ min (0.01659) ] [ medium ] [ max ] CEM 1 Med14 458.8 592.4 1070.8 P ( S | Z, I ) = 0.98 Med21 1096.4 1647.8 2299.0 Mean Corr = 0.17808 Med6 505.5 638.9 855.8 Cdk8 1945.4 2275.5 2753.8 Ccnc 337.1 391.3 706.6 Med10 2689.1 3134.5 3825.9 Med23 515.2 698.3 997.3 Prpf40a 942.4 1189.1 1657.8 Rbm12 763.9 985.2 1260.8 0610009D07Rik 4791.9 6027.8 7179.3 Srsf10 756.5 1086.8 1761.0 Ccdc58 1244.9 2366.5 3135.2 CEM 1 + Pfdn4 2135.4 2561.0 3425.7 Top 10 Genes Pno1 2305.6 3110.9 4033.7 Orc6 1150.8 1576.0 1938.8 Abce1 1275.8 1870.0 2184.1 Magoh 3388.0 4016.4 4611.9

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 (0.0637157) 3 (Affymetrix)Tg,Calcineurin biological (0.0921962) 4 (Affymetrix)Tg,Calcineurin biological (0.0638559) replicate Tg,Differentiating biological (0.0537734) replicate Tg, 1 (Affymetrix)Differentiating biological replicate 2 P19CL6(Affymetrix)Differentiating replicate (0.0180111) 3 P19CL6(Affymetrix)Differentiating cells (0.0363526) 4at P19CL6(Affymetrix)Differentiating cellsday (0.0221697)6 at afterP19CL6Differentiating cellsday DMSO(0.0503668)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 (0.0746558)replicate 3 (Affymetrix) treatment, (0.137994)replicate [1 (Affymetrix)medium (0.0792526)replicate 2 (Affymetrix) (0.187992) 3 (Affymetrix) ] (0.0664473) (0.0532166)[ max ] CEM 1 Med14 306.6 582.8 1133.9 P ( S | Z, I ) = 0.97 Med21 525.0 746.3 1282.7 Mean Corr = 0.53531 Med6 347.6 521.7 962.8 Cdk8 553.1 1011.5 2978.0 Ccnc 126.0 166.7 209.2 Med10 1159.0 2018.0 3327.5 Med23 353.3 429.4 1324.3 Prpf40a 187.5 285.6 1085.7 Rbm12 342.4 423.8 1695.9 0610009D07Rik 885.9 1345.7 3703.9 Srsf10 357.1 464.9 1425.9 Ccdc58 706.2 973.3 2252.4 CEM 1 + Pfdn4 666.0 935.0 3259.2 Top 10 Genes Pno1 1444.5 1879.1 4554.5 Orc6 159.4 267.2 2446.8 Abce1 584.9 820.9 1286.9 Magoh 1680.1 2253.5 6282.5

Null module GEO Series "GSE11356" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

Keywords: time course

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

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

0.771 Kernel fit Pairwise Correlations Normal fit

Density 0.386

0.000 CEM 1

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

Pre-normalization Quantiles

NCCs atNCCs E8.5, atbiologicalNCCs E8.5, atbiologicalNCCs E8.5, rep1 at biological(0.0774995)NCCs E13.5, rep2 at (0.321399) NCCsbiological E13.5, rep3 at (0.147981) NCCsbiological E13.5, rep1 at NCCs biological(0.0469172)P90, rep2 biologicalatNCCs (0.160376)P90, rep3 biologicalat (0.0212403) P90,rep1 biological(0.0421029) rep2 (0.0283749) rep3 (0.154109)[ min ] [ medium ] [ max ] CEM 1 Med14 295.7 824.9 2076.9 P ( S | Z, I ) = 0.96 Med21 35.2 159.0 385.8 Mean Corr = 0.61830 Med6 34.5 68.7 177.4 Cdk8 199.0 1184.2 3028.8 Ccnc 12.7 57.0 91.5 Med10 3479.2 4649.7 5694.0 Med23 594.8 1041.5 1523.0 Prpf40a 176.2 311.1 995.7 Rbm12 412.5 1203.3 2720.9 0610009D07Rik 468.6 980.5 2068.9 Srsf10 235.3 426.8 1219.4 Ccdc58 286.1 325.9 1397.7 CEM 1 + Pfdn4 384.1 1562.8 2439.1 Top 10 Genes Pno1 583.4 1253.3 4482.2 Orc6 85.9 643.8 2520.7 Abce1 233.6 378.4 1061.0 Magoh 390.1 1662.9 4186.7

Null module GEO Series "GSE21711" 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=GSE21711 Status: Public on May 07 2010 Title: Effect of cholera toxin or forskolin on mouse bone marrow-derived dendritic cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20479237 Summary & Design: Summary: Bone marrow-derived dendritic cells from C57BL/6 mice were treated with 1 ug/ml cholera toxin, 10 uM forskolin or control medium for 2 h.

Overall design: drug treatment groups

Background corr dist: KL-Divergence = 0.0361, L1-Distance = 0.0260, L2-Distance = 0.0007, Normal std = 0.6542

0.629 Kernel fit Pairwise Correlations Normal fit

Density 0.314

0.000 CEM 1

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

Pre-normalization Quantiles

control controlmedium, choleramedium, biologicalcholera toxin, biological rep biologicalforskolin, toxin, 1 (0.0824796) rep biologicalforskolin, 2 repbiological (0.0944778) 1 (0.321349) repbiological rep 2 (0.233491) 1 (0.116273) rep 2 (0.151929)[ min ] [ medium ] [ max ] CEM 1 Med14 968.9 1039.3 1622.8 P ( S | Z, I ) = 0.96 Med21 668.1 753.6 1112.6 Mean Corr = 0.28210 Med6 321.9 379.3 499.9 Cdk8 1014.9 1123.2 1240.8 Ccnc 294.4 325.5 351.7 Med10 3423.0 3510.7 3780.3 Med23 661.8 802.0 1052.4 Prpf40a 992.5 1071.5 1237.9 Rbm12 1046.5 1110.8 1462.0 0610009D07Rik 3319.8 4207.9 4346.2 Srsf10 856.0 916.4 967.6 Ccdc58 510.4 585.3 627.2 CEM 1 + Pfdn4 1209.0 1282.2 1475.3 Top 10 Genes Pno1 2398.9 2543.3 2726.7 Orc6 221.3 367.5 399.7 Abce1 812.4 881.6 1031.3 Magoh 3602.8 4105.9 4912.4

Null module GEO Series "GSE15330" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 27 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15330 Status: Public on Apr 03 2009 Title: Gene expression data from mouse hematopoietic cells, Ikaros wt and null mutant Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19345118 Summary & Design: Summary: Regulation of lineage potential and transcriptional priming by Ikaros. New insight is provided into a bivalent regulation of lineage priming in the HSC and its lympho-myeloid restricted progeny the LMPP by the lymphoid lineage-determining factor Ikaros

Whereas Ikaros is responsible for the activation of a cascade of lymphoid expression programs and for the establishment of lymphoid potential from the HSC to the LMPP it is also responsible for the repression of stem cell and erythroid genetic programs that are incompatible with further lineage restrictions emanating from the LMPP

Keywords: Ikaros null versus wt

Overall design: Ikaros null versus wt

Background corr dist: KL-Divergence = 0.1031, L1-Distance = 0.0552, L2-Distance = 0.0075, Normal std = 0.4330

0.921 Kernel fit Pairwise Correlations Normal fit

Density 0.461

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 LSKWT GFPneg-lo, LSKWT GFPneg-lo, LSK biologicalWT GFPneg-lo, LSK biologicalWT rep1GFPhi, LSK biological(0.0176029)WT rep2biologicalGFPhi, LSK (0.0454279)WT rep3biologicalGFPhi, LKrep1 (0.0152118) GFPneg,WT biological(0.0197677) LKrep2 GFPneg,WT biological(0.0508124) LKrep3 GFPneg,WT biological(0.0112048) LK rep1 GFPhi,WT biological(0.0716585) LK rep2 biologicalGFPhi,WT (0.0088594) LK rep3 biologicalGFPhi,WT (0.0656543)rep1 ProB, biologicalWT(0.0366926) biologicalrep2 ProB, WT(0.0159323) biologicalrep3 ProB, rep1 KO(0.0375303) biological (0.0162901)LSK rep2KO GFPneg-lo, (0.0483994)LSK rep3KO GFPneg-lo, (0.0974293)LSK biologicalKO GFPneg-lo, LSK biologicalKO rep1GFPhi, LSK biological(0.00443552)KO rep2biologicalGFPhi, LSK (0.0276782)KO rep3biologicalGFPhi, LKrep1 (0.00624126) GFPneg,KO biological(0.0147168) LKrep2 GFPneg,KO biological(0.0278721) LKrep3 GFPneg,KO biological(0.0316479) LK rep1 GFPhi,KO biological(0.0791141) LK rep2 biologicalGFPhi,KO (0.0113906) LK rep3 biologicalGFPhi, (0.19299)rep1 biological(0.00807779) rep2 (0.0192018) rep3 [(0.0181599) min ] [ medium ] [ max ] CEM 1 Med14 623.2 1704.0 3675.3 P ( S | Z, I ) = 0.92 Med21 112.4 210.7 495.3 Mean Corr = 0.62390 Med6 89.5 108.5 227.9 Cdk8 1162.4 1715.6 3259.5 Ccnc 44.9 99.0 213.6 Med10 1201.5 1372.3 3324.8 Med23 609.9 868.1 1246.7 Prpf40a 206.0 286.5 996.0 Rbm12 1429.6 2356.9 3727.6 0610009D07Rik 1680.1 2758.1 4282.6 Srsf10 448.5 835.2 1731.9 Ccdc58 231.1 415.9 945.6 CEM 1 + Pfdn4 311.9 609.2 1037.4 Top 10 Genes Pno1 294.8 865.6 3300.5 Orc6 710.5 951.9 2217.9 Abce1 470.9 1478.3 4860.5 Magoh 1677.3 3456.8 6216.9

Null module GEO Series "GSE51628" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.843 Kernel fit Pairwise Correlations Normal fit

Density 0.422

0.000 CEM 1

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

Pre-normalization Quantiles

TICNX_48h_rep1TICNX_48h_rep2TICNX_48h_rep3 (0.0555703)TICNX_48h_rep4 (0.118935)TICNX_96h_rep1 (0.0761285)TICNX_96h_rep2 (0.0538017)TICNX_96h_rep3 (0.0427474)MTB/TICNX_48h_rep1 (0.025101)MTB/TICNX_48h_rep2 (0.0408269)MTB/TICNX_48h_rep3 MTB/TICNX_48h_rep4(0.00887876) MTB/TICNX_96h_rep1(0.0116446) MTB/TICNX_96h_rep2(0.0213942) MTB/TICNX_96h_rep3(0.0962843) MTB/TICNX_96h_rep4(0.0203168) (0.120379) (0.102773) (0.205219)[ min ] [ medium ] [ max ] CEM 1 Med14 892.1 1291.9 2000.2 P ( S | Z, I ) = 0.92 Med21 559.7 770.9 875.7 Mean Corr = 0.48413 Med6 191.4 228.5 331.9 Cdk8 876.4 1215.1 1859.2 Ccnc 124.3 161.0 214.1 Med10 1820.5 2132.0 2387.9 Med23 315.2 382.0 550.9 Prpf40a 361.7 451.6 580.0 Rbm12 451.3 725.5 915.5 0610009D07Rik 2772.1 3331.3 3978.7 Srsf10 656.3 925.7 1102.0 Ccdc58 426.6 571.5 858.1 CEM 1 + Pfdn4 744.3 935.8 1166.4 Top 10 Genes Pno1 1177.0 1335.6 1752.0 Orc6 349.4 460.2 766.0 Abce1 974.3 1143.9 1332.4 Magoh 2636.6 4149.8 6146.1

Null module GEO Series "GSE31028" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.594 Kernel fit Pairwise Correlations Normal fit

Density 0.297

0.000 CEM 1

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

Pre-normalization Quantiles

QuiescentQuiescent hair Activatedfollicle hair Activatedstemfollicle hair cells, follicleTransient-amplifyingstem hair rep1 cells, stemfollicleTransient-amplifying (0.0928693) rep2 cells, stem (0.155006) rep1 cells, matrix (0.0571718) rep2 cells,matrix (0.113501) rep1 cells,[ (0.213227)min rep2 (0.368226) ] [ medium ] [ max ] CEM 1 Med14 1128.0 1639.8 3294.1 P ( S | Z, I ) = 0.91 Med21 1211.4 1420.3 1909.8 Mean Corr = 0.44501 Med6 469.8 749.4 913.1 Cdk8 683.3 966.0 1538.5 Ccnc 98.2 158.5 200.4 Med10 2341.7 2977.5 3363.6 Med23 504.0 689.4 721.7 Prpf40a 245.4 388.0 492.0 Rbm12 762.3 1473.5 1921.2 0610009D07Rik 7165.5 7743.2 10291.4 Srsf10 861.5 1150.4 1992.3 Ccdc58 703.8 1283.4 2393.7 CEM 1 + Pfdn4 1789.1 3249.4 3835.4 Top 10 Genes Pno1 909.2 1460.3 3559.8 Orc6 413.9 555.0 1179.3 Abce1 839.0 1286.6 2226.6 Magoh 8649.1 9751.4 15100.2

Null module GEO Series "GSE11258" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11258 Status: Public on Sep 24 2008 Title: Npas4-regulated genes in mouse hippocampal neurons Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18815592 Summary & Design: Summary: we performed a DNA microarray experiment to identify activity-regulated genes that are misregulated in the absence of Npas4.

Keywords: Primary neuron culture, depolarization, activity-dependent, Npas4

Overall design: We infected mouse hippocampal neurons with lentivirus expressing Npas4-RNAi or control-RNAi @ 3 DIV and depolarized the neurons @ 8 DIV with 50 mM of KCl for 0, 1, 3 or 6 hours. Neurons were lysed, mRNA isolated and hybridized to Affymetrix arrays. Data were collected from 3 independent experiments.

Background corr dist: KL-Divergence = 0.2486, L1-Distance = 0.0389, L2-Distance = 0.0028, Normal std = 0.3070

1.299 Kernel fit Pairwise Correlations Normal fit

Density 0.650

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

Npas4_RNAi_0hr_1Npas4_RNAi_0hr_2Npas4_RNAi_0hr_3 (0.0352068)Npas4_RNAi_1hr_1 (0.0327365)Npas4_RNAi_1hr_2 (0.0166466)Npas4_RNAi_1hr_3 (0.0148888)Npas4_RNAi_3hr_1 (0.0245503)Npas4_RNAi_3hr_2 (0.0373896)Npas4_RNAi_3hr_3 (0.041204)Npas4_RNAi_6hr_1 (0.0461126)Npas4_RNAi_6hr_3 (0.0348789)Control_RNAi_0hr_1 (0.0606381)Npas4_RNAi_6hr_2 (0.0698523)Control_RNAi_0hr_2 (0.0763561)Control_RNAi_0hr_3 (0.0534843)Control_RNAi_1hr_1 (0.0499246)Control_RNAi_1hr_2 (0.0573588)Control_RNAi_1hr_3 (0.0631817)Control_RNAi_3hr_1 (0.0408798)Control_RNAi_3hr_2 (0.0500127)Control_RNAi_3hr_3 (0.0712234)Control_RNAi_6hr_1 (0.0399465)Control_RNAi_6hr_2 (0.0205252)Control_RNAi_6hr_3 (0.0121972) (0.0318165) (0.0189887)[ min ] [ medium ] [ max ] CEM 1 Med14 464.3 664.6 891.4 P ( S | Z, I ) = 0.90 Med21 694.2 802.7 896.0 Mean Corr = 0.21601 Med6 188.0 309.3 632.4 Cdk8 1109.4 1597.9 2106.1 Ccnc 140.6 198.5 316.7 Med10 3381.8 4020.9 4671.7 Med23 326.8 457.1 618.3 Prpf40a 412.2 486.1 606.9 Rbm12 915.6 1226.2 1800.6 0610009D07Rik 3583.1 4028.1 4947.1 Srsf10 476.4 626.3 952.7 Ccdc58 483.2 552.9 608.3 CEM 1 + Pfdn4 2968.4 3312.3 3842.6 Top 10 Genes Pno1 1486.9 2131.6 2891.6 Orc6 577.7 936.6 1102.6 Abce1 1679.7 2120.3 2391.9 Magoh 3456.1 4064.4 4362.0

Null module GEO Series "GSE15794" 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=GSE15794 Status: Public on Apr 25 2009 Title: Gene expression profiles of E13 bladder neck/urethral compartments. (GUDMAP Series ID: 25) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: The long term objective is to create an encyclopedia of the expression levels of all genes in multiple components of the developing bladder. The central thesis is straightforward. The combination of micro dissected tissues and FACS sorted cells plus microarray analysis offers a powerful, efficient and effective method for the creation of a global gene expression atlas of the developing urogenital system. Microarrays with essentially complete genome coverage can be used to quantitate expression levels of every gene. The ensuing rapid read-out provides an expression atlas that is more sensitive, more economical and more complete than would be possible by in situ hybridizations alone. The data submitted here delineates the gene expression profiles of the mesenchymal and epithelial compartments of the E13 mouse bladder neck/urethral compartment.

Overall design: FVB/N mice were time mated. At embryonic day 13 mice were euthanized by decapitation and the bladders were microdissected and cut just below the ureters. Since the EDTA dissociation was ineffective, the bladder neck and urethra were collected and treated with 1 mg/ml trypsin in Tyrode’s solution for 20 minutes at 37´C. The layers were separated using a fine needle and rimming. The samples were placed in RLT and stored at -80´C. RNA was prepared and the Epicentre 2-round amplification scheme described under the Lessard Group Protocols on the GUDMAP pages were performed. The amplified RNA was examined with the Affymetrix GeneChip Mouse Genome 430 2.0 Array.

Background corr dist: KL-Divergence = 0.0453, L1-Distance = 0.0594, L2-Distance = 0.0048, Normal std = 0.7260

0.597 Kernel fit Pairwise Correlations Normal fit

Density 0.298

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

urothelium1_200209urothelium2_200209urothelium5_200209 (0.0340762)mesenchyme1_200209 (0.37821)mesenchyme2_200209 (0.108229)mesenchyme3_200209 (0.318335) (0.0110123) (0.150138)[ min ] [ medium ] [ max ] CEM 1 Med14 2181.2 2413.6 3719.9 P ( S | Z, I ) = 0.87 Med21 226.5 361.3 431.5 Mean Corr = 0.56779 Med6 102.1 352.6 554.5 Cdk8 4275.4 5438.0 6963.2 Ccnc 67.0 232.8 360.8 Med10 1129.3 1429.2 2052.8 Med23 677.9 1613.3 1813.6 Prpf40a 461.5 772.9 1404.2 Rbm12 2919.2 4552.5 7023.8 0610009D07Rik 571.1 732.6 1098.7 Srsf10 233.8 557.7 818.7 Ccdc58 322.6 359.0 759.2 CEM 1 + Pfdn4 922.6 1737.3 1936.8 Top 10 Genes Pno1 1149.9 1507.4 2818.2 Orc6 422.2 1418.8 1581.3 Abce1 1828.5 2541.5 2851.0 Magoh 781.9 1856.6 4074.3

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 (0.109353) cellspurified basalFACS(0.129018) (0.0831147) epidermal purified matrix cellsORS cells [ (0.439726)cells (0.0931757)min (0.145614) ] [ medium ] [ max ] CEM 1 Med14 1477.1 2013.7 2865.7 P ( S | Z, I ) = 0.87 Med21 433.5 648.7 1330.4 Mean Corr = 0.60129 Med6 341.9 524.9 797.5 Cdk8 1396.1 1683.4 2296.2 Ccnc 118.5 243.5 357.0 Med10 2119.7 2600.3 2745.2 Med23 402.1 573.4 583.8 Prpf40a 516.9 682.8 1072.3 Rbm12 1372.6 1580.4 2038.8 0610009D07Rik 3187.6 4924.3 6113.6 Srsf10 696.8 893.2 1386.9 Ccdc58 703.4 1251.3 1858.5 CEM 1 + Pfdn4 1009.6 2156.3 2840.8 Top 10 Genes Pno1 1337.0 2172.1 4632.3 Orc6 701.7 1133.9 1627.4 Abce1 1143.7 1711.9 2983.3 Magoh 7318.2 9683.0 10791.0

Null module GEO Series "GSE32277" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 33 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

1.012 Kernel fit Pairwise Correlations Normal fit

Density 0.506

0.000 CEM 1

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

Pre-normalization Quantiles

iKras5-T-on-1iKras5-T-on-2 (0.0209018)iKras5-T-off-1 (0.00965118)iKras5-T-off-2 (0.00940119)iKras1-T-on-1 (0.0213658)iKras1-T-on-2 (0.0137895)iKras1-T-off-1 (0.0298052)iKras2-T-on-1 (0.0168935)iKras2-T-on-2 (0.0326433)iKras2-T-off-1 (0.0573589)iKras2-T-off-2 (0.0142936)iKras3-T-on-1 (0.0175221)iKras3-T-on-2 (0.0112173)iKras3-T-off-1 (0.0198807)iKras3-T-off-2 (0.0146853)iKras4-T-on-1 (0.0142586)iKras4-T-on-2 (0.0128524)iKras4-T-off-1 (0.0327449)iKras4-T-off-2 (0.0141266)iKras5-C-on (0.0417193)iKras1-C-on (0.0141786)iKras2-C-on (0.00926381)iKras3-C-on (0.00716293)iKras4-C-on (0.0193712)iKras5-C-off (0.0106238)iKras1-C-off (0.0133062)iKras2-C-off (0.0337883)iKras3-C-off (0.0217597)iKras4-C-off (0.00577205)LSL-Kras2-on (0.0175545)LSL-Kras2-off (0.0847878)LSL-Kras1-on (0.0937083)LSL-Kras1-off (0.132332) (0.13128) [ min ] [ medium ] [ max ] CEM 1 Med14 721.3 1116.7 1818.5 P ( S | Z, I ) = 0.85 Med21 339.5 490.6 1987.7 Mean Corr = 0.30509 Med6 104.0 338.8 836.1 Cdk8 1082.0 1396.6 4489.0 Ccnc 43.8 108.3 273.3 Med10 1774.3 2228.6 3393.8 Med23 523.5 717.2 960.3 Prpf40a 512.2 780.9 1342.3 Rbm12 498.1 932.7 1360.3 0610009D07Rik 725.3 2176.9 5996.0 Srsf10 357.8 578.1 1160.5 Ccdc58 363.6 588.7 2376.8 CEM 1 + Pfdn4 976.9 1855.3 5071.2 Top 10 Genes Pno1 873.9 1820.1 3995.2 Orc6 157.4 527.3 2284.9 Abce1 731.9 1593.6 3395.2 Magoh 2004.5 2905.8 7265.5

Null module GEO Series "GSE45820" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

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

0.477 Kernel fit Pairwise Correlations Normal fit

Density 0.239

0.000 CEM 1

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

Pre-normalization Quantiles

Tie2cre Tie2crelineage Tie2cre lineagetraced Tie2cre fibroblastnon-lineagetraced Endothelialfibroblastnon-lineage SHAM, tracedEndothelial BiologicalTAC, cells fibroblasttraced Biological SHAM, cellsfibroblast Replicate SHAM, BiologicalTAC, Replicate BiologicalTAC, 1 (0.026821) ReplicateBiological 1[ (0.105066) minReplicate 1 Replicate (0.333669) ] 1 (0.0416484)(0.152803) 1 (0.339992)[ medium ] [ max ] CEM 1 Med14 487.6 776.1 1838.3 P ( S | Z, I ) = 0.77 Med21 1731.7 1978.0 2417.9 Mean Corr = 0.58690 Med6 425.1 605.2 751.6 Cdk8 322.8 1073.1 1286.6 Ccnc 51.5 199.0 297.8 Med10 1310.4 1567.3 1936.0 Med23 466.7 546.6 674.1 Prpf40a 364.8 430.9 467.8 Rbm12 1110.1 1277.6 1431.4 0610009D07Rik 969.4 1571.5 1823.4 Srsf10 326.6 444.8 471.7 Ccdc58 634.6 1108.0 1328.4 CEM 1 + Pfdn4 628.9 787.1 957.6 Top 10 Genes Pno1 123.9 467.6 926.4 Orc6 527.1 695.0 1013.6 Abce1 783.3 1296.0 1783.9 Magoh 1504.7 2132.2 2568.5

Null module GEO Series "GSE16874" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.423 Kernel fit Pairwise Correlations Normal fit

Density 0.212

0.000 CEM 1

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

Pre-normalization Quantiles

BCells_WildType_day0_REP1BCells_WildType_day0_REP2BCells_WildType_day0_REP3BCells_Transgenic_day0_REP1 BCells_Transgenic_day0_REP2(0.0377269) BCells_Transgenic_day0_REP3(0.0803102) BCells_WildType_day2_REP1(0.123522)BCells_WildType_day2_REP2 (0.0659783)BCells_WildType_day2_REP3 (0.0610359)BCells_Transgenic_day2_REP1 (0.11642) BCells_Transgenic_day2_REP2(0.105199) BCells_Transgenic_day2_REP3(0.0821378) (0.149751) (0.06589) (0.0348324)[ (0.0771972)min ] [ medium ] [ max ] CEM 1 Med14 711.8 1172.5 1553.2 P ( S | Z, I ) = 0.75 Med21 558.4 1050.7 1670.9 Mean Corr = 0.60086 Med6 476.1 574.9 697.7 Cdk8 1404.5 2583.9 3668.5 Ccnc 123.3 365.9 384.4 Med10 2095.8 3185.0 3413.5 Med23 778.9 914.7 1005.1 Prpf40a 459.9 1049.4 1201.8 Rbm12 817.9 1827.1 2594.0 0610009D07Rik 4659.2 7575.0 8324.5 Srsf10 747.1 1494.4 1548.2 Ccdc58 320.7 1752.7 1979.6 CEM 1 + Pfdn4 876.3 2652.5 3084.9 Top 10 Genes Pno1 926.4 6622.4 7842.1 Orc6 562.6 1764.9 2337.9 Abce1 1205.5 3046.9 4243.3 Magoh 4345.3 10487.5 11001.0

Null module GEO Series "GSE5861" 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=GSE5861 Status: Public on Sep 19 2006 Title: Searching for Brca1 regulated X-linked genes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17350580 Summary & Design: Summary: We compared the expression levels of X-linked genes in the mammary glands of Brca1 D11/D11;p53+/- mutant and control (p53+/-) mice at three different stages of the mammary cycle: virgin, pregnant day 16.5, and lactation day 1, using a cDNA microarray. In about 690 X-linked genes that are expressed at these three stages of mammary cycle of development, we found 16 X-linked genes showed altered expression levels in Brca1 D11/D11;p53+/- mammary glands in comparison with controls at all three time points. Among them, 9 genes were up-regulated and 7 were down-regulated. This result indicates that mutation of Brca1 could affect expression of a few X-linked genes in mammary tissues. However, this was unlikely caused by failure of X chromosome inactivation, as seven of them were down-regulated, and Xist RNA was expressed in all the Brca1 mutant mammary tissues.

Keywords: BRCA1 mutation analysis

Overall design: Mutations in breast cancer associated gene-1 (BRCA1) are associated with hereditary breast and ovarian cancers. BRCA1 encodes a tumor suppressor protein that functions in DNA repair, transcriptional regulation, chromatin remodeling, centrosome duplication and checkpoint control, etc.. We were interested in fishing out the genes regulated by Brca1. Three pairs of mammary glands from Brca1 D11/D11;p53+/- mutant and control (p53+/-) mice at three different stages of the mammary cycle were analyzed by microarray for gene expression levels.

Background corr dist: KL-Divergence = 0.0156, L1-Distance = 0.0313, L2-Distance = 0.0012, Normal std = 0.8049

0.496 Kernel fit Pairwise Correlations Normal fit

Density 0.248

0.000 CEM 1

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

Pre-normalization Quantiles

02-07-05_Deng_Mouse430_2_79602-07-05_Deng_Mouse430_2_80102-07-05_Deng_Mouse430_2_I44202-07-05_Deng_Mouse430_2_I44305-24-04_Deng_Mouse430_2_1548 (0.0743524)05-24-04_Deng_Mouse430_2_T744 (0.0494084) (0.200771) (0.196021) (0.167894)[ min (0.311553) ] [ medium ] [ max ] CEM 1 Med14 1124.2 1191.3 1278.8 P ( S | Z, I ) = 0.67 Med21 141.2 586.2 766.3 Mean Corr = 0.59044 Med6 31.1 267.0 328.6 Cdk8 757.3 1021.7 1809.1 Ccnc 109.3 204.3 258.8 Med10 1567.7 1822.6 2045.3 Med23 336.1 594.6 780.4 Prpf40a 226.6 633.8 878.9 Rbm12 330.1 773.4 942.6 0610009D07Rik 1133.3 2553.4 3089.1 Srsf10 459.5 1149.3 1237.8 Ccdc58 393.9 662.5 735.5 CEM 1 + Pfdn4 902.8 1067.6 1473.9 Top 10 Genes Pno1 899.0 2231.8 2754.5 Orc6 106.6 475.4 616.2 Abce1 700.6 1765.9 2570.5 Magoh 1319.5 3536.5 4262.7

Null module GEO Series "GSE8322" 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=GSE8322 Status: Public on Mar 06 2008 Title: Identification of MCIP1 as an ATF6-inducible ER Stress Response Gene in the Heart by Gene Expression Profiling Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18319259 Summary & Design: Summary: We recently found that the endoplasmic reticulum (ER) stress response (ERSR) is activated in surviving cardiac myocytes in a mouse model of in vivo myocardial infarction. ATF6 is an ER stress-activated transcription factor that induces ERSR genes, some of which encode proteins that may protect against ischemic damage. However, few ERSR genes have been identified in the heart, and there have been no gene expression profiling studies of ATF6-inducible genes, in vivo. We previously generated transgenic (TG) mice that express tamoxifen-activated ATF6, ATF6-MER, in the heart; ATF6-MER conferred tamoxifen-dependent ATF6 activation and protection from ischemic damage. To understand of the mechanism of ATF6-mediated cardioprotection, gene expression profiling of ATF6-MER TG mouse hearts was performed. Activated ATF6 changed expression levels of 1,162 genes in the heart; of the 775 ATF6-inducible genes, only 23 are known ERSR genes. One of the genes not expected to be induced by ATF6 is modulatory calcinuerin-interacting protein-1 (MCIP1). MCIP1 is induced in a calcineurin/NFAT-dependent manner during myocardial hypertrophy and it can feedback inhibit cardiomyocyte growth. We found that MCIP1 expression in cultured cardiomyocytes was increased by the prototypical ER stresser, tunicamycin (TM), or by simulated ischemia. Moreover, infecting cardiomyocytes with adenovirus encoding activated ATF6 induced MCIP1 expression and inhibited myocyte growth in response to the alpha 1-adrenergic agonist, phenylephrine. These results suggest that MCIP1 can be induced in the heart by ER stresses, such as ischemia. Moreover, b integrating hypertrophy and ER stress, MCIP-modulated myocyte growth may help rejuvenate nascent ER protein folding, which could contribute to protection from ischemic damage.

Keywords: Gene expression analysis of the effect of activating ATF6 in the hearts of transgenic mice upon treatment with tamoxifen.

Overall design: 12 mice were analyzed in this study. Four treatment groups were included in this study: transgenic ATF6-MER mice treated with tamoxifen, transgenic ATF6-MER mice treated with vehicle, nontransgenic littermates treated with tamoxifen, and nontransgenic littermates treated with vehicle. Each treatment group included 3 separate biological replicate samples. Each mouse sampled was male, C57/BL6, ~30 weeks old. Each mouse was treated, then the mouse was sacrificed, the heart was extracted, and left ventricle was isolated. Total RNA was isolated from the left ventricle, and used for hybridization onto an Affymetrix mus 430 2.0 full-genome chip. Each heart was hybridized onto its own chip.

Background corr dist: KL-Divergence = 0.1158, L1-Distance = 0.0244, L2-Distance = 0.0009, Normal std = 0.4173

0.956 Kernel fit Pairwise Correlations Normal fit

Density 0.478

0.000 CEM 1

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

Pre-normalization Quantiles

ATF6-MERATF6-MER TG mouse_tamoxifen1ATF6-MER TG mouse_tamoxifen2ATF6-MER TG mouse_tamoxifen3ATF6-MER TG (0.145656) mouse_vehicle1ATF6-MER TG (0.117996) mouse_vehicle2NTG TG (0.124139)mouse_tamoxifen1 mouse_vehicle3NTG (0.0494326) mouse_tamoxifen2NTG (0.0747981) mouse_tamoxifen3NTG (0.0783025)(0.0760303) mouse_vehicle1NTG (0.0910051) mouseNTG (0.0536198) vehicle2mouse_vehicle3 (0.0861527) (0.0592) (0.0436674)[ min ] [ medium ] [ max ] CEM 1 Med14 275.2 411.5 582.3 P ( S | Z, I ) = 0.66 Med21 376.0 787.9 2222.9 Mean Corr = 0.41709 Med6 133.3 234.4 382.6 Cdk8 305.6 526.7 677.9 Ccnc 37.4 90.5 182.8 Med10 1206.5 2073.1 3062.4 Med23 157.4 325.8 472.4 Prpf40a 76.0 242.5 685.3 Rbm12 233.2 334.2 413.6 0610009D07Rik 1480.3 2344.9 4457.1 Srsf10 178.8 355.8 727.4 Ccdc58 820.5 1205.2 1868.1 CEM 1 + Pfdn4 1043.0 1220.4 1748.1 Top 10 Genes Pno1 1013.5 2074.2 5473.5 Orc6 79.5 251.0 388.1 Abce1 599.1 980.0 2063.5 Magoh 1312.9 2388.1 4577.0

Null module GEO Series "GSE6998" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 32 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6998 Status: Public on Feb 09 2007 Title: Expression profiling of developmental and regenerating liver in mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17227769 Summary & Design: Summary: Normal adult liver is uniquely capable of renewal

and repair after injury. Whether this response

represents simple hyperplasia of various liver elements

or requires recapitulation of the genetic program of

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

we examined transcriptional programs of

adult liver after partial hepatectomy and contrasted

these with developing embryonic liver. Principal component

analysis demonstrated that the time series of

gene expression during liver regeneration does not segregate

according to developmental transcription patterns.

Gene ontology analysis revealed that liver restoration

after hepatectomy and liver development differ

dramatically with regard to transcription factors

and chromatin structure modification. In contrast, the

tissues are similar with regard to proliferationassociated

genes. Consistent with these findings, realtime

polymerase chain reaction showed transcription

factors known to be important in liver development

are not induced during liver regeneration. These three

lines of evidence suggest that at a transcriptional level,

restoration of liver mass after injury is best described

as hepatocyte hyperplasia and not true regeneration.

We speculate this novel pattern of gene expression may

underlie the unique capacity of the liver to repair itself

after injury.

Keywords: time course

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

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

0.727 Kernel fit Pairwise Correlations Normal fit

Density 0.364

0.000 CEM 1

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

Pre-normalization Quantiles

baselinebaseline sampleregeneration sampleat T0,regeneration rep1 at T0, (0.0103297)sampleregeneration rep2 (0.0377722) sampleatregeneration T1, rep1 sampleatregeneration T1, (0.016781) rep2 sampleatregeneration T2, (0.0148279) rep1 sampleatregeneration T2, (0.0209214) rep2 sampleatregeneration T6, (0.0248387) rep1 sampleatregeneration T6, (0.0284285) rep2 sampleatregeneration T12, (0.02284) samplerep1atregeneration T12, (0.016578) samplerep2atregeneration T18, (0.0420602) samplerep1atregeneration T18, (0.0136954) samplerep2atregeneration T24, (0.0109158) samplerep1atregeneration T24, (0.0175478) samplerep2atregeneration T30, (0.0130033) samplerep1atregeneration T30, (0.0174397) samplerep2atregeneration T48, (0.0150054) samplerep1atdevelopmental T48, (0.0158542) samplerep2atdevelopmental T72, (0.0559192) rep1at developmentalsample T72, (0.013272) rep2 developmental sampleat T105,(0.0121825) developmental sampleat rep1 T105, (0.0594342) developmental sampleat rep2 T115, (0.0959175) developmental sampleat rep1 T115, (0.074405) developmental sampleat rep2 T125, (0.0923205) developmental sampleat rep1 T125, (0.033908) developmental sampleat rep2 T135, (0.0363149) developmental sampleat rep1 T135, (0.0328349) developmental sampleat rep2 T145, (0.0514366) sampleat rep1 T145, (0.0253488) sampleat rep2 T165, (0.0375163) at rep1 T165, (0.028081)[ rep2min (0.0122697) ] [ medium ] [ max ] CEM 1 Med14 363.4 547.9 1044.0 P ( S | Z, I ) = 0.62 Med21 132.2 361.9 654.1 Mean Corr = 0.33308 Med6 441.3 568.5 812.5 Cdk8 423.8 596.7 2172.3 Ccnc 272.4 416.0 613.9 Med10 723.0 1126.0 2434.8 Med23 86.8 253.2 775.6 Prpf40a 115.3 300.2 869.6 Rbm12 139.5 259.4 1252.7 0610009D07Rik 860.5 1615.2 3675.5 Srsf10 283.5 447.9 1148.8 Ccdc58 367.2 739.0 1412.3 CEM 1 + Pfdn4 552.6 889.5 2419.4 Top 10 Genes Pno1 804.6 1196.4 2506.1 Orc6 20.5 96.1 1346.4 Abce1 714.4 1029.5 2026.3 Magoh 941.3 1500.1 6003.1

Null module GEO Series "GSE36513" 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=GSE36513 Status: Public on Feb 18 2013 Title: Long noncoding RNA as regulatory switch of protein turnover Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24521543 Summary & Design: Summary: Long intervening noncoding RNAs (lincRNAs) are prevalent genes with poorly understood functions. Here we discover a pathway of lincRNA-regulated proteolysis. The enhancer-like lincRNA HOTTIP extends the half-life of its binding protein WDR5, a subunit of the MLL H3K4 methylase complex, resulting in increased chromatin occupancy and gene activation. LincRNA-mediated stabilization requires direct RNA-protein interaction in a long RNA context, and blocks turnover at a step after target protein poly-ubiquitination. We elucidate the lincRNA binding interface on WDR5. A WDR5 mutant that selectively abrogates lincRNA binding becomes unstable, and is defective in gene activation, maintenance of histone H3 lysine 4 trimethylation, and embryonic stem cell self renewal. The ability to modulate protein turnover may allow lincRNAs to control the lifespan of molecular interactions at chromatin and elsewhere, broadening their scope in epigenetics and cell fate control.

Overall design: Gene expression analysis: To establish a differentiation signature for mouse V6.5 ES cells infected with anti mouse WDR5 shRNA, rescued with doxycycline inducible WDR5 WT or WDR5 F266A, total RNA was isolated in biologic duplicate from cells in different conditions and hybridized to Affymetrix Mouse 430 2.0 arrays.

Background corr dist: KL-Divergence = 0.0512, L1-Distance = 0.0247, L2-Distance = 0.0007, Normal std = 0.5684

0.721 Kernel fit Pairwise Correlations Normal fit

Density 0.360

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

WDR5_WT_dox_rep1WDR5_WT_dox_rep2WDR5_WT_NOdox_rep1 (0.21833)WDR5_WT_NOdox_rep2 (0.188411)WDR5_F266A_dox_rep1WDR5_F266A_dox_rep2 (0.0533584)WDR5_F266A_NOdox_rep1 (0.0319268)WDR5_F266A_NOdox_rep2 (0.0161003) (0.0716192) (0.134806) (0.285448)[ min ] [ medium ] [ max ] CEM 1 Med14 664.4 981.9 1488.1 P ( S | Z, I ) = 0.61 Med21 1314.2 1393.4 1513.9 Mean Corr = 0.27582 Med6 585.2 636.1 692.3 Cdk8 2414.6 2839.0 3102.8 Ccnc 222.3 290.0 365.3 Med10 1890.2 2228.1 2522.6 Med23 775.9 882.2 897.3 Prpf40a 867.3 1100.4 1355.4 Rbm12 1559.5 1938.9 2239.1 0610009D07Rik 6572.2 7091.7 7645.9 Srsf10 773.3 908.6 1114.4 Ccdc58 2677.7 3358.7 3838.3 CEM 1 + Pfdn4 3127.4 3383.8 3640.0 Top 10 Genes Pno1 3861.2 4627.9 4986.2 Orc6 2580.9 2845.8 3726.7 Abce1 4090.3 4423.9 5090.0 Magoh 8507.9 10471.4 11590.8

Null module GEO Series "GSE27605" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27605 Status: Public on Mar 14 2011 Title: The intestinal stem cell signature identifies colorectal cancer stem cells and predicts disease relapse Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21419747 Summary & Design: Summary: Using EphB2 or the ISC marker Lgr5, we have FACS-purified and profiled intestinal stem cells (ISCs), crypt proliferative progenitors and late transient amplifying cells to define a gene expression program specific for normal ISCs.

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

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

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

0.614 Kernel fit Pairwise Correlations Normal fit

Density 0.307

0.000 CEM 1

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

Pre-normalization Quantiles

intestine-Lgr5High-R1intestine-Lgr5Low-R1intestine-EphB2High-R1 intestine-EphB2Medium-R1(0.100859) (0.0465747)intestine-EphB2Low-R1intestine-EphB2High-R2 (0.0633448)intestine-EphB2Medium-R2 (0.0431083)intestine-EphB2Low-R2 (0.164977) (0.136947) (0.133201) (0.310988)[ min ] [ medium ] [ max ] CEM 1 Med14 807.3 1499.9 1662.8 P ( S | Z, I ) = 0.41 Med21 1492.7 2386.4 2925.8 Mean Corr = 0.58991 Med6 1173.8 1683.4 1919.8 Cdk8 3614.5 3970.7 4222.0 Ccnc 343.7 368.5 497.2 Med10 1650.1 1980.0 2255.2 Med23 658.1 815.8 902.1 Prpf40a 142.9 171.6 217.2 Rbm12 695.2 1049.5 1169.0 0610009D07Rik 3664.1 4903.7 5684.2 Srsf10 549.6 967.5 1165.8 Ccdc58 3172.1 4552.5 4691.5 CEM 1 + Pfdn4 507.2 1034.9 1125.2 Top 10 Genes Pno1 919.7 1498.0 1728.5 Orc6 686.1 2469.3 2743.2 Abce1 1693.4 4590.7 5780.8 Magoh 2834.2 4260.7 4758.4

Null module GEO Series "GSE43373" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 130 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

Details of this dataset are not shown due to large number of samples and the page size limit. Find details in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43373

Background corr dist: KL-Divergence = 0.1128, L1-Distance = 0.0557, L2-Distance = 0.0090, Normal std = 0.4228 GEO Series "GSE10210" 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=GSE10210 Status: Public on Jul 14 2008 Title: Gene expression analysis of embryonic stem cells expressing VE-cadherin (CD144) during endothelial differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18498633 Summary & Design: Summary: Endothelial differentiation occurs during normal vascular development in the developing embryo. Mouse embryonic stem (ES) cells were used to further define the molecular mechanisms of endothelial differentiation. By flow cytometry a population of VEGF-R2 positive cells was identified as early as 2.5 days after differentiation of ES cells, and a subset of VEGF-R2 + cells, that were CD41+ positive at 3.5 days. A separate population of VEGF-R2+ stem cells expressing the endothelial-specific marker CD144 (VE-cadherin) was also identified at this same time point. Microarray analysis of >45,000 transcripts was performed on RNA obtained from cells expressing VEGF-R2, CD41, and CD144.

Keywords: expression analysis

Overall design: We identified four populations of cells; cells expressing VEGF-R2 (day 2.5), CD41 expressing cells (day 3.5), cells expressing CD144 (VE-Cadherin, day 3.5), and cells expressing CD144 (day 6.5). In addition to this, we have also obtained the negative control cells at each time such as VEGF-R2 (day 2.5) negative, CD41 negative (day 3.5), CD144 negative (VE-Cadherin, day 3.5), and negative CD144 (day 6.5). RNA for the microarray experiments were obtained in duplicate from two separately conducted experiments using the murine embryonic stem cells..

Background corr dist: KL-Divergence = 0.0996, L1-Distance = 0.0266, L2-Distance = 0.0013, Normal std = 0.4386

0.910 Kernel fit Pairwise Correlations Normal fit

Density 0.455

0.000 CEM 1

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

Pre-normalization Quantiles

HB1 (0.0514346)HB2 (0.104353)HP1 (0.0459577)HP2 (0.0374553)AB1 (0.0578079)AB2 (0.0930244)ET1 (0.0420296)ET2 (0.0859692)NHB2 (0.0837748)NHB1 (0.08041)NAB2 (0.0482702)NET1 (0.0491028)NET2 (0.0562048)NAB1 (0.0693344)NHP2 (0.0515233)NHP1 (0.0433479) [ min ] [ medium ] [ max ] CEM 1 Med14 559.1 1019.2 2215.0 P ( S | Z, I ) = 0.38 Med21 872.5 1166.5 1787.1 Mean Corr = -0.06074 Med6 612.0 835.3 2373.2 Cdk8 1518.1 3330.8 4518.8 Ccnc 74.4 158.8 226.0 Med10 2348.6 3631.8 6068.1 Med23 722.9 872.2 1186.0 Prpf40a 776.8 1113.8 1303.5 Rbm12 870.2 2158.8 2620.8 0610009D07Rik 3972.5 5843.4 8753.7 Srsf10 535.8 1020.3 1442.8 Ccdc58 3441.2 4971.3 7997.4 CEM 1 + Pfdn4 2965.4 3967.8 7310.8 Top 10 Genes Pno1 2900.1 6398.4 9643.2 Orc6 1619.8 2224.8 4493.8 Abce1 2053.8 3073.9 3864.9 Magoh 8302.7 10787.9 22288.4

Null module GEO Series "GSE15325" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 23 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15325 Status: Public on Mar 01 2010 Title: MEF-mKras-WT1 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: K-ras is one of the most frequently mutated human oncogenes. Activation of K-ras can lead to either senescence or proliferation in primary cells. The precise mechanism governing these distinct outcomes remains unclear. Here we utilized a loss-of-function screen to assess the role of specific genes identified as potential key regulators of K-ras driven oncogenesis. Using this approach, we identify the transcription factor Wt1 as an inhibitor of senescence in primary cells expressing oncogenic K-ras. Deletion or suppression of Wt1 expression leads to senescence of primary cells expressing oncogenic K-ras under the control of the native promotor at physiological levels, but has no effect on cells expressing wild-type K-ras. Wt1 contributes to K-ras driven lung tumorigenesis in vivo and loss of Wt1 is specifically deleterious to human lung cancer cell lines that are dependent on oncogenic K-ras. Taken together, these observations reveal a novel role for Wt1 as a key regulator of the complex genetic network required for the oncogenic effect of the small GTPase K-ras.

We compare the expression profiles of Wild type, K-ras mutant, Wt1-null, and double K-ras mutant/Wt1-null mouse embryonic fibroblasts (MEFs). The study provides insights into the transcriptional role of Wt1 in the context of oncogenic K-ras.

Overall design: MEFs were infected with adenoviral Cre to activate K-ras (6 samples), knockout Wt1 (5 samples), both activate K-ras and knockout Wt1 (7 samples). As a control, MEFs were infected with adenoviral GFP (5 samples). RNA was isolated using Trizol 7 days after infection. RNA was further prepared by passage over an RNeasy column. cDNA synthesis, biotinylation of cRNA and hybridization to mouse Genechip 430A v2 containing 39,000 probes was performed according to the manufacturer's instructions (Affymetrix, Santa Clara). Microarray data was normalized with Expression Console software (Affymetrix, Santa Clara) using RMA algorithms.

Background corr dist: KL-Divergence = 0.0997, L1-Distance = 0.0402, L2-Distance = 0.0035, Normal std = 0.4350

0.917 Kernel fit Pairwise Correlations Normal fit

Density 0.459

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

mKras-MEFs-1mKras-MEFs-2 Wt1-null(0.0202103) Wt1-null(0.0584634) MEFs-1Wt1-null MEFs-2 (0.00528919)Wt1-null MEFs-3 (0.00901385)Wt1-null MEFs-4 (0.0771786)MEFs-1 MEFs-5 (0.0537886)MEFs-2 (0.0451669) (0.0298832)MEFs-3 (0.01752)MEFs-4 (0.00957472)MEFs-5 (0.0116497)mKras-MEFs-3 (0.0154921)mKras-MEFs-4 mKras-MEFs-5(0.0194164) mKras-MEFs-6(0.176189) mKras-Wt1(0.0119801) mKras-Wt1(0.00809631) null-MEFs-1mKras-Wt1 null-MEFs-2mKras-Wt1 (0.0491635) null-MEFs-3mKras-Wt1 (0.0163677) null-MEFs-4mKras-Wt1 (0.0186004) null-MEFs-5mKras-Wt1 (0.301279) null-MEFs-6 (0.0109608) null-MEFs-7 (0.0296229) (0.00509393)[ min ] [ medium ] [ max ] CEM 1 Med14 488.8 1043.4 1628.8 P ( S | Z, I ) = 0.33 Med21 172.8 1010.9 1332.4 Mean Corr = 0.18975 Med6 138.9 690.8 960.4 Cdk8 597.4 1208.8 2038.2 Ccnc 38.7 218.7 321.4 Med10 1425.6 2754.0 3396.6 Med23 448.1 586.9 1618.0 Prpf40a 141.3 794.5 982.1 Rbm12 745.3 1068.3 1529.5 0610009D07Rik 1864.4 4441.4 4811.3 Srsf10 153.3 742.4 1305.5 Ccdc58 550.2 889.6 1263.9 CEM 1 + Pfdn4 292.2 1619.7 2620.8 Top 10 Genes Pno1 608.5 2138.3 3373.2 Orc6 224.9 779.8 1395.8 Abce1 483.4 2758.4 3679.0 Magoh 1175.4 5053.6 6795.5

Null module