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: 13 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. Aldh6a1 Suclg2 Suclg1 Sucla2 Acacb Acss1 Acss2 Mlycd Hibch Mcee Num ofGenesinQueryGeneset:13.CEMs:1. Overview ofCo-ExpressionModules(CEMs)withDatasetWeighting Pccb Pcca Mut

Pcca Aldh6a1 Mut Mcee Pccb Suclg1 Suclg2 Acss2 Hibch Mlycd Acacb Acss1 Sucla2 Singletons CEM 1(232datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page1 Aldh6a1 Bckdhb Bckdha Acad11 Uqcrc2 Ndufv1 Ndufa9 Ndufs1 Rmdn1 Hibadh Adhfe1 Ndufs3 Acadm Suclg2 Suclg1 Acadvl Hadhb Mccc1 Retsat Adck3 Acacb Acaa2 Echs1 Acss1 Acss2 Mlycd Decr1 Hibch Cisd1 Acat1 Vwa8 Gcdh Etfdh Mcee Hint2 Hadh Coq9 Sdhc Phyh Sdha Clybl Ech1 Pccb Pcca Cpt2 Eci1 Etfb Etfa Mut Ivd 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE16110 [16] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE13302 [30] GSE13071 [15] GSE46496 [9] GSE52597 [7] GSE41759 [14] GSE7424 [8] GSE51483 [45] GSE20152 [8] GSE3126 [6] GSE15729 [15] GSE46209 [21] GSE13224 [6] GSE50813 [24] GSE13432 [12] GSE51080 [18] GSE23006 [48] GSE31208 [8] GSE43825 [31] GSE3313 [24] GSE34839 [6] GSE7111 [6] GSE38831 [7] GSE10589 [6] GSE48338 [8] GSE20696 [8] GSE39766 [6] GSE13044 [59] GSE26671 [12] GSE50439 [15] GSE14891 [8] GSE52474 [154] GSE11291 [60] GSE8249 [46] GSE8044 [6] GSE23833 [12] GSE3530 [36] GSE28559 [30] GSE19668 [50] GSE39886 [24] GSE17796 [39] GSE41907 [7] GSE25295 [25] GSE42049 [8] GSE49128 [17] GSE13874 [14] GSE13873 [27] GSE3837 [12] GSE24489 [14] GSE17266 [59] GSE43779 [6] GSE3889 [20] GSE17297 [32] GSE51365 [28] GSE37546 [20] GSE10246 [182] GSE39621 [51] GSE28593 [9] GSE17794 [44] GSE17923 [6] GSE31106 [18] GSE48790 [8] GSE24243 [6] GSE43373 [130] GSE18907 [12] GSE33156 [18] GSE16675 [72] GSE9441 [36] GSE49346 [6] GSE17097 [20] GSE22086 [6] GSE46185 [6] GSE31004 [8] GSE8679 [12] GSE9368 [12] GSE4230 [8] GSE38754 [40] GSE20426 [35] GSE34351 [12] GSE28417 [12] GSE10192 [24] GSE56236 [12] GSE4671 [28] GSE9954 [70] GSE44261 [12] GSE32937 [8] GSE50794 [60] GSE1479 [36] GSE21836 [8] GSE30485 [15] GSE15315 [6] GSE20235 [6] GSE30688 [9] GSE19004 [9] GSE11186 [33] GSE17825 [18] GSE48884 [12] GSE19925 [6] GSE10525 [18] GSE28091 [12] GSE17096 [20] GSE24207 [73] GSE41925 [8] GSE16902 [21] GSE6998 [32] GSE9338 [42] GSE11990 [20] GSE25640 [12] GSE1871 [12] GSE53077 [8] GSE48811 [20] GSE14004 [9] GSE23584 [36] GSE44091 [32] GSE5500 [21] GSE33891 [19] GSE15914 [9] GSE45051 [18] GSE33341 [227] GSE5371 [8] GSE31166 [6] GSE24203 [8] GSE42877 [14] GSE44363 [16] GSE39562 [26] GSE22124 [18] GSE1986 [17] GSE19299 [6] GSE54349 [6] GSE9297 [27] GSE24625 [12] GSE9012 [10] GSE29813 [18] GSE45028 [22] GSE36826 [12] GSE20302 [12] GSE12881 [6] GSE43145 [12] GSE23408 [39] GSE18745 [6] GSE43556 [8] GSE47414 [18] GSE48935 [12] GSE59437 [30] GSE41558 [8] GSE6383 [6] GSE11201 [18] GSE14769 [24] GSE1435 [27] GSE16377 [6] GSE26745 [24] GSE39273 [6] CEM+ CEM GSE23782 [18] GSE8949 [20] GSE32986 [18] GSE11628 [12] GSE13149 [25] GSE51628 [15] 0.0 GSE24695 [9] GSE8039 [32]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 182.94 182.96 184.83 185.63 186.07 186.82 187.46 187.83 188.44 189.05 196.35 199.86 202.64 203.04 204.09 207.08 209.07 211.10 214.23 218.28 220.30 221.01 222.29 222.29 222.62 224.99 229.13 229.20 230.41 233.48 233.64 238.69 242.18 247.54 252.37 259.01 259.18 267.72 1.0 Notes C030006K11Rik 1110001J03Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page2 Hsd17b10 Fam195a Chchd10 Hsd17b4 Macrod1 Ndufb11 Ndufb10 Uqcrfs1 Ehhadh Echdc3 Immp2l H2-Ke6 Ndufb3 Ndufb9 Ndufb5 Uqcr11 Ndufs8 Ndufv2 Ndufs7 Ndufa6 Ndufv3 Akr7a5 Atp5c1 Acot13 Pxmp2 Hadha Ephx2 Acox1 Acads Pank1 Fahd1 Gstk1 Oxld1 Aifm1 Ccbl2 Trap1 Gstz1 Mpc1 Sdhd Cmbl Pdk2 Cyc1 Pex7 Cbr4 Sirt3 Ak3 Fh1 Dbt 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 140.32 141.04 141.36 141.87 142.51 143.39 144.04 144.38 144.50 144.77 146.40 146.80 147.05 147.43 148.58 149.04 150.12 150.23 151.17 152.05 152.09 154.85 155.19 156.03 156.09 156.19 156.61 156.74 156.93 159.55 159.96 160.93 162.70 163.00 165.06 166.62 167.41 168.16 168.36 168.83 169.67 169.77 170.99 172.44 173.00 174.27 178.68 180.32 181.21 181.22 1.0 Notes Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page3 Tmem135 Slc25a11 Ndufaf1 Acadsb Acad10 Echdc1 Fahd2a Ndufb6 Uqcrc1 Ndufa3 Nudt12 Ndufa8 Ndufs2 Ndufc1 Pmpcb Atp5a1 Dcaf11 Pet112 Mrpl42 Amacr Atp5f1 Endog Atp5j2 Abcd3 Pdha1 Fbxo8 Tcaim Uqcrb Mipep Lace1 Gpam Ppara Grhpr Acadl Fars2 Idh3g Pyurf Apoo Hint3 Pdhb Aco2 Ppa2 Ecsit Qdpr Fdx1 Sirt5 Cluh Dlat Ddt Cat 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 108.43 108.47 110.09 110.45 110.46 110.68 110.84 110.98 112.62 113.58 114.08 115.08 115.27 116.46 117.13 117.19 117.39 118.26 118.46 118.55 119.07 119.25 120.07 120.67 121.00 121.15 121.20 121.24 121.48 121.76 121.84 123.81 125.93 128.37 129.08 129.90 130.41 131.02 131.34 131.85 132.54 132.84 132.90 133.01 133.95 135.10 135.69 136.60 139.72 139.78 1.0 Notes Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page4 Tmem205 Slc25a42 Slc25a20 Osbpl1a Aldh4a1 Smim19 D2hgdh L2hgdh Mrps35 Ddrgk1 Ndufa1 Rmnd1 Ndufa5 Higd2a Pxmp4 Pnpla8 Lactb2 Mccc2 Rdh14 Ces1d Pex19 Ndrg2 Mmaa Dhrs4 Mlxipl Atp5h Atp5b Nubpl Chpt1 Prdx3 Bola3 Acsl1 Hacl1 Lpin1 Mtfp1 Ptgr2 Mavs Suox Msra Sord Cryz Selo Eci2 Crat Adk Nit2 Nit1 Pcx Dld Tst 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 87.30 87.32 87.35 87.77 88.17 88.43 89.05 89.28 89.38 89.99 90.10 90.14 90.45 90.47 90.89 93.13 93.15 93.35 93.41 93.60 93.87 94.17 95.15 95.65 96.44 96.55 97.12 97.84 97.95 98.71 98.77 99.11 99.82 100.20 100.28 100.30 101.67 103.05 103.41 104.12 104.25 104.26 104.38 104.67 106.09 106.33 107.02 107.42 107.50 107.76 1.0 Notes 4931406C07Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page5 BC004004 Slc25a16 Abhd14b Mmachc Ndufa13 Gm5617 Dnajc15 Fastkd1 Ggnbp1 Slc37a4 Oxnad1 Poldip2 Pex11a Apopt1 Ndufa4 Trmt2b Entpd5 Aamdc Cox4i1 Abcb8 Hmgcl Cox6c Akap1 Uqcc1 Coasy Fbxo3 Ghitm Oplah Atp5d Apool Sar1b Fuom Emc9 Fitm2 Fmo1 Flad1 Gfm2 Gbe1 Hagh Coq3 Atp5j Sod2 Klf15 Aco1 Clpb Clpx Tecr Fah Dbi 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 74.67 74.72 75.44 77.33 78.07 78.26 78.45 78.99 79.37 79.64 79.72 79.77 80.35 80.46 80.67 80.77 81.08 81.15 81.24 81.52 81.55 81.56 81.71 81.96 82.01 82.07 82.12 82.48 82.63 82.86 82.96 82.98 82.99 83.09 83.18 83.35 83.40 83.62 84.21 84.27 84.37 84.56 84.67 84.84 85.93 86.31 86.50 86.87 86.88 87.13 1.0 Notes B230118H07Rik 9030617O03Rik 2300009A05Rik 2310039H08Rik 1110058L19Rik 2310061I04Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page6 Selenbp1 Fam210a Anapc13 Samm50 Mettl7a2 Aldh5a1 Ndufaf6 Rtn4ip1 Cox6b1 Coq10a Cox7a2 Cox7a1 S100a1 Hrsp12 Ndufa7 Gm561 Alkbh7 Stradb Acad8 Msrb2 Fxyd1 Marc2 Mmab Nudt8 Thrsp Acsf3 Mrpl2 Idh3a Maob Gpd1 Galm Coq6 Atp5l Coq5 Ldhd Lmf1 Iars2 Mtg1 Iscu Ddo Rilp Dlst C8g Ghr 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 57.14 57.62 57.77 58.42 59.51 59.55 59.96 60.11 60.48 60.65 60.95 61.26 61.91 61.94 62.20 62.82 63.78 63.80 64.67 65.08 65.52 65.81 65.95 66.82 67.31 67.44 67.79 68.31 68.54 68.88 69.28 69.95 69.97 70.23 70.86 71.03 71.17 71.44 71.61 71.70 71.91 72.07 72.13 72.40 72.73 73.40 73.47 73.65 74.31 74.64 1.0 Notes 0610009B22Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page7 Ppargc1b Slc25a35 Apoa1bp L3hypdh Cyp27a1 Tmem70 Osgepl1 Foxred1 Synj2bp Pm20d1 Timm21 Mrps16 Mrps31 Mrps36 Ndufb7 Uqcr10 Smim8 Thnsl2 Mrpl39 Mrpl34 Grpel1 Lrpprc As3mt Abcb6 Atp5sl Cox5a Pcbd2 Zadh2 Uqcrh Gnpat Tcea3 Nudt6 Atp5k Dgat2 Vegfb Amy1 Bcs1l Surf1 Coq7 Acp6 Pdhx Acy3 Plin5 Mfn2 Lias Galt Khk Ccs Pts 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 40.35 40.83 41.06 41.17 41.83 41.87 42.31 42.82 43.01 44.41 44.46 44.71 45.19 46.36 46.43 46.59 47.15 47.22 47.23 47.28 47.52 47.65 47.69 48.01 48.21 48.32 48.60 48.85 50.76 50.93 51.63 51.88 52.87 52.97 54.31 54.33 54.37 54.74 54.86 55.33 55.67 55.72 55.78 55.85 56.24 56.28 56.42 56.49 56.50 56.91 1.0 Notes 1700021F05Rik 0610011F06Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page8 Tmem147 AI317395 AI462493 AI464131 Aurkaip1 Sepsecs Znrd1as Slc47a1 Ndufaf3 Cpped1 Abhd11 Sult1a1 Mrps21 Mrps24 Dhtkd1 Agpat3 Atp5g2 Akr1e1 Ptges2 Mrpl16 Mrpl48 Mrpl27 Mrpl55 Slc2a4 Ginm1 Gstm7 Atpaf1 Vdac1 Tarsl2 Prodh Lars2 Mrpl4 Gphn Serhl Cdo1 Dpyd Phkb Acn9 Aspa Deb1 Tufm Lipt1 Fggy Txn2 Mecr Mfn1 Urod Clpp 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 27.91 28.39 28.80 29.20 29.79 30.14 30.45 30.49 30.71 31.06 31.29 31.42 31.82 31.87 32.18 32.20 32.36 32.72 32.74 32.78 32.81 32.86 32.87 32.96 33.58 33.80 33.94 34.28 34.62 34.69 35.14 35.15 35.54 36.22 36.29 36.63 36.65 36.75 37.17 37.33 37.94 37.94 38.13 38.44 39.13 39.21 39.53 39.70 39.95 40.08 1.0 Notes 2700089E24Rik 2010107E04Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page9 Tmem223 Lamtor2 Lamtor4 Aldh9a1 Dnajc30 Nmnat1 Tysnd1 Tm7sf2 Immp1l Ogfod3 Dhrs7b Agpat2 Usmg5 Mrpl12 Mrpl14 Mrpl28 Mrpl10 Gstm4 Gucd1 Dram2 Cox20 Cgrrf1 Atraid Car14 Prosc Atp5s Bnip3 Park7 Ces1f Pink1 Pcyt2 Gstt2 Dhdh Isca2 Ganc Mkks Adh1 Scp2 Pck1 Pex6 Mtif2 Mto1 Uros Ubr3 Mcat Cutc Dolk Idh1 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 15.80 15.92 16.35 16.79 17.32 17.40 17.92 17.99 18.54 18.59 18.67 18.70 18.74 18.95 19.06 19.36 19.54 19.56 19.79 20.08 20.31 20.36 20.37 21.33 21.69 22.00 22.46 22.52 22.59 22.83 23.07 23.33 23.88 24.04 24.04 24.41 24.53 25.90 25.98 26.03 26.17 26.33 26.65 27.02 27.02 27.11 27.42 27.51 27.51 27.59 1.0 Notes Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page10 Tmem126a Fam213b Ccpg1os Tmem53 Ndufa10 Cyp4f13 Slc46a3 Cyb5d2 Echdc2 Mrps34 Dhrs11 Malsu1 Atp5g3 Atp5g1 Nudt19 Prkaa2 Dnajc4 Acsm3 Tmco1 Polrmt Jmjd8 Mfsd3 Agmo Idh3b Lactb Fmo5 Fbxl4 Ttc36 Mdh2 Ugp2 Nqo2 Cog4 Coq2 Cml1 Ldhb Tob1 Pex1 Pex3 Fn3k Cbr1 Apip Adi1 Svip Pstk Me1 Glul Aes Spr Lpl Cs 0.0 1.0

GSE2019 [12] GSE10989 [6]

GSE7309 [12] Scale ofaveragePearsoncorrelations GSE42061 [12] GSE50729 [6] GSE36513 [8] GSE3501 [6] GSE11382 [10] GSE39916 [6] 0.2 GSE3843 [8] GSE6837 [8] GSE21224 [16] GSE7487 [24] GSE58307 [20] GSE10634 [16] GSE10902 [6] GSE9566 [38] GSE8681 [25] 0.4 GSE29929 [14] GSE40156 [42] GSE27378 [8] GSE24920 [19] GSE18534 [15] GSE38574 [32] GSE43059 [8] GSE33942 [12] GSE59672 [12] 0.6 GSE11898 [9] GSE21716 [28] GSE5313 [6] GSE53986 [16] GSE8966 [12] GSE5657 [20] GSE36569 [6] GSE18224 [32] GSE9892 [12] 0.8 GSE7430 [12] GSE32095 [24] GSE27455 [12] GSE33446 [18] Score 5.04 5.06 5.29 5.55 6.05 6.07 6.64 6.68 6.68 7.36 7.48 7.56 7.79 7.91 7.96 8.07 8.33 8.49 8.63 8.66 8.69 8.79 9.22 9.69 9.71 10.14 10.36 10.61 10.72 10.78 10.87 11.03 11.83 11.88 12.04 12.19 12.36 12.95 13.02 13.40 13.68 14.18 14.82 14.87 15.08 15.12 15.28 15.66 15.74 15.76 1.0 Notes 2610507B11Rik Symbol Num ofCEMGenes:12.Predicted516.SelectedDatasets:232.Strength:9.0 CEM 1,Geneset"[K]Propanoatemetabolism",Page11 Tmem242 Zfyve21 Stard10 Acaa1b Ndufa2 Pafah2 Tmed4 Mrpl50 Naprt1 Abhd3 Pfkfb1 Mgst3 Carkd Magix Decr2 Atg10 Ngly1 Bcat2 Ethe1 Adtrp Tmx2 Gstt1 Isca1 Csad Cycs Rorc ND5 0.0 1.0

GSE2019 [12] GSE10989 [6]

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE2019 Status: Public on Dec 21 2004 Title: Microarray Based Comparison of three Amplification Methods For Nanogram Amounts of Total RNA Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 15613496 Summary & Design: Summary: Two T7 based methods One round of Amplification (Affymetrix) and Two round of Amplification were compared to two Ribo-SPIA based systems, RiboSPIA and pico Ribo SPIA systems. Data for Pico-RiboSPIA are listed here.

All Hybridisation were performed using Affymetrix Mouse 430-2 gene chips. Data were all scaled to 500.

For 12 chips performed with pico Ribo SPIA the scaling factor average was 2.0 +/- 0.3, background intensities 74.4 +/- 12.7 , noise 3.9 +/- 0.6, rawQ 2.5 +/- 0.3

Keywords: ordered

Overall design:

Background corr dist: KL-Divergence = 0.0933, L1-Distance = 0.0666, L2-Distance = 0.0072, Normal std = 0.5386

0.832 Kernel fit Pairwise Correlations Normal fit

Density 0.416

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 Kidneymouse KidneymousepRS 10 KidneymousepRSng -1 10 (0.231591) referencemousepRSng -2 10 (0.228837) referencemouseng pRS -3 (0.195226) 10referencemouse pRSng -1 10referencemouse (0.029218) pRSng -2 10referencemouse (0.0358844) pRSng -3 3referencemouse (0.0284921) ng pRS -1 (0.0903334)3referencemouse ng pRS -2 (0.031421)3referencemouse ng pRS -3 (0.0270744)0.3reference pRS ng -1 0.3 (0.0511218) pRS ng -2 0.3 (0.0229842) ng -3[ (0.0278168) min ] [ medium ] [ max ] CEM 1 Pcca 2.0 229.0 1647.6 P ( S | Z, I ) = 1.00 Aldh6a1 69.2 504.7 7390.8 Mean Corr = 0.92393 Mut 29.0 197.0 1145.9 Mcee 447.5 829.3 3617.6 Pccb 53.8 223.3 1317.1 Suclg1 968.1 1122.1 5056.8 Suclg2 359.2 548.0 3353.9 Acss2 68.7 299.1 3367.9 Hibch 94.8 145.2 263.6 Mlycd 17.5 114.7 306.6 Acacb 176.3 484.6 1156.3 Acss1 818.0 1321.6 7280.5 Echs1 423.4 576.1 1797.8 Hibadh 254.4 404.6 3143.8 Clybl 87.1 371.1 1370.7 Acadm 422.9 824.6 7706.7 Coq9 305.7 499.8 1544.4 CEM 1 + Hadh 7166.3 10293.3 11080.4 Top 10 Genes Decr1 44.7 277.9 3498.7 Mccc1 199.3 699.6 2327.2 Sdha 1352.9 2320.6 5927.7 Ivd 61.9 291.4 1688.0

Null module Sucla2 GEO Series "GSE10989" 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=GSE10989 Status: Public on Dec 22 2010 Title: Expression data of cystic renal epithelial tissue from mice deficient for fumarate hydratase. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Fumarate hydratase (FH) mutations cause hereditary leiomyomatosis and renal cell cancer (HLRCC). We have conditionally inactivated the murine ortholog (Fh1) in renal tubular epithelial cells in order to generate an in vivo model of HLRCC. Fh1 knockout mice recapitulates important aspects of HLRCC including the development of renal cysts that overexpress hypoxia inducible factor alpha (Hifa) and Hif-target genes.

We used microarrays to detail the global programme of gene expression underlying cyst development in Fh1 knockout mice and identified distinct classes of up-regulated genes during this process.

Keywords: gene expression, comparison (wild-type n=3 vs knockout n=3)

Overall design: Renal epithelial tissue was macro-dissected from Fh1 knockout mice and sex-matched litter mate control disease-free animals for RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0186, L1-Distance = 0.0758, L2-Distance = 0.0076, Normal std = 0.9701

0.411 Kernel fit Pairwise Correlations Normal fit

Density 0.206

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 mousewild-type kidneymouseknockout -kidneymouse 1 (0.150482)knockout -kidneymouse 2 (0.168399)knockout -kidneymouse 3 (0.219987) -kidneymouse 1 (0.157016) -kidney 2 (0.162535) - 3 (0.14158)[ min ] [ medium ] [ max ] CEM 1 Pcca 3027.0 5839.0 6343.7 P ( S | Z, I ) = 1.00 Aldh6a1 6306.0 14079.0 14896.1 Mean Corr = 0.91681 Mut 3629.8 8862.0 9233.4 Mcee 1137.7 2244.7 2521.9 Pccb 1915.5 3854.8 4557.5 Suclg1 5103.0 8782.4 9876.3 Suclg2 1590.1 2830.5 3411.3 Acss2 3810.2 5349.1 10801.6 Hibch 113.1 251.2 338.6 Mlycd 354.5 668.5 859.6 Acacb 139.5 342.7 444.1 Acss1 889.0 3473.7 4825.0 Echs1 2931.2 5934.7 7951.8 Hibadh 5148.1 12412.6 13741.4 Clybl 1748.4 3509.7 3674.4 Acadm 9019.8 18043.5 25948.4 Coq9 1995.4 3974.1 4361.9 CEM 1 + Hadh 5938.1 12206.6 14100.5 Top 10 Genes Decr1 3873.8 6100.1 7520.7 Mccc1 1660.1 3200.7 4900.1 Sdha 7299.7 12154.6 12728.0 Ivd 1813.9 5637.7 9230.8

Null module Sucla2 GEO Series "GSE16110" 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=GSE16110 Status: Public on Jul 01 2009 Title: Altered mouse mammary gland gene expression and tumor growth following chronic social isolation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Clinical studies have revealed that social support improves the outcome of cancer patients while epidemiological studies suggest that social isolation increases the risk of death associated with several chronic diseases. However, the precise biological consequences of an unfavorable social environment have not been defined. To do so, robust, reproducible pre-clinical models are needed to study the mechanisms whereby an adverse environment impacts on gene expression and cancer biology. Because random assignment of inbred laboratory mice to well-defined social environments allows accurate and repeated measurements of behavioral and endocrine parameters, transgenic mice provide a pre-clinical framework with which to begin to determine gene-environment mechanisms. In this study, we found that female C3(1)/SV40 T-antigen mice deprived of social interaction from weaning exhibited increased expression of genes encoding key metabolic pathway enzymes in the pre-malignant mammary gland. Chronic social isolation was associated with upregulated fatty acid synthesis and glycolytic pathway gene expression - both pathways known to contribute to increased breast cancer growth. Consistent with the expression of metabolic genes, isolated mice subsequently developed significantly larger mammary gland tumors compared to group-housed mice. Endocrine evaluation confirmed that isolated mice developed a heightened corticosterone stress response compared to group-housed mice. Together, these transdisciplinary studies show for the first time that an adverse social environment is associated with altered mammary gland gene expression and tumor growth. Moreover, the identification of specific alterations in metabolic pathways favoring tumor growth suggests potential molecular biomarkers and/or targets (e.g. fatty acid synthesis) for preventive intervention in breast cancer.

Overall design: SV40 Tag mice we isolated or grouped at weaning. Mouse mammary glands were rapidly excised at necropsy and immediatley flash frozen to detect difference in gene expression between thoraci MG from isolated versus group-housed female mice.

Background corr dist: KL-Divergence = 0.0385, L1-Distance = 0.0261, L2-Distance = 0.0009, Normal std = 0.6020

0.663 Kernel fit Pairwise Correlations Normal fit

Density 0.331

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_Group_15w_Rep1Mouse_Group_15w_Rep2Mouse_Group_15w_Rep3Mouse_Group_15w_Rep4 (0.0313036)Mouse_Iso_15w_Rep1 (0.0451351)Mouse_Iso_15w_Rep2 (0.158005)Mouse_Iso_15w_Rep3 (0.015508)Mouse_Iso_15w_Rep4 (0.0409528)Mouse_Group_20w_Rep1 (0.0577427)Mouse_Group_20w_Rep2 (0.0775414)Mouse_Group_20w_Rep3 (0.0698858)Mouse_Group_20w_Rep4 (0.0523826)Mouse_Iso_20w_Rep1 (0.0325949)Mouse_Iso_20w_Rep2 (0.0140236)Mouse_Iso_20w_Rep3 (0.0335449)Mouse_Iso_20w_Rep4 (0.173711) (0.103879) (0.0728196) (0.0209705)[ min ] [ medium ] [ max ] CEM 1 Pcca 556.4 2365.0 3408.1 P ( S | Z, I ) = 1.00 Aldh6a1 1089.2 5048.7 6720.1 Mean Corr = 0.91582 Mut 1077.3 2215.6 2940.1 Mcee 510.5 1155.4 1681.5 Pccb 737.7 1622.3 2214.1 Suclg1 1775.7 5260.8 6446.6 Suclg2 372.5 793.8 1110.9 Acss2 628.8 2341.8 5780.1 Hibch 90.8 592.9 1007.3 Mlycd 371.7 637.8 876.4 Acacb 381.6 2481.2 4221.3 Acss1 294.0 596.3 763.4 Echs1 976.2 4121.3 5782.5 Hibadh 1184.8 3288.6 4675.9 Clybl 151.8 675.2 1184.3 Acadm 2175.6 8550.2 10228.0 Coq9 704.9 1804.3 2673.8 CEM 1 + Hadh 1888.6 6878.3 8888.7 Top 10 Genes Decr1 1117.8 4162.6 5857.6 Mccc1 443.2 1446.4 2240.1 Sdha 2554.4 6770.9 8829.4 Ivd 769.9 2547.6 3777.1

Null module Sucla2 GEO Series "GSE13302" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 30 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13302 Status: Public on May 12 2009 Title: Gene expression profiling in the lung and liver of Perfluorooctane sulfonate (PFOS) exposed mouse fetuses Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19429403 Summary & Design: Summary: Most of the transcriptional changes induced by PFOS in the fetal mouse liver and lung were related to activation of PPARalpha. When compared to the transcript profiles induced by PFOA (Pubmed ID 17681415), few remarkable differences were found other than up-regulation of Cyp3a genes. Because PFOS and PFOA have been shown to differ in their mode of action in the murine neonate, these data suggest that changes related to PFOS-induced neonatal toxicity may not be evident in the fetal transcriptome at term.

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

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

0.471 Kernel fit Pairwise Correlations Normal fit

Density 0.236

0.000 CEM 1

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

Pre-normalization Quantiles

0mg/kg/day0mg/kg/day PFOS,0mg/kg/day lungPFOS,0mg/kg/day rep1 liverPFOS, (0.0313522)0mg/kg/day rep1 lungPFOS, (0.0138631)0mg/kg/day rep2 liverPFOS, (0.0313599)0mg/kg/day rep2 lungPFOS, (0.0296399)0mg/kg/day rep3 liverPFOS, (0.0361135)0mg/kg/day rep3 lungPFOS, (0.0221601)0mg/kg/day rep4 liverPFOS, (0.0274156)5mg/kg/day rep4 lungPFOS, (0.039653)5mg/kg/day rep5 liverPFOS, (0.0253001)5mg/kg/day rep5 lungPFOS, (0.0346726)5mg/kg/day rep1 liverPFOS, (0.0270661)5mg/kg/day rep1 lungPFOS, (0.0400064)5mg/kg/day rep2 liverPFOS, (0.0303644)5mg/kg/day rep2 lungPFOS, (0.0327976)5mg/kg/day rep3 liverPFOS, (0.030207)5mg/kg/day rep3 lungPFOS, (0.038315)5mg/kg/day rep4 liverPFOS, (0.0239728)10mg/kg/day rep4 lungPFOS, (0.0269128)10mg/kg/day rep5 liver PFOS, (0.0292128)10mg/kg/day rep5 lungPFOS, (0.0540519)10mg/kg/day rep1 liverPFOS, 10mg/kg/day(0.0329094) rep1 lungPFOS, 10mg/kg/day(0.0488881) rep2 liverPFOS, 10mg/kg/day(0.0342476) rep2 lungPFOS, 10mg/kg/day(0.0367757) rep3 liverPFOS, 10mg/kg/day(0.0265526) rep3 lungPFOS, 10mg/kg/day(0.0593386) rep4 liverPFOS, (0.0263535) rep4 lungPFOS, (0.0464853) rep5 liver (0.0209597) rep5 [(0.0430527) min ] [ medium ] [ max ] CEM 1 Pcca 789.1 2916.1 4090.7 P ( S | Z, I ) = 1.00 Aldh6a1 2805.3 3885.4 6085.3 Mean Corr = 0.86281 Mut 1142.8 2012.5 3407.4 Mcee 700.6 1041.1 1482.9 Pccb 1183.8 1468.7 1804.1 Suclg1 2226.3 5090.4 7266.7 Suclg2 448.4 1508.9 1791.2 Acss2 726.8 1030.3 3982.2 Hibch 47.5 193.9 358.0 Mlycd 295.4 649.7 1288.0 Acacb 127.9 523.9 2419.5 Acss1 630.4 1342.6 1917.8 Echs1 2836.1 5969.5 7041.5 Hibadh 1816.1 3738.5 5328.2 Clybl 68.0 443.6 790.7 Acadm 2471.4 12258.1 19608.1 Coq9 728.1 1567.8 1833.6 CEM 1 + Hadh 3711.3 10697.0 12368.1 Top 10 Genes Decr1 1752.8 6520.5 15664.9 Mccc1 1354.7 1538.0 2019.5 Sdha 2973.8 5058.0 6159.0 Ivd 1646.0 2738.1 3989.1

Null module Sucla2 GEO Series "GSE13071" 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=GSE13071 Status: Public on Aug 26 2009 Title: Knee joint synovium from different grades of inflammation in mouse collagen induced arthritis (CIA) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19690516 Summary & Design: Summary: Knee joint synovium was used for gene expression analysis of mouse collagen induced arthritis (CIA). Synovium was prepared at day 30 after initial sensitization from: healthy controls, CIA animals with no, with mild, with moderate, or with severe joint inflammation. Each sample group is represented by three replicates, each consisting of tissue collected from three to four animals.

Keywords: disease severity analysis

Overall design: The data set consists of 15 samples: five groups with three replicates each. One sample group is from healthy controls, the other groups are from CIA animals with different degress of joint inflammation.

Background corr dist: KL-Divergence = 0.0611, L1-Distance = 0.0572, L2-Distance = 0.0049, Normal std = 0.5641

0.778 Kernel fit Pairwise Correlations Normal fit

Density 0.389

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

synovium_naive_rep1synovium_naive_rep2synovium_naive_rep3 synovium_CIA_NoJointInflammation_rep1(0.0989582) synovium_CIA_NoJointInflammation_rep2(0.0898916) synovium_CIA_NoJointInflammation_rep3(0.0924293)synovium_CIA_MildJointInflammation_rep1synovium_CIA_MildJointInflammation_rep2synovium_CIA_MildJointInflammation_rep3 (0.0536756)synovium_CIA_ModerateJointInflammation_rep1 (0.0735121)synovium_CIA_ModerateJointInflammation_rep2 (0.14568)synovium_CIA_ModerateJointInflammation_rep3 (0.0204089)synovium_CIA_SevereJointInflammation_rep1 (0.0253722)synovium_CIA_SevereJointInflammation_rep2 (0.048566)synovium_CIA_SevereJointInflammation_rep3 (0.0677516) (0.0600761) (0.0328865)[ (0.0718718)min (0.0414964) ] (0.0774239)[ medium ] [ max ] CEM 1 Pcca 808.8 1404.9 3301.3 P ( S | Z, I ) = 1.00 Aldh6a1 644.4 1955.2 5588.2 Mean Corr = 0.86028 Mut 1102.0 1578.1 3220.4 Mcee 666.1 935.8 2066.1 Pccb 943.0 1514.9 2580.4 Suclg1 2727.6 5339.4 12811.4 Suclg2 490.0 590.8 975.3 Acss2 213.2 320.6 860.8 Hibch 7.4 123.7 287.0 Mlycd 1174.5 1378.4 2132.8 Acacb 658.2 1450.7 3756.1 Acss1 189.8 334.0 535.2 Echs1 2073.8 2419.1 4470.5 Hibadh 1759.8 2780.7 5198.3 Clybl 214.0 542.3 1268.1 Acadm 3155.2 6859.7 14388.5 Coq9 2056.1 4991.1 12818.8 CEM 1 + Hadh 2172.1 3986.4 8179.1 Top 10 Genes Decr1 1820.9 2689.1 5167.0 Mccc1 908.6 1164.8 1814.3 Sdha 5686.8 9673.5 18875.7 Ivd 711.2 1226.9 1700.7

Null module Sucla2 GEO Series "GSE46496" 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=GSE46496 Status: Public on Jun 07 2013 Title: Atrial Identity Is Determined by A COUP-TFII Regulatory Network (RNA) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23725765 Summary & Design: Summary: Atria and ventricles exhibit distinct molecular profiles that produce structural and functional differences between the two cardiac compartments. However, factors that determine these differences remain largely undefined. Cardiomyocyte-specific COUP- TFII ablation produces ventricularized atria that exhibit ventricle-like action potentials, increased cardiomyocyte size, and development of extensive T-tubules.

We used microarrays to examine the molecular profile of cardiomyocyte-specific COUP-TFII knockout adult atria in comparison with that of normal atria.

Overall design: We extracted RNA from mutant right atria, control right atria and control ventricles from 2 months old adult mice, followed by gene expression profiling using Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0268, L1-Distance = 0.0394, L2-Distance = 0.0028, Normal std = 0.6869

0.581 Kernel fit Pairwise Correlations Normal fit

Density 0.290

0.000 CEM 1

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

Pre-normalization Quantiles

Atria, Mutant,Atria, Mutant, biologicalAtria, Mutant, biologicalAtria, replicate Control, biologicalAtria, replicate 1 (0.0312348)Control, biologicalAtria, replicate 2 (0.0345931)Control, biologicalVentricles, replicate 3 (0.0691193) biologicalVentricles, replicate Control, 1 (0.100372)Ventricles, replicate Control, 2biological (0.0492444) Control, 3biological (0.117457) replicate biological replicate 1 (0.15167) [replicate 2min (0.276719) 3 (0.169591)] [ medium ] [ max ] CEM 1 Pcca 2048.3 2474.6 4356.2 P ( S | Z, I ) = 1.00 Aldh6a1 5955.8 6423.5 9530.5 Mean Corr = 0.84753 Mut 4355.5 4713.1 6291.4 Mcee 1411.8 1569.0 3379.6 Pccb 654.9 783.8 1100.5 Suclg1 7496.2 8688.5 12020.8 Suclg2 495.7 651.0 1440.9 Acss2 1020.8 1135.0 1183.3 Hibch 247.0 409.9 1107.7 Mlycd 664.9 902.1 1679.6 Acacb 940.4 1311.0 2543.4 Acss1 3509.1 4260.6 6984.5 Echs1 5347.9 7169.4 11554.6 Hibadh 5184.3 5551.9 9123.1 Clybl 1776.6 2128.8 3193.6 Acadm 16783.1 23771.3 30542.9 Coq9 7045.1 9143.8 16064.0 CEM 1 + Hadh 6656.7 9288.1 18205.1 Top 10 Genes Decr1 3651.2 6440.9 11242.4 Mccc1 2604.1 3389.1 6308.7 Sdha 12584.6 14340.9 20102.4 Ivd 2256.3 2702.8 4445.4

Null module Sucla2 GEO Series "GSE52597" 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=GSE52597 Status: Public on Feb 20 2014 Title: Expression data during plantaris muscle hypertrophy with/without satellite cells induced by synergist ablation in young adult Pax7-DTA mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24376025 Summary & Design: Summary: Global gene expression patterns were determined from microarray results from sham surgery or following 1 week of plantaris muscle hypertrophy induced by synergist ablation in young adult Pax7-DTA mice (4 months).

Vehicle treated mice have their full complement of satellite cells; tamoxifen treated mice have had their satellite cells genetically depleted through Cre-loxP technology

Overall design: After sham surgery or 1 week of overload, Affymetrix chips (mouse430_2.0) were used with 1 ´g of total RNA derived from a pooled sample of the right and left plantaris muscles from 11 animals.

Background corr dist: KL-Divergence = 0.0322, L1-Distance = 0.0265, L2-Distance = 0.0008, Normal std = 0.6614

0.622 Kernel fit Pairwise Correlations Normal fit

Density 0.311

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

Vehicle-treated,Tamoxifen-treated,Vehicle-treated, sham Vehicle-treated,operated shamTamoxifen-treated, 1 male weekoperated youngTamoxifen-treated, 1following week male mouseTamoxifen-treated, following young surgery 1 week(0.29611) mouse surgery 1followingfemale week (0.307468) young1followingmale week surgery young mouse following surgery [female mousemin (0.0427046) surgery youngmale (0.0652239) ] young mouse male mouseyoung (0.0611424)[ 1mousemedium (0.0999209) 2 (0.127431) ] [ max ] CEM 1 Pcca 1288.6 1385.5 3285.4 P ( S | Z, I ) = 1.00 Aldh6a1 3919.8 4448.3 8944.1 Mean Corr = 0.84660 Mut 1259.8 1877.1 2435.8 Mcee 852.3 1395.9 2163.0 Pccb 1248.9 1368.5 2110.4 Suclg1 6516.9 8554.4 14025.7 Suclg2 749.6 955.7 1222.2 Acss2 937.0 1104.6 1808.4 Hibch 142.2 231.5 255.6 Mlycd 737.8 1005.4 1870.1 Acacb 921.7 1422.2 3409.6 Acss1 240.4 542.6 939.7 Echs1 2900.0 3725.6 6091.3 Hibadh 3586.1 4792.4 7638.7 Clybl 1051.1 1488.6 2088.4 Acadm 8253.9 11286.2 23742.5 Coq9 5213.4 7545.9 12662.7 CEM 1 + Hadh 4379.4 6401.6 10744.9 Top 10 Genes Decr1 2612.3 3251.5 5098.3 Mccc1 1080.1 1369.9 2478.5 Sdha 8634.2 10475.2 19395.0 Ivd 844.3 1434.3 3390.5

Null module Sucla2 GEO Series "GSE41759" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

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

0.408 Kernel fit Pairwise Correlations Normal fit

Density 0.204

0.000 CEM 1

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

Pre-normalization Quantiles

muscle brainVastus tissue muscleLateralis, sample, brainVastus wild tissuewild muscletypeLateralis, type sample,mice, brainVastusmice, wild biological tissuewild biological muscletypeLateralis, type sample,mice, replica brainVastusmice, replica wild biological tissue wild1biological muscletypeLateralis,(0.0752654) 1 type (0.0924315) sample,mice, replica brainVastusmice, replica wild biological tissue wild2biological muscletypeLateralis,(0.0861947) 2 type (0.0783172) sample,mice, replica brainVastusmice, replica mutant biological tissue mutant3biological muscleLateralis,(0.0671102) 3 mice, (0.0682108) sample, mice,replica brainVastus biological replica mutant biological tissue mutant4 Lateralis,(0.064897) 4 mice, (0.0530045) replicasample, mice, replica biological mutant 1biological mutant(0.0906618) 1 (0.0539357) mice, replica mice, replica[ biological min 2biological (0.0935522) 2 (0.051064) replica] replica 3 (0.061459) 3 (0.0638959)[ medium ] [ max ] CEM 1 Pcca 855.6 2334.8 3031.0 P ( S | Z, I ) = 1.00 Aldh6a1 1251.1 6089.5 6693.9 Mean Corr = 0.84398 Mut 1204.0 3185.7 3554.9 Mcee 761.7 2793.0 3213.6 Pccb 1049.4 2361.9 3117.6 Suclg1 3093.6 8991.1 10273.6 Suclg2 255.0 1609.7 1841.2 Acss2 649.5 1019.6 1813.3 Hibch 20.2 279.2 407.1 Mlycd 290.2 775.5 1299.7 Acacb 46.9 3210.9 4677.7 Acss1 367.6 569.6 981.1 Echs1 1120.3 5184.3 6714.3 Hibadh 1490.1 6216.8 6900.7 Clybl 372.1 1517.4 1727.0 Acadm 1372.6 10641.9 13144.3 Coq9 1305.8 8039.3 9054.9 CEM 1 + Hadh 776.7 6619.1 8083.0 Top 10 Genes Decr1 403.4 3281.1 4395.1 Mccc1 545.0 1367.6 1843.9 Sdha 5220.0 11160.0 13749.9 Ivd 891.5 2489.7 3326.9

Null module Sucla2 GEO Series "GSE7424" 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=GSE7424 Status: Public on Apr 03 2007 Title: Intragraft gene expression profile associated with the induction of tolerance Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18267024 Summary & Design: Summary: Xenotransplantation holds the promise of providing an unlimited supply of donor organs for terminal patients with organ failure. The gal carbohydrate results in rejection of wild type pig grafts, however, chimerism established by expression of the GalT gene prior to transplantation in GalT knockout mice results in tolerance to Gal+ heart grafts.

We used microarrays in order to further understand the early events that occur within grafts that demonstrate tolerance.

Keywords: transplntation tolerance

Overall design: The GalT BMT recipient is a GalT knockout mouse which recieved GalT gene transduced allo-bone marrow cells transplantation after sublethal irradiation. A heart of wild type C57BL/6 was heterotopically transplanted into the recipient after GalT BMT. Syngeneic Control recipient is a wild type C57BL/6 transplanted a heart of wild C57BL/6.

Background corr dist: KL-Divergence = 0.0600, L1-Distance = 0.0214, L2-Distance = 0.0007, Normal std = 0.5344

0.747 Kernel fit Pairwise Correlations Normal fit

Density 0.373

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

heartgraft_GalTBMT_early_rep1.heartgraft_GalTBMT_early_rep2.heartgraft_GalTBMT_early_rep3.heartgraft_GalTBMT_early_rep4.heartgraft_Syngeneic_early_rep1. (0.0651176)heartgraft_Syngeneic_early_rep2. (0.118516)heartgraft_Syngeneic_early_rep3. (0.212438)heartgraft_Syngeneic_early_rep4. (0.10164) (0.154148) (0.0539331) (0.131213)[ min (0.162996) ] [ medium ] [ max ] CEM 1 Pcca 1391.9 2038.5 2606.4 P ( S | Z, I ) = 1.00 Aldh6a1 1791.3 3350.8 4751.6 Mean Corr = 0.81475 Mut 2008.2 3378.2 4023.0 Mcee 3148.9 4970.5 5262.3 Pccb 2097.0 3131.6 4020.7 Suclg1 4252.4 5007.7 7776.5 Suclg2 961.8 1205.3 2331.8 Acss2 724.6 883.8 1163.9 Hibch 138.4 218.1 418.8 Mlycd 484.1 986.0 1294.9 Acacb 1328.6 2828.6 3825.0 Acss1 1621.4 3573.7 4860.3 Echs1 2178.1 3351.7 4474.2 Hibadh 2544.6 3185.7 5222.8 Clybl 744.4 1090.0 1672.3 Acadm 6774.6 11642.6 14283.1 Coq9 2775.4 5041.3 6016.0 CEM 1 + Hadh 4162.2 8347.7 9667.7 Top 10 Genes Decr1 3017.2 4673.6 5755.8 Mccc1 1741.7 3281.2 3672.9 Sdha 6613.2 9138.2 11650.9 Ivd 1423.0 2926.5 3734.8

Null module Sucla2 GEO Series "GSE51483" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 45 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

0.789 Kernel fit Pairwise Correlations Normal fit

Density 0.394

0.000 CEM 1

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

Pre-normalization Quantiles

Mouse R1Mouse Stem R1Mouse Cells Stem R1.1R1Mouse Cells Stem (0.0195519) R1.2E7.5Mouse Cells (0.0193086)whole R1.3E7.5Mouse embryo (0.0193585)whole E7.5Mouse embryo tissuewhole E8.5Mouse E7.1embryo tissuewhole E8.5Mouse (0.0229548) E7.2heart tissuewhole E8.5Mouse (0.023331) tissue E7.3heart whole E9.5Mouse (0.0226491)(heart tissue heart left E9.5Mousetube) ventricle(heart tissue left E8.1 E9.5Mousetube) ventricle(heart tissue (0.0204547) left E8.2 E9.5Mousetube) ventricle E9L.1 tissue (0.0190636) right E8.3 E9.5Mouse (0.0109051) E9L.2ventricletissue (0.0170058) right E9.5Mouse (0.010393) E9L.3ventricle tissueright E12.5Mouse (0.011162) ventricle E9R.1 tissue left E12.5Mouse ventricle(0.013717) E9R.2 tissue left E12.5Mouse ventricle(0.0145114) E9R.3tissue left E12.5Mouse ventricle(0.0151101) E12L.1 tissue right E12.5Mouse (0.00673234)E12L.2ventricletissue right E12.5Mouse (0.00526625)E12L.3ventricle tissueright E14.5Mouse (0.0122418)ventricle E12R.1 tissueleft E14.5Mouse ventricle E12R.2(0.00676608) tissueleft E14.5Mouse ventricle tissue E12R.3(0.0076776) left E14.5Mouse ventricle E14L.1 tissue (0.00778992) right E14.5Mouse (0.00493698)E14L.2ventricletissue right E14.5Mouse (0.00539573)E14L.3ventricle tissueright E18.5Mouse (0.00620334)ventricle E14R.1 tissueleft E18.5Mouse ventricle E14R.2(0.00820371) tissueleft E18.5Mouse ventricle tissue E14R.3(0.00319696) left E18.5Mouse ventricle E18L.1 tissue (0.00356009) right E18.5Mouse (0.00973243)E18L.2ventricletissue right E18.5Mouse (0.00630986)E18L.3ventricle tissueright leftMouse (0.00712749)ventricle E18R.1 tissue leftMouse ventricle E18R.2 (0.00891522)tissue leftMouse ventricle atE18R.3 (0.00486774)tissue 3rightMouse days at (0.00719753)ventricletissue after3rightMouse days birth atventricle aftertissue3rightAdult days D3L.1 birth ventricle mouseat aftertissueAdult 3(0.0136368) D3L.2 days birth leftmouseat tissueAdult after3(0.0105325) ventricleD3L.3 days leftbirthmouseatAdult after3(0.0128808) ventricle days D3R.1tissue leftbirthmouseAdult after ventricle (0.0152807) AdltL.1D3R.2tissue rightbirthmouseAdult (0.0211984) AdltL.2(0.0926626)ventricleD3R.3tissue rightmouse (0.00963302) AdltL.3(0.0976593)ventricle tissueright (0.0932018)ventricle AdltR.1 tissue AdltR.2(0.11891)tissue[ min AdltR.3(0.0531768) ] (0.0796302) [ medium ] [ max ] CEM 1 Pcca 600.8 1301.5 5373.1 P ( S | Z, I ) = 1.00 Aldh6a1 496.1 1833.7 9053.2 Mean Corr = 0.81047 Mut 1238.6 1882.0 6463.1 Mcee 547.0 2131.8 6032.5 Pccb 423.8 818.7 1564.0 Suclg1 4316.3 8542.5 18382.3 Suclg2 859.8 1407.1 1978.5 Acss2 109.7 276.6 1138.7 Hibch 38.6 159.0 701.5 Mlycd 165.9 421.6 2462.7 Acacb 83.4 457.5 3451.5 Acss1 86.7 373.4 7357.6 Echs1 1587.3 5078.2 15958.4 Hibadh 1259.7 2932.9 11441.7 Clybl 410.1 1710.1 3061.5 Acadm 2682.9 10000.9 38485.6 Coq9 771.0 3994.6 22122.3 CEM 1 + Hadh 2134.0 6528.7 14169.9 Top 10 Genes Decr1 764.3 3152.9 15151.4 Mccc1 613.3 1341.0 2353.0 Sdha 3795.7 9790.6 22073.3 Ivd 490.2 1336.0 5089.0

Null module Sucla2 GEO Series "GSE20152" 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=GSE20152 Status: Public on Jan 15 2011 Title: The role of SphK1 in hTNFÎ± induced inflammation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20644167 Summary & Design: Summary: The study analyzes analyzes gene expression changes in the ankle joint in mouse TNFa overexpression models with or without sphingosine kinase 1 activity.

SphK1 is a sphingolipid enzyme that converts sphingosine to bioactive sphingosine-1-phosphate (S1P). Recent data suggest a potential relationship between SphK1 and TNFÎ± and have implicated SphK1/S1P in the development and progression of inflammation. Here we further study the relationship of TNFÎ± and SphK1 using an in vivo model. Transgenic hTNFÎ± mice, which develop a spontaneous arthritis (limited to paws) at 20 weeks, were crossed with SphK1 activity null mice (SphK1-/-) to study the development of inflammatory arthritis in the functional absence of SphK1. Results show that hTNF/SphK1-/- have significantly less severity and progression of arthritis and bone erosions as measured through micro-CT images. Additionally, less COX-2 protein, mTNFÎ± transcript levels and fewer Th 17 cells were detected in the joints of hTNF/SphK1-/- compared to hTNF/SphK1+/+ mice. Microarray analysis of the ankle joint showed that hTNF/SphK1-/- mice have increased transcript levels of IL-6 and SOCS3 compared to hTNF/SphK1+/+ mice. Finally, fewer mature osteoclasts were detected in the ankle joints of hTNF/SphK1-/- mice compared to hTNF/SphK1+/+ mice. These data show that SphK1 plays a role in hTNFÎ± induced inflammatory arthritis, potentially through a novel pathway involving IL-6 and SOCS3.

Overall design: Two wild-type replicates; three replicates of human TNFa transgene overexpression and normal sphingosine kinase 1; three replicates of human TNFa transgene overexpression and sphingosine kinase 1 null.

Background corr dist: KL-Divergence = 0.0305, L1-Distance = 0.0370, L2-Distance = 0.0018, Normal std = 0.6871

0.616 Kernel fit Pairwise Correlations Normal fit

Density 0.308

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

Ankle-hTNFaAnkle-hTNFa overexpressionAnkle-Sphk1 overexpressionAnkle-hTNFa norm-1 andAnkle-Sphk1 SphK1 overexpression(0.340802) andAnkle-hTNFa null-1SphK1 norm-2Ankle-hTNFa (0.049353) null-2 overexpression(0.286461) andAnkle-hTNFa (0.0815886) SphK1 overexpression null-3 overexpression and (0.0681377) Sphk1 and norm-1Sphk1 and[ min norm-2(0.0430862)Sphk1 norm-3(0.0800096)] (0.0505615)[ medium ] [ max ] CEM 1 Pcca 723.9 883.1 1107.6 P ( S | Z, I ) = 1.00 Aldh6a1 424.5 771.6 1714.1 Mean Corr = 0.80613 Mut 1246.7 1361.7 1771.6 Mcee 600.3 795.9 1170.7 Pccb 777.0 858.9 1281.1 Suclg1 2096.8 2382.6 4430.4 Suclg2 522.1 575.9 719.5 Acss2 349.6 452.3 849.7 Hibch 22.5 29.3 52.1 Mlycd 479.8 512.4 794.1 Acacb 363.0 530.7 1655.7 Acss1 381.7 482.4 588.5 Echs1 1442.1 1664.9 2246.1 Hibadh 1325.0 1446.4 2246.1 Clybl 331.7 448.3 783.2 Acadm 3103.4 3593.6 6797.6 Coq9 1143.8 1434.5 3856.8 CEM 1 + Hadh 1562.5 2074.1 4020.6 Top 10 Genes Decr1 1089.6 1340.3 2370.2 Mccc1 854.9 1053.7 1439.0 Sdha 5162.8 5409.3 8738.7 Ivd 736.2 862.1 1461.5

Null module Sucla2 GEO Series "GSE3126" 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=GSE3126 Status: Public on Dec 31 2005 Title: Comparison of HNF4 null mouse embryonic livers with control mouse embryonic livers Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 16714383 Summary & Design: Summary: To study the role of hepatic nuclear factor alpha (HNF4a in hepatogenesis, we used loxP-Cre technology to eliminate it from developing mouse livers.

A comparison of control and experimental livers revealed that hepatocytes lacking HNF4a_failed to fully differentiate. Specifically, HNF4a null liver cells failed to express genes that are markers of mature hepatocytes including Gys2, Pck1, and G6pc. These cells also failed to form normal cellular junctions, which are critical for establishment of the hepatic epithelium [Parviz et al. (2003) Nat.Genet. 34, 292-96]. Because HNF4a functions as a transcription factor, we hypothesized that it regulates liver development by controlling the expression of genes whose products are essential in executing cellular differentiation and morphogenesis. To identify these genes, we compared expression profiles between HNF4a null and wild type E18.5 fetal livers using Affymetrix gene arrays. We identified 564 genes whose expression was decreased by at least 2.5-fold and 34 genes whose expression was increased by at least 2.5-fold when HNF4a was eliminated from hepatocytes. These represent genes involved in diverse molecular pathways, reflecting the pleiotropic phenotype of HNF4a null livers. Our goal was to use the information from the gene arrays to define the mechanisms through which HNF4a controls the generation of the hepatic epithelium. We identified 27 genes from our list of downregulated genes with either defined or predicted roles in cellular junctions and/or adhesion. Most striking was that loss of HNF4a altered the expression of genes encoding proteins involved in virtually all types of cellular junctions including tight junctions (Cldn1, Cldn-2, Cldn-12, Ocln, F11r/Jam1, Cxadr, Crb3), adherens junctions (Cdh1), desmosomes (Dsc2, Pkp2, Krt2-8), and gap junctions (Gjb1, Gjb2). Using immunoblotting and immunohistochemistry, we found that the expression of proteins representing each of these junction types was reduced or absent. Analysis of these genes for the presence of putative HNF4a binding sites revealed that 25 of 27 contain such sites. We have used chromatin immunoprecipitation to confirm that HNF4a occupies several of these sites in vivo, including Cdh1, Cldn1, and F11r/Jam1. From these data, we conclude that HNF4a is a central mediator of the fully differentiated hepatocyte gene expression program and that it orchestrates the expression of cell junction and adhesion proteins required for establishing the hepatic epithelium.

Keywords: E18.5 fetal hnf4 null and control mouse livers

Overall design: comparison of three hnf4 null livers to three control

Background corr dist: KL-Divergence = 0.0251, L1-Distance = 0.0111, L2-Distance = 0.0001, Normal std = 0.6969

0.572 Kernel fit Pairwise Correlations Normal fit

Density 0.286

0.000 CEM 1

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

Pre-normalization Quantiles

HNF4 Control_8HNF4 Control_1192HNF4 (0.229682) Control_1193HNF4 (0.136212) Null_61HNF4 (0.119491) Null_1191 (0.175877)HNF4 Null_1195 (0.162786) (0.175952) [ min ] [ medium ] [ max ] CEM 1 Pcca 738.0 1642.5 1896.3 P ( S | Z, I ) = 1.00 Aldh6a1 985.6 2718.7 3422.2 Mean Corr = 0.80246 Mut 752.4 1606.3 1891.9 Mcee 1152.0 1802.7 2096.7 Pccb 848.0 1431.9 1750.4 Suclg1 878.4 2764.8 3077.6 Suclg2 569.1 1316.1 1631.7 Acss2 449.2 708.2 1230.0 Hibch 11.3 137.3 151.3 Mlycd 432.0 624.4 668.0 Acacb 46.5 289.2 381.8 Acss1 756.5 1113.9 1198.4 Echs1 1680.5 3586.6 3967.8 Hibadh 856.8 1941.6 2195.4 Clybl 123.9 339.3 452.9 Acadm 3773.7 7047.7 9372.0 Coq9 567.9 979.0 1086.2 CEM 1 + Hadh 2569.2 5050.7 5362.1 Top 10 Genes Decr1 932.4 2548.6 2892.4 Mccc1 597.2 810.4 965.2 Sdha 2485.6 3417.8 3796.4 Ivd 521.1 1013.2 1280.2

Null module Sucla2 GEO Series "GSE15729" 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=GSE15729 Status: Public on Mar 01 2010 Title: Gene Expression of ApoE Null and ApoE Null/RAGE Diabetic and Non-diabetic Mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20133903 Summary & Design: Summary: The multi-ligand Receptor for AGE (RAGE) contributes to atherosclerosis in apolipoprotein (ApoE) null mice in both the non-diabetic and diabetic states. Previous studies using soluble RAGE, the extracellular ligand-binding domain of RAGE, or homozygous RAGE null mice showed that blockade or deletion of RAGE resulted in marked reduction in atherosclerotic lesion area and complexity compared to control animals. In parallel, significant down-regulation of inflammatory mediators and matrix metalloproteinases was evident in ApoE null mice aortas devoid of RAGE compared to those of ApoE null RAGE-expressing mice. Although these findings suggested that RAGE triggered pro-atherogenic mechanisms via regulation of inflammatory gene expression, these studies did not reveal the broader pathways by which RAGE contributed to atherosclerosis in ApoE null mice.

Therefore, we performed Affymetrix gene expression arrays on aortas of non-diabetic and diabetic ApoE null mice expressing RAGE or devoid of RAGE at nine weeks of age, as this reflected a time point at which frank atherosclerotic lesions were not yet present, but, that we would be able to identify the genes likely involved in diabetes- and RAGE-dependent atherogenesis. The comparisons were as follows: 1. diabetic ApoE null relative to non-diabetic ApoE null; 2. non-diabetic ApoE null / RAGE null relative to non-diabetic ApoE null; 3. diabetic ApoE null / RAGE null relative to non-diabetic ApoE null / RAGE null; and 4. diabetic ApoE null / RAGE null relative to diabetic ApoE null aorta.

Our data reveal that there is very little overlap of the genes which are differentially expressed both in the onset of diabetes in ApoE null mice, and in the effect of RAGE deletion in diabetic ApoE null mice. We next performed a Pathway-Express analysis to determine the pathways that were most associated with the onset of diabetes in ApoE null mice and the effect of RAGE gene deletion in diabetic ApoE null mice. Rigorous statistical analysis was undertaken and revealed that the transforming growth factor-Î² pathway (tgf-Î²) and focal adhesion pathways might be expected to play a significant role in both the mechanism by which diabetes facilitates the formation of atherosclerotic plaques in ApoE null mice, and the mechanism by which deletion of RAGE ameliorates this effect. We focused on three genes of the tgf-Î² family which were found to be up-regulated in diabetic vs. non-diabetic ApoE null aorta, and which were reduced by deletion of RAGE. These included: thrombospondin1 (Thbs1), transforming growth factor-Î²2 (tgf-Î²2) and rho-associated kinase (ROCK1). Real-time quantitative polymerase chain reaction and Western blotting experiments were performed, as well as ROCK1 activity assays in mouse aorta, and validated the findings of the Affymetrix gene array. Further, confocal microscopy revealed that a principal cell type in the ApoE null aorta expressing these factors was the vascular smooth muscle cell. Our data suggest the novel finding that the observed reduction of accelerated atherosclerosis in diabetic ApoE null / RAGE null vs. diabetic ApoE null mice occurs, all or in part, through the ROCK1 branch of the TGF-Î² pathway. We have inferred a detailed mechanism for this process.

Taken together, these data suggest that suppression of ROCK1 activity in the atherosclerosis-vulnerable vessel wall, especially in diabetes, but in non-diabetes as well, may underlie the beneficial effects of RAGE antagonism and genetic deletion in murine models. These findings highlight logical and novel targets for therapeutic intervention in cardiovascular disease and diabetes.

Overall design: There were 4 mice in each group initially. However there are only 3 non-diabetic ApoE null / RAGE null mice in the final experimental sample in group 3 due to a failure to generate cRNA from that sample. All samples were normalized to remove chip-dependent regularities using the RMA method. Chips and controls at each combination of genotype and disease sate were normalized together. The statistical significance of differential expression was calculated using the empirical Bayesian LIMMA (LInear Model for MicroArrays) method A cut-off B>0 was used for the statistical significance of gene expression.

Background corr dist: KL-Divergence = 0.1445, L1-Distance = 0.0344, L2-Distance = 0.0024, Normal std = 0.3840

1.039 Kernel fit Pairwise Correlations Normal fit

Density 0.519

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

APOE_KO_DM_9W_1APOE_KO_DM_9W_2APOE_KO_DM_9W_3 (0.0903382)APOE_KO_DM_9W_4 (0.0159145)APOE_KO_NODM_9W_5 (0.145262)APOE_KO_NODM_9W_6 (0.115839)APOE_KO_NODM_9W_7APOE_KO_NODM_9W_8 (0.0631902)APOE_KO_RAGE_KO_DM_9W_9 (0.00947182)APOE_KO_RAGE_KO_DM_9W_10 (0.0118235)APOE_KO_RAGE_KO_DM_9W_11 (0.055528)APOE_KO_RAGE_KO_DM_9W_12APOE_KO_RAGE_KO_NODM_9W_13 (0.0243803)APOE_KO_RAGE_KO_NODM_9W_14 (0.0881219)APOE_KO_RAGE_KO_NODM_9W_15 (0.0678937) (0.105079) (0.0217946) [(0.0332752) min (0.152088) ] [ medium ] [ max ] CEM 1 Pcca 1934.3 3856.6 5596.2 P ( S | Z, I ) = 1.00 Aldh6a1 4290.0 6714.2 8721.6 Mean Corr = 0.79861 Mut 2710.4 4293.4 6889.1 Mcee 797.7 1491.4 2421.3 Pccb 751.0 1448.2 2045.6 Suclg1 4867.3 9857.4 14379.3 Suclg2 672.9 915.4 1054.6 Acss2 718.9 1855.0 6074.5 Hibch 129.6 327.3 475.8 Mlycd 390.2 631.6 989.2 Acacb 538.8 2159.1 3550.9 Acss1 549.7 1347.2 2293.7 Echs1 2549.6 5354.6 8815.2 Hibadh 2868.4 4787.0 7245.8 Clybl 812.4 1625.2 2702.5 Acadm 10309.0 19374.0 24568.0 Coq9 1851.4 4003.9 5643.2 CEM 1 + Hadh 6042.8 10911.9 15134.0 Top 10 Genes Decr1 4970.4 9610.9 14866.2 Mccc1 1316.2 2607.7 3674.1 Sdha 7580.4 13762.3 18308.8 Ivd 1481.2 2198.4 3413.6

Null module Sucla2 GEO Series "GSE46209" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 21 -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=GSE46209 Status: Public on Jun 01 2013 Title: Non-telomeric role for Rap1 in regulating metabolism and protecting against obesity Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23791522 Summary & Design: Summary: The mammalian telomere-binding protein Rap1 was found to have additional non-telomeric functions, acting as a transcriptional cofactor and a regulator of the NF-kB pathway. Here, we assess the effect of disrupting mouse Rap1 in vivo, and report on its unanticipated role in metabolic regulation and body weight homeostasis. Rap1 inhibition causes dysregulation in hepatic as well as adipose function. In addition, using a separation-of-function allele, we show that the metabolic function of Rap1 is independent of its recruitment to TTAGGG binding elements found at telomeres, and at other interstitial loci.

We have utilized microarrays to outline gene expression changes resulting from Rap1-deficiency when compared to the wild-type controls.

Overall design: Total RNA was isolated from the liver and intra-abdominal white adipose tissue of 3 female Rap1 deficient mice and 3 control littermates at 6-8 weeks of age. Rap1 deficient mouse embryonic fibroblasts (MEF) were isolated from 13.5 day embryos, immortalized with SV40LgT, and stably infected with vector, Rap1-wildtype, or Rap1 carrying an isoleucine to arginine mutation at amino acid 312. Total RNA was extracted from MEFs following a similar protocol. The samples were labeled, hybridized, and scanned using standard protocols by the Core Facility at NYU Langone Medical Center on Affymetrix GeneChip Mouse Genome 430 2.0 Arrays.

Background corr dist: KL-Divergence = 0.0649, L1-Distance = 0.0432, L2-Distance = 0.0037, Normal std = 0.5275

0.756 Kernel fit Pairwise Correlations Normal fit

Density 0.378

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

wildtypewildtype liver, biologicalwildtype liver, biologicalknockout liver, rep 1 biologicalknockout (0.0314877) liver,rep 2 knockoutbiological(0.0357971) liver,rep 3 wildtypebiological(0.0260002) liver, rep 1 wildtypebiological white(0.028417) rep 2wildtypeadipose white(0.0303805) rep 3knockoutadipose tissue,white(0.021822) knockoutadipose biologicaltissue, whiteknockout biologicaladiposetissue, white rep wildtype1 biologicaladipose tissue,(0.00847609)white rep wildtype2 adipose mousebiologicaltissue,(0.0844436) rep wildtype3 embryonicmousebiologicaltissue,(0.365263) repknockout 1 embryonicmousebiological (0.0182689) repfibroblast,knockout 2embryonic mouse(0.0110215) repfibroblast,knockout biological3 embryonic mouse(0.0140845) fibroblast,mutant biological embryonicmouse rep fibroblast, mutantmouse1 biological (0.0406203)embryonic rep fibroblast, mutantembryonicmouse2 biological(0.0354318) rep fibroblast, embryonicmouse3 biological(0.035995) fibroblast, rep embryonic 1 biological (0.0320028) fibroblast, rep biological 2 (0.0319531) fibroblast, rep biological[ 3 repmin(0.0417238) 1 biological (0.0386723) rep ] 2 (0.0347752) rep 3 (0.0333639)[ medium ] [ max ] CEM 1 Pcca 168.5 3009.9 8661.3 P ( S | Z, I ) = 1.00 Aldh6a1 296.6 9390.0 12440.7 Mean Corr = 0.78370 Mut 685.5 5245.8 10056.4 Mcee 222.5 1613.2 6379.3 Pccb 164.8 2125.9 6345.8 Suclg1 1360.7 3730.8 19382.6 Suclg2 278.9 686.3 2469.5 Acss2 198.8 4554.1 13289.7 Hibch 90.2 527.8 1911.7 Mlycd 288.3 794.0 2139.9 Acacb 105.9 794.4 8412.0 Acss1 68.1 91.9 2783.5 Echs1 611.7 6419.3 17245.4 Hibadh 656.5 5973.0 11838.1 Clybl 319.5 1336.6 6056.2 Acadm 1479.8 11759.2 29756.1 Coq9 673.3 3069.7 8738.2 CEM 1 + Hadh 1594.0 10138.2 26815.4 Top 10 Genes Decr1 758.6 6439.0 16782.0 Mccc1 307.6 2444.9 7463.1 Sdha 2474.5 9069.3 24837.8 Ivd 260.9 2858.0 3970.0

Null module Sucla2 GEO Series "GSE13224" 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=GSE13224 Status: Public on Nov 30 2008 Title: (AKR/J x FVB/NJ)F1 versus (DBA/2J x FVB)F1 lung expression data Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19118016 Summary & Design: Summary: F1 hybrids from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses display a 20-fold difference in mammary tumor metastatic capacity, due to differences in inherited polymorphisms. Expression studies were performed to determine whether polymorphism-driven gene expression signatures predictive of outcome could be generated from normal tissues

Keywords: Basal transcription profiles

Overall design: Lung from adult F1 animals from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses was collected and arrayed on Affymetrics chip to identify basal differences in gene expression between the different genotypes

Background corr dist: KL-Divergence = 0.0425, L1-Distance = 0.0175, L2-Distance = 0.0003, Normal std = 0.6020

0.669 Kernel fit Pairwise Correlations Normal fit

Density 0.335

0.000 CEM 1

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

Pre-normalization Quantiles

lung akr1lung (0.139552) akr2lung (0.0726068) akr3lung (0.154732) dba1lung (0.143801) dba2lung (0.404715) dba3 (0.0845928) [ min ] [ medium ] [ max ] CEM 1 Pcca 1022.1 1233.4 1667.9 P ( S | Z, I ) = 1.00 Aldh6a1 1109.4 1493.2 1634.1 Mean Corr = 0.78020 Mut 1836.2 2381.0 2499.9 Mcee 1126.7 1231.6 1284.2 Pccb 1162.1 1237.1 1524.7 Suclg1 3313.9 3565.5 5269.6 Suclg2 640.3 742.7 812.6 Acss2 862.9 1020.0 1219.0 Hibch 29.0 44.5 60.9 Mlycd 551.4 1027.4 1115.6 Acacb 417.0 549.2 1313.1 Acss1 871.5 1035.5 1149.0 Echs1 2300.8 2775.0 3866.7 Hibadh 2144.0 2380.0 2781.4 Clybl 165.4 259.5 489.3 Acadm 3211.0 3429.9 6445.0 Coq9 943.7 1055.7 1478.9 CEM 1 + Hadh 4546.1 5269.5 7530.0 Top 10 Genes Decr1 1495.0 1866.7 3172.1 Mccc1 739.3 963.5 1268.2 Sdha 3781.2 4047.8 5225.6 Ivd 2017.0 2366.0 2569.1

Null module Sucla2 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(0.00912076)weeks Mammary35 type8 wild(0.0207585)weeks Mammary36 type8 tumor(0.0549916)weeks Mammary37 8Mammary1 tumor(0.00694463)weeks 8Mammary2 tumor(0.019111)weeks (0.0476835) 8Mammary3 tumorweeks (0.0276918) 12Mammary4 tumor weeks (0.0301775) 12Mammary5 tumorweeks (0.0162345)12 Mammary6 tumorweeks (0.0406284)12 Mammary7 tumorweeks (0.0209915)12 Mammary8 tumorweeks (0.00583789)16 Mammary9 tumorweeks (0.0232258)16 Mammary10 tumorweeks (0.00957577)16 Mammary11 tumorweeks (0.0141485)16 Mammary13 tumorweeks (0.0352604)16 Mammary14 tumorweeks (0.0146547)20 Mammary15 tumorweeks (0.0249602)20 Mammary32 tumorweeks (0.0143429)20 Mammary22 tumorweeks (0.0162271)20 Mammary23 tumorweeks (0.102968) Mammary24 tumor (0.122808) Mammary31 (0.169167) (0.15249)[ min ] [ medium ] [ max ] CEM 1 Pcca 205.1 2792.0 3636.8 P ( S | Z, I ) = 1.00 Aldh6a1 317.3 7420.9 8839.6 Mean Corr = 0.75276 Mut 859.9 3246.0 4089.4 Mcee 447.9 1785.5 2449.4 Pccb 236.7 1444.6 1797.8 Suclg1 1270.1 5825.1 8632.0 Suclg2 210.8 1017.0 1413.6 Acss2 73.3 3375.1 8088.6 Hibch 36.2 614.1 977.3 Mlycd 211.5 646.5 956.9 Acacb 42.8 1781.3 2645.0 Acss1 118.9 730.2 1174.2 Echs1 918.3 6405.0 7666.3 Hibadh 833.8 4686.4 5502.2 Clybl 151.8 1830.6 2405.9 Acadm 2106.2 13124.1 17507.1 Coq9 557.3 3908.3 6750.1 CEM 1 + Hadh 1094.0 9128.3 11574.7 Top 10 Genes Decr1 848.7 7100.2 8629.6 Mccc1 377.4 2865.8 3504.8 Sdha 2722.9 7559.0 10138.6 Ivd 294.5 2381.1 2861.6

Null module Sucla2 GEO Series "GSE13432" 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=GSE13432 Status: Public on Feb 01 2009 Title: Adipose tissue exposed to cold Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19117550 Summary & Design: Summary: Cold triggers VEGF dependent but hypoxia independent angiogenesis in adipose tissues and anti-VEGF agents modulate adipose metabolism

The molecular mechanisms of angiogenesis in relation to adipose tissue metabolism remain poorly understood. Here we show that exposure of mice to cold led to conversion of white adipose tissue (WAT) to brown-like adipose tissue, accompanying the switch of an active angiogenic phenotype. Gene expression profile analysis showed VEGF was upregulated via most likely hypoxia-independent PGC-1 transcriptional activation. Intriguingly, VEGFR2 blockage abolished the cold-induced angiogenesis, significantly impaired nonshivering thermogenesis capacity, and markedly reduced adipose metabolism. Unexpectedly, VEGFR1 blockage resulted in opposite effects by increasing adipose vascularity and metabolism. These findings demonstrate that VEGFR2 and VEGFR1 mediate polarized activities in modulating adipose angiogenesis and metabolism. Taken together, our findings have conceptual implications in applying angiogenesis modulators for the treatment of obesity and metabolic disorders.

Keywords: Time course

Overall design: Mice were exposed to cold and white addipose tissue was collected at different time points

Background corr dist: KL-Divergence = 0.0338, L1-Distance = 0.0273, L2-Distance = 0.0009, Normal std = 0.6614

0.603 Kernel fit Pairwise Correlations Normal fit

Density 0.302

0.000 CEM 1

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

Pre-normalization Quantiles

1 week 130 week degrees 130 week degrees rep 1 301 week (0.0362583) degrees rep 1 42 week degrees(0.0774382) repl 14 3weekdegrees (0.0678173)rep 1 54 (0.116187)weeksdegrees rep 25 (0.116978)30weeks rep degrees 35 (0.152148)30weeks degrees rep5 30weeks1 (0.0798517) degrees rep5 4weeks2 degrees(0.0800457) rep5 4weeks3 degrees(0.0757486) rep 1 4 (0.072699) degrees rep 2 (0.0661639) rep 3 (0.0586641)[ min ] [ medium ] [ max ] CEM 1 Pcca 2429.6 6694.9 8399.0 P ( S | Z, I ) = 1.00 Aldh6a1 12031.0 14132.5 16384.2 Mean Corr = 0.74462 Mut 2453.6 3824.7 5730.5 Mcee 1125.8 1640.5 4982.0 Pccb 2840.2 4250.7 6684.6 Suclg1 5382.0 16730.6 25411.9 Suclg2 1178.3 1758.7 2614.8 Acss2 6826.3 13332.4 28289.7 Hibch 1975.6 3296.3 4594.8 Mlycd 208.0 596.2 951.9 Acacb 1768.2 8633.4 12060.9 Acss1 527.3 1266.6 1484.6 Echs1 4778.8 6757.5 17865.3 Hibadh 5338.4 10006.3 11094.0 Clybl 1435.0 3905.4 6075.8 Acadm 9750.4 24483.0 38500.1 Coq9 2085.7 6003.4 8592.3 CEM 1 + Hadh 12425.4 28429.1 33770.5 Top 10 Genes Decr1 5597.0 12327.6 22029.4 Mccc1 4483.8 6516.1 7572.4 Sdha 10112.2 19436.2 22842.2 Ivd 2387.3 2881.5 3574.5

Null module Sucla2 GEO Series "GSE51080" 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=GSE51080 Status: Public on Mar 01 2014 Title: Expression data from exposure of BAT and WAT at 6 and 28 degrees C Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: We run microarrays from three per group Sv129 female mice, ten weeks old, which were maintained at 28´C (warm conditions) or 6´ C (cold stimulated) for ten days, while standard animal house temperature is 22 ´C.

After ten days, three types of tissue were collected: Brown Adipose Tissue (BAT), Mesenteric (visceral) White Adipose Tissue (MES) and Posterior Subcutaneous White Adipose Tissue (WAT)

Overall design: Different adipose tissue depots were taken for RNA extraction and hybridization on Affymetrix microarrays. We sought to determine the differences between white and brown adipose tissues at different temperatures

Background corr dist: KL-Divergence = 0.0623, L1-Distance = 0.0392, L2-Distance = 0.0026, Normal std = 0.5381

0.741 Kernel fit Pairwise Correlations Normal fit

Density 0.371

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

SubcutaneousMesenteric Brownwhite white adipose adiposeSubcutaneous adipose 6degBrown 6deg 28deg (S0510F001) (S0510F003) adiposeBrownwhite (S0510F002) adipose adiposeSubcutaneous 28deg (0.02398) (0.11813) 28degSubcutaneous(S0510F005) 28deg(0.0647849) (S0510F004) Subcutaneous(S0510F006)white (0.0937103) adipose Subcutaneouswhite (0.0569889) (0.0595877) adipose 6degBrownwhite (S0510F007) adipose adipose28degMesentericwhite adipose(S0510F008) 28degMesenteric 6deg (0.0199327) white (S0510F011)(S0510F009) 6degBrown adipose white(0.0299451) (S0510F010) adiposeMesenteric adipose 28deg(0.108551)(0.0211969)Mesenteric 6deg (S0510F012) (0.016502) 28degwhite (S0510F014)Brown adipose(S0510F013) white adiposeMesenteric (0.0652336) adipose 6deg(0.128556) 28deg(0.026178) (S0510F015) 6degwhite (S0510F017) (S0510F016) adipose (0.0361551) 6deg (0.0716966) (0.0405672)[ (S0510F018)min ] (0.0183043)[ medium ] [ max ] CEM 1 Pcca 1570.9 3508.3 6567.2 P ( S | Z, I ) = 1.00 Aldh6a1 3047.7 4416.9 6328.2 Mean Corr = 0.73840 Mut 1405.9 2855.6 4624.5 Mcee 1225.2 2154.3 6728.7 Pccb 1428.9 3319.3 6632.6 Suclg1 2431.4 5001.3 8698.5 Suclg2 716.5 1183.7 2529.7 Acss2 3952.9 4925.6 7030.0 Hibch 1201.9 2521.2 4899.5 Mlycd 309.9 715.1 2464.4 Acacb 3144.6 7666.2 12634.2 Acss1 2439.9 4032.7 10652.6 Echs1 2162.1 4180.1 8293.8 Hibadh 1256.8 2157.7 3996.7 Clybl 982.5 2231.8 4473.4 Acadm 2775.2 6285.1 9314.5 Coq9 1724.8 4312.8 7842.3 CEM 1 + Hadh 5165.2 9186.0 11906.4 Top 10 Genes Decr1 3343.1 7922.8 10766.9 Mccc1 1710.0 3327.5 4235.2 Sdha 4573.0 6963.8 9733.5 Ivd 1969.7 3356.0 4002.2

Null module Sucla2 GEO Series "GSE23006" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 48 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23006 Status: Public on Jul 20 2010 Title: Transcriptional profiling of a wound healing process in skin and oral mucosa Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20704739 Summary & Design: Summary: When compared to skin, oral mucosal wounds heal rapidly and with reduced scar formation. This study used an Affymetrix microarray platform to compare the transcriptomes of oral mucosa and skin wounds in order to identify critical differences in the healing response at these two sites.

Overall design: Using microarrays, we explored the differences in gene expression in skin and oral mucosal wound healing in a murine model of paired equivalent-sized wounds. Samples were examined from day 0 to day 10 and spanned all stages of the wound healing process. Unwounded matched tissue was used as a control. Tissue samples collected at each post-wounding time point, as well as control samples, were represented by 3 biological replicates.

Background corr dist: KL-Divergence = 0.1559, L1-Distance = 0.0300, L2-Distance = 0.0016, Normal std = 0.3721

1.072 Kernel fit Pairwise Correlations Normal fit

Density 0.536

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

unwoundedunwounded tongue,unwounded tongue, biologicalunwounded tongue, biologicalunwounded replicate1 skin, biologicalunwounded replicate2 biological (0.0328662) skin,tongue, replicate3 biological (0.0374471) skin, replicate1tongue, 6hrs biological (0.0490849) post-wounding,replicate2tongue, 6hrs (0.0108226) post-wounding,replicate3skin, 6hrs (0.0114694) 6hrspost-wounding, biologicalskin, (0.00823447) post-wounding, 6hrs biologicalskin, replicate1post-wounding, 6hrs biologicaltongue, replicate2post-wounding, biological (0.0117797)tongue, 12hrs replicate3 biological (0.00869836) post-wounding,replicate1tongue, 12hrs biological (0.0129261) post-wounding,replicate2skin, 12hrs (0.038199) 12hrs post-wounding,replicate3skin, biological (0.0336193) post-wounding, 12hrsskin, biological (0.0354994) replicate1post-wounding, 12hrstongue, biological replicate2post-wounding, biological (0.00274633)tongue, 24hrs replicate3 biological (0.00362923)post-wounding,tongue, 24hrsreplicate1 biological (0.0142294)post-wounding,skin, 24hrsreplicate2 (0.0280511) 24hrs post-wounding,skin, biologicalreplicate3 (0.0185405)post-wounding, 24hrsskin, biological replicate1(0.0336259)post-wounding, 24hrstongue, biological replicate2post-wounding, biological (0.0110175)tongue, 3days replicate3 biological (0.005281)post-wounding,tongue, 3daysreplicate1 biological (0.00600736)post-wounding,skin, 3daysreplicate2 (0.0311526) 3days post-wounding,skin, replicate3biological (0.0310663)post-wounding, 3daysskin, biological (0.0261024)replicate1post-wounding, 3daystongue, biological replicate2post-wounding, biological (0.00978674)tongue, 5days replicate3 biological (0.0296968)post-wounding,tongue, 5days replicate1 biological (0.0162683)post-wounding,skin, 5days replicate2 (0.0106642) 5days post-wounding,skin, biologicalreplicate3 (0.017363)post-wounding, 5daysskin, biological replicate1(0.0156545)post-wounding, 5daystongue, biological replicate2post-wounding, biological (0.0227751)tongue, 7days replicate3 biological (0.0168709)post-wounding,tongue, 7days replicate1 biological (0.0204376)post-wounding,skin, 7days replicate2 (0.0165878) 7days post-wounding,skin, biologicalreplicate3 (0.0214869)post-wounding, 7daysskin, biological replicate1(0.00988054)post-wounding, 7daystongue, biological replicate2post-wounding, biological (0.0176942)tongue, 10days replicate3 biological (0.0431244)tongue, 10days post-wounding,replicate1 biological (0.0394668)skin, 10days post-wounding,replicate2 (0.0108368) 10daysskin, post-wounding,replicate3 biological (0.0142299) 10dayspost-wounding,skin, biological (0.0217432) replicate110dayspost-wounding, biological replicate2post-wounding, biological (0.0389126) replicate3 biological (0.0328168) replicate1 biological[ (0.0322249) replicate2min (0.0154849) replicate3 ] (0.0134543) (0.0104424)[ medium ] [ max ] CEM 1 Pcca 380.6 1047.6 1657.1 P ( S | Z, I ) = 1.00 Aldh6a1 590.1 1793.1 3137.9 Mean Corr = 0.73502 Mut 816.1 1557.6 3157.4 Mcee 215.1 657.4 1280.0 Pccb 701.8 1164.7 1598.4 Suclg1 2669.6 5375.1 8157.4 Suclg2 295.7 675.8 926.5 Acss2 384.0 877.2 1240.3 Hibch 13.7 50.7 97.7 Mlycd 284.5 749.9 1355.5 Acacb 243.7 828.9 1851.0 Acss1 103.4 424.2 1076.2 Echs1 874.5 2490.7 4822.5 Hibadh 1217.6 2319.9 3740.2 Clybl 103.2 442.4 1015.0 Acadm 1786.8 5369.3 10696.1 Coq9 1060.4 4735.2 8032.3 CEM 1 + Hadh 2389.8 5514.7 8420.2 Top 10 Genes Decr1 762.4 1963.5 3627.7 Mccc1 980.8 1645.1 2350.3 Sdha 2894.7 6205.8 10326.9 Ivd 429.8 1070.3 1696.2

Null module Sucla2 GEO Series "GSE31208" 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=GSE31208 Status: Public on Dec 31 2011 Title: Expression data of MCK conditional frataxin knock-out mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Frataxin deficiency in human is the cause of Friedreich's ataxia (FA), a lethal neuro- and cardio-degenerative disease. Knock-out (KO) mice of this mouse model of FA exhibit classical cardiomyopathy of the patients. The onset of FA phenotypes in the KO mice is approximately 6-7 weeks of age. This genearray analysis was conducted to examine the changes in gene expression in the heart of KO mice relative to their wild-type (WT) littermates at 4- and 10-weeks of age. At 10-weeks of age, the KO mice begin to die from severe cardiomyopathy.

Overall design: RNA from the heart of four female 4-week-old MCK littermates (two WT and two KO) and four female 10-week-old MCK littermates (two WT and two KO) was extracted and hybridised to Affymetrix Mouse Genome 430 2.0 Array.

Background corr dist: KL-Divergence = 0.0279, L1-Distance = 0.0409, L2-Distance = 0.0027, Normal std = 0.6823

0.585 Kernel fit Pairwise Correlations Normal fit

Density 0.292

0.000 CEM 1

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

Pre-normalization Quantiles

Heart_10wk_KO_mouse_1Heart_10wk_WT_mouse_1Heart_10wk_WT_mouse_2Heart_10wk_KO_mouse_2 (0.411054)Heart_4wk_KO_mouse_1 (0.107089)Heart_4wk_WT_mouse_1 (0.0443807)Heart_4wk_KO_mouse_2 (0.152224)Heart_4wk_WT_mouse_2 (0.054606) (0.074252) (0.0367345) (0.11966)[ min ] [ medium ] [ max ] CEM 1 Pcca 2107.6 3897.3 4274.6 P ( S | Z, I ) = 1.00 Aldh6a1 1514.5 3503.9 4333.5 Mean Corr = 0.72353 Mut 2125.2 4297.3 5062.2 Mcee 1234.2 4596.0 7372.6 Pccb 1165.8 1588.3 1848.8 Suclg1 8919.3 13872.5 15563.8 Suclg2 779.7 1521.7 1865.1 Acss2 753.7 1196.0 1456.3 Hibch 206.3 357.6 387.6 Mlycd 1081.2 1654.5 1813.6 Acacb 1427.9 2881.3 3487.2 Acss1 2755.5 4718.9 5027.6 Echs1 4957.6 9475.6 10615.2 Hibadh 3908.9 6969.4 7266.5 Clybl 910.7 2017.8 2940.2 Acadm 19223.2 27371.2 29816.8 Coq9 4775.0 9951.4 11660.3 CEM 1 + Hadh 10984.8 22308.8 23358.6 Top 10 Genes Decr1 6748.2 12892.7 15765.8 Mccc1 2000.0 4706.4 5206.5 Sdha 17128.4 24062.9 26041.2 Ivd 2655.8 4680.0 5754.3

Null module Sucla2 GEO Series "GSE43825" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 31 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43825 Status: Public on Dec 31 2013 Title: Gene expression profiles from mammary tissue of control mice, small K5˛N˛†cat hyperplasia, large K5˛N˛†cat hyperplasia and K5˛N˛†cat tumor Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Basal-like breast cancer is a heterogeneous disease characterised by the expression of basal cell markers, no oestrogen or progesterone receptor expression and a lack of HER2 overexpression. Recent studies have linked activation of the Wnt/beta-catenin pathway to basal-like breast cancer. Transgenic mice expressing N-terminally truncated stabilised beta-catenin in the mammary basal/myoepithelial cell layer (K5deltaNbetacat strain) develop mammary hyperplasias that progress to invasive carcinomas. Histological and microarray analyses of these lesions have revealed their high similarity to a subset of basal-like human breast tumours with squamous differentiation. As in human basal-like carcinomas, the Myc pathway was found to be activated in the mammary lesions of K5deltaNbetacat mice. Mammosphere and transplantation assays showed that a basal cell population with stem/progenitor characteristics was amplified in K5deltaNbetacat mouse preneoplastic glands. Myc deletion from the mammary basal layer of K5deltaNbetacat mice abolished both basal cell regenerative capacity and tumorigenesis. These results show that Myc is essential for beta-catenin-induced stem cell amplification and tumorigenesis and that basal stem/progenitor cells may be at the origin of a subset of basal-like breast tumours.

Overall design: mammary tissue from K5˛N˛†cat mice were dissected at successive stages of development (small hyperplasia (n=5), large hyperplasia (n=5), tumor (n=11) and control (n=4)) for RNA extraction and hybridization on Affymetrix microarrays

Background corr dist: KL-Divergence = 0.0953, L1-Distance = 0.0371, L2-Distance = 0.0022, Normal std = 0.4542

0.902 Kernel fit Pairwise Correlations Normal fit

Density 0.451

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

K5˛N˛†catK5˛N˛†cat miceK5˛N˛†cat tumor miceK5˛N˛†cat 1 tumor (0.00733921) miceK5˛N˛†cat 2 tumor (0.00840943) miceK5˛N˛†cat 3 tumor (0.00909968) miceK5˛N˛†cat 4 tumor (0.0177612) miceK5˛N˛†cat 5 tumor (0.0146233) miceK5˛N˛†cat 6 tumor (0.0205728) miceK5˛N˛†cat 7 tumor (0.0115819) miceK5˛N˛†cat 8 tumor (0.0110762) miceK5˛N˛†cat 9 tumor (0.0154187) miceK5˛N˛†cat 10 tumor (0.018806)smallK5˛N˛†cat 11 hyperplasia (0.0150962)smallK5˛N˛†cat hyperplasia small 1K5˛N˛†cat (0.0260508) hyperplasia small 2K5˛N˛†cat (0.0298725) hyperplasia small 3K5˛N˛†cat (0.0479536) hyperplasia Large 4K5˛N˛†cat (0.0456626) hyperplasia Large 5K5˛N˛†cat (0.0323591) hyperplasia Large 1K5˛N˛†cat (0.00560286) hyperplasia Large 2Control (0.00373612) hyperplasia Large 3Control mice (0.00513191) hyperplasia 1 4Control (0.092021)mice (0.026096) 2 5Control (0.0700699)mice (0.0287434) 3 sorted (0.120184)mice 4 basal sorted(0.0487788) cells basalsorted Control cells basalsorted Control mice cells basalsorted 1 Control (0.0292112)mice cells basalsorted 2 K5creL/L (0.0794017)mice cells basal 3 K5creL/L(0.0234524) micecells K5creL/L1 (0.0490443)mice 2 (0.049317)mice[ min3 (0.0375256) ] [ medium ] [ max ] CEM 1 Pcca 129.6 878.9 3393.9 P ( S | Z, I ) = 1.00 Aldh6a1 245.4 1075.7 7854.1 Mean Corr = 0.72214 Mut 216.1 1045.4 4782.2 Mcee 243.7 672.0 1463.7 Pccb 249.6 681.7 2450.0 Suclg1 390.5 2452.9 6181.0 Suclg2 29.3 528.5 936.5 Acss2 16.2 537.9 5665.4 Hibch 41.5 165.2 468.2 Mlycd 9.8 222.7 815.3 Acacb 5.0 178.7 2854.0 Acss1 22.8 434.4 873.3 Echs1 126.0 1834.7 7300.8 Hibadh 242.7 1579.1 6971.4 Clybl 85.7 338.4 1948.9 Acadm 519.4 2645.6 15385.4 Coq9 187.5 736.6 3160.8 CEM 1 + Hadh 663.6 2737.3 13375.0 Top 10 Genes Decr1 372.6 1602.1 10156.9 Mccc1 362.6 1261.2 5281.8 Sdha 1304.6 4267.3 12805.0 Ivd 5.0 506.3 3943.6

Null module Sucla2 GEO Series "GSE3313" 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=GSE3313 Status: Public on Jun 30 2014 Title: Impaired revascularization in a mouse model of diabetes associated with dysregulation of angiogenic-regulatory network. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 15920034 Summary & Design: Summary: Diabetes is a risk factor for the development of cardiovascular diseases that are associated with impaired angiogenesis or increased endothelial cell apoptosis. Here is it shown that angiogenic repair of ischemic hind limbs was impaired in Lepr db/db mice, a leptin receptor deficient model of diabetes, compared to wild-type C57BL/6 (WT) mice as evaluated by laser Doppler flow and capillary density analyses. To identify molecular targets associated with this disease process, hind limb cDNA expression profiles were created from adductor muscle of Lepr db/db and WT mice before and after hind limb ischemia using Affymetrix GeneChipÂ® Mouse Expression Set microarrays. The expression patterns of numerous angiogenesis related proteins were altered in Lepr db/db versus WT mice following ischemic injury. These transcripts included neuropilin-1, VEGF-A, placental growth factor, elastin and matrix metalloproteinases that are implicated in blood vessel growth and maintenance of vessel wall integrity. These data illustrate that impaired ischemia-induced neovascularization in type 2 diabetes is associated with the dysregulation of a complex angiogenesis-regulatory network.

Keywords: Diabetes, ischemia, angiogenesis, microarrays

Overall design: Gene expression data for adductor muscle in the ischemic limb from wild type mice and Lepr db/db mice of 4 time points (before hind limb ischemia, 1 day, 7 days and 14 days after hind limb ischemia surgery). Three independent experimental replicates of each condition for each time point.

Background corr dist: KL-Divergence = 0.1724, L1-Distance = 0.0358, L2-Distance = 0.0026, Normal std = 0.3616

1.106 Kernel fit Pairwise Correlations Normal fit

Density 0.553

0.000 CEM 1

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

Pre-normalization Quantiles

WT1_hindlimb_d0_rep1WT2_hindlimb_d0_rep2WT3_hindlimb_d0_rep3WT4_hindlimb_d1_rep1 (0.0801468)WT5_hindlimb_d1_rep2 (0.0600003)WT6_hindlimb_d1_rep3 (0.11669)WT7_hindlimb_d7_rep1 (0.0284584)WT8_hindlimb_d7_rep2 (0.0461499)WT9_hindlimb_d7_rep3 (0.157053)WT10_hindlimb_d14_rep1 (0.00884344)WT11_hindlimb_d14_rep2 (0.0501626)WT12_hindlimb_d14_rep3 (0.0304764)LEPRDB/DB1_hindlimb_d0_rep1 (0.0163176)LEPRDB/DB2_hindlimb_d0_rep2 (0.0225097)LEPRDB/DB3_hindlimb_d0_rep3 (0.0373025)LEPRDB/DB4_hindlimb_d1_rep1LEPRDB/DB5_hindlimb_d1_rep2 (0.0360996)LEPRDB/DB6_hindlimb_d1_rep3 (0.0272533)LEPRDB/DB7_hindlimb_d7_rep1 (0.0402781)LEPRDB/DB8_hindlimb_d7_rep2 (0.021198)LEPRDB/DB9_hindlimb_d7_rep3 (0.0113956)LEPRDB/DB10_hindlimb_d14_rep1 (0.0160381)LEPRDB/DB11_hindlimb_d14_rep2 (0.0387561)LEPRDB/DB12_hindlimb_d14_rep3 (0.0094851) (0.0411429) (0.013859) (0.0487545)[ min (0.0416288) ] [ medium ] [ max ] CEM 1 Pcca 853.7 1543.9 2608.2 P ( S | Z, I ) = 1.00 Aldh6a1 1216.5 4018.1 6399.5 Mean Corr = 0.71642 Mut 1033.2 2086.5 3152.0 Mcee 712.8 1448.6 3746.1 Pccb 659.9 1030.2 2285.9 Suclg1 3386.2 8514.7 17723.5 Suclg2 213.9 664.3 1329.3 Acss2 310.4 854.1 1734.8 Hibch 70.5 172.2 503.5 Mlycd 480.4 1627.7 2669.5 Acacb 460.3 2443.1 5218.8 Acss1 354.8 654.2 2188.9 Echs1 702.3 2364.1 7494.6 Hibadh 2170.6 3851.3 7220.3 Clybl 394.1 872.0 1888.6 Acadm 3688.9 9212.4 17622.6 Coq9 2047.9 7493.0 17437.9 CEM 1 + Hadh 3174.9 6253.1 10523.5 Top 10 Genes Decr1 1573.1 3178.9 6638.0 Mccc1 811.4 1418.4 1960.2 Sdha 6724.2 10847.9 21660.0 Ivd 654.3 1484.0 2480.8

Null module Sucla2 GEO Series "GSE34839" 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=GSE34839 Status: Public on Feb 28 2012 Title: Pten loss and RAS/MAPK activation cooperate to promote EMT and prostate cancer metastasis initiated from stem/progenitor cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22350410 Summary & Design: Summary: PTEN loss or PI3K/AKT signaling pathway activation correlates with human prostate cancer progression and metastasis. However, in preclinical murine models, deletion of Pten alone fails to mimic the significant metastatic burden that frequently accompanies the end stage of human disease. To identify additional pathway alterations that cooperate with PTEN loss in prostate cancer progression, we surveyed human prostate cancer tissue microarrays and found that the RAS/MAPK pathway is significantly elevated both in primary and metastatic lesions. In an attempt to model this event, we crossed conditional activatable K-rasG12D/WT mice with the prostate conditional Pten deletion model we previously generated. Although RAS activation alone cannot initiate prostate cancer development, it significantly accelerated progression caused by PTEN loss, accompanied by epithelial-to-mesenchymal transition (EMT) and macrometastasis with 100% penitence. A novel stem/progenitor subpopulation with mesenchymal characteristics was isolated from the compound mutant prostates, which was highly metastatic upon orthotopic transplantation. Importantly, inhibition of RAS/MAPK signaling by PD325901, a MEK inhibitor, significantly reduced the metastatic progression initiated from transplanted stem/progenitor cells. Collectively, these data indicate that activation of RAS/MAPK signaling serves as a potentiating second hit to alteration of the PTEN/PI3K/AKT axis and co-targeting both pathways is highly effective in preventing the development of metastatic prostate cancers.

Overall design: Murine mutants with prostate specific loss of Pten and K-ras activation (K-rasG12D) under regulation of the probasin promoter developed high grade, invasive prostate cancer. RNA was extracted from dissected prostate lobes from individual mutants with pathology thought to closely mimic human disease. Prostate tissue was subject to RNA extraction and hybridization on Affymetrix cDNA microarrays.

Background corr dist: KL-Divergence = 0.0408, L1-Distance = 0.0392, L2-Distance = 0.0022, Normal std = 0.6408

0.647 Kernel fit Pairwise Correlations Normal fit

Density 0.323

0.000 CEM 1

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

Pre-normalization Quantiles

Pb-Cre+;PtenL/W;K-rasG12D/W,Pb-Cre+;PtenL/W;K-rasG12D/W,Pb-Cre+;PtenL/W;K-rasG12D/W,Pten null,Pten biological null,Pten biological null,rep1 biological(0.0705688)(0.151243) rep2 (0.369371)(0.241838) rep3 (0.128144)(0.0388351)[ min ] [ medium ] [ max ] CEM 1 Pcca 484.1 766.0 1633.3 P ( S | Z, I ) = 1.00 Aldh6a1 417.3 2483.4 2993.4 Mean Corr = 0.71485 Mut 1068.2 1228.3 1857.9 Mcee 388.1 586.3 704.1 Pccb 505.8 998.8 1742.4 Suclg1 2498.8 3295.2 3627.0 Suclg2 601.8 764.2 785.0 Acss2 269.4 423.1 1001.7 Hibch 29.4 44.9 75.2 Mlycd 387.6 505.8 575.0 Acacb 88.7 167.4 280.9 Acss1 115.2 2117.1 4261.2 Echs1 1299.8 1703.8 1914.2 Hibadh 1551.8 1851.4 3633.2 Clybl 204.6 268.5 481.5 Acadm 2921.2 3884.5 4844.6 Coq9 1061.2 1698.1 2071.6 CEM 1 + Hadh 2708.9 3121.6 3923.5 Top 10 Genes Decr1 1196.1 1554.5 1658.5 Mccc1 703.1 885.3 1103.0 Sdha 2872.8 3557.5 4182.1 Ivd 503.2 736.9 1449.2

Null module Sucla2 GEO Series "GSE7111" 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=GSE7111 Status: Public on Dec 25 2012 Title: Resveratrol treatment of 3T3-L1 cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Murine 3T3-L1 progenitor adipocytes cell cultures, treated and untreated (Control) with resveratrol before the induction of differentiation and the effects on adipogenesis and insulin signaling was investigated.

Keywords: Treatment response

Overall design: 3 Replicates of treated and untreated (Control) cell cultures

Background corr dist: KL-Divergence = 0.0438, L1-Distance = 0.0219, L2-Distance = 0.0005, Normal std = 0.6019

0.678 Kernel fit Pairwise Correlations Normal fit

Density 0.339

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

ResveratrolResveratrol treatmentResveratrol treatment Resveratrolexp 3T3-L1treatment Resveratrolexp cells,3T3-L1treatment Resveratrolexp CT1 cells,3T3-L1treatment (0.144185)exp CT2 cells,3T3-L1treatment (0.205331)exp CT3 cells,3T3-L1 (0.142913)exp T1 cells,3T3-L1 (0.187789)[ T2min cells, (0.124331) T3 ] (0.195451) [ medium ] [ max ] CEM 1 Pcca 2567.6 3914.6 4073.2 P ( S | Z, I ) = 1.00 Aldh6a1 3543.0 5848.7 6034.4 Mean Corr = 0.71065 Mut 1576.9 3412.4 3961.4 Mcee 1121.7 1553.5 1691.5 Pccb 1328.7 2408.3 2606.7 Suclg1 10786.3 14448.6 17757.3 Suclg2 1895.7 2035.1 2218.7 Acss2 1437.5 2590.4 3330.4 Hibch 479.6 732.6 1033.0 Mlycd 498.1 675.4 844.4 Acacb 65.0 191.2 255.8 Acss1 3.4 63.6 80.8 Echs1 4796.4 5426.8 6361.8 Hibadh 9631.8 10802.4 12418.5 Clybl 496.0 759.9 904.8 Acadm 8151.3 13651.5 14877.3 Coq9 4170.3 4793.1 5732.1 CEM 1 + Hadh 7328.1 8898.2 9901.6 Top 10 Genes Decr1 3450.8 5889.0 6920.0 Mccc1 3120.3 5320.3 5673.3 Sdha 5267.1 8351.2 9275.5 Ivd 2040.8 3617.8 4053.8

Null module Sucla2 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 (0.128193)C57BL/6JE16.5 (0.0839345)C57BL/6JE17.5 (0.0801061)C57BL/6JE18.5 (0.0543325)C57BL/6JADULT (0.0921356) (0.0768881) COLON (0.48441)[ min ] [ medium ] [ max ] CEM 1 Pcca 181.0 215.3 963.0 P ( S | Z, I ) = 1.00 Aldh6a1 594.9 783.8 939.8 Mean Corr = 0.70685 Mut 197.3 222.6 243.7 Mcee 778.2 1162.6 1741.0 Pccb 402.5 540.3 757.6 Suclg1 1034.0 1483.5 3137.9 Suclg2 553.9 841.1 1555.5 Acss2 103.1 210.2 594.5 Hibch 134.6 144.3 237.2 Mlycd 223.2 303.2 464.3 Acacb 334.0 448.8 824.1 Acss1 1150.1 2151.2 2894.6 Echs1 597.9 706.0 771.0 Hibadh 283.9 360.4 429.3 Clybl 498.8 653.3 1706.3 Acadm 562.7 722.0 2087.2 Coq9 236.6 467.1 1316.6 CEM 1 + Hadh 6019.3 8535.9 10433.7 Top 10 Genes Decr1 530.2 958.4 1778.0 Mccc1 969.8 1210.5 1325.9 Sdha 1858.4 2461.1 3753.0 Ivd 396.5 444.1 708.4

Null module Sucla2 GEO Series "GSE10589" 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=GSE10589 Status: Public on Feb 19 2009 Title: Comparison of gene expression between the thyroid of mice lacking Slc26a4 and heterzygous controls. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19692489 Summary & Design: Summary: Determination of differential expression of genes in the thyroid of pendrin (Slc26a4) heterozygous and knockout mice at a time point corresponding to maximal thyroid gland activity, postnatal day 15 (P15).

Keywords: Differential expression under disease state

Overall design: A total of Six samples of thyroid RNA obtained from P15 mice were analyzed. Triplicates from pendrin (Slc26a4) heterozygous and knockout mice were run and analyzed.

Background corr dist: KL-Divergence = 0.0392, L1-Distance = 0.0183, L2-Distance = 0.0004, Normal std = 0.6178

0.653 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

PostnatalPostnatal day 15Postnatal (P15)day 15Postnatal thyroid (P15)day 15Postnatal thyroidSlc26a4 (P15)day 15Postnatal thyroidSlc26a4 (heterozygous) (P15)day 15 thyroidSlc26a4 (knockout) (P15)day 15 thyroidSlc26a4 (heterozygous) (P15)mice mice (sample1)thyroidSlc26a4 (knockout) (sample2)[ Slc26a4 (heterozygous) micemin (0.0461197) mice (0.210658) (sample3) (knockout) (sample4)] mice (0.254635) mice (0.0782409) (sample5)[ (sample6) medium (0.23407) (0.176276) ] [ max ] CEM 1 Pcca 1644.5 2823.4 3302.9 P ( S | Z, I ) = 1.00 Aldh6a1 5158.1 5901.6 6476.2 Mean Corr = 0.70642 Mut 1342.7 1936.4 2202.8 Mcee 3131.1 4365.8 4584.7 Pccb 1586.7 2276.6 2493.1 Suclg1 6333.7 8282.8 8308.7 Suclg2 1129.0 1414.9 1635.4 Acss2 835.5 1142.6 1324.5 Hibch 1730.4 2744.5 3472.7 Mlycd 493.4 726.2 951.2 Acacb 1715.3 2901.9 3726.5 Acss1 3677.5 4339.6 4839.4 Echs1 1916.0 3273.5 4066.4 Hibadh 2002.3 2393.1 2757.7 Clybl 568.1 923.3 1116.4 Acadm 6404.7 8505.9 8643.6 Coq9 2399.4 3725.0 4509.5 CEM 1 + Hadh 6773.9 8106.7 8477.6 Top 10 Genes Decr1 4236.4 6525.5 6742.3 Mccc1 2110.7 2619.2 2948.7 Sdha 4806.6 6227.4 6612.7 Ivd 1056.0 1489.4 1698.8

Null module Sucla2 GEO Series "GSE48338" 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=GSE48338 Status: Public on Jun 03 2014 Title: Tpl2 promotes chemokine/chemokine receptor expression and macrophage migration during acute inflammation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24713702 Summary & Design: Summary: In autoimmune diseases, accumulation of activated leukocytes correlates with inflammation and disease progression, and therefore, disruption of leukocyte trafficking is an active area of research. The protein kinase Tpl2 (MAP3K8) regulates leukocyte inflammatory responses and is also being investigated for therapeutic inhibition during autoimmunity. Herein, we addressed the contribution of Tpl2 to the regulation of macrophage chemokine and chemokine receptor expression and subsequent migration in vivo using a mouse model of Tpl2 ablation. We found that gene expression of the chemokine ligands CCL2, CCL7, CXCL2, and CXCL3 as well as the chemokine receptors CCR1 and CCR5 were reduced in macrophages from the bone marrow and peritoneal cavities of tpl2-/- mice following stimulation with LPS. LPS stimulation repressed chemokine receptor expression of CCR1, CCR2 and CCR5. Notably, LPS-induced repression of CCR1 and CCR5 was significantly enhanced in Tpl2-deficient macrophages and was observed to be dependent upon Erk activation and independent of PI3K and mTOR signaling. Consistent with alterations in chemokine and chemokine receptor expression, tpl2-/- macrophages were defective in trafficking to the peritoneal cavity following thioglycollate-induced inflammation. Overall, this study demonstrates a Tpl2-dependent mechanism for macrophage expression of both chemokine receptors and their ligands and provides further insight into how Tpl2 inhibition may disrupt inflammatory networks in vivo.

Overall design: microarray was used to profile the genome-wide expression patterns in Tpl2 wild-type and deficient macrophage.

Background corr dist: KL-Divergence = 0.0154, L1-Distance = 0.0201, L2-Distance = 0.0004, Normal std = 0.8097

0.493 Kernel fit Pairwise Correlations Normal fit

Density 0.246

0.000 CEM 1

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

Pre-normalization Quantiles

BMDM, BMDM,Tpl2 WT, BMDM,Tpl2 unstimulated, WT, BMDM,Tpl2 unstimulated, KO, BMDM,Tpl2 biologicalunstimulated, KO, BMDM,Tpl2 biologicalunstimulated, replicate WT, BMDM,Tpl2 biological LPS replicate WT, 1treated, BMDM, Tpl2(0.117318) biological LPS replicate KO, 2treated, biologicalTpl2(0.178529) LPS replicate KO, 1treated, biological(0.103377) LPS replicate 2treated, biological(0.105407) replicate 1 (0.162884) biological[ minreplicate 2 (0.170381) replicate ]1 (0.0971437) 2 (0.0649606)[ medium ] [ max ] CEM 1 Pcca 699.1 1278.5 1402.8 P ( S | Z, I ) = 1.00 Aldh6a1 363.9 706.7 811.1 Mean Corr = 0.70614 Mut 555.4 999.8 1252.4 Mcee 619.3 1214.0 1351.0 Pccb 298.7 553.0 675.1 Suclg1 2070.6 3175.5 3822.3 Suclg2 148.9 250.2 307.0 Acss2 118.7 176.8 189.3 Hibch 14.3 46.2 68.4 Mlycd 332.7 441.8 566.6 Acacb 81.5 110.7 141.3 Acss1 244.2 445.6 477.2 Echs1 598.8 1775.1 1983.8 Hibadh 1473.8 1574.1 1743.5 Clybl 179.0 209.8 240.4 Acadm 1291.0 5140.3 5286.5 Coq9 441.7 1312.9 1457.6 CEM 1 + Hadh 882.1 2303.9 2595.2 Top 10 Genes Decr1 652.4 998.8 1207.6 Mccc1 500.8 788.1 840.0 Sdha 3288.5 4465.6 4833.6 Ivd 463.0 1011.7 1231.8

Null module Sucla2 GEO Series "GSE20696" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20696 Status: Public on Sep 30 2010 Title: Expression profiling of 3T3-L1 adipogenesis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20887899 Summary & Design: Summary: 3T3-L1 pre-adipocyte cells were grown to confluence and induced to differentiate in adipogeneic media.

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

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

0.651 Kernel fit Pairwise Correlations Normal fit

Density 0.325

0.000 CEM 1

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

Pre-normalization Quantiles

3T3-L1_t1_rep13T3-L1_t1_rep23T3-L1_t2_rep1 (0.0782269)3T3-L1_t2_rep2 (0.0633693)3T3-L1_t3_rep1 (0.0599787)3T3-L1_t3_rep2 (0.0483245)3T3-L1_t4_rep1 (0.0403809)3T3-L1_t4_rep2 (0.059801) (0.362974) (0.286945) [ min ] [ medium ] [ max ] CEM 1 Pcca 943.0 1685.9 4844.6 P ( S | Z, I ) = 1.00 Aldh6a1 474.6 3739.8 13747.7 Mean Corr = 0.70402 Mut 1007.9 1636.3 5975.0 Mcee 377.7 816.6 1881.7 Pccb 403.0 433.4 2386.4 Suclg1 3611.7 5082.1 8212.9 Suclg2 1004.6 1419.3 2198.3 Acss2 307.6 650.8 3292.6 Hibch 98.3 320.1 2103.9 Mlycd 140.6 220.1 433.6 Acacb 81.8 152.3 298.0 Acss1 20.9 22.4 23.4 Echs1 1594.5 4199.5 8541.9 Hibadh 1886.9 4653.7 10735.3 Clybl 473.6 1035.2 3447.1 Acadm 3258.7 10018.0 22820.5 Coq9 842.7 2046.5 4316.0 CEM 1 + Hadh 3636.0 7420.9 12777.0 Top 10 Genes Decr1 1970.3 2840.3 10468.2 Mccc1 1557.0 2400.5 12218.7 Sdha 4226.8 5256.5 12097.1 Ivd 1095.6 2140.4 5959.1

Null module Sucla2 GEO Series "GSE39766" 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=GSE39766 Status: Public on Aug 10 2012 Title: Blockade of TNFÎ± after ischemia reperfusion injury ameliorates renal prognosis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Recently, acute kidney injury (AKI) is thought to develop a predisposition toward chronic kidney disease. But the detailed mechanism of the disease progression after AKI is unknown. We made two ischemia-reperfusion injury (IRI) mice models, repaired kidney model and atrophic kidney model, and studied the mechanism that kidney after IRI became atrophy. We found that the atrophy kidney model had two peaks of apoptosis 3 and 14 days after IRI, whereas the repaired kidney model had only one apoptosis peak 3 days after IRI. We showed that the second apoptosis is responsible for the kidney atrophy. Moreover, apoptotic ligands, TNFÎ± and FasL were upregulated at the same time of two apoptosis peaks on the atrophic kidney, and blockade of them before IRI prevented kidney from falling into atrophy. Surprisingly, inhibition of the second apoptosis by anti-TNFÎ± antibody protected from renal atrophy. We propose that apoptosis might play a major role in AKI progression and blockade of TNFÎ± after IRI will be a new therapeutic approach for AKI.

Overall design: Mice were subjected for 0, 45, and 60 min of unilateral IRI. Mice kidneys were collected at day 1 and 3 after IRI for RNA extraction and hybridization on Affymetrix microarrays. There are 6 samples, 1day IRI45(1), 1day IRI60(2), 1day IRI0(3), 3day IRI45(4), 3day IRI60(5), 3day IRI0(6).

Background corr dist: KL-Divergence = 0.0415, L1-Distance = 0.0215, L2-Distance = 0.0005, Normal std = 0.6111

0.661 Kernel fit Pairwise Correlations Normal fit

Density 0.331

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

1day_IRI451day_IRI60 (0.0418951)1day_IRI0 (0.251086)3day_IRI45 (0.144573)3day_IRI60 (0.105096)3day_IRI0 (0.235809) (0.221541) [ min ] [ medium ] [ max ] CEM 1 Pcca 2878.4 4136.0 5861.8 P ( S | Z, I ) = 1.00 Aldh6a1 11211.4 17076.4 17722.1 Mean Corr = 0.70232 Mut 4073.6 7031.8 7814.9 Mcee 1530.0 2239.8 2458.8 Pccb 2635.7 3103.0 4193.8 Suclg1 10307.6 13449.8 15134.9 Suclg2 3503.5 3874.2 4274.2 Acss2 4665.1 6887.3 7766.8 Hibch 434.3 638.2 828.0 Mlycd 516.4 793.5 1021.0 Acacb 153.9 210.5 311.4 Acss1 2440.3 3782.1 5273.9 Echs1 5266.8 7163.8 8849.0 Hibadh 6047.7 11199.4 11958.0 Clybl 1567.3 1991.6 2412.5 Acadm 16912.1 29625.7 31934.5 Coq9 2537.3 3464.0 4209.6 CEM 1 + Hadh 9654.5 14133.2 14902.6 Top 10 Genes Decr1 5432.1 8220.1 9990.2 Mccc1 1883.9 3236.4 4706.4 Sdha 8412.1 12069.0 15024.4 Ivd 2218.0 3534.3 5246.1

Null module Sucla2 GEO Series "GSE13044" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 59 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13044 Status: Public on Oct 07 2008 Title: Gene expression profiling in the lung and liver of low and high dose Perfluorooctanoic Acid exposed mouse fetuses Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17681415 Summary & Design: Summary: Exposure to PFOA during gestation altered the expression of genes related to fatty acid catabolism in both the fetal liver and lung. In the fetal liver, the effects of PFOA were robust and also included genes associated with lipid transport, ketogenesis, glucose metabolism, lipoprotein metabolism, cholesterol biosynthesis, steroid metabolism, bile acid biosynthesis, phospholipid metabolism, retinol metabolism, proteosome activation, and inflammation. These changes are consistent with activation of PPAR alpha. Non-PPAR alpha related changes were suggested as well.

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

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

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

0.664 Kernel fit Pairwise Correlations Normal fit

Density 0.332

0.000 CEM 1

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

Pre-normalization Quantiles

0mg/kg/day0mg/kg/day PFOA,0mg/kg/day RepPFOA,0mg/kg/day 1, Block RepPFOA,0mg/kg/day 1, 2 Block ReplungPFOA,0mg/kg/day 2,(high 2 Block RepliverPFOA, 0mg/kg/daydose) 2,(high 1 Block ReplungPFOA, (0.0143808) 0mg/kg/daydose) 3,(high 1 Block RepliverPFOA, (0.0145301) 0mg/kg/daydose) 3,(high 3 Block ReplungPFOA, (0.0137162) 0mg/kg/daydose) 4,(high 3, Block Rep PFOA,liver (0.0184688) 5mg/kg/daydose) 4, (high4, Block Rep PFOA,lung (0.0147912)5mg/kg/day dose) 5, (high4, Block Rep PFOA,liver (0.0129535)5mg/kg/day dose)5, (high5, Block Rep PFOA,lung (0.0147368)5mg/kg/day dose) 1, (high5, Block Rep PFOA,liver (0.01781)5mg/kg/day dose)1, (high5, Block Rep PFOA,lung (0.0150794)5mg/kg/day dose) 2, (high5, Block Rep PFOA,liver (0.0199117)5mg/kg/day dose)2, (high1, Block Rep PFOA,lung (0.0141786)5mg/kg/day dose) 3, (high1, Block Rep PFOA,liver (0.0175705)5mg/kg/day dose)3, (high2, Block Rep PFOA,lung (0.00941007)5mg/kg/day dose) 4, (high2, Block Rep PFOA,liver (0.0168898)10mg/kg/day dose)4, (high3, Block Rep PFOA,lung (0.0146851)10mg/kg/day dose) 5, (high3, BlockRep liver PFOA, (0.0210953)10mg/kg/day dose)5, (high4, Block lung RepPFOA, (0.0111192)10mg/kg/day dose) (high1,4, Blockliver RepPFOA, (0.0175714)10mg/kg/day dose) (high1, 2, Block Rep PFOA,lung (0.0141204)10mg/kg/day dose) 2, (high2, Block Rep PFOA,liver (0.0186512)10mg/kg/day dose)2, (high1, Block Rep PFOA,lung10mg/kg/day (0.019649) dose) 3, (high1, Block Rep PFOA,liver10mg/kg/day (0.00989266) dose)3, (high3, Block Rep PFOA,lung10mg/kg/day (0.0187721) dose) 4, (high3, Block Rep PFOA,liver0mg/kg/day (0.0189828) dose)4, (high4, Block Rep PFOA,lung0mg/kg/day (0.013666) dose) 5, (high4, PFOA, BlockRep liver0mg/kg/day (0.00901962) dose)5, (high 5, RepPFOA,Block lung0mg/kg/day (0.0146928) 1,dose) (highBlock5, RepPFOA, liver0mg/kg/day (0.0233967) 1, dose) 5 (high Block ReplungPFOA,0mg/kg/day (0.0128728) 2,dose)(low 5 Block RepliverPFOA, dose)0mg/kg/day (0.0165512) 2,(low 1 Block ReplungPFOA, (0.0127949) dose)0mg/kg/day 3,(low 1 Block RepliverPFOA, (0.00652817) dose)0mg/kg/day 3,(low 2 Block ReplungPFOA, (0.0109091) dose)0mg/kg/day 4,(low 2, Block Rep PFOA, liver(0.0164407) dose)1mg/kg/day 4, (low4, Block Rep PFOA, lung(0.0152145) dose)1mg/kg/day 5, (low4, Block Rep PFOA,liver (0.0543694) dose)1mg/kg/day 5, (low3, Block Rep PFOA,lung (0.0124441) dose)1mg/kg/day 1, (low3, Block Rep PFOA,liver (0.0146216) dose)1mg/kg/day 1, (low5, Block Rep PFOA,liver (0.0139179) dose)1mg/kg/day 1, (low2, Block Rep PFOA,lung (0.016759) dose)1mg/kg/day 2, (low2, Block Rep PFOA,liver (0.011213) dose)1mg/kg/day 2, (low3, Block Rep PFOA,lung (0.0132258) dose)1mg/kg/day 3, (low3, Block Rep PFOA,liver (0.0414258) dose)3mg/kg/day 3, (low4, Block Rep PFOA,lung (0.0127866) dose)3mg/kg/day 4, (low4, Block Rep PFOA,liver (0.0169359) dose)3mg/kg/day 4, (low1, Block Rep PFOA,lung (0.0141596) dose)3mg/kg/day 1, (low1, Block Rep PFOA,liver (0.0216716) dose)3mg/kg/day 1, (low3, Block Rep PFOA,lung (0.0126148) dose)3mg/kg/day 2, (low3, Block Rep PFOA,liver (0.0175662) dose)3mg/kg/day 2, (low1, Block Rep PFOA,lung (0.0121787) dose)3mg/kg/day 3, (low1, Block Rep PFOA,liver (0.0237837) dose)3mg/kg/day 3, (low5, Block Rep PFOA,lung (0.0133387) dose)3mg/kg/day 4, (low5, Block Rep PFOA,liver (0.0185684) dose) 4, (low4, Block Rep PFOA,lung (0.013627) dose) 5, (low4, BlockRep liver (0.0367563) dose) 5, (low2, Block lung (0.0116413) dose)[ (low2,min liver (0.0341261) dose) (low ] (0.0133445) dose) (0.0178712)[ medium ] [ max ] CEM 1 Pcca 714.5 2823.7 4532.9 P ( S | Z, I ) = 1.00 Aldh6a1 2207.2 3535.2 7469.9 Mean Corr = 0.70008 Mut 1439.4 2674.2 4739.0 Mcee 662.4 1223.2 1971.3 Pccb 1045.9 1437.2 2466.3 Suclg1 2317.6 5378.5 10141.9 Suclg2 611.2 1893.7 2654.4 Acss2 713.7 1400.7 7434.7 Hibch 33.3 87.0 300.2 Mlycd 206.6 517.9 1721.5 Acacb 108.7 537.3 3327.1 Acss1 464.7 721.7 2445.1 Echs1 2960.3 5708.4 9466.8 Hibadh 1597.0 3236.4 5417.3 Clybl 73.9 371.7 783.1 Acadm 2371.0 10471.6 26521.2 Coq9 794.3 1495.9 2235.8 CEM 1 + Hadh 3955.1 11535.4 20879.7 Top 10 Genes Decr1 1820.9 6818.3 23901.7 Mccc1 1292.2 1748.6 2413.0 Sdha 3414.0 5813.4 7367.1 Ivd 1570.5 2743.5 5402.4

Null module Sucla2 GEO Series "GSE26671" 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=GSE26671 Status: Public on Dec 31 2011 Title: Expression data of murine model of cardiac hypertrophy Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: An initial cellular change in the pathogenesis of heart failure is cardiomyocyte hypertrophy, characterized by increased cell size, enhanced protein synthesis and reactivation of fetal genes. In addition to mechanical stresses, several neurohumoral factors have been identified as potent hypertrophic agents, including angiotensin II, endothelin, and catecholamines.

We used microarrays to study the gene expression during cardiac hypertrophy.

Overall design: Balb/c mice (6-8w) were treated with TAC, ATII infusion, and myocardial infarction. TAC model: The transverse aorta (TAC) was constricted at the upper left sternal border by ligation with a 7-silk surgical thread and 27-gauge needle, which was removed thereafter. Sham-operated controls underwent an identical procedure without TAC. At 1 week and 1month after the procedure, LV was harvested. Ang II model.: Ang II was dissolved in 0.9% NaCl at concentrations sufficient to allow an infusion rate of 2.0 mg/kg/day, known to produce hypertension and cardiac hypertrophy. Control mice received a vehicle (saline) via an osmotic minipump. At 1 week after the procedure, LV was harvested. MI model: The proximal portion of the left coronary artery was ligated using an 8-0 nylon thread. Myocardial ischemia was confirmed by the discoloration of the heart and typical ECG changes. After 30 min occlusion, the left coronary artery was reperfused by loosening the ligature. In sham-operated mice (SHAM), the pericardium was opened, but the coronary artery was not ligated. At 1 day, 1week, and 1 month after the procedure, LV was harvested.

Background corr dist: KL-Divergence = 0.1406, L1-Distance = 0.0310, L2-Distance = 0.0018, Normal std = 0.3847

1.037 Kernel fit Pairwise Correlations Normal fit

Density 0.518

0.000 CEM 1

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

Pre-normalization Quantiles

BD (0.0672128)SD (0.185841)BW (0.115648)SW (0.0347379)BM (0.0619918)SM (0.0351586)MI1W (0.127846)SI1W (0.0284665)MI1M (0.109767)SI1M (0.0663305)AI (0.0468359)AS (0.120164) [ min ] [ medium ] [ max ] CEM 1 Pcca 3462.8 4994.3 5894.0 P ( S | Z, I ) = 1.00 Aldh6a1 3532.7 5526.5 7001.2 Mean Corr = 0.69593 Mut 2445.1 4067.0 5745.1 Mcee 2359.6 3541.3 4929.3 Pccb 1805.1 2395.8 2867.9 Suclg1 12208.9 16517.7 19683.1 Suclg2 1594.4 2395.4 2752.0 Acss2 1315.2 1622.1 1888.8 Hibch 199.1 417.1 565.4 Mlycd 833.3 1339.7 2471.3 Acacb 2258.6 3347.0 4787.0 Acss1 4573.8 6213.5 10100.2 Echs1 9702.6 13723.7 16185.4 Hibadh 6142.5 10368.6 12099.8 Clybl 1317.6 1871.4 2551.8 Acadm 22513.1 30211.3 35948.9 Coq9 9948.2 15497.7 16776.8 CEM 1 + Hadh 15045.6 22218.4 24633.5 Top 10 Genes Decr1 7157.1 11104.5 12915.7 Mccc1 3155.2 4712.7 5954.9 Sdha 18660.6 24298.8 25647.2 Ivd 3412.5 5071.8 6102.9

Null module Sucla2 GEO Series "GSE50439" 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=GSE50439 Status: Public on Mar 01 2014 Title: Examining efficiency of enrichment of kidney pericyte-specific messages by TRAP (Translating Ribosome Affinity Purification) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24652793 Summary & Design: Summary: The long term goal is to define the transcriptional changes that accompany pericyte-to-myofibroblast transition in fibrotic kidney disease. Medullary pericytes are identified by their expression of a eGFPL10a fusion protein whose expression is driven by a Col1a1 promoter. Pericyte-specific RNA is generated by eGFP-affinity purification of polysomes from medullary lysates and then subject to microarray analysis.

Overall design: Col1a1-eGFPL10a mice were subject to Sham or unilateral ureteral obstruction surgery. Sham kidneys were collected at day 0, and UUO kidneys were collected at day 2 or day 5 for TRAP.

Background corr dist: KL-Divergence = 0.1276, L1-Distance = 0.0385, L2-Distance = 0.0032, Normal std = 0.4031

0.990 Kernel fit Pairwise Correlations Normal fit

Density 0.495

0.000 CEM 1

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

Pre-normalization Quantiles

1_day0_bound2_day0_bound 3_day0_bound(0.0151316) 4_day0_unbound(0.0310056) 5_day0_unbound(0.142968)6_day0_unbound (0.149006)7_day2_bound (0.123388)8_day2_bound (0.0994275) 9_day2_bound(0.0567454) 10_day5_bound(0.0500578) 11_day5_bound(0.0535555)12_day5_bound (0.0548158)13_day5_unbound (0.104057)14_day5_unbound (0.0639064)15_day5_unbound (0.0214968) (0.0224437) (0.0119952)[ min ] [ medium ] [ max ] CEM 1 Pcca 425.4 1079.0 2867.9 P ( S | Z, I ) = 1.00 Aldh6a1 1050.2 3031.5 4491.6 Mean Corr = 0.69414 Mut 625.1 1361.3 5188.6 Mcee 941.1 2123.3 4210.9 Pccb 343.2 1268.5 3187.8 Suclg1 217.5 992.4 5209.9 Suclg2 486.0 1680.1 3295.0 Acss2 247.7 948.9 2374.1 Hibch 45.1 401.2 936.1 Mlycd 272.1 563.2 1076.5 Acacb 264.2 811.1 4505.5 Acss1 475.5 2417.8 4128.7 Echs1 781.9 1494.1 2896.1 Hibadh 970.9 2108.2 4508.7 Clybl 345.8 566.7 1530.1 Acadm 1849.5 4846.6 7082.3 Coq9 596.7 1058.8 4313.0 CEM 1 + Hadh 3074.6 4292.9 6466.1 Top 10 Genes Decr1 2438.8 3387.7 5123.7 Mccc1 745.3 1286.4 4740.2 Sdha 4226.1 6138.7 9080.5 Ivd 1092.0 1580.0 3551.5

Null module Sucla2 GEO Series "GSE14891" 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=GSE14891 Status: Public on Feb 19 2009 Title: Expression data of LPS-stimulated macrophages from wild-type and Zc3h12a-/- mice. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19322177 Summary & Design: Summary: Lipopolysaccharide (LPS), a Toll-like receptor (TLR) 4 ligand, induces the expression of various genes including proinflammatory cytokines, and the expression is modified by the presence of Zc3h12a.

We used microarrays to examine influence of Zc3h12a deficiency in LPS-inducible gene expression.

Keywords: Time course after LPS (100 ng/ml) stimulation

Overall design: Peritoneal macrophages from wild-type and Zc3h12a-/- mice were stimulated with LPS for 0, 1, 2 and 4 hours, followed by RNA extraction. Then hybridization on affymetrix microarrays was performed.

Background corr dist: KL-Divergence = 0.0555, L1-Distance = 0.0263, L2-Distance = 0.0011, Normal std = 0.5497

0.726 Kernel fit Pairwise Correlations Normal fit

Density 0.363

0.000 CEM 1

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

Pre-normalization Quantiles

Wild-typeWild-type macrophagesWild-type macrophagesWild-type 0h macrophages (0.299061)Zc3h12aKO_macrophages_0h 1h macrophages (0.0524071)Zc3h12aKO_macrophages_1h 2h (0.027633)Zc3h12aKO_macrophages_2h 4h (0.128648)Zc3h12aKO_macrophages_4h (0.103873) (0.109769) (0.059291)[ (0.219318) min ] [ medium ] [ max ] CEM 1 Pcca 437.2 1002.6 1336.6 P ( S | Z, I ) = 1.00 Aldh6a1 195.2 358.2 420.6 Mean Corr = 0.69108 Mut 146.2 230.0 284.6 Mcee 443.3 1213.3 1589.2 Pccb 128.5 180.5 236.9 Suclg1 803.1 1158.9 1529.3 Suclg2 44.4 77.9 114.0 Acss2 54.1 140.0 264.0 Hibch 33.0 40.3 54.7 Mlycd 67.5 83.8 162.9 Acacb 40.5 46.1 53.0 Acss1 221.9 462.6 1010.7 Echs1 184.6 411.1 586.3 Hibadh 737.4 941.6 974.4 Clybl 31.3 59.5 93.0 Acadm 944.0 2342.2 3493.9 Coq9 148.9 353.5 567.7 CEM 1 + Hadh 520.4 1745.0 2179.1 Top 10 Genes Decr1 196.3 339.4 438.7 Mccc1 93.9 144.0 360.5 Sdha 2446.7 3294.8 4004.4 Ivd 182.4 1102.9 1493.4

Null module Sucla2 GEO Series "GSE52474" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 154 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

Background corr dist: KL-Divergence = 0.1954, L1-Distance = 0.0793, L2-Distance = 0.0167, Normal std = 0.3721 GEO Series "GSE11291" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 60 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11291 Status: Public on Jun 10 2008 Title: Effect of age, calorie restriction and resveratrol on gene expression in mouse heart, brain, and skeletal muscle Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18523577 Summary & Design: Summary: Resveratrol in high doses has been shown to extend lifespan in some studies in invertebrates and to prevent early mortality in mice fed a high-fat diet. We fed mice from middle age (14-months) to old age (30-months) either a control diet, a low dose of resveratrol (4.9 mg kg-1 day-1), or a calorie restricted (CR) diet and examined genome-wide transcriptional profiles.

We report a striking transcriptional overlap of CR and resveratrol in heart, skeletal muscle and brain. Both dietary interventions inhibit gene expression profiles associated with cardiac and skeletal muscle aging. Gene expression profiling suggests that both CR and resveratrol may retard some aspects of aging through alterations in chromatin structure and transcription. Resveratrol, at doses that can be readily achieved in humans, fulfills the definition of a dietary compound that mimics some aspects of CR.

Keywords: aging intervention study

Overall design: Heart, neocortex tissue, and gastrocnemius muscle was collected from young and old mice at 5 and 30 months of age, respectively; mice were subjected to either a calorie restricted diet or a control diet supplemented with resveratrol

Background corr dist: KL-Divergence = 0.0995, L1-Distance = 0.0458, L2-Distance = 0.0038, Normal std = 0.4744

0.888 Kernel fit Pairwise Correlations Normal fit

Density 0.444

0.000 CEM 1

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

Pre-normalization Quantiles

heart-5 heart-5months heart-5months of age-control heart-5months of age-control heart-5 months diet-biologicalof age-control heart-30 months diet-biologicalof age-controlheart-30 replicate1diet-biological ofmonths age-controlheart-30 replicate2diet-biological months of (0.0039396) age-controlheart-30 replicate3diet-biological months of (0.0331943) age-controlheart-30 replicate4 months diet-biologicalof (0.0222514) age-controlheart-30 replicate5 months diet-biologicalof (0.0138965) age-controlheart-30 months replicate1diet-biologicalof (0.0165315) age-controlheart-30 months replicate2diet-biologicalof age-CR(0.020653)heart-30 months replicate3diet-biologicalof age-CR(0.0199723)diet-biologicalheart-30 months replicate4of age-CR(0.0206905)diet-biologicalheart-30 months replicate5of age-CR(0.0169428)replicate1diet-biologicalheart-30 months of age-CR(0.0186114)replicate2diet-biologicalheart-30 (0.0232635) months of age-resveratrolreplicate3diet-biologicalheart-30 (0.0281007) months of age-resveratrolreplicate4heart-30 (0.01668) months of age-resveratrol replicate5diet-biologicalgastrocnemius-5 (0.0230845) months of age-resveratrol diet-biologicalgastrocnemius-5 (0.0179386) of age, replicate1diet-biologicalgastrocnemius-5 resveratrolmonths replicate2diet-biologicalgastrocnemius-5 (0.0144494) months of replicate3age-controldiet-biologicalgastrocnemius-5 (0.0314492) months of replicate4age-controlgastrocnemius-30 (0.0238461) months diet-biologicalof age-controlreplicate5gastrocnemius-30 (0.0244297) months diet-biologicalof age-controlgastrocnemius-30 (0.0139586) replicate1diet-biological ofmonths age-controlgastrocnemius-30 replicate2diet-biological months of (0.00271998) age-controlgastrocnemius-30 replicate3diet-biological months of (0.00737959) age-controlgastrocnemius-30 replicate4 months diet-biologicalof (0.0045798) age-controlgastrocnemius-30 replicate5 months diet-biologicalof (0.0080314) age-controlgastrocnemius-30 months replicate1diet-biologicalof (0.00199376) age-controlgastrocnemius-30 months replicate2diet-biologicalof age-CR(0.00786762)gastrocnemius-30 months replicate3diet-biologicalof age-CR(0.0110749)gastrocnemius-30diet-biological months replicate4of age-CR(0.0134658)gastrocnemius-30diet-biological months replicate5of age-CR(0.0068007)gastrocnemius-30replicate1diet-biological months of age-CR(0.0045764)gastrocnemius-30replicate2diet-biological (0.0136524) months of age-resveratrolgastrocnemius-30replicate3diet-biological (0.0320873) months of age-resveratrolneocortex-5replicate4 (0.00880376) months of age-resveratrol neocortex-5replicate5diet-biological (0.00704877) months of months age-resveratrol neocortex-5diet-biological (0.0108846) of months of age, neocortex-5 replicate1diet-biologicalage-control resveratrol months of neocortex-5 replicate2diet-biologicalage-control (0.00777387) months diet-biologicalof neocortex-30 replicate3age-controldiet-biological (0.00704647) months diet-biologicalof neocortex-30 replicate4age-control (0.00563421) replicate1diet-biological ofmonthsneocortex-30 replicate5age-control (0.0122269) replicate2diet-biological months ofneocortex-30 (0.0215937) age-control (0.00745676) replicate3diet-biological months ofneocortex-30 (0.0213245) age-control replicate4 months diet-biologicalofneocortex-30 (0.0229645) age-control replicate5 months diet-biologicalofneocortex-30 (0.0212528) age-control months replicate1diet-biologicalofneocortex-30 (0.0238439) age-control months replicate2diet-biologicalofneocortex-30 age-CR(0.0215344) months replicate3diet-biologicalofneocortex-30 age-CR(0.0204504)diet-biological months replicate4ofneocortex-30 age-CR(0.0194141)diet-biological months replicate5ofneocortex-30 age-CR(0.0200166)replicate1diet-biological months ofneocortex-30 age-CR(0.0199119)replicate2diet-biological (0.0201205) months ofneocortex-30 age-resveratrolreplicate3diet-biological (0.0186135) months ofneocortex-30 age-resveratrolreplicate4 (0.018993) months of age-resveratrol replicate5diet-biological (0.02221) months of age-resveratrol diet-biological (0.0214052) of age, replicate1diet-biological resveratrol[ minreplicate2diet-biological (0.0205216) replicate3 diet-biological] (0.0216686) replicate4 (0.0197421) [replicate5 medium(0.019872) (0.019558) ] [ max ] CEM 1 Pcca 961.8 2517.6 6898.0 P ( S | Z, I ) = 1.00 Aldh6a1 1041.1 5292.9 8362.4 Mean Corr = 0.68695 Mut 510.1 1593.2 2430.2 Mcee 738.1 2356.8 4729.8 Pccb 758.1 1593.6 2827.1 Suclg1 4439.4 14578.6 20941.6 Suclg2 215.6 1201.2 2495.9 Acss2 878.9 1271.4 2583.1 Hibch 44.1 281.5 839.9 Mlycd 276.4 1240.7 2694.2 Acacb 5.5 2778.9 5890.5 Acss1 282.7 904.9 8852.5 Echs1 1313.2 2611.2 14796.0 Hibadh 1564.9 7323.3 13334.4 Clybl 284.8 1605.7 2686.1 Acadm 1629.3 13654.1 43696.6 Coq9 2080.1 12555.3 22589.9 CEM 1 + Hadh 1002.7 15148.4 35206.5 Top 10 Genes Decr1 476.5 4825.7 22280.1 Mccc1 739.4 1951.2 4310.6 Sdha 5928.1 15671.2 32671.4 Ivd 759.3 1653.0 7323.9

Null module Sucla2 GEO Series "GSE8249" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 46 -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=GSE8249 Status: Public on Aug 02 2007 Title: Systematic discovery and classification of ovarian fertility factors. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17660561 Summary & Design: Summary: Female infertility syndromes are among the most prevalent chronic health disorders in women, but their molecular basis remains unknown because of the complexity of oogenesis and uncertainty regarding the number and identity of ovarian factors controlling the assembly, preservation, and maturation of ovarian follicles. To systematically discover such ovarian fertility factors en masse, we employed a mouse model (Foxo3), where follicles are assembled normally but are then synchronously activated. Gene expression profiling of mutant and normal ovaries led to the identification a surprisingly large set of ovarian factors. The set included the vast majority of known ovarian factors, many of which when mutated produce female sterility phenotypes, but most were novel. Subsequent analyses revealed novel classes of ovarian factors and significant overrpresentation on the X chromosome, among other insights into the general properties of oogenesis genes and their patterns of expression.

Keywords: time course, ovarian fertility factors, Foxo3 mutant

Overall design: Total ovarian RNA from +/+ and -/- ovaries at PND1, 3, 7, and 14 (n=3 replicates per timepoint and genotype, a total of 24 microarrays) was subjected to linear RNA amplification and hybridized to Affymetrix 430 2.0 mouse whole-genome microarrays, which interrogate >39K transcripts including the vast majority of protein-coding genes. We also profiled 14 somatic tissues. Additionally, to provide more refined views of gene expression, we profiled adult ovaries, adult testis, KitlSl/KitlSl-d testis (devoid of germ cells except for rare spermatogonia) (Shinohara et al., 2000), ES cells, laser-capture microdissected (LCM) primary oocytes, LCM somatic cells (granulosa cells + surrounding stroma), superovulated unfertilized eggs, cumulus granulosa cells, and E11 Foxo3 +/+ and -/- embryos. Each array data set was independently normalized by global median scaling, and the signal strengths were averaged for those samples for which replicates were available (PND1-14).

Background corr dist: KL-Divergence = 0.3733, L1-Distance = 0.0696, L2-Distance = 0.0162, Normal std = 0.2829

1.470 Kernel fit Pairwise Correlations Normal fit

Density 0.735

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

Ovary_PD7_Foxo3Ovary_PD7_Foxo3Ovary_PD7_Foxo3 Wt_ReplicaOvary_PD7_Foxo3 Wt_ReplicaOvary_PD7_Foxo3 1 (0.00213262) Wt_ReplicaOvary_PD7_Foxo3 2 (0.00248074) Null_ReplicaOvary_PD14_Foxo3 3 (0.00727183) Null_ReplicaOvary_PD14_Foxo3 1 Null_Replica(0.00195991)Ovary_PD14_Foxo3 2 (0.00366591) Wt_ReplicaOvary_PD14_Foxo3 3 (0.00556068) Wt_ReplicaOvary_PD14_Foxo3 1 (0.00155757) Wt_ReplicaOvary_PD14_Foxo3 2 (0.00237507) Null_ReplicaOvary_PD1_Foxo3 3 (0.0054531) Null_ReplicaOvary_PD1_Foxo3 1 Null_Replica(0.00250128)Ovary_PD1_Foxo3 2Wt_Replica (0.00248001)Ovary_PD1_Foxo3 3Wt_Replica (0.00547079)Ovary_PD1_Foxo3 1 (0.00393874) Wt_ReplicaOvary_PD1_Foxo3 2 (0.00263375) Null_ReplicaOvary_PD3_Foxo3 3 (0.00287779) Null_ReplicaOvary_PD3_Foxo3 1 Null_Replica(0.00647792)Ovary_PD3_Foxo3 2 Wt_Replica(0.00650152)Ovary_PD3_Foxo3 3 Wt_Replica(0.0481313)Ovary_PD3_Foxo3 1 (0.00299519) Wt_ReplicaOvary_PD3_Foxo3 2 (0.00506155) Null_ReplicaOvary_6wk_FVB 3 (0.0151468) Null_ReplicaTestis_6wk_FVB 1 Null_Replica(0.00244745)Adrenal Wt2 (0.00496084) (0.00448866)Placenta_9wk_FVB Gland_6wk_FVB_Female Wt3 (0.00573097) (0.0068621)Uterus_6wk_FVBBone Wt Marrow_6wk_FVB_FemaleSpleen_6wk_FVB_Female (0.00605654) Wt (0.0247144) (0.00209133)Brain_6wk_FVB_MaleEye_6wk_FVB_MaleSkeletal (0.00899402) (0.00994064) Heart_6wk_FVB_Female(0.00392565) Muscle_6wk_FVB_Female (0.00330936)Intestine_6wk_FVB_FemaleKidney_6wk_FVB_FemaleLiver_6wk_FVB_Female (0.118406) (0.0874462)Lung_6wk_FVB_Female (0.00730666)Testis_16wk._Kitl(Sl)/Kitl(Sl-d) (0.214494)Embryo_E11.5_Foxo3 (0.279757)Embryo_E11.5_Foxo3 (0.00495643)LCM oocytes_3wk LCMWt_Female (0.0144145) Somatic_3wk. CumulusNull_Female ovary_FVB(0.00775705)Unfertilized Granulosa ovary_FVB (0.00525464) (0.0146064) Egg_3wk. Cells_FVB (0.00991468) FVB (0.00682709) (0.00866289)[ min ] [ medium ] [ max ] CEM 1 Pcca 419.6 1779.6 6083.3 P ( S | Z, I ) = 1.00 Aldh6a1 122.0 1232.3 9908.9 Mean Corr = 0.68398 Mut 777.6 1441.1 6863.9 Mcee 330.6 833.3 2898.3 Pccb 152.7 681.7 5205.0 Suclg1 1192.5 2741.6 12470.2 Suclg2 222.4 857.7 4963.6 Acss2 264.8 520.2 11254.2 Hibch 7.1 85.7 681.4 Mlycd 258.9 609.0 2646.7 Acacb 25.4 252.2 3670.9 Acss1 27.5 262.6 7820.9 Echs1 392.3 1312.5 10945.7 Hibadh 311.3 1653.9 13596.6 Clybl 17.9 342.7 1479.4 Acadm 1108.4 2978.9 21595.0 Coq9 501.7 1184.3 11060.2 CEM 1 + Hadh 846.8 2654.6 12811.4 Top 10 Genes Decr1 557.9 1715.9 8549.7 Mccc1 281.2 627.9 3828.3 Sdha 1924.5 4860.7 15950.3 Ivd 181.3 1263.7 3685.5

Null module Sucla2 GEO Series "GSE8044" 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=GSE8044 Status: Public on Jun 08 2007 Title: Brown versus white tissue adipose selective genes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17618855 Summary & Design: Summary: The aim of this study was to identify genes expressed selectively in brown adipose tissue as compared to white adipose tissue from the same animals. This analysis provides a gene set that is brown and white adipose selective.

Keywords: tissue comparison from mice

Overall design: Interscapular brown adipose tissue and epididymal white adipose tissue was carefully dissected from 3 male C57Bl/6 mice. These samples were profiled independently using Affymetrix mouse 430_2 gene arrays, representing 3 biological replicates for each brown and white adipose tissues.

Background corr dist: KL-Divergence = 0.0069, L1-Distance = 0.0138, L2-Distance = 0.0002, Normal std = 0.9444

0.428 Kernel fit Pairwise Correlations Normal fit

Density 0.214

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

White adiposeWhite adipose adultWhite rep1 adipose adultBrown (0.159669) rep2 adiposeadultBrown (0.218431) rep3 adiposeBrown adult (0.131444) rep1 adipose adult (0.163097) rep2 adult (0.132885) rep3 (0.194475)[ min ] [ medium ] [ max ] CEM 1 Pcca 4531.5 10769.2 11037.3 P ( S | Z, I ) = 1.00 Aldh6a1 11048.1 11682.0 13711.4 Mean Corr = 0.67485 Mut 2838.3 6209.2 6870.4 Mcee 3897.2 8263.3 8530.6 Pccb 4980.0 10366.5 11192.3 Suclg1 3866.8 20595.2 22160.4 Suclg2 1078.8 2270.3 2979.5 Acss2 2448.3 8063.7 9838.6 Hibch 272.5 911.3 1040.7 Mlycd 1029.7 2135.1 2570.5 Acacb 1932.9 11733.6 12759.8 Acss1 204.2 3454.8 3920.2 Echs1 5095.9 13340.5 15126.1 Hibadh 7405.7 12656.4 14165.8 Clybl 835.8 2956.1 3328.5 Acadm 11075.0 29657.7 30069.1 Coq9 3159.8 10119.3 11532.4 CEM 1 + Hadh 7604.7 16825.5 18878.0 Top 10 Genes Decr1 4836.4 18098.1 18964.5 Mccc1 5221.8 6178.4 7057.6 Sdha 7677.6 23787.1 24629.6 Ivd 4132.1 5005.2 5798.8

Null module Sucla2 GEO Series "GSE23833" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

Overall design:

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

0.668 Kernel fit Pairwise Correlations Normal fit

Density 0.334

0.000 CEM 1

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

Pre-normalization Quantiles

2h_co._enriched12h_co._enriched22h_co._enriched3 (0.0689274)2h_co._total1 (0.0662764)2h_co._total2 (0.0722275) (0.0505038)2h_co._total3 (0.0782057)2h_TGFbeta_enriched1 (0.148572)2h_TGFbeta_enriched22h_TGFbeta_enriched32h_TGFbeta_total1 (0.0819825)2h_TGFbeta_total2 (0.153781)2h_TGFbeta_total3 (0.112666) (0.0386744) (0.0589864) (0.0691972)[ min ] [ medium ] [ max ] CEM 1 Pcca 225.4 616.9 839.5 P ( S | Z, I ) = 1.00 Aldh6a1 82.1 292.7 382.1 Mean Corr = 0.66769 Mut 845.2 1502.9 1933.3 Mcee 108.6 333.7 517.5 Pccb 97.1 261.3 380.7 Suclg1 1597.6 5466.5 6032.9 Suclg2 173.0 659.0 839.0 Acss2 80.2 165.9 215.8 Hibch 22.7 32.1 39.8 Mlycd 129.7 203.7 267.5 Acacb 55.3 74.2 84.6 Acss1 33.1 39.3 44.8 Echs1 182.5 681.0 866.4 Hibadh 280.2 969.9 1190.4 Clybl 38.0 118.1 148.0 Acadm 920.4 2028.5 3178.5 Coq9 441.9 1045.8 1586.6 CEM 1 + Hadh 606.4 2432.0 2703.4 Top 10 Genes Decr1 432.1 1395.6 1776.3 Mccc1 280.7 697.2 910.1 Sdha 2275.9 5357.4 6000.5 Ivd 288.5 799.9 979.7

Null module Sucla2 GEO Series "GSE3530" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 36 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE3530 Status: Public on Nov 01 2005 Title: Distinct Gene Expression Profiles in Adult Mouse Heart Following Targeted MAP Kinase Activation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 16368875 Summary & Design: Summary: Three major MAP kinase signaling cascades, ERK, p38 and JNK, play significant roles in the development of cardiac hypertrophy and heart failure in response to external stress and neural/hormonal stimuli. In order to study the specific function of each MAP kinase branch in adult heart, we have generated three transgenic mouse models with cardiac specific and temporally regulated expression of activated mutants of Ras, MKK3 and MKK7, which are selective upstream activators for ERK, p38 and JNK, respectively. Gene expression profiles in transgenic adult hearts were determined using cDNA microarrays at both early (4-7 days) and late (2-4 weeks) time points following transgene induction. From this study, we revealed common changes in gene expression among the three models, particularly involving extracellular matrix remodeling. However, distinct expression patterns characteristic for each pathway were also identified in cell signaling, growth and physiology. In addition, genes with dynamic expression differences between early vs. late stages illustrated primary vs. secondary changes upon MAP kinase activation in adult hearts. These results provide an overview to both short term and long term effects of MAP kinase activation in heart and support some common as well as unique roles for each MAP kinase cascade in the development of heart failure.

Keywords: MAP Kinase induction comparison, time course

Overall design: Î±MHC-floxed-HRas-v12/MKK3bE/MKK7D transgenic mice were bred with Î±MHC-Mer-Cre-Mer (MCM) mice (from Dr. J. Molkentin, Cincinnati Childrens Hospital)to generate double transgenic animals harboring both floxed transgenes and Mer-Cre-Mer transgene. At 12 weeks of age the double transgenic mice and non-transgenic littermate controls were treated via i.p. injection of tamoxifen at a dosage of 20mg/kgBW once a day for 3 consecutive days as reported. The hearts were harvested at an early (4-7 days post first tamoxifen injection) and a late (2-4 weeks) time point. Left ventricles were dissected and rapidly frozen in liquid nitrogen and stored at -80¸C prior to protein and RNA analysis.

Background corr dist: KL-Divergence = 0.3192, L1-Distance = 0.0530, L2-Distance = 0.0066, Normal std = 0.2747

1.452 Kernel fit Pairwise Correlations Normal fit

Density 0.726

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 male replicate1 controlmale replicate controlmale (0.0261227) replicate control2female (0.0255304) control5replicatefemale (0.0221638) MKK7Dreplicatefemale 4 (0.0272768) MKK7D replicatecontrol 1 (0.035186)MKK7D controlfemale 2 (0.0507655)MKK7D controlreplicatefemaleMKK7D transgenicreplicatefemale 1 earlyMKK7D transgenicreplicate timepoint2 earlyfemaleMKK7D transgenic timepoint3 replicateearly female(0.0170133)MKK7D control timepoint replicate female(0.00774468) 5 MKK7D earlycontrolfemale replicate (0.0582286) timepoint6 MKK7D earlycontrolreplicatefemale timepoint7 MKK7D earlytransgenicreplicatefemale(0.0139179) 8 late timepointMKK7D transgenicreplicate(0.00639844)timepoint 9 latefemaleHRas-v12 transgenic(0.0035092)timepoint 10 (0.0115511)replicatefemale lateHRas-v12 timepointtransgenic (0.0314491)replicatefemale 13HRas-v12 late transgenic replicate (0.0450354) timepoint 14femaleHRas-v12 late transgenic timepoint 15replicatefemaleHRas-v12 (0.0146404) late transgenic timepoint replicatemaleHRas-v12 1(0.0109363) earlytransgenic replicate male HRas-v12 timepoint3(0.0124214) earlytransgenic replicate 1male HRas-v12timepointearly transgenic(0.0133536) replicate timepoint2female HRas-v12early transgenic(0.0442771) timepoint3replicatefemale HRas-v12early (0.0909733) transgenic timepointreplicatefemaleHRas-v12 2(0.0598509) latetransgenic replicatemaletimepointMKK3bE 3(0.0595495) latetransgenic replicate maletimepointMKK3bE 4 transgenic(0.00426258) late replicate 1maletimepoint MKK3bElate transgenic(0.0193681) replicatetimepoint female 3 MKK3bElate transgenic(0.0095106) timepoint replicatefemale 4 (0.0504147) MKK3bElate transgenic timepoint replicatemale 1(0.07531)MKK3bE earlytransgenic replicate male timepoint2(0.048895)MKK3bE earlytransgenic replicate 2male timepointlate transgenic(0.0231847) replicatetimepoint 3female late (0.017012) timepoint 4replicatefemale (0.0152954) late timepoint replicate (0.012732) 2[ late min timepoint (0.00686896) 3 late ] timepoint (0.0232452) (0.00600534)[ medium ] [ max ] CEM 1 Pcca 1280.7 3127.4 5004.4 P ( S | Z, I ) = 1.00 Aldh6a1 1464.3 3369.8 6380.5 Mean Corr = 0.66217 Mut 1053.0 2848.0 5204.8 Mcee 705.3 2661.9 3950.6 Pccb 1428.4 2327.1 3351.9 Suclg1 5048.8 10122.5 13763.2 Suclg2 652.9 2462.4 3848.2 Acss2 870.1 1785.3 2590.0 Hibch 153.4 333.1 570.7 Mlycd 720.1 1746.2 2581.7 Acacb 870.8 3130.4 5575.7 Acss1 1809.5 6666.8 11580.8 Echs1 4467.1 9761.4 15482.1 Hibadh 3365.7 6489.7 9412.8 Clybl 564.8 1453.5 1999.4 Acadm 7687.9 18813.1 27537.3 Coq9 3729.0 10145.2 14549.8 CEM 1 + Hadh 2468.9 7282.5 14588.8 Top 10 Genes Decr1 5384.5 9014.9 15246.8 Mccc1 560.4 1999.9 4316.0 Sdha 8868.9 14027.6 20380.5 Ivd 1303.3 3147.2 5947.6

Null module Sucla2 GEO Series "GSE28559" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 30 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28559 Status: Public on Jul 15 2011 Title: An expression microarray approach for the identification of candidate metastable epialleles in the mouse genome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Genetic loci displaying environmentally responsive epigenetic marks, termed metastable epialleles, offer a solution to the paradox presented by genetically identical yet phenotypically distinct individuals. The murine viable yellow agouti (Avy) locus is a well-described metastable epiallele that serves as a visual epigenetic biosensor. The Avy locus exhibits a high R-value or ratio of inter-individual (Vi) to inter-tissue (Vt) variance in gene expression, characteristic of what we term the Agouti Expression Fingerprint. We propose a novel method for identification of candidate metastable epialleles based on the Agouti Expression Fingerprint, defining candidates as loci with R-values greater than 1.5 on expression microarray.

Using Expression data from tissues of the three germ layers (liver, kidney, brain), high variance in agouti RNA levels among isogenic animals coupled with low variance among tissue types in individual animals is demonstrated. Here, we provide proof of concept for the Agouti Expression Fingerprint; the characterization of epigenetically labile loci in humans will be crucial to the development of novel screening and therapeutic targets for human disease prevention.

Overall design: For expression microarray studies, total RNA was isolated from liver, kidney, and brain tissue from 10 male Avy/a mice (2 per each of the 5 coat color classes) at time of weaning and coat color determination (day 22). Using Affymetrix GeneChip Mouse Genome 2.0 arrays (Santa Clara, CA), we queried the entire mouse genome for candidate metastable epialleles that display the Agouti Fingerprint. Approximately 100 of the greater than 40,000 transcripts on the mouse array displayed an expression pattern characterized as high inter-individual variation coupled with low inter-tissue variation (R-value > 1.5).

Background corr dist: KL-Divergence = 0.0741, L1-Distance = 0.0520, L2-Distance = 0.0050, Normal std = 0.5242

0.825 Kernel fit Pairwise Correlations Normal fit

Density 0.413

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-Yellow1Kidney-Yellow1 (0.0328597)Brain-Yellow1Liver-Slightly_Mottled1 (0.0289074) (0.0422842)Kidney-Slightly_Mottled1Brain-Slightly_Mottled1Liver-Mottled1 (0.0248305)Kidney-Mottled1 (0.0200788) Brain-Mottled1(0.0635639) (0.0462188)Liver-Heavily_Mottled1 (0.0160393) Kidney-Heavily_Mottled1(0.0462891)Brain-Heavily_Mottled1Liver-Pseudo_Ag1 (0.0536926)Kidney-Pseudo_Ag1 (0.0545303)Brain-Pseudo_Ag1 (0.0430122) (0.0366201)Liver-Yellow2 (0.0312535)Kidney-Yellow2 (0.0402715) (0.0212711)Brain-Yellow2Liver-Slightly_Mottled2 (0.0122863) (0.0401029)Kidney-Slightly_Mottled2Brain-Slightly_Mottled2Liver-Mottled2 (0.0134672)Kidney-Mottled2 (0.0100914) Brain-Mottled2(0.0350264) (0.0420736)Liver-Heavily_Mottled2 (0.00746997) Kidney-Heavily_Mottled2(0.0455156)Brain-Heavily_Mottled2Liver-Pseudo_Ag2 (0.0422792)Kidney-Pseudo_Ag2 (0.0238825)Brain-Pseudo_Ag2 (0.0404723) (0.0337215) (0.00644139) (0.0454468)[ min ] [ medium ] [ max ] CEM 1 Pcca 970.0 4425.0 5711.7 P ( S | Z, I ) = 1.00 Aldh6a1 1133.3 9826.7 13097.8 Mean Corr = 0.66083 Mut 742.5 4883.0 7695.5 Mcee 640.3 2235.6 3730.2 Pccb 879.0 2819.9 5214.6 Suclg1 2802.1 8764.2 14640.6 Suclg2 232.5 2960.0 4276.2 Acss2 1012.2 2788.4 8327.4 Hibch 50.0 194.7 782.0 Mlycd 339.0 634.9 2285.3 Acacb 9.3 389.4 1078.3 Acss1 3.1 558.5 6314.8 Echs1 765.4 4969.4 9977.4 Hibadh 1084.5 9738.3 14336.6 Clybl 230.5 834.5 1730.5 Acadm 1401.6 12508.8 24045.0 Coq9 1069.2 3169.9 4976.8 CEM 1 + Hadh 918.0 8788.4 14654.4 Top 10 Genes Decr1 530.0 5321.1 11354.7 Mccc1 675.4 3037.4 5450.6 Sdha 4603.0 10743.8 18664.3 Ivd 797.5 2398.0 4378.5

Null module Sucla2 GEO Series "GSE19668" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 50 -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=GSE19668 Status: Public on Aug 01 2010 Title: Genetic Determinants for Susceptibility to Staphylococcus aureus Infection in A/J and C57BL/6J Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20824097 Summary & Design: Summary: Although it has recently been shown that A/J mice are highly susceptible to Staphylococcus aureus sepsis as compared to C57BL/6J, the specific genes responsible for this differential phenotype are unknown. Using chromosome substitution strains (CSS), we found that factors on chromosomes (chr) 8, 11, and 18 are responsible for susceptibility to S. aureus sepsis in A/J mice. F1 mice from C57BL/6J X CSS8 cross (C8A) and C57BL/6J X CSS18 (C18A) were also susceptible to S. aureus (median survival < 48 h), whereas F1 mice from C57BL/6J X CSS11 cross (C11A) were resistant (median survival > 120 h) to S. aureus. Bacterial loads in the kidney were consistent with F1 median survivals, with higher bacterial counts in susceptible mice. No sexlinked associations with susceptibility were noted in F1 intercrosses. Using whole genome transcription profiling, we identified a total of 192 genes on chromosomes 8, 11, and 18 which are differentially expressed between A/J and C57BL/6J in the setting of S. aureus infection. Of these, 28 genes had Gene Ontology annotations indicating a potential immune response function. These 28 genes are associated with susceptibility to S. aureus in A/J mice, and are potential determinants of susceptibility to S. aureus infection in humans.

Overall design: To identify genes for which differential expression between A/J and C57BL/6J mice could contribute to host susceptibility to S. aureus infection, we compared the gene expression profiles between uninfected A/J and C57BL/6J mice and between infected A/J and C57BL/6J mice at 2, 4, 6, and 12 hours after infection.

Background corr dist: KL-Divergence = 0.1340, L1-Distance = 0.0649, L2-Distance = 0.0110, Normal std = 0.3963

1.007 Kernel fit Pairwise Correlations Normal fit

Density 0.503

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

blood A/Jblood 0hours A/Jblood 2hoursrep5 A/J blood(0.00569804) 4hoursrep5 A/J blood(0.181951) 6hoursrep5 A/J blood(0.0207064) 12hoursrep5 C57BL/6J blood(0.00569963) rep5 C57BL/6Jblood 0hours(0.0115978) C57BL/6Jblood 2hoursrep5 C57BL/6J(0.00859935)blood 4hoursrep5 C57BL/6J(0.0159018)blood 6hoursrep5 A/J(0.00884705)blood 12hoursrep5 0hours A/J(0.0115694)blood 2hoursrep1rep5 A/J blood(0.00571146)(0.00848967) 4hoursrep1 A/J blood(0.00504994) 6hoursrep1 A/J blood(0.00596322) 12hoursrep1 C57BL/6J blood(0.00946842) rep1 C57BL/6Jblood 0hours(0.00831186) C57BL/6Jblood 2hoursrep1 C57BL/6J(0.0219517)blood 4hoursrep1 C57BL/6J(0.0479658)blood 6hoursrep1 A/J(0.00739236)blood 12hoursrep1 0hours A/J(0.0122434)blood 2hoursrep2rep1 A/J blood(0.00800597)(0.00582314) 4hoursrep2 A/J blood(0.00469436) 6hoursrep2 A/J blood(0.00237659) 12hoursrep2 C57BL/6J blood(0.0307258) rep2 C57BL/6Jblood 0hours(0.0147068) C57BL/6Jblood 2hoursrep2 C57BL/6J(0.0142469)blood 4hoursrep2 C57BL/6J(0.00199935)blood 6hoursrep2 A/J(0.00412608)blood 12hoursrep2 0hours A/J(0.00656644)blood 0hoursrep3rep2 A/J blood(0.286925)(0.00195781) 2hoursrep4 A/J blood(0.0131755) 2hoursrep3 A/J blood(0.00609794) 4hoursrep4 A/J blood(0.00494235) 4hoursrep3 A/J blood(0.00550178) 6hoursrep4 A/J blood(0.00756395) 6hoursrep3 A/J blood(0.0111658) 12hoursrep4 A/J blood(0.00707571) 12hours rep3 C57BL/6Jblood (0.0139955) rep4 C57BL/6Jblood 0hours(0.00559781) C57BL/6Jblood 0hoursrep3 C57BL/6J(0.0298011)blood 2hoursrep4 C57BL/6J(0.0161251)blood 2hoursrep3 C57BL/6J(0.0502322)blood 4hoursrep4 C57BL/6J(0.00391948)blood 4hoursrep3 C57BL/6J(0.00536092)blood 6hoursrep4 C57BL/6J(0.00470169)blood 6hoursrep3 C57BL/6J(0.00481348) 12hoursrep4 (0.00876811) 12hours rep3 (0.00914561) rep4 [(0.00674281) min ] [ medium ] [ max ] CEM 1 Pcca 143.6 265.2 1153.7 P ( S | Z, I ) = 1.00 Aldh6a1 100.5 249.3 5287.8 Mean Corr = 0.65969 Mut 567.1 723.1 1855.8 Mcee 193.7 435.3 1818.9 Pccb 476.3 674.5 1532.6 Suclg1 1247.0 2625.5 7303.6 Suclg2 209.9 392.8 1420.8 Acss2 131.2 338.8 1808.9 Hibch 32.0 43.6 85.8 Mlycd 416.1 535.9 1021.7 Acacb 121.9 212.4 620.0 Acss1 258.8 598.0 1614.5 Echs1 325.3 743.8 3855.5 Hibadh 587.1 1134.4 4528.1 Clybl 46.7 79.2 342.5 Acadm 706.7 1326.2 8811.3 Coq9 409.6 623.3 2377.5 CEM 1 + Hadh 326.8 707.0 4267.9 Top 10 Genes Decr1 237.6 446.4 3452.6 Mccc1 312.5 410.0 1027.6 Sdha 1406.0 2270.1 4667.7 Ivd 505.2 718.0 2145.1

Null module Sucla2 GEO Series "GSE39886" 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=GSE39886 Status: Public on Aug 04 2012 Title: Selective inhibition of CD4+ T-cell cytokine production and autoimmunity by BET protein and c-Myc inhibitors Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22912406 Summary & Design: Summary: Bromodomain-containing proteins bind acetylated lysine residues on histone tails and are involved in the recruitment of additional factors that mediate histone modifications and enable transcription. A compound, I-BET-762, that inhibits binding of an acetylated histone peptide to BRD4 and other proteins of the BET (bromodomain and extra-terminal domain) family, was previously shown to suppress the production of pro-inflammatory proteins by macrophages and block acute inflammation in mice. Here we investigate the effect of I-BET-762 on T cell function. We show that treatment of naÃ¯ve CD4+ T cells with I-BET-762 during early differentiation modulates subsequent cytokine production, and inhibits the ability of Th1-skewed cells to induce autoimmune pathogenesis in a model of experimental autoimmune encephalomyelitis (EAE) in vivo. The suppressive effects of I-BET-762 on T-cell mediated inflammation were not due to inhibition of expression of the pro-inflammatory cytokines, IFN-. or IL-17, but correlated with the ability to suppress GM-CSF production from CNS-infiltrating T cells, resulting in decreased recruitment of macrophages and granulocytes. The effects of I-BET-762 were distinct from those of the fumarate ester, dimethyl fumarate (DMF), a candidate drug for treatment of multiple sclerosis (MS). Our data suggest that I-BET and DMF could have complementary roles in the treatment of MS, and provide a strong rationale for inhibitors of BET-family proteins in the treatment of autoimmune diseases, based on their dual ability to suppress granulocyte and macrophage recruitment by T cells as well as production of pro-inflammatory proteins by macrophages.

Overall design: RNA from resting or activated CD4+ T cells grown in the presence of a control substance (DMSO or Control-768) or two different concentrations of I-BET-762, was hybridized to the chip. There are 3 biological replicates for a total of 2 (cell states) x 4 (conditions) x 3 (replicates) = 24 samples.

Background corr dist: KL-Divergence = 0.1425, L1-Distance = 0.0653, L2-Distance = 0.0080, Normal std = 0.4122

1.069 Kernel fit Pairwise Correlations Normal fit

Density 0.535

0.000 CEM 1

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

Pre-normalization Quantiles

CD4Tcells_resting_DMSO_rep1CD4Tcells_resting_68A_rep1CD4Tcells_resting_62A_0.5_rep1CD4Tcells_resting_62A_0.25_rep1CD4Tcells_activated_DMSO_rep1 (0.0483617) (0.049731)CD4Tcells_activated_68A_rep1CD4Tcells_activated_62A_0.5_rep1 (0.0415631)CD4Tcells_activated_62A_0.25_rep1 (0.0205004)CD4Tcells_resting_DMSO_rep2 (0.0306293)CD4Tcells_resting_68A_rep2 (0.0345327)CD4Tcells_resting_62A_0.5_rep2 (0.0195858)CD4Tcells_resting_62A_0.25_rep2 (0.0266089)CD4Tcells_activated_DMSO_rep2 (0.0433231) (0.0500749)CD4Tcells_activated_68A_rep2CD4Tcells_activated_62A_0.5_rep2 (0.0435664)CD4Tcells_activated_62A_0.25_rep2 (0.0742872)CD4Tcells_resting_DMSO_rep3 (0.0304816)CD4Tcells_resting_68A_rep3 (0.0204751)CD4Tcells_resting_62A_0.5_rep3 (0.0151889)CD4Tcells_resting_62A_0.25_rep3 (0.00850533)CD4Tcells_activated_DMSO_rep3 (0.0339043) (0.0128566)CD4Tcells_activated_68A_rep3CD4Tcells_activated_62A_0.5_rep3 (0.0922301)CD4Tcells_activated_62A_0.25_rep3 (0.0598499) (0.0465505) (0.0398768) (0.128782)[ min (0.0285341) ] [ medium ] [ max ] CEM 1 Pcca 286.6 687.0 1089.3 P ( S | Z, I ) = 1.00 Aldh6a1 17.3 56.3 171.3 Mean Corr = 0.65728 Mut 260.6 765.0 1015.4 Mcee 337.1 637.4 1137.2 Pccb 589.0 901.6 1182.6 Suclg1 2556.7 3414.7 4007.8 Suclg2 233.3 777.8 1227.7 Acss2 104.0 312.0 833.8 Hibch 19.2 76.1 166.7 Mlycd 80.3 151.8 219.3 Acacb 1.4 9.9 26.0 Acss1 25.6 173.5 761.0 Echs1 437.7 659.5 834.8 Hibadh 1066.7 1473.3 2347.5 Clybl 88.6 279.9 558.1 Acadm 943.4 1362.3 2020.7 Coq9 290.5 694.8 987.0 CEM 1 + Hadh 810.6 2533.7 3374.7 Top 10 Genes Decr1 142.1 386.5 671.6 Mccc1 238.6 320.2 467.5 Sdha 2479.6 3871.5 4629.9 Ivd 113.8 317.8 626.1

Null module Sucla2 GEO Series "GSE17796" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 39 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17796 Status: Public on Jan 11 2010 Title: Expression data from B6C3F1 mice treated with reduced oxygen Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice received decreasing oxygen concentrations from 21% to 6% O2 for ~ 30 minutes. Then, the mice remained an additional 120 minutes at 6% O2, control mice were placed insimilarchambers but recieved normal (21%) oxygen.

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

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

0.502 Kernel fit Pairwise Correlations Normal fit

Density 0.251

0.000 CEM 1

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

Pre-normalization Quantiles

liver-vehicle-2hours-repliver-vehicle-2hours-repliver-vehicle-2hours-repliver-vehicle-2hours-rep 1 (0.0441261)liver-hypoxia-2hours-rep 2 (0.0256321)liver-hypoxia-2hours-rep 3 (0.0224641)liver-hypoxia-2hours-rep 4 (0.0437151)liver-hypoxia-2hours-rep 1 (0.0591039)liver-hypoxia-2hours-rep 2 (0.0320449)liver-hypoxia-2hours-rep 3 (0.0208869)liver-hypoxia-2hours-rep 4 (0.0307022)liver-hypoxia-2hours-rep 5 (0.0377341)liver-vehicle-2hours-rep 6 (0.0270946)liver-vehicle-2hours-rep 7 (0.0336002)liver-vehicle-2hours-rep 8 (0.025504)liver-vehicle-2hours-rep 5 (0.0514044)bone 6 (0.0462879) marrow-vehicle-2hours-repbone 7 (0.0476678) marrow-vehicle-2hours-repbone 8 (0.0504181) marrow-vehicle-2hours-repbone marrow-hypoxia-2hours-repbone 1 (0.0159398)marrow-hypoxia-2hours-repbone 2 (0.0147277)marrow-hypoxia-2hours-repbone 3 (0.0151063)marrow-hypoxia-2hours-repspleen-vehicle-2hours-rep 1 (0.0148206)spleen-vehicle-2hours-rep 2 (0.0149688)spleen-vehicle-2hours-rep 3 (0.015267)spleen-vehicle-2hours-rep 41 (0.0158018)(0.0185398)spleen-hypoxia-2hours-rep 2 (0.0201707)spleen-hypoxia-2hours-rep 3 (0.0228865)spleen-hypoxia-2hours-rep 4 (0.021067)spleen-hypoxia-2hours-rep 1 (0.0158948)spleen-vehicle-2hours-rep 2 (0.0193073)spleen-hypoxia-2hours-rep 3 (0.0178986)spleen-hypoxia-2hours-rep 4 (0.0205425)spleen-vehicle-2hours-rep 5 (0.0182077)spleen-vehicle-2hours-rep 7 (0.0181264)spleen-vehicle-2hours-rep 8 (0.0181973)spleen-hypoxia-2hours-rep 6 (0.0155526)spleen-hypoxia-2hours-rep 7 (0.0175817) 8 (0.0160925) 5 (0.0178439) 6 (0.0170721)[ min ] [ medium ] [ max ] CEM 1 Pcca 448.5 636.8 3534.7 P ( S | Z, I ) = 1.00 Aldh6a1 280.5 531.6 13769.5 Mean Corr = 0.64838 Mut 806.4 1016.3 5805.8 Mcee 293.5 720.4 2356.8 Pccb 593.5 939.5 4131.5 Suclg1 1708.7 2453.3 10254.3 Suclg2 495.0 742.2 3869.7 Acss2 314.7 476.3 8749.3 Hibch 28.5 80.9 792.5 Mlycd 322.4 460.6 1995.0 Acacb 115.9 214.3 1629.9 Acss1 28.4 1814.6 3226.2 Echs1 795.5 1277.8 12026.8 Hibadh 1036.6 1340.0 15355.7 Clybl 97.7 202.2 1729.3 Acadm 1987.3 2496.8 15467.3 Coq9 667.7 882.2 4330.0 CEM 1 + Hadh 1276.6 1763.6 12371.0 Top 10 Genes Decr1 801.5 1173.3 9615.9 Mccc1 600.1 882.8 3224.0 Sdha 3959.6 4806.7 12757.0 Ivd 603.5 917.4 5564.5

Null module Sucla2 GEO Series "GSE41907" 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=GSE41907 Status: Public on Dec 01 2012 Title: Transcriptional regulation of myoblasts in HMGA2 KO mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23177649 Summary & Design: Summary: We sought to identify critical factors regulating muscle stem cell activation and commitment, and determined through loss-of-function analyses that HMGA2 (high mobility group AT-hook 2) is a key regulator of myogenesis both in vitro and in vivo.

Overall design: mRNAs were isolated from Hmga2 -/- and Hmga2 +/+ mice myoblasts, and a microarray experiment was performed.

Background corr dist: KL-Divergence = 0.0533, L1-Distance = 0.0165, L2-Distance = 0.0003, Normal std = 0.5505

0.725 Kernel fit Pairwise Correlations Normal fit

Density 0.362

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

MyoblastMyoblast from Myoblastwild from type Myoblastwild mice,from type Myoblastwild biological mice,from type MyoblastHMGA2 biological mice,from replicate MyoblastHMGA2 biologicalKO from replicate mice, 1 (0.026756)HMGA2 KO from biological replicate mice, 2 (0.170634)HMGA2 KO biological mice, 3replicate (0.227706) KO biological mice, replicate [1 (0.2234) minbiological replicate 2 (0.0920559) ] replicate 3 (0.10756) 4 (0.151888)[ medium ] [ max ] CEM 1 Pcca 206.9 275.8 369.3 P ( S | Z, I ) = 1.00 Aldh6a1 516.3 677.0 793.9 Mean Corr = 0.64824 Mut 271.6 301.4 346.0 Mcee 349.9 441.4 579.6 Pccb 145.3 200.7 235.7 Suclg1 1691.4 2031.5 2415.3 Suclg2 733.0 900.9 1272.6 Acss2 35.1 72.3 120.1 Hibch 370.5 463.6 481.7 Mlycd 85.1 102.2 135.2 Acacb 72.7 78.3 94.8 Acss1 30.7 35.7 36.6 Echs1 697.0 754.3 912.9 Hibadh 567.1 608.5 751.4 Clybl 170.9 216.6 362.3 Acadm 633.5 798.7 913.0 Coq9 524.4 677.5 967.3 CEM 1 + Hadh 3123.8 3373.8 3729.0 Top 10 Genes Decr1 993.5 1073.2 1591.5 Mccc1 287.9 372.0 395.5 Sdha 2750.0 3029.6 4100.7 Ivd 315.8 369.1 418.5

Null module Sucla2 GEO Series "GSE25295" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 25 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25295 Status: Public on Nov 17 2010 Title: Critical Role of Sphingolipid Pathway Components in Murine Radiation-Induced Lung Injury: Protection by Sphingosine-1-Phosphate Analogues Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21712494 Summary & Design: Summary: Clinically significant radiation-induced lung injury (RILI) is associated with significant morbidity and mortality and a common toxicity in patients administered thoracic radiotherapy. While the molecular etiology of RILI is poorly understood, we previously characterized a murine model of RILI in which alterations in lung endothelial barrier integrity surfaced as a potentially important pathobiologic event. In these studies, inhibition of HMG-CoA reductase activity (simvastatin) reduced murine RILI-associated lung inflammation and vascular leak and attenuated radiation-induced dysregulation of sphingolipid metabolic pathway genes identified by genome-wide lung gene expression profiling. In the present study, we test the hypothesis that sphingolipid signaling components serve as important modulators of RILI pathobiology and novel therapeutic targets. Sphingolipid involvement in murine RILI was confirmed by radiation-induced increases in lung expression of sphingosine kinase (SphK) isoforms 1 and 2 and increases in the ratio of ceramide to cumulative sphingosine-1-phosphate (S1P) and dihydro-S1P (DHS1P) levels in plasma, bronchoalveolar lavage (BAL) fluid and lung tissue following 25 Gy exposure (6 weeks). Moreover, genetically-engineered mice with either targeted deletion of SphK1 (SphK1-/-), or with reduced expression of selective members of the S1P receptor family (S1PR1+/-, S1PR2-/-, S1PR3-/-,), exhibited marked susceptibility to RILI-mediated lung inflammation. Finally, we assessed the efficacy of three potent vascular barrier-protective S1P analogues FTY720 (FTY), fTysiponate (fTyS) and SEW-2871 (SEW) in attenuating indices of RILI. The phosphonate analogue, fTyS, and to a lesser degree SEW, exhibited significant attenuation of RILI and RILI-induced gene dysregulation compared to control RILI-challenged mice (6 weeks). In contrast, FTY failed to significantly alter physiologic or genomic changes compared to RILI-challenged controls. Together, these results support the targeting of sphingolipid components as a novel and effective therapeutic strategy in RILI.

Overall design: Four mice were treated with PBS as a control. Three mice were treated with (S)-FTY-phosphonate (0.1mg/kg) as a drug control. Three mice were treated with SEW-2871 (0.1mg/kg) as a drug control. Three mice were treated with FTY720 (0.1mg/kg) as a drug control. Three mice were treated with administered radiation (25 Gy) alone. Three mice were treated with both administered radiation (25 Gy) and (S)-FTY-phosphonate (0.1mg/kg). Three mice were treated with both administered radiation (25 Gy) and SEW-2871 (0.1mg/kg). Three mice were treated with both administered radiation (25 Gy) and FTY720 (0.1mg/kg).

Background corr dist: KL-Divergence = 0.2603, L1-Distance = 0.0508, L2-Distance = 0.0060, Normal std = 0.2985

1.336 Kernel fit Pairwise Correlations Normal fit

Density 0.668

0.000 CEM 1

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

Pre-normalization Quantiles

Control,Control, rep1 (0.0315362)Control, rep2 (0.0221875)Control, rep3 (0.0400738)Drug rep4 control (0.0364015)Drug controlfTyS,Drug rep1 controlfTyS,Drug (0.0327832) rep2 controlfTyS,Drug (0.0458272) rep3 controlSEW,Drug (0.0197316) rep1 controlSEW,Drug (0.0555741) rep2 controlSEW,Drug (0.0269301) rep3 controlFTY,Drug (0.0168415) rep1 controlFTY,Radiation (0.0345089) rep2 FTY,Radiation (0.0113562) alone, rep3Radiation (0.0802791) rep1 alone, (0.0557203)Radiation rep2 alone, (0.0282069)Radiation rep3 with (0.021755)RadiationfTyS, with rep1 RadiationfTyS, with (0.0524982) rep2 RadiationfTyS, with (0.108592) rep3 RadiationSEW, with (0.0418325) rep1 RadiationSEW, with (0.0265579) rep2 RadiationSEW, with (0.0196929) rep3 RadiationFTY, with (0.0213417) rep1 FTY, with(0.076731) rep2 FTY, (0.0233795) rep3 (0.0696614)[ min ] [ medium ] [ max ] CEM 1 Pcca 685.2 940.5 1337.7 P ( S | Z, I ) = 1.00 Aldh6a1 1872.3 2328.7 3229.3 Mean Corr = 0.64698 Mut 1376.1 1587.9 1900.4 Mcee 1713.1 1942.6 2442.7 Pccb 1414.5 1783.4 2461.8 Suclg1 1487.3 2079.1 3743.4 Suclg2 506.2 644.6 801.3 Acss2 624.1 963.4 2801.5 Hibch 79.9 113.1 245.0 Mlycd 253.3 311.2 366.8 Acacb 127.6 382.7 1322.3 Acss1 852.4 1384.0 1939.8 Echs1 1347.0 1632.7 3028.5 Hibadh 1668.5 1837.6 2567.7 Clybl 133.6 212.4 547.8 Acadm 3038.2 3725.3 6767.9 Coq9 567.8 785.2 1967.2 CEM 1 + Hadh 2773.3 3443.9 4812.7 Top 10 Genes Decr1 981.6 1283.5 2435.5 Mccc1 756.7 949.0 1708.5 Sdha 3013.1 3479.9 4671.9 Ivd 1177.3 1379.2 1781.5

Null module Sucla2 GEO Series "GSE42049" 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=GSE42049 Status: Public on Oct 04 2013 Title: TWEAK-treated time course in CAKI cells grown as xenografts Organism: Homo sapiens Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23974006 Summary & Design: Summary: Tumor necrosis factor-related weak inducer of apoptosis, TWEAK, is a TNF superfamily member that mediates signaling through its receptor fibroblast growth factor inducible-14, Fn14. In tumor cell lines, TWEAK induces proliferation, survival and NF-kappaB signaling and gene expression that promote tumor growth and suppress antitumor immune responses. Anti-TWEAK antibody, RG7212, inhibits tumor growth in vivo with decreases in pathway activation markers and modulation of tumor, blood and spleen immune cell composition. Candidate response prediction markers, including Fn14, have been identified in mouse models. Phase I pharmacodynamic data from patients are consistent with preclinical results. TWEAK:Fn14 signaling is upregulated in human cancer and pathway activation induces tumor proliferation and survival signaling. Blockade with anti-TWEAK mAb, RG7212, inhibits tumor growth in multiple models in mice. TWEAK induces changes that suppress anti-tumor immune responses and RG7212 blocks these effects resulting in changes in tumor immune cell composition and decreases in cytokines that promote immunosuppression. Antitumor efficacy in mice was observed in a range of Fn14 expressing models with pathway activation and expressing either wild-type or mutant p53, BRAF or KRAS suggesting both a patient selection strategy and potential broad clinical applicability. Preclinical mechanism of action hypotheses are supported by Phase I clinical data, with decreases in proliferation markers and increased tumor T cell infiltration.

Overall design: CAKI cells impanted as xenografts in Athymic, Nu/Nu nude mice, treated with anti-TWEAK antibody (TW212) or Vehicle for 24 hours. Four replicates for each condition were performed. RNA was extracted from xenografts, processed and hybridized to human and mouse chips.

Background corr dist: KL-Divergence = 0.0413, L1-Distance = 0.0299, L2-Distance = 0.0016, Normal std = 0.5969

0.668 Kernel fit Pairwise Correlations Normal fit

Density 0.334

0.000 CEM 1

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

Pre-normalization Quantiles

JH_101019_TweakCaki_12_TW212_MouseJH_101019_TweakCaki_14_TW212_MouseJH_101019_TweakCaki_18_TW212_MouseJH_101019_TweakCaki_19_TW212_MouseJH_101019_TweakCaki_11_Vehicle_MouseJH_101019_TweakCaki_15_Vehicle_Mouse (0.356459)JH_101019_TweakCaki_16_Vehicle_Mouse (0.0496757)JH_101019_TweakCaki_17_Vehicle_Mouse (0.0826271) (0.0920977) (0.0356889) (0.0708986)[ min (0.255289) ] (0.0572637) [ medium ] [ max ] CEM 1 Pcca 490.3 704.4 1052.5 P ( S | Z, I ) = 1.00 Aldh6a1 575.0 1093.6 3129.0 Mean Corr = 0.64561 Mut 832.6 966.5 1391.2 Mcee 565.8 756.3 1108.4 Pccb 513.8 605.8 845.9 Suclg1 2131.3 2504.5 3184.5 Suclg2 223.6 323.8 544.4 Acss2 117.8 181.2 717.0 Hibch 38.4 61.1 205.6 Mlycd 291.4 337.0 392.7 Acacb 117.4 156.9 630.7 Acss1 446.8 608.6 1033.7 Echs1 831.9 1161.0 1936.0 Hibadh 1050.3 1181.1 2115.8 Clybl 103.1 164.5 399.9 Acadm 2005.8 2846.7 4202.8 Coq9 854.5 923.9 1313.1 CEM 1 + Hadh 1138.7 1705.4 2513.2 Top 10 Genes Decr1 700.7 1723.7 2201.5 Mccc1 422.3 655.0 1246.5 Sdha 2123.5 2307.4 3070.1 Ivd 535.7 752.2 1170.8

Null module Sucla2 GEO Series "GSE49128" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 17 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49128 Status: Public on Jul 23 2013 Title: Otitis Media Impact on Middle Ear Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24124478 Summary & Design: Summary: Objective: Otitis media is known to alter expression of cytokine and other genes in the mouse middle ear and inner ear. However, whole mouse genome studies of gene expression in otitis media have not previously been undertaken. Ninety-nine percent of mouse genes are shared in the human, so these studies are relevant to the human condition.

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

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

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

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

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

0.937 Kernel fit Pairwise Correlations Normal fit

Density 0.469

0.000 CEM 1

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

Pre-normalization Quantiles

ME controlME controlrep ME1 (0.0900782) TTrep Hflu ME2 (0.0243687) controlrep ME1 (0.0534556) controlrep ME3 (0.0720798) TTrep Hflu ME4 (0.0436905) controlrep ME2 (0.0633117) controlrep ME5 (0.143792) controlrep ME6 (0.0417812) TTrep Hflu ME7 (0.0190154) TTrep Hflu ME3 (0.0297291) TTrep Hflu ME4 (0.103579) controlrep ME5 (0.0262617) TTrep Hflu ME8 (0.0372311) TTrep Hflu ME6 (0.0571937) TTrep Hflu ME7 (0.0273694) TTrep Hflu 8 (0.0385953) rep 9 (0.128468) [ min ] [ medium ] [ max ] CEM 1 Pcca 632.1 847.8 1074.4 P ( S | Z, I ) = 1.00 Aldh6a1 879.8 1196.4 1597.6 Mean Corr = 0.64525 Mut 611.4 806.5 1038.5 Mcee 785.2 1017.0 1519.5 Pccb 666.8 799.4 1001.0 Suclg1 1944.7 2539.7 3095.1 Suclg2 297.6 361.0 425.1 Acss2 379.4 566.0 720.8 Hibch 125.7 155.7 192.4 Mlycd 244.5 386.3 476.5 Acacb 883.7 1101.3 1585.4 Acss1 2848.1 3634.1 4229.7 Echs1 820.0 1008.3 1269.6 Hibadh 414.6 514.1 610.6 Clybl 362.7 542.4 744.6 Acadm 766.8 1012.9 1368.6 Coq9 1573.0 2018.4 2380.0 CEM 1 + Hadh 2193.4 2900.0 3596.1 Top 10 Genes Decr1 1208.2 1510.7 2271.0 Mccc1 666.2 960.8 1346.1 Sdha 3386.7 3587.6 4044.1 Ivd 974.1 1207.3 1392.6

Null module Sucla2 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 (0.113914) 3 (Affymetrix)Tg,Calcineurin biological (0.0852599) 4 (Affymetrix)Tg,Calcineurin biological (0.0852726) replicate Tg,Differentiating biological (0.120636) replicate Tg, 1 (Affymetrix)Differentiating biological replicate 2 P19CL6(Affymetrix)Differentiating replicate (0.0304326) 3 P19CL6(Affymetrix)Differentiating cells (0.0269533) 4at P19CL6(Affymetrix)Differentiating cellsday (0.034007)6 at afterP19CL6Differentiating cellsday DMSO(0.0216372)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 (0.0719958)replicate 3 (Affymetrix) treatment, (0.0684027)replicate [1 (Affymetrix)medium (0.0672141)replicate 2 (Affymetrix) (0.0738519) 3 (Affymetrix) ] (0.0835864) (0.116836)[ max ] CEM 1 Pcca 329.3 2422.7 3630.5 P ( S | Z, I ) = 1.00 Aldh6a1 854.5 2645.6 4942.8 Mean Corr = 0.64244 Mut 553.9 1235.8 3109.4 Mcee 685.0 2505.3 5415.7 Pccb 1266.6 1721.2 2871.0 Suclg1 2391.1 6344.9 11028.4 Suclg2 775.4 1681.5 2231.6 Acss2 484.4 957.8 1505.0 Hibch 14.1 406.5 568.8 Mlycd 173.5 1000.5 1440.7 Acacb 35.9 1508.5 2630.4 Acss1 83.7 5271.1 7130.8 Echs1 3116.2 5261.7 10026.1 Hibadh 591.2 5797.9 8955.5 Clybl 116.5 1530.0 2036.0 Acadm 1978.3 14001.9 16474.8 Coq9 711.4 7444.0 11170.9 CEM 1 + Hadh 2777.1 6056.5 12342.2 Top 10 Genes Decr1 1617.6 3481.6 10612.0 Mccc1 951.4 1694.1 3839.1 Sdha 3577.5 10049.8 14311.7 Ivd 785.7 2995.9 3952.2

Null module Sucla2 GEO Series "GSE13873" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 27 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

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

0.692 Kernel fit Pairwise Correlations Normal fit

Density 0.346

0.000 CEM 1

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

Pre-normalization Quantiles

IMPGE untreatedIMPGE IFNGIMPGE (0.0974504) 1 (0.103324)IFNGIMPGE 2 (0.0946319)IFNGstomach 3 (0.100761)stomach uninfectedstomach uninfected 1 (0.0511268)stomach infected 2 (0.0403513)stomach infected gastritisstomach infected gastritis 1 (0.00770023)stomach infected gastritis 2 (0.0054626)stomach infected gastritis 3 (0.0221988)stomach infected metaplasia 4 (0.00955049)stomach infected hyperplasia 1stomach (0.0232566)infected hyperplasia stomach1 infected(0.009071) hyperplasia stomach2 infected(0.00529372) hyperplasia stomach3 infected(0.00751893) hyperplasia stomach4 infected(0.00770994) metaplasia stomach5 infected(0.0091407) metaplasia 2stomach (0.0350722)infected metaplasia 3stomach (0.0257628)uninfected metaplasia 4stomach (0.0219566)uninfected Rg 5stomach (0.0212637) infected1 (0.0518489) Rgstomach infected2 Rg (0.00421626) 1stomach (0.0365779)infected Rg 2stomach (0.069649)infected Rg 3 (0.0602384)infected Rg 4 (0.0351106) Rg 5 (0.0437549)[ min ] [ medium ] [ max ] CEM 1 Pcca 615.5 2033.0 4644.6 P ( S | Z, I ) = 1.00 Aldh6a1 401.2 2670.9 8127.8 Mean Corr = 0.64196 Mut 583.8 2101.3 3557.4 Mcee 184.2 992.8 1761.6 Pccb 557.5 1537.4 3087.5 Suclg1 2768.6 5892.4 7462.1 Suclg2 812.4 1383.3 2265.5 Acss2 121.2 1320.9 1828.1 Hibch 40.5 93.4 155.4 Mlycd 258.5 925.9 1152.7 Acacb 65.8 1282.7 1848.3 Acss1 33.1 3198.4 5874.9 Echs1 2029.3 3144.6 5408.9 Hibadh 841.1 3636.9 9148.6 Clybl 186.9 735.0 1599.4 Acadm 1339.3 3271.9 6043.4 Coq9 794.9 2454.5 4441.6 CEM 1 + Hadh 2049.1 6449.3 10253.2 Top 10 Genes Decr1 1859.7 2752.9 3390.4 Mccc1 783.2 2483.2 6145.1 Sdha 4140.2 6890.3 10546.9 Ivd 756.5 1370.2 2920.9

Null module Sucla2 GEO Series "GSE3837" 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=GSE3837 Status: Public on Oct 31 2006 Title: Methylglyoxal treatment of MH-S cell line induces apoptosis and immune response Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17183656 Summary & Design: Summary: Mycobacteria-induced apoptosis of macrophages plays an important role in modulation of the host immune response involving TNF-alpha as major cytokine. The underlying mechanisms are still ill-defined. Here, we show for the first time that methylglyoxal (MG) and AGEs levels were elevated during mycobacterial infection of macrophages and that their increased levels mediated mycobacteria-induced apoptotic and immune response of macrophages. Moreover, we show that high levels of AGEs were formed at the sites of pulmonary tuberculosis. This observation represents the first evidence of the potential involvement of AGEs in tuberculosis and in infectious diseases in general. Global gene expression profiling of MG-treated macrophages reveals diversified potential roles of MG in cellular processes, including apoptosis, immune response, and growth regulation. The results of this study provide new insights into intervention strategies to develop therapeutic tools against infectious diseases in which MG and AGE production plays critical roles.

Keywords: time course, replicates, immune response, apoptosis

Overall design: MH-S cells (ATCC Number: CRL-2019), an alveolar macrophage cell line, was treated with 0.8 mM MG. At different time points after treatment (30 min, 4 h, and 8 h) the cells were harvested for total RNA preparation. As negative control the cells without treatment were included. RNA preparation was performed using Trizol method. Totally three independent experiments were performed, so that each time point consists of biological triplicates.

Background corr dist: KL-Divergence = 0.1074, L1-Distance = 0.0377, L2-Distance = 0.0029, Normal std = 0.4288

0.930 Kernel fit Pairwise Correlations Normal fit

Density 0.465

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

MHS+MG,MHS+MG, 0 min,MHS+MG, replica 0 min,MHS+MG, Areplica 0 (0.0151969)min,MHS+MG, Breplica 30 (0.0448807) min,MHS+MG, C 30replica (0.149958) min,MHS+MG, 30Areplica (0.247838)min,MHS+MG, 240Breplica (0.0440708) min,MHS+MG, 240C replica (0.0778238) min,MHS+MG, 240 Areplica (0.0569115)min,MHS+MG, 480 Breplica (0.0496818)min,MHS+MG, 480 Creplica (0.09223)min, 480 Areplica (0.0943119)min, Breplica (0.0885303) C (0.0385663)[ min ] [ medium ] [ max ] CEM 1 Pcca 391.0 1353.9 1858.3 P ( S | Z, I ) = 1.00 Aldh6a1 67.9 228.3 448.0 Mean Corr = 0.64139 Mut 305.8 770.3 1214.0 Mcee 324.0 505.7 895.7 Pccb 193.2 546.7 643.0 Suclg1 2144.2 4472.7 6747.4 Suclg2 382.4 722.8 2217.6 Acss2 342.9 782.8 1181.9 Hibch 5.4 62.4 155.1 Mlycd 107.4 141.6 397.0 Acacb 12.1 124.5 451.1 Acss1 6.2 37.5 104.7 Echs1 772.4 1232.1 2353.4 Hibadh 817.4 1465.2 2026.3 Clybl 154.7 399.4 694.3 Acadm 1500.9 2261.2 3567.3 Coq9 742.9 1823.4 2406.1 CEM 1 + Hadh 1149.2 2493.3 2906.4 Top 10 Genes Decr1 9.0 73.1 216.2 Mccc1 392.4 660.5 1198.6 Sdha 2720.9 5344.5 8279.4 Ivd 464.1 1310.6 1611.5

Null module Sucla2