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

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

CLIC PDF output has three sections:

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

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

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

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

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

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

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

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

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

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

Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Hadhb Acaa2 Num ofGenesinQueryGeneset:5.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Mecr Ppt1 Ppt2

Acaa2 Hadhb Mecr Ppt2 Ppt1 Singletons CEM 1(293datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 Symbol Num ofCEMGenes:3.Predicted117.SelectedDatasets:293.Strength:0.7 CEM 1,Geneset"[K]Fattyacidelongation",Page1 Fam195a Hsd17b4 Samm50 Uqcrfs1 Ndufb9 Uqcr11 Uqcrc1 Uqcrc2 Ndufs2 Ndufv2 Ndufs1 Ndufs3 Ndufa9 Ndufv1 Ndufs7 Ndufa8 Pmpcb Acadm Atp5a1 Acadvl Suclg1 Atp5f1 Hadhb Retsat Hadha Acads Echs1 Acaa2 Atp5d Atp5b Decr1 Trap1 Acadl Etfdh Coq9 Sdhd Hadh Sdhc Aco2 Clybl Sdha Cyc1 Ech1 Mecr Cluh Cpt2 Eci1 Etfb Etfa Fh1 0.0 1.0

GSE14004 [9] GSE51080 [18]

GSE13224 [6] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE31004 [8] GSE16110 [16] GSE15729 [15] GSE13432 [12] GSE17266 [59] GSE17794 [44] GSE44663 [6] GSE17709 [18] GSE7141 [6] GSE21156 [6] GSE23833 [12] GSE12730 [24] GSE42858 [12] GSE8044 [6] GSE11484 [6] GSE8966 [12] GSE15069 [15] GSE19286 [6] GSE55855 [6] GSE45028 [22] GSE13044 [59] GSE17796 [39] GSE28559 [30] GSE8949 [20] GSE43145 [12] GSE42473 [15] GSE13302 [30] GSE50865 [12] GSE54581 [21] GSE15914 [9] GSE14753 [6] GSE6623 [12] GSE8199 [9] GSE56162 [18] GSE8679 [12] GSE50813 [24] GSE43825 [31] GSE13693 [9] GSE11291 [60] GSE51432 [15] GSE17297 [32] GSE13707 [20] GSE46646 [12] GSE38574 [32] GSE3837 [12] GSE10589 [6] GSE11684 [16] GSE8295 [16] GSE18907 [12] GSE23408 [39] GSE42299 [8] GSE55525 [71] GSE11496 [16] GSE44091 [32] GSE34773 [26] GSE10273 [9] GSE26671 [12] GSE9441 [36] GSE37316 [31] GSE32966 [24] GSE40795 [50] GSE48884 [12] GSE33931 [42] GSE25825 [8] GSE10246 [182] GSE8683 [11] GSE46496 [9] GSE41910 [12] GSE45968 [6] GSE22086 [6] GSE12337 [16] GSE59437 [30] GSE3313 [24] GSE33199 [64] GSE14929 [38] GSE7487 [24] GSE9247 [15] GSE8863 [18] GSE1806 [22] GSE51804 [10] GSE3296 [16] GSE55756 [47] GSE43419 [20] GSE40087 [15] GSE30688 [9] GSE32706 [33] GSE5657 [20] GSE23006 [48] GSE34064 [6] GSE8488 [15] GSE28237 [6] GSE27195 [6] GSE38138 [20] GSE11343 [19] GSE8684 [10] GSE31646 [11] GSE27429 [8] GSE19793 [32] GSE10634 [16] GSE9297 [27] GSE25295 [25] GSE51365 [28] GSE3067 [28] GSE5313 [6] GSE27309 [10] GSE33726 [48] GSE40156 [42] GSE25645 [17] GSE8681 [25] GSE7475 [16] GSE7605 [18] GSE9338 [42] GSE24920 [19] GSE52550 [12] GSE10627 [51] GSE39562 [26] GSE20696 [8] GSE23101 [20] GSE9533 [35] GSE20371 [12] GSE19675 [22] GSE17513 [12] GSE49689 [23] GSE16707 [6] GSE9400 [8] GSE32937 [8] GSE9044 [6] GSE22871 [30] GSE41558 [8] GSE9892 [12] GSE15433 [9] GSE5334 [19] GSE15330 [27] GSE17925 [12] GSE56755 [13] GSE43713 [16] GSE19204 [6] GSE9012 [10] GSE39233 [40] GSE48004 [6] GSE18033 [56] GSE58915 [21] GSE27563 [93] GSE38754 [40] GSE6383 [6] GSE32199 [6] GSE46209 [21] GSE42047 [24] GSE13873 [27] GSE15872 [18] GSE17096 [20] CEM+ CEM GSE3554 [6] GSE5891 [6] GSE46723 [6] GSE14672 [12] GSE41085 [6] GSE32078 [12] 0.0 GSE10989 [6] GSE53077 [8]

GSE31378 [9] Scale ofaveragePearsoncorrelations GSE22307 [23] GSE1479 [36] GSE44356 [18] GSE3100 [23] GSE4671 [28] GSE41759 [14] 0.2 GSE43042 [6] GSE25088 [24] GSE8039 [32] GSE37546 [20] GSE56135 [8] GSE21299 [12] GSE11443 [6] GSE55733 [24] GSE10182 [7] 0.4 GSE40412 [14] GSE6676 [8] GSE5500 [21] GSE39916 [6] GSE50439 [15] GSE34126 [19] GSE10365 [9] GSE2019 [12] GSE33891 [19] 0.6 GSE39621 [51] GSE7424 [8] GSE5861 [6] GSE5497 [6] GSE29262 [12] GSE49283 [12] GSE44261 [12] GSE42565 [6] GSE38831 [7] 0.8 GSE41746 [18] GSE4718 [6] GSE27848 [16] GSE50794 [60] Score 88.89 90.41 96.17 96.24 96.27 98.46 100.86 102.57 102.77 102.87 104.37 105.07 108.26 120.57 121.38 123.40 128.50 132.61 133.57 133.59 138.00 139.57 140.43 141.08 143.52 146.95 153.00 154.46 154.79 155.85 164.30 164.86 170.47 172.28 173.85 176.52 181.10 193.10 197.14 208.76 220.18 230.41 230.43 246.44 247.50 262.54 315.62 1.0 Notes Symbol Num ofCEMGenes:3.Predicted117.SelectedDatasets:293.Strength:0.7 CEM 1,Geneset"[K]Fattyacidelongation",Page2 Hsd17b10 Slc25a20 Bckdhb Cox6b1 Bckdha Acad11 Dhrs7b Ndufb7 Ndufb5 Ndufb6 Hibadh Ndufs8 Acot13 Atp5c1 Mrpl55 Mrpl12 Mrpl42 Mrpl16 Grpel1 Cox5a Mipep Dhrs4 Atp5h Prdx3 Grhpr Acat1 Cisd1 Mrpl2 Idh3g Mdh2 Vwa8 Mpc1 Gcdh Mcee Pdhb Coq3 Pdhx Phb2 Sod2 Tufm Pccb Pcca Txn2 Cbr4 Clpb Clpp Dlat Dlst Dld Cs 0.0 1.0

GSE14004 [9] GSE51080 [18]

GSE13224 [6] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE31004 [8] GSE16110 [16] GSE15729 [15] GSE13432 [12] GSE17266 [59] GSE17794 [44] GSE44663 [6] GSE17709 [18] GSE7141 [6] GSE21156 [6] GSE23833 [12] GSE12730 [24] GSE42858 [12] GSE8044 [6] GSE11484 [6] GSE8966 [12] GSE15069 [15] GSE19286 [6] GSE55855 [6] GSE45028 [22] GSE13044 [59] GSE17796 [39] GSE28559 [30] GSE8949 [20] GSE43145 [12] GSE42473 [15] GSE13302 [30] GSE50865 [12] GSE54581 [21] GSE15914 [9] GSE14753 [6] GSE6623 [12] GSE8199 [9] GSE56162 [18] GSE8679 [12] GSE50813 [24] GSE43825 [31] GSE13693 [9] GSE11291 [60] GSE51432 [15] GSE17297 [32] GSE13707 [20] GSE46646 [12] GSE38574 [32] GSE3837 [12] GSE10589 [6] GSE11684 [16] GSE8295 [16] GSE18907 [12] GSE23408 [39] GSE42299 [8] GSE55525 [71] GSE11496 [16] GSE44091 [32] GSE34773 [26] GSE10273 [9] GSE26671 [12] GSE9441 [36] GSE37316 [31] GSE32966 [24] GSE40795 [50] GSE48884 [12] GSE33931 [42] GSE25825 [8] GSE10246 [182] GSE8683 [11] GSE46496 [9] GSE41910 [12] GSE45968 [6] GSE22086 [6] GSE12337 [16] GSE59437 [30] GSE3313 [24] GSE33199 [64] GSE14929 [38] GSE7487 [24] GSE9247 [15] GSE8863 [18] GSE1806 [22] GSE51804 [10] GSE3296 [16] GSE55756 [47] GSE43419 [20] GSE40087 [15] GSE30688 [9] GSE32706 [33] GSE5657 [20] GSE23006 [48] GSE34064 [6] GSE8488 [15] GSE28237 [6] GSE27195 [6] GSE38138 [20] GSE11343 [19] GSE8684 [10] GSE31646 [11] GSE27429 [8] GSE19793 [32] GSE10634 [16] GSE9297 [27] GSE25295 [25] GSE51365 [28] GSE3067 [28] GSE5313 [6] GSE27309 [10] GSE33726 [48] GSE40156 [42] GSE25645 [17] GSE8681 [25] GSE7475 [16] GSE7605 [18] GSE9338 [42] GSE24920 [19] GSE52550 [12] GSE10627 [51] GSE39562 [26] GSE20696 [8] GSE23101 [20] GSE9533 [35] GSE20371 [12] GSE19675 [22] GSE17513 [12] GSE49689 [23] GSE16707 [6] GSE9400 [8] GSE32937 [8] GSE9044 [6] GSE22871 [30] GSE41558 [8] GSE9892 [12] GSE15433 [9] GSE5334 [19] GSE15330 [27] GSE17925 [12] GSE56755 [13] GSE43713 [16] GSE19204 [6] GSE9012 [10] GSE39233 [40] GSE48004 [6] GSE18033 [56] GSE58915 [21] GSE27563 [93] GSE38754 [40] GSE6383 [6] GSE32199 [6] GSE46209 [21] GSE42047 [24] GSE13873 [27] GSE15872 [18] GSE17096 [20] CEM+ CEM GSE3554 [6] GSE5891 [6] GSE46723 [6] GSE14672 [12] GSE41085 [6] GSE32078 [12] 0.0 GSE10989 [6] GSE53077 [8]

GSE31378 [9] Scale ofaveragePearsoncorrelations GSE22307 [23] GSE1479 [36] GSE44356 [18] GSE3100 [23] GSE4671 [28] GSE41759 [14] 0.2 GSE43042 [6] GSE25088 [24] GSE8039 [32] GSE37546 [20] GSE56135 [8] GSE21299 [12] GSE11443 [6] GSE55733 [24] GSE10182 [7] 0.4 GSE40412 [14] GSE6676 [8] GSE5500 [21] GSE39916 [6] GSE50439 [15] GSE34126 [19] GSE10365 [9] GSE2019 [12] GSE33891 [19] 0.6 GSE39621 [51] GSE7424 [8] GSE5861 [6] GSE5497 [6] GSE29262 [12] GSE49283 [12] GSE44261 [12] GSE42565 [6] GSE38831 [7] 0.8 GSE41746 [18] GSE4718 [6] GSE27848 [16] GSE50794 [60] Score 23.77 24.62 25.73 26.24 26.38 27.80 28.27 28.27 28.46 30.74 30.75 31.16 32.85 34.93 35.82 36.70 40.62 40.78 41.46 42.12 42.20 42.74 44.25 47.37 47.84 47.85 50.34 51.25 51.81 53.45 55.02 55.24 56.75 57.29 60.66 60.95 63.44 66.06 66.34 70.92 72.04 76.09 78.60 79.34 79.50 81.46 83.10 84.78 87.05 88.72 1.0 Notes Symbol Num ofCEMGenes:3.Predicted117.SelectedDatasets:293.Strength:0.7 CEM 1,Geneset"[K]Fattyacidelongation",Page3 Ndufb11 Ndufb10 Ndufaf1 Mrps35 Immp2l Ndufc1 Ndufa4 Cox4i1 Mrpl10 Atpaf2 Atp5j2 Ephx2 Mrps7 Fars2 Flad1 Apoo Coq6 Ecsit Eci2 Mut 0.0 1.0

GSE14004 [9] GSE51080 [18]

GSE13224 [6] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE31004 [8] GSE16110 [16] GSE15729 [15] GSE13432 [12] GSE17266 [59] GSE17794 [44] GSE44663 [6] GSE17709 [18] GSE7141 [6] GSE21156 [6] GSE23833 [12] GSE12730 [24] GSE42858 [12] GSE8044 [6] GSE11484 [6] GSE8966 [12] GSE15069 [15] GSE19286 [6] GSE55855 [6] GSE45028 [22] GSE13044 [59] GSE17796 [39] GSE28559 [30] GSE8949 [20] GSE43145 [12] GSE42473 [15] GSE13302 [30] GSE50865 [12] GSE54581 [21] GSE15914 [9] GSE14753 [6] GSE6623 [12] GSE8199 [9] GSE56162 [18] GSE8679 [12] GSE50813 [24] GSE43825 [31] GSE13693 [9] GSE11291 [60] GSE51432 [15] GSE17297 [32] GSE13707 [20] GSE46646 [12] GSE38574 [32] GSE3837 [12] GSE10589 [6] GSE11684 [16] GSE8295 [16] GSE18907 [12] GSE23408 [39] GSE42299 [8] GSE55525 [71] GSE11496 [16] GSE44091 [32] GSE34773 [26] GSE10273 [9] GSE26671 [12] GSE9441 [36] GSE37316 [31] GSE32966 [24] GSE40795 [50] GSE48884 [12] GSE33931 [42] GSE25825 [8] GSE10246 [182] GSE8683 [11] GSE46496 [9] GSE41910 [12] GSE45968 [6] GSE22086 [6] GSE12337 [16] GSE59437 [30] GSE3313 [24] GSE33199 [64] GSE14929 [38] GSE7487 [24] GSE9247 [15] GSE8863 [18] GSE1806 [22] GSE51804 [10] GSE3296 [16] GSE55756 [47] GSE43419 [20] GSE40087 [15] GSE30688 [9] GSE32706 [33] GSE5657 [20] GSE23006 [48] GSE34064 [6] GSE8488 [15] GSE28237 [6] GSE27195 [6] GSE38138 [20] GSE11343 [19] GSE8684 [10] GSE31646 [11] GSE27429 [8] GSE19793 [32] GSE10634 [16] GSE9297 [27] GSE25295 [25] GSE51365 [28] GSE3067 [28] GSE5313 [6] GSE27309 [10] GSE33726 [48] GSE40156 [42] GSE25645 [17] GSE8681 [25] GSE7475 [16] GSE7605 [18] GSE9338 [42] GSE24920 [19] GSE52550 [12] GSE10627 [51] GSE39562 [26] GSE20696 [8] GSE23101 [20] GSE9533 [35] GSE20371 [12] GSE19675 [22] GSE17513 [12] GSE49689 [23] GSE16707 [6] GSE9400 [8] GSE32937 [8] GSE9044 [6] GSE22871 [30] GSE41558 [8] GSE9892 [12] GSE15433 [9] GSE5334 [19] GSE15330 [27] GSE17925 [12] GSE56755 [13] GSE43713 [16] GSE19204 [6] GSE9012 [10] GSE39233 [40] GSE48004 [6] GSE18033 [56] GSE58915 [21] GSE27563 [93] GSE38754 [40] GSE6383 [6] GSE32199 [6] GSE46209 [21] GSE42047 [24] GSE13873 [27] GSE15872 [18] GSE17096 [20] CEM+ CEM GSE3554 [6] GSE5891 [6] GSE46723 [6] GSE14672 [12] GSE41085 [6] GSE32078 [12] 0.0 GSE10989 [6] GSE53077 [8]

GSE31378 [9] Scale ofaveragePearsoncorrelations GSE22307 [23] GSE1479 [36] GSE44356 [18] GSE3100 [23] GSE4671 [28] GSE41759 [14] 0.2 GSE43042 [6] GSE25088 [24] GSE8039 [32] GSE37546 [20] GSE56135 [8] GSE21299 [12] GSE11443 [6] GSE55733 [24] GSE10182 [7] 0.4 GSE40412 [14] GSE6676 [8] GSE5500 [21] GSE39916 [6] GSE50439 [15] GSE34126 [19] GSE10365 [9] GSE2019 [12] GSE33891 [19] 0.6 GSE39621 [51] GSE7424 [8] GSE5861 [6] GSE5497 [6] GSE29262 [12] GSE49283 [12] GSE44261 [12] GSE42565 [6] GSE38831 [7] 0.8 GSE41746 [18] GSE4718 [6] GSE27848 [16] GSE50794 [60] Score 1.85 4.53 6.65 8.89 10.16 10.19 11.39 11.50 11.60 12.70 12.81 12.98 13.63 15.09 17.40 17.79 20.87 21.37 22.09 23.23 1.0 Notes GEO Series "GSE14004" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

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

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

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

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

0.586 Kernel fit Pairwise Correlations Normal fit

Density 0.293

0.000 CEM 1

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

Pre-normalization Quantiles

preadipocytepreadipocyte rep1preadipocyte (0.0907352) rep2control (0.0745531) rep3 controlsiRNA (0.100295) rep1controlsiRNA (0.175746) rep2PPARsiRNA (0.151655) gamma rep3PPAR (0.201061) gammasiRNAPPAR rep1gammasiRNA (0.0184182) rep2siRNA (0.0808288) rep3 (0.106707)[ min ] [ medium ] [ max ] CEM 1 Acaa2 1541.0 1697.3 7374.4 P ( S | Z, I ) = 1.00 Hadhb 2114.4 4587.5 19640.2 Mean Corr = 0.98217 Mecr 274.0 470.9 1124.0 Acadvl 1951.0 3496.6 15087.8 Etfdh 1618.1 3200.0 11692.4 Etfb 2986.1 3857.9 17602.4 Hadha 2500.9 3812.3 9371.9 Decr1 2345.6 4308.5 16581.2 CEM 1 + Ndufv1 3955.3 6582.8 18777.4 Top 10 Genes Etfa 4351.2 7502.2 17756.2 Hadh 2776.7 5184.0 14990.7 Atp5a1 11345.4 15089.9 31479.7 Suclg1 4485.4 5326.0 16661.3

Null module Ppt2 Ppt1 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 (0.0124006) (0.10001) 28degSubcutaneous(S0510F005) 28deg(0.0617427) (S0510F004) Subcutaneous(S0510F006)white (0.095652) adipose Subcutaneouswhite (0.0350206) (0.064224) adipose 6degBrownwhite (S0510F007) adipose adipose28degMesentericwhite adipose(S0510F008) 28degMesenteric 6deg (0.00391403) white (S0510F011)(S0510F009) 6degBrown adipose white(0.0349858) (S0510F010) adiposeMesenteric adipose 28deg(0.112189)(0.0352214)Mesenteric 6deg (S0510F012) (0.00650609) 28degwhite (S0510F014)Brown adipose(S0510F013) white adiposeMesenteric (0.0901643) adipose 6deg(0.0856651) 28deg(0.0372028) (S0510F015) 6degwhite (S0510F017) (S0510F016) adipose (0.0862252) 6deg (0.0758868) (0.0340068)[ (S0510F018)min ] (0.0289827)[ medium ] [ max ] CEM 1 Acaa2 3215.8 8548.6 14804.4 P ( S | Z, I ) = 1.00 Hadhb 5385.6 9251.6 13374.3 Mean Corr = 0.97877 Mecr 1076.5 3084.5 6192.7 Acadvl 3069.2 8884.5 13753.8 Etfdh 1935.9 5352.3 9737.2 Etfb 7368.1 11666.6 17731.6 Hadha 1453.7 4329.8 8762.1 Decr1 3343.1 7922.8 10766.9 CEM 1 + Ndufv1 4331.6 8052.9 11836.7 Top 10 Genes Etfa 5031.9 8378.9 12457.7 Hadh 5165.2 9186.0 11906.4 Atp5a1 7688.5 10486.4 13804.1 Suclg1 2431.4 5001.3 8698.5

Null module Ppt2 Ppt1 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 (0.0491555) akr2lung (0.193958) akr3lung (0.137351) dba1lung (0.176307) dba2lung (0.427549) dba3 (0.0156795) [ min ] [ medium ] [ max ] CEM 1 Acaa2 1808.5 2741.8 3848.7 P ( S | Z, I ) = 1.00 Hadhb 3803.3 4578.7 9361.5 Mean Corr = 0.96932 Mecr 190.4 216.2 305.6 Acadvl 2396.6 2971.3 5690.9 Etfdh 1216.3 1488.8 2594.5 Etfb 2952.8 3280.3 4444.6 Hadha 2493.0 2733.2 4418.4 Decr1 1495.0 1866.7 3172.1 CEM 1 + Ndufv1 3214.0 3474.3 4342.7 Top 10 Genes Etfa 2370.7 2762.2 4050.6 Hadh 4546.1 5269.5 7530.0 Atp5a1 11942.5 12943.0 14470.0 Suclg1 3313.9 3565.5 5269.6

Null module Ppt2 Ppt1 GEO Series "GSE31004" 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=GSE31004 Status: Public on Dec 15 2011 Title: Effects of Nicotine on the Fetal Mouse Palate Development and Transcriptome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Nonsyndromic cleft palate is a common birth defect (1:700) with a complex etiology involving both genetic and environmental risk factors. Nicotine, a major teratogen present in tobacco products, was shown to cause alterations and delays in the developing fetus. To demonstrate the effect of nicotine on craniofacial development, particularly palatogenesis, we delivered three different doses of nicotine (1.5, 3.0 and 4.5 mg/kg/day) into pregnant BALB/c mice throughout their entire pregnancy using subcutaneous osmotic mini-pump. We assessed the pups for morphological anomalies, as well as genome-wide mRNA (transcriptome) microarray analysis. Consistent administration of nicotine caused developmental retardation, still birth, low birth weight, and significant palatal size and shape abnormality in the pups. However, it did not cause obvious cleft palate. The microarray data analysis using IPA identified differential expression of genes involved in various biological pathways, particularly cancer, genetic diseases, and tissue development in response to consistent nicotine exposure. 6232 up-regulated and 6310 down-regulated genes were detected in nicotine-treated groups compared to the control. Moreover, 45% of the genes associated with cleft palate were found to be affected by nicotine. Alterations of a subset of differentially expressed genes were illustrated with hierarchal clustering and RT-PCR. We concluded that consistent nicotine exposure during pregnancy interferes with normal growth and development of the fetus including palatogenesis; however, this interference does not result in cleft palate, rather smaller palate size with persistent MES. To our knowledge, this is the first experiment revealing the impact of nicotine on the fetal palate transcriptome in mice.

Overall design: Total 8 samples were analyzed. Using an osmotic minipump, duplicate samples from palates of either sterile physiological saline or nicotine (1.5 mg/kg/day, 3.0 mg/kg/day, or 4.5 mg/kg/day)-treated newborn pups.

Background corr dist: KL-Divergence = 0.0673, L1-Distance = 0.0308, L2-Distance = 0.0016, Normal std = 0.5256

0.759 Kernel fit Pairwise Correlations Normal fit

Density 0.379

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

Saline control,Saline control, Nicbiological 1.5mg/kg/day, Nicbiological rep1 1.5mg/kg/day,Nic (0.152393) rep2 biological3.0mg/kg/day,Nic (0.12958) biological3.0mg/kg/day, rep1Nic biological4.5mg/kg/day,(0.146398) rep2Nic biological4.5mg/kg/day,(0.0672781) rep1 biological(0.0915863) rep2 biological(0.131501) rep1 (0.245957) rep2[ min (0.035307) ] [ medium ] [ max ] CEM 1 Acaa2 2396.9 5875.7 13624.4 P ( S | Z, I ) = 1.00 Hadhb 5441.6 9415.0 19099.2 Mean Corr = 0.96888 Mecr 260.6 417.6 1104.9 Acadvl 2617.4 7539.7 15052.9 Etfdh 2665.9 8140.3 12092.1 Etfb 4787.4 9708.4 17736.4 Hadha 2360.2 5770.1 11705.7 Decr1 1134.4 4054.7 8838.9 CEM 1 + Ndufv1 2810.5 6072.8 8464.7 Top 10 Genes Etfa 2895.8 6998.4 14383.0 Hadh 3938.4 8094.3 13773.4 Atp5a1 10674.2 16640.4 22974.5 Suclg1 3847.4 7157.1 17464.4

Null module Ppt2 Ppt1 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 (0.0587933)Mouse_Iso_15w_Rep1 (0.0200045)Mouse_Iso_15w_Rep2 (0.103795)Mouse_Iso_15w_Rep3 (0.0125774)Mouse_Iso_15w_Rep4 (0.0488634)Mouse_Group_20w_Rep1 (0.0921486)Mouse_Group_20w_Rep2 (0.0757725)Mouse_Group_20w_Rep3 (0.0701249)Mouse_Group_20w_Rep4 (0.0725333)Mouse_Iso_20w_Rep1 (0.0356727)Mouse_Iso_20w_Rep2 (0.0145458)Mouse_Iso_20w_Rep3 (0.042514)Mouse_Iso_20w_Rep4 (0.14847) (0.103407) (0.0595779) (0.0411993)[ min ] [ medium ] [ max ] CEM 1 Acaa2 1520.5 4141.7 5203.4 P ( S | Z, I ) = 1.00 Hadhb 2131.0 8935.4 10979.5 Mean Corr = 0.96762 Mecr 300.1 547.0 717.7 Acadvl 2052.1 6436.1 8095.3 Etfdh 1292.4 3934.6 5091.9 Etfb 1430.5 4509.1 5961.4 Hadha 1647.0 4486.5 5813.1 Decr1 1117.8 4162.6 5857.6 CEM 1 + Ndufv1 2980.6 4675.4 5636.7 Top 10 Genes Etfa 3141.2 5962.1 7295.2 Hadh 1888.6 6878.3 8888.7 Atp5a1 6987.2 9608.4 11586.1 Suclg1 1775.7 5260.8 6446.6

Null module Ppt2 Ppt1 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-β pathway (tgf-β) 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-β 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-β2 (tgf-β2) 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-β 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 (0.0934934)APOE_KO_DM_9W_4 (0.0344737)APOE_KO_NODM_9W_5 (0.123397)APOE_KO_NODM_9W_6 (0.131069)APOE_KO_NODM_9W_7APOE_KO_NODM_9W_8 (0.0671243)APOE_KO_RAGE_KO_DM_9W_9 (0.0341452)APOE_KO_RAGE_KO_DM_9W_10 (0.0111219)APOE_KO_RAGE_KO_DM_9W_11 (0.0408199)APOE_KO_RAGE_KO_DM_9W_12APOE_KO_RAGE_KO_NODM_9W_13 (0.0229518)APOE_KO_RAGE_KO_NODM_9W_14 (0.0661938)APOE_KO_RAGE_KO_NODM_9W_15 (0.13356) (0.0709841) (0.0182788) [(0.0250496) min (0.127337) ] [ medium ] [ max ] CEM 1 Acaa2 4239.0 8807.5 13046.1 P ( S | Z, I ) = 1.00 Hadhb 7959.8 17494.9 25298.7 Mean Corr = 0.96652 Mecr 462.7 852.9 1420.7 Acadvl 6041.4 12304.0 17421.9 Etfdh 3262.3 7210.8 10709.9 Etfb 6784.9 10411.8 15141.0 Hadha 3115.7 6526.3 10302.3 Decr1 4970.4 9610.9 14866.2 CEM 1 + Ndufv1 3834.4 6682.8 9319.4 Top 10 Genes Etfa 8289.3 12484.8 19014.6 Hadh 6042.8 10911.9 15134.0 Atp5a1 9062.2 14023.1 20089.0 Suclg1 4867.3 9857.4 14379.3

Null module Ppt2 Ppt1 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 (0.0461003) degrees rep 1 42 week degrees(0.0792906) repl 14 3weekdegrees (0.141014)rep 1 54 (0.116817)weeksdegrees rep 25 (0.0938673)30weeks rep degrees 35 (0.257429)30weeks degrees rep5 30weeks1 (0.0848309) degrees rep5 4weeks2 degrees(0.0479803) rep5 4weeks3 degrees(0.0528326) rep 1 4 (0.02689) degrees rep 2 (0.0285099) rep 3 (0.0244378)[ min ] [ medium ] [ max ] CEM 1 Acaa2 3299.3 13288.4 25035.1 P ( S | Z, I ) = 1.00 Hadhb 7022.6 33758.0 42506.7 Mean Corr = 0.96207 Mecr 566.3 1444.1 3058.2 Acadvl 3780.7 15878.9 30125.5 Etfdh 2742.0 13239.6 17044.0 Etfb 4440.2 7415.1 12737.8 Hadha 3700.8 13253.1 26339.2 Decr1 5597.0 12327.6 22029.4 CEM 1 + Ndufv1 2717.5 6012.8 9050.8 Top 10 Genes Etfa 13007.3 25622.6 34130.7 Hadh 12425.4 28429.1 33770.5 Atp5a1 15582.6 25177.6 39715.5 Suclg1 5382.0 16730.6 25411.9

Null module Ppt2 Ppt1 GEO Series "GSE17266" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 59 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17266 Status: Public on Jan 12 2010 Title: Expression data from B6C3F1 mice treated with baclofen Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice were treated with either 100mg/kg baclofen or 0.5% methylcellulose alone by oral gavage for 1 or 5 days.

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

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

0.507 Kernel fit Pairwise Correlations Normal fit

Density 0.254

0.000 CEM 1

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

Pre-normalization Quantiles

liver-vehicle-1day-repliver-baclofen-1day-repliver-baclofen-1day-rep 1liver-vehicle-1day-rep (0.0332761)liver-baclofen-1day-rep 1 (0.0350444)liver-vehicle-1day-rep 2 (0.0354645) 2liver-baclofen-1day-rep (0.0367358)liver-vehicle-5day-rep 3 (0.036453) 3liver-baclofen-5day-rep (0.0256455)liver-vehicle-5day-rep 4 (0.0371995) 1liver-baclofen-5day-rep (0.0214574)liver-vehicle-5day-rep 1 (0.0306952) 2liver-baclofen-5day-rep (0.0278436)liver-vehicle-5day-rep 2 (0.0352809) 3liver-baclofen-5day-rep (0.0378884)liver-baclofen-5day-rep 3 (0.0314304) 4liver-baclofen-5day-rep (0.0359931)liver-baclofen-5day-rep 4 (0.0386758)liver-baclofen-5day-rep 5 (0.0354204)bone 6 (0.0296593) marrow-vehicle-1day-repbone 7 (0.0357562) marrow-baclofen-1day-repbone 8 (0.022848) marrow-vehicle-1day-repbone marrow-baclofen-1day-repbone 1 (0.0125245) marrow-vehicle-1day-repbone 1 (0.00709969) marrow-baclofen-1day-repbone 2 (0.00855796) marrow-vehicle-1day-repbone 2 (0.00880905) marrow-baclofen-1day-repbone 3 (0.00955263) marrow-vehicle-5day-repbone 3 (0.007791) marrow-baclofen-5day-repbone 4 (0.00873962) marrow-vehicle-5day-repbone 4 (0.00796711) marrow-baclofen-5day-repbone 1 (0.008617) marrow-vehicle-5day-repbone 1 (0.0107512) marrow-baclofen-5day-repbone 2 (0.00841457) marrow-vehicle-5day-repbone 2 (0.00828385) marrow-baclofen-5day-repbone 3 (0.00848306) marrow-baclofen-5day-repbone 3 (0.00868696) marrow-baclofen-5day-repbone 4 (0.00848775) marrow-baclofen-5day-repbone 4 (0.00938039) marrow-baclofen-5day-repspleen-vehicle-1day-rep 5 (0.00662389)spleen-baclofen-1day-rep 6 (0.00549473)spleen-vehicle-1day-rep 7 (0.00693153)spleen-baclofen-1day-rep 1 8 (0.00350007) (0.00537441)spleen-vehicle-1day-rep 1 (0.00895946)spleen-baclofen-1day-rep 2 (0.00919423)spleen-vehicle-1day-rep 2 (0.0102739)spleen-baclofen-1day-rep 3 (0.00608755)spleen-vehicle-5day-rep 3 (0.023195)spleen-baclofen-5day-rep 4 (0.00669942)spleen-vehicle-5day-rep 4 (0.0186651)spleen-baclofen-5day-rep 1 (0.00835191)spleen-vehicle-5day-rep 1 (0.00888634)spleen-baclofen-5day-rep 2 (0.0111121)spleen-vehicle-5day-rep 2 (0.0104092)spleen-baclofen-5day-rep 3 (0.0122647)spleen-baclofen-5day-rep 3 (0.00826653)spleen-baclofen-5day-rep 4 (0.01439)spleen-baclofen-5day-rep 4 (0.0099)spleen-baclofen-5day-rep 5 (0.00890047) 6 (0.00909102) 7 (0.0115639) 8 (0.0109506)[ min ] [ medium ] [ max ] CEM 1 Acaa2 964.8 1724.0 18251.5 P ( S | Z, I ) = 1.00 Hadhb 1883.1 2210.5 8925.4 Mean Corr = 0.97229 Mecr 195.7 302.9 784.4 Acadvl 1147.3 1402.5 13678.0 Etfdh 720.5 1233.7 11500.3 Etfb 1996.5 4060.7 16708.7 Hadha 1796.1 2774.8 6744.9 Decr1 697.0 997.6 9814.5 CEM 1 + Ndufv1 1806.5 3084.2 6801.1 Top 10 Genes Etfa 1707.8 2956.0 16413.6 Hadh 1244.0 1634.3 13738.3 Atp5a1 7791.8 12785.5 24627.0 Suclg1 1688.9 2136.8 10506.1

Null module Ppt2 Ppt1 GEO Series "GSE17794" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 44 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17794 Status: Public on Jan 11 2010 Title: Expression data from B6C3F1 mice treated with 2-butoxyethanol Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice were dosed with 2-BE (900mg/kg) or vehicle by oral gavage and sacrificied either after 4 hours of a single dose or after 7 days of daily dosing.

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. 44 arrays.

Background corr dist: KL-Divergence = 0.0249, L1-Distance = 0.0283, L2-Distance = 0.0013, Normal std = 0.6953

0.574 Kernel fit Pairwise Correlations Normal fit

Density 0.287

0.000 CEM 1

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

Pre-normalization Quantiles

liver-vehicle-4hours-repliver-vehicle-4hours-repliver-vehicle-4hours-repliver-2BE-4hours-rep 1 (0.0632087)liver-2BE-4hours-rep 2 (0.046176)liver-2BE-4hours-rep 3 (0.0475717) 1liver-2BE-4hours-rep (0.0571443) 2spleen-vehicle-4hours-rep (0.0507761) 3spleen-vehicle-4hours-rep (0.0486436) 4spleen-vehicle-4hours-rep (0.0343395)spleen-vehicle-4hours-rep 1 (0.00933341)spleen-2BE-4hours-rep 2 (0.0115191)spleen-2BE-4hours-rep 3 (0.0110352)spleen-2BE-4hours-rep 4 (0.0125512)spleen-2BE-4hours-rep 1 (0.0187745)liver-vehicle-7days-rep 2 (0.0208276)liver-vehicle-7days-rep 3 (0.0123315)liver-vehicle-7days-rep 4 (0.014834)liver-vehicle-7days-rep 1 (0.0209088)liver-2BE-7days-rep 2 (0.0257706)liver-2BE-7days-rep 3 (0.02295)liver-2BE-7days-rep 4 (0.0166857) 1 (0.0271951)liver-2BE-7days-rep 2 (0.0214183)liver-2BE-7days-rep 3 (0.0253151)bone 4marrow-vehicle-7days-rep (0.0309407)bone 5marrow-vehicle-7days-rep (0.0239544)bone marrow-vehicle-7days-repbone marrow-vehicle-7days-repbone 1 (0.0115051) marrow-vehicle-7days-repbone 2 (0.0115868) marrow-2BE-7days-repbone 3 (0.0129983) marrow-2BE-7days-repbone 4 (0.0121345) marrow-2BE-7days-repbone 5 (0.0100512) marrow-2BE-7days-rep 1bone (0.0129795) marrow-2BE-7days-rep 2spleen-vehicle-7days-rep (0.01622) 3spleen-vehicle-7days-rep (0.0124009) 4spleen-vehicle-7days-rep (0.0122007) 5spleen-vehicle-7days-rep (0.0128849) 1 (0.012177)spleen-vehicle-7days-rep 2 (0.012285)spleen-2BE-7days-rep 3 (0.0186131)spleen-2BE-7days-rep 4 (0.0253377)spleen-2BE-7days-rep 5 (0.0155885) spleen-2BE-7days-rep1 (0.0185229) spleen-2BE-7days-rep2 (0.0309521) 3 (0.0281617) 4 (0.0258211) 5 (0.013374)[ min ] [ medium ] [ max ] CEM 1 Acaa2 1205.5 1919.9 18873.1 P ( S | Z, I ) = 1.00 Hadhb 2038.2 2489.1 13187.1 Mean Corr = 0.96485 Mecr 233.4 313.5 819.3 Acadvl 1173.8 1481.2 15643.0 Etfdh 800.4 1326.7 14455.5 Etfb 1966.0 3920.6 19379.5 Hadha 1590.3 2698.9 9018.0 Decr1 782.4 1071.3 15567.7 CEM 1 + Ndufv1 1797.9 3044.7 6653.0 Top 10 Genes Etfa 2027.1 3083.2 19094.9 Hadh 1007.9 1619.1 14691.8 Atp5a1 8594.2 12735.0 26075.3 Suclg1 1338.4 2077.7 11958.6

Null module Ppt2 Ppt1 GEO Series "GSE44663" 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=GSE44663 Status: Public on Feb 26 2013 Title: Expression data from adult mouse mesenteric arteries Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Vascular smooth muscle cells require beta1 integrin for survival. Following the induced deletion of smooth muscle beta1 integrin, smooth muscle cells undergo apoptosis and arteries become fibrotic. This microarray study on mesenteric arteries 2 weeks after the initiation of beta1 integrin deletion specifically in smooth muscle cells of the adult mouse aimed to examine early changes in expression following deletion.

Overall design: Mesenteric arteries from three wild type mixed background and three beta1 integrin smooth muscle knockout mixed background mice are examined.

Background corr dist: KL-Divergence = 0.0392, L1-Distance = 0.0238, L2-Distance = 0.0007, Normal std = 0.6246

0.649 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

Adult mouseAdult controlmouseAdult controlmousesmoothAdult controlmousesmooth muscleAdult smoothmouse musclebeta1Adult smoothintegrinmouse muscle beta1 smoothintegrin musclewildbeta1 type integrin musclewildbeta1 mesenteric type integrin nullwildbeta1[ mesenteric minmesenteric type integrinarteries, null mesenteric mesenteric] arteries, null 30M_ctrlarteries, mesenteric arteries, 74M_ctrlarteries, (0.0789387)72M_exp[ medium 75M_ctrlarteries, (0.494686)73M_exp (0.068496) (0.137254)86F_exp (0.0972685) ] (0.123357) [ max ] CEM 1 Acaa2 905.3 1091.9 2236.9 P ( S | Z, I ) = 1.00 Hadhb 4140.9 5167.0 10616.7 Mean Corr = 0.95300 Mecr 212.9 328.4 638.1 Acadvl 1997.0 2248.3 4409.7 Etfdh 1446.4 1539.3 3128.1 Etfb 1834.9 2326.9 4422.5 Hadha 1296.5 1680.5 3986.9 Decr1 832.8 1334.3 2931.2 CEM 1 + Ndufv1 1731.2 2074.4 3536.2 Top 10 Genes Etfa 2161.7 2269.2 4282.3 Hadh 1773.7 2863.7 6580.2 Atp5a1 5426.2 6121.7 9707.5 Suclg1 1155.5 1473.0 2966.9

Null module Ppt2 Ppt1 GEO Series "GSE17709" 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=GSE17709 Status: Public on Aug 19 2009 Title: Gene expression analysis of a podocyte specific PTIP deletion in mouse glomerular preparations at 1 month of age Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21060806 Summary & Design: Summary: Glomerular RNA comparison between wild-type and podocyte specific deletion of the PTIP gene in 1 month old kidneys. The PTIP gene was deleted using a floxed allele and a Podocin-Cre driver strain.

These mice develop protein urea by 3 months of age. This study was designed to find gene expression differences prior to the onset of the phenotype.

Overall design: Kidneys were excised at 1 month of age. Glomeruli enriched fractions were generated by sieving of the tissue homogenates. RNA was prepared from glomerular enriched fractions.

Background corr dist: KL-Divergence = 0.0391, L1-Distance = 0.0385, L2-Distance = 0.0021, Normal std = 0.6195

0.644 Kernel fit Pairwise Correlations Normal fit

Density 0.322

0.000 CEM 1

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

Pre-normalization Quantiles

wild-type,wild-type, PTIP+,wild-type, rep1PTIP+, wild-type,(0.0264112) rep2PTIP+, wild-type,(0.0334927) rep3PTIP+, wild-type,(0.0219603) rep4PTIP+, wild-type,(0.0426214) rep5PTIP+, wild-type,(0.0672975) rep6PTIP+, Pod-Cre,(0.0398647) rep7PTIP+, Pod-Cre,(0.0577453) PTIP-,rep8 Pod-Cre,(0.0845714) rep1 PTIP-, (0.0200079)Pod-Cre, rep2 PTIP-, (0.0274321)Pod-Cre, rep3 PTIP-, (0.0174565)Pod-Cre, rep4 PTIP-, (0.0239842)Pod-Cre, rep5 PTIP-, (0.0849958)Pod-Cre, rep6 PTIP-, (0.204605)Pod-Cre, rep7 PTIP-, (0.0446014)Pod-Cre, rep8 PTIP-, (0.0754852) rep9 PTIP-, (0.0781282) rep10 (0.0493392)[ min ] [ medium ] [ max ] CEM 1 Acaa2 3700.0 5576.8 8406.2 P ( S | Z, I ) = 1.00 Hadhb 2691.8 3189.5 5879.9 Mean Corr = 0.95076 Mecr 152.0 502.3 1230.6 Acadvl 2327.5 3400.1 5566.6 Etfdh 1208.0 2907.3 5420.1 Etfb 2794.7 5722.1 9828.8 Hadha 763.1 1481.7 1919.4 Decr1 3092.2 4597.6 7004.2 CEM 1 + Ndufv1 3445.9 4925.5 6440.6 Top 10 Genes Etfa 4721.6 6119.5 8331.5 Hadh 6048.5 6677.5 7394.5 Atp5a1 7548.8 8903.3 9911.8 Suclg1 3018.2 4747.6 5840.9

Null module Ppt2 Ppt1 GEO Series "GSE7141" 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=GSE7141 Status: Public on Jan 01 2008 Title: mRNA expression analysis of undifferentiated Dicer +/- (D4) and Dicer -/- (27H10) embryonic cell lines Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18311153 Summary & Design: Summary: We have analyzed the transcript expression levels in Dicer heterozygous and Dicer knock-out embryonic stem (ES) cells in order to identify which transcripts are regulated by RNAi pathway in mouse ES cells.

Keywords: Cell type comparison of cell line with or without knock-out

Overall design: Two cell lines were analysed in an undifferentiated state. Triplicates of both cell lines were analyzed.

Background corr dist: KL-Divergence = 0.0260, L1-Distance = 0.0446, L2-Distance = 0.0022, Normal std = 0.7653

0.564 Kernel fit Pairwise Correlations Normal fit

Density 0.282

0.000 CEM 1

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

Pre-normalization Quantiles

UndifferentiatedUndifferentiatedUndifferentiated Dicer Undifferentiated+/- Dicer (D4) Undifferentiated+/-ES Dicer (D4) cell Undifferentiated+/-ESline Dicer (D4) cell replicate_1 -/-ESline Dicer (27H) cell replicate_2 -/-line ES (0.215373)Dicer (27H) cellreplicate_3 -/- ESline(0.248009) (27H) cell replicate_1[ ESline(0.127281) min cell replicate_2 line (0.137782) ] replicate_3 (0.153957) (0.117599)[ medium ] [ max ] CEM 1 Acaa2 920.3 1787.5 1982.8 P ( S | Z, I ) = 1.00 Hadhb 3238.8 5056.0 6122.8 Mean Corr = 0.95784 Mecr 552.7 865.1 1059.3 Acadvl 661.3 1314.4 1456.8 Etfdh 929.5 1232.5 1343.1 Etfb 3337.6 6379.2 7303.2 Hadha 1500.2 1763.2 2124.7 Decr1 503.5 774.9 867.7 CEM 1 + Ndufv1 6418.9 8478.9 10042.5 Top 10 Genes Etfa 3412.7 5090.7 5626.2 Hadh 3321.0 5470.4 5606.4 Atp5a1 17185.8 19465.7 20442.1 Suclg1 4409.6 4622.8 4669.9

Null module Ppt2 Ppt1 GEO Series "GSE21156" 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=GSE21156 Status: Public on Apr 02 2010 Title: Expression data from rostral forebrains of wild-type and Fezf1-/- Fezf2-/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20431123 Summary & Design: Summary: Zinc-finger genes Fezf1 and Fezf2 encode transcriptional repressors. Fezf1 and Fezf2 are expressed in the early neural stem/progenitor cells and control neuronal differentiation in mouse dorsal telencephalon.

We compared gene expression profiles of rostral forebrains, which contain the telencephalon and the rostral part of the diencephalon, from embryonic day (E) 9.5, E10.5, and E12.5 wild-type control and Fezf1-/- Fezf2 -/- mouse embryos.

Overall design: The forebrain rostral to the caudal limit of the lateral ventricles was isolated manually from E9.5, E10.5, and E12.5 wild-type and Fezf1-/- Fezf2-/- mice. Total RNAs were isolated by Separsol-RNA I and were used for microarray analyses.

Background corr dist: KL-Divergence = 0.0250, L1-Distance = 0.0333, L2-Distance = 0.0012, Normal std = 0.7381

0.570 Kernel fit Pairwise Correlations Normal fit

Density 0.285

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-typeFezf1Fezf2KO rostralwild-type forebrain rostralFezf1Fezf2KO rostral at E9.5forebrainwild-type forebrain (0.160089) rostralFezf1Fezf2KO at rostral E9.5at E10.5forebrain (0.135513)forebrain (0.216332) rostral at E10.5at E12.5forebrain (0.294807) (0.0822194)[ at min E12.5 (0.111039) ] [ medium ] [ max ] CEM 1 Acaa2 436.8 494.9 866.3 P ( S | Z, I ) = 1.00 Hadhb 1560.9 1813.1 2468.5 Mean Corr = 0.96362 Mecr 233.6 356.2 527.7 Acadvl 435.6 614.6 703.9 Etfdh 808.9 942.9 1155.0 Etfb 1995.0 2170.4 2845.0 Hadha 1043.2 1359.7 1533.7 Decr1 816.1 1096.8 1281.6 CEM 1 + Ndufv1 2565.2 3587.1 4101.9 Top 10 Genes Etfa 1480.7 2589.3 3327.5 Hadh 2147.4 4056.4 5940.2 Atp5a1 10851.1 13247.6 16782.4 Suclg1 2755.6 3343.8 3703.1

Null module Ppt2 Ppt1 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 (0.0540771)2h_co._total1 (0.101878)2h_co._total2 (0.0442544) (0.0600257)2h_co._total3 (0.0739792)2h_TGFbeta_enriched1 (0.0895679)2h_TGFbeta_enriched22h_TGFbeta_enriched32h_TGFbeta_total1 (0.0691689)2h_TGFbeta_total2 (0.0937375)2h_TGFbeta_total3 (0.114288) (0.0350983) (0.0720246) (0.1919) [ min ] [ medium ] [ max ] CEM 1 Acaa2 193.4 843.9 1098.4 P ( S | Z, I ) = 1.00 Hadhb 1103.0 2293.9 2677.5 Mean Corr = 0.96084 Mecr 111.2 212.7 277.0 Acadvl 593.9 2523.8 3329.5 Etfdh 395.0 1057.4 1329.1 Etfb 333.4 1178.1 2039.5 Hadha 92.5 233.4 410.3 Decr1 432.1 1395.6 1776.3 CEM 1 + Ndufv1 1072.8 5716.2 7889.5 Top 10 Genes Etfa 1494.2 5568.3 6242.0 Hadh 606.4 2432.0 2703.4 Atp5a1 4199.1 12114.9 14889.0 Suclg1 1597.6 5466.5 6032.9

Null module Ppt2 Ppt1 GEO Series "GSE12730" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12730 Status: Public on Nov 07 2009 Title: Mouse gestational protein restriction: Newborn offspring liver and hindleg muscle Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19823102 Summary & Design: Summary: Gestational protein restriction is a model for low birth size. We hypothesized that taurine supplementation would protect against changes in newborn liver and muscle caused by a maternal low protein diet.

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

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

0.615 Kernel fit Pairwise Correlations Normal fit

Density 0.307

0.000 CEM 1

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

Pre-normalization Quantiles

MaternalMaternal normalMaternal normalproteinMaternal normalproteinoffspringMaternal normalproteinoffspring liver,Maternal normalprotein offspringbiological liver,Maternal normalprotein +biological 1%liver, replicate Maternaltaurine lowprotein +biological 1% replicateprotein 1Maternaltaurineoffspring (0.00500096) low+ 1% replicateproteinoffspring 2Maternaltaurineoffspring (0.0200927)low liver, proteinoffspring 3Maternal offspringbiologicalliver, (0.0251638)low liver, protein offspringbiologicalMaternal biologicalliver, low liver, replicate protein +biological Maternal 1%biologicalliver, lowreplicate replicatetaurine 1protein +biological (0.00930092) Maternal1% normalreplicate replicate1taurineoffspring 2(0.0166858) + (0.127058) Maternal1% normalproteinreplicate 2taurineoffspring 3(0.0422158) liver, (0.0103431)Maternal normalproteinoffspring 3 offspringbiological (0.0689194) liver,Maternal normalproteinoffspring muscle,biological liver, Maternalreplicate normalproteinoffspring muscle,biological biological Maternalreplicate normalprotein1+ (0.0695363) 1%muscle, biological Maternalreplicatetaurine replicate lowprotein2+ (0.0440649)1% biologicalprotein Maternaltaurineoffspring replicate low3 +1 (0.0110185) 1%(0.0255778) proteinoffspring Maternaltaurineoffspring replicate low muscle,2 (0.0222875) proteinoffspring Maternaloffspring muscle, low muscle,3 biological (0.0291418) proteinoffspringMaternal muscle, lowbiological muscle, biological protein +replicate 1%muscle, lowbiological biologicaltaurine replicate protein +replicate 1%1 biological (0.0342965) taurineoffspring replicate +replicate1 1%2(0.0459154) (0.0370301) taurineoffspring replicate muscle,2[ 3(0.0464134) (0.0210004)min offspring muscle,3 biological (0.0424989) ] muscle, biological replicate biological [replicate 1medium (0.196712) replicate 2 (0.0279547) 3 (0.0217713) ] [ max ] CEM 1 Acaa2 2257.6 10299.6 15288.2 P ( S | Z, I ) = 1.00 Hadhb 3407.5 8169.2 13054.8 Mean Corr = 0.94785 Mecr 235.7 541.5 1002.7 Acadvl 2758.1 8105.6 12118.1 Etfdh 1832.2 5130.4 8136.3 Etfb 3070.9 7178.2 11694.9 Hadha 2485.1 4941.5 8751.2 Decr1 1086.9 5522.4 8190.0 CEM 1 + Ndufv1 3776.5 5270.7 6407.4 Top 10 Genes Etfa 2929.0 8289.6 12947.7 Hadh 3960.9 7822.2 12088.5 Atp5a1 15112.7 24076.6 30787.8 Suclg1 2932.6 6326.7 7044.3

Null module Ppt2 Ppt1 GEO Series "GSE42858" 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=GSE42858 Status: Public on Aug 27 2013 Title: Progesterone receptor-dependent gene signatures in the mouse mammary gland after acute progesterone treatment Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23979845 Summary & Design: Summary: Progesterone (P) acting through its cognate nuclear receptors (PRs) plays an essential role in driving pregnancy-associated branching morphogenesis of the mammary gland. However, the fundamental mechanisms, including global cistromic and acute genomic transcriptional responses that are required to elicit active branching morphogenesis in response to P, have not been elucidated. We used microarray analysis to identify global gene expression signatures that are acutely regulated by PRs in the mouse mammary gland after acute P treatment.

Overall design: Mammary gland gene expression data from 10-week-old ovariectomized wildtype and progesterone receptor null mice treated subcutaneously with 17β-Estradiol for 24 hours and then 17β-Estradiol plus Progesterone for 8 or 24 hours. Three replicate pools were tested with three mice per pool.

Background corr dist: KL-Divergence = 0.1073, L1-Distance = 0.0330, L2-Distance = 0.0020, Normal std = 0.4239

0.941 Kernel fit Pairwise Correlations Normal fit

Density 0.471

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 mice treatedWildtype mice treatedProgesteronewith mice E+EP8h, treatedProgesteronewith E+EP8h, biologicalreceptor Progesteronewith E+EP8h, biologicalreceptorWildtype null rep mice 1 biologicalreceptor Wildtype(0.111938) null micerep treated mice 2 treatedWildtype(0.0809866) null micerep treatedwith mice 3 treatedProgesteronewith (0.143622)E+EP8h, mice treatedwith E+EP24h, treatedProgesteronewith E+EP8h, biological with E+EP24h, receptor Progesteronewith biologicalE+EP8h, biological E+EP24h,rep receptor biological null 1 biological rep(0.0748589) micerep receptor1 biological null (0.0335015)2 treatedrep(0.0172753) micerep 2 null (0.0916122)3 treatedrepwith(0.0216191) mice 3 [E+EP24h, (0.0755295) mintreatedwith E+EP24h, with biological] E+EP24h, biological rep 1 [biological (0.245054)medium rep 2 (0.0469262) rep 3 (0.0570767) ] [ max ] CEM 1 Acaa2 3565.8 5396.3 8907.9 P ( S | Z, I ) = 1.00 Hadhb 13798.6 20187.1 27051.3 Mean Corr = 0.92076 Mecr 1017.0 1410.5 1752.4 Acadvl 6714.3 10310.5 14927.8 Etfdh 4808.5 7043.7 10289.2 Etfb 8705.5 9707.0 12254.3 Hadha 4550.0 6627.9 9312.6 Decr1 7283.9 8772.2 12067.2 CEM 1 + Ndufv1 5725.8 7331.1 9928.8 Top 10 Genes Etfa 11212.8 13519.4 17524.7 Hadh 12282.8 15704.5 19718.0 Atp5a1 16908.6 18822.5 23214.3 Suclg1 6114.4 9205.1 12793.8

Null module Ppt2 Ppt1 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 (0.128964) rep2 adiposeadultBrown (0.183287) rep3 adiposeBrown adult (0.172902) rep1 adipose adult (0.157846) rep2 adult (0.0909423) rep3 (0.266058)[ min ] [ medium ] [ max ] CEM 1 Acaa2 2315.4 19421.6 21085.7 P ( S | Z, I ) = 1.00 Hadhb 5503.2 27832.2 29252.1 Mean Corr = 0.97785 Mecr 3235.1 5405.2 5913.5 Acadvl 1900.9 20457.6 22037.0 Etfdh 2076.3 12206.8 13651.6 Etfb 9067.5 24689.3 25191.6 Hadha 3175.7 19064.2 19868.6 Decr1 4836.4 18098.1 18964.5 CEM 1 + Ndufv1 3575.5 15970.1 17146.6 Top 10 Genes Etfa 7388.7 20169.4 20504.5 Hadh 7604.7 16825.5 18878.0 Atp5a1 13237.5 29603.6 30983.5 Suclg1 3866.8 20595.2 22160.4

Null module Ppt2 Ppt1 GEO Series "GSE11484" 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=GSE11484 Status: Public on Nov 15 2008 Title: Gene expression analysis of ctrl_islets versus VhlhKO_islets Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19056893 Summary & Design: Summary: Understanding the nature of the various glucose-derived signals for insulin secretion (both triggering and amplifying) is essential for gaining insight into the functional failure of the beta-cells in diabetes and the development of drugs for correcting this problem. The beta-cells uniquely couple changes in cellular metabolism to electrical activity and thus insulin release. In mice, beta-cell specific deletion of the von Hippel-Lindau (VHL) tumor suppressor protein leads to the activation of a HIF transcription program that includes genes involved in glycolysis, suppression of mitochondrial activity and lactate production. This reprogramming of cellular metabolism results in abnormal insulin secretion properties.

Overall design: Three batches of isolated islets from each genotype where used for RNA isolation and Affymetrix measurements.

Background corr dist: KL-Divergence = 0.0441, L1-Distance = 0.0255, L2-Distance = 0.0008, Normal std = 0.6009

0.671 Kernel fit Pairwise Correlations Normal fit

Density 0.336

0.000 CEM 1

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

Pre-normalization Quantiles

mouse_islets_ctrl_01mouse_islets_ctrl_02mouse_islets_ctrl_03 (0.0263084)mouse_islets_VhlhKO_01 (0.104596)mouse_islets_VhlhKO_02 (0.106676)mouse_islets_VhlhKO_03 (0.187757) (0.298292) (0.276371)[ min ] [ medium ] [ max ] CEM 1 Acaa2 195.8 673.4 1656.6 P ( S | Z, I ) = 1.00 Hadhb 3028.0 7731.2 10219.6 Mean Corr = 0.93290 Mecr 99.7 220.8 397.6 Acadvl 2263.8 4850.2 7298.6 Etfdh 1256.6 2319.8 2774.7 Etfb 1716.1 2553.7 2827.6 Hadha 623.6 801.2 1151.1 Decr1 826.5 932.0 1158.9 CEM 1 + Ndufv1 4101.0 6731.4 8845.6 Top 10 Genes Etfa 1701.5 3537.0 3998.3 Hadh 9581.3 13605.0 18304.0 Atp5a1 5784.9 13074.6 14649.8 Suclg1 4146.2 5033.1 6533.9

Null module Ppt2 Ppt1 GEO Series "GSE8966" 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=GSE8966 Status: Public on Aug 17 2009 Title: Liver Transcriptome Profiles Associated with Strain-Specific Ehrlichia chaffeensisinduced Hepatitis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19001077 Summary & Design: Summary: Infection of humans with Ehrlichia chaffeensis, the etiologic agent of human monocytic ehrlichiosis, can cause hepatitis of varying severity. When the three human isolates of E. chaffeensis, each belongs to different geno-groups, are inoculated into severe combined immunodeficiency mice, the severity of clinical signs and bacterial burden detected in the liver are strain Wakulla>Liberty>Arkansas. Disseminated and granulomatous inflammation is evident in the liver of mice infected with strains Wakulla and Arkansas, respectively, but not in mice infected with strain Liberty. In this paper, we used microarray analysis to define transcriptional profiles characteristic to the histopathological features in the mouse liver. Cytokine and chemokine profiles were strikingly different among three strains of E. chaffeensis: IFN-γ, CCL5, CXCL1, CXCL2, CXCL7 and CXCL9 were highly up-regulated with strain Arkansas, TNF-α, CCL2, CCL3, CCL5, CCL6, CCL12, CCL20, CXCL2, CXCL7, CXCL9 and CXCL13 were highly up-regulated with strain Wakulla. With strain Liberty, only CXCL13 was highly up-regulated. In the livers infected with the Arkansas strain, monocytes/macrophages and NK cells were enriched in the granulomas and increase of NK cell-marker mRNAs was detected. Livers infected with the Wakulla strain displayed infiltration of significantly more neutrophils and increase of neutrophil-marker mRNAs. Genes up-regulated commonly in the liver infected with the three stains are other host innate immune and inflammatory response genes including several acute phase proteins. Genes down-regulated commonly are related to host physiologic functions. The results suggest that marked modulation of host cytokine and chemokine profiles by E. chaffeensis strains underlie the distinct host liver disease.

Overall design: Three mice were examined for each of the 4 groups.

Background corr dist: KL-Divergence = 0.1002, L1-Distance = 0.0277, L2-Distance = 0.0013, Normal std = 0.4441

0.898 Kernel fit Pairwise Correlations Normal fit

Density 0.449

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

Arkansas-infectedArkansas-infectedArkansas-infected SCIDLiberty-infected mouse SCIDLiberty-infected liver_Sample113mouse SCIDLiberty-infected SCIDliver_Sample114mouse mouseWakulla-infected SCIDliver_Sample115 (0.015962) liver_Sample118mouseWakulla-infected SCID (0.0487845) liver_Sample119mouseWakulla-infected SCID (0.135481) liver_Sample121Mock-infected mouse (0.0947458) SCID Mock-infectedliver_Sample151mouse (0.0563767) SCID SCID Mock-infectedliver_Sample152mouse (0.0236399) mouse SCID liver_Sample153 (0.0937621) liver_Sample141mouse SCID (0.0730152) liver_Sample142mouse (0.069779) liver_Sample143 (0.191169)[ min (0.100182) ] (0.0971026)[ medium ] [ max ] CEM 1 Acaa2 4632.4 9200.6 14866.3 P ( S | Z, I ) = 1.00 Hadhb 5962.2 8008.1 12192.1 Mean Corr = 0.91157 Mecr 430.5 626.2 1050.9 Acadvl 6649.2 11367.8 18605.6 Etfdh 3517.3 5191.3 8404.7 Etfb 10795.7 15986.8 23224.1 Hadha 3259.8 4354.7 7466.5 Decr1 4711.8 6862.8 12895.1 CEM 1 + Ndufv1 4665.8 6527.0 8833.3 Top 10 Genes Etfa 8338.0 12602.9 18610.6 Hadh 5790.6 11717.8 16013.1 Atp5a1 17009.2 22723.4 33588.1 Suclg1 4871.7 8014.1 9941.9

Null module Ppt2 Ppt1 GEO Series "GSE15069" 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=GSE15069 Status: Public on Apr 30 2009 Title: Inhibitor trials in chondrocytes - MAS 5.0 normalization Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20111593 Summary & Design: Summary: Objectives: To identify similarities and differences in gene expression data in the MEK/ERK and PI3K pathways and to determine how histone modification affects these same pathways. Goal: To identify and functionally characterize novel targets of these signaling pathways in the context of chondrocyte differentiation.

Keywords: Treatment, signaling, one-colour array, signaling pathway comparison

Overall design:

Background corr dist: KL-Divergence = 0.0933, L1-Distance = 0.0484, L2-Distance = 0.0037, Normal std = 0.4765

0.897 Kernel fit Pairwise Correlations Normal fit

Density 0.448

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

DMSO1_24HRDMSO2_24HR (0.0549342)DMSO3_24HR (0.0467584)LY1_24HR (0.0226579)LY2_24HR (0.0497719)LY3_24HR (0.0362841)UO126_1_24HR (0.0421673)UO126_2_24HRUO126_3_24HR (0.0188672)SB202190_1_24HR (0.156017)SB202190_2_24HR (0.0371146)SB202190_3_24HR (0.0401265)TSA1_24HR (0.0166139)TSA2_24HR (0.0247618)(0.162718)TSA3_24HR (0.162934) (0.128273) [ min ] [ medium ] [ max ] CEM 1 Acaa2 386.9 667.5 1678.6 P ( S | Z, I ) = 1.00 Hadhb 2784.8 3048.3 5641.5 Mean Corr = 0.90848 Mecr 324.2 397.7 758.2 Acadvl 1980.6 2317.3 4775.0 Etfdh 882.3 1074.6 1914.9 Etfb 4189.2 5314.3 6791.4 Hadha 2649.0 2946.1 4462.7 Decr1 1525.4 2084.2 2519.0 CEM 1 + Ndufv1 3630.1 4099.7 6737.4 Top 10 Genes Etfa 3317.1 3889.1 5819.7 Hadh 2032.4 2468.3 7012.1 Atp5a1 9126.4 10977.1 12619.7 Suclg1 3396.6 4445.1 8295.5

Null module Ppt2 Ppt1 GEO Series "GSE19286" 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=GSE19286 Status: Public on Dec 03 2009 Title: Microarray gene expression profiling of aorta genes of APOE-deficient mice receiving the ACE inhibitor captopril Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20504763 Summary & Design: Summary: Microarray gene expression profiling of aorta genes of APOE-deficient mice receiving atherosclerosis treatment with the ACE inhibitor captopril.

Hypercholesterolemic APOE-deficient mice were used as a standard model of atherosclerosis to study gene expression changes during atherosclerosis treatment with the ACE inhibitor captopril. Microarray analysis was performed of whole aortas isolated from captopril-treated APOE-deficient mice relative to untreated APOE-deficient mice with overt atherosclerosis, and nontransgenic control mice. Microarray gene expression profiling revealed that captopril-mediated atherosclerosis prevention involved inhibition of aorta-infiltrating immune cells such as pro-atherogenic T lymphocytes and macrophages.

Overall design: Microarray gene expression profiling was performed of whole aortas isolated from APOE-deficient mice with atherosclerosis relative to captopril-treated APOE-deficient mice, and nontransgenic control mice. Three study groups were analyzed, i.e. 8-months-old untreated APOE-deficient mice with overt atherosclerosis, age-matched APOE-deficient mice treated for 7 months with the angiotensin-converting enzyme (ACE) inhibitor, captopril (20 mg/kg in drinking water), and nontransgenic control C57BL/6J mice. Two biological replicates were made of each group, and total RNA of three aortas was pooled for one gene chip.

Background corr dist: KL-Divergence = 0.0254, L1-Distance = 0.0174, L2-Distance = 0.0003, Normal std = 0.7080

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

Aorta_APOE-deficientAorta_APOE-deficientAorta_APOE-deficient Aorta_APOE-deficientwith atherosclerosis_1 Aorta_non-transgenicwith atherosclerosis_2 Aorta_non-transgenicand captopril and (0.105996) captopril treated_1 C57BL/6J (0.126599) treated_2 C57BL/6J (0.305353) control_1[ (0.276004) control_2min (0.12428) ] (0.0617678) [ medium ] [ max ] CEM 1 Acaa2 5453.1 8823.0 9659.1 P ( S | Z, I ) = 1.00 Hadhb 19263.5 24046.4 25294.3 Mean Corr = 0.93212 Mecr 1012.2 1696.4 1935.2 Acadvl 14034.8 16350.5 17852.1 Etfdh 4032.0 5671.1 8377.4 Etfb 15103.4 17469.8 19108.7 Hadha 7073.6 8312.1 11154.9 Decr1 7929.5 10331.0 13712.9 CEM 1 + Ndufv1 9124.6 11940.2 12657.7 Top 10 Genes Etfa 6447.0 10676.1 11863.3 Hadh 13163.5 15274.2 17601.4 Atp5a1 14248.7 18886.0 19234.0 Suclg1 8798.7 13941.1 14609.6

Null module Ppt2 Ppt1 GEO Series "GSE55855" 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=GSE55855 Status: Public on Mar 13 2014 Title: Effect of CSF1R inhibition in tumor macrophages on gene expression in metastatic epithelial cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Metastasis is the primary cause of mortality in breast cancer patients. Tumor associated macrophages (TAMs) are active collaborators in mediating several steps of the tumor metastatic cascade, but the molecular details governing this collaboration remain ill-defined. Colony Stimulating Factor 1 (CSF1), a factor critical for macrophage differentiation and survival, functions to recruit TAMs to the primary tumor site, and anti-CSF1 therapies are in clinical trials.In this study, we tested the effect of inhibiting CSF1 signaling in macrophages on gene expression in metastatic tumor cells in mouse models of breast cancer metastasis. Tumor cells were sorted from lung metastases from control and CSF1R inhibitor treated mice. Several pro-tumor processes were significantly affected by CSF1R inhibitor treatment, including angiogenesis and tumor cell proliferation. In addition, a 29 gene signature derived from this data could retrospectively predict survival in a cohort of luminal B breast cancer patients. Collectievly, our results highlight the utility of employing CSF1R inhibitors for the treatment of metastatic breast cancer.

Overall design: GFP tagged MVT1 metastatic mammary tumor cells were injected intravenously into FVB/N mice. Mice were gavaged with the CSF1R inhibitor GW2580 or vehicle starting one week post injection. GFP tagged tumor cells were sorted from metastatic tumor bearing lungs 1 and 2 weeks post injection from 2 vehicle treated mice for each. These are denoted 1_week_WT and 2_week_WT respectively. GFP tagged tumor cells were simultaneously sorted from mice gavaged with GW2580. These samples are denoted 2_week_GW. RNA was extracted and gene expression profiling was performed using the Affymetrix Mouse Genome 430 2.0 Array platform.

Background corr dist: KL-Divergence = 0.0388, L1-Distance = 0.0168, L2-Distance = 0.0003, Normal std = 0.6188

0.648 Kernel fit Pairwise Correlations Normal fit

Density 0.324

0.000 CEM 1

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

Pre-normalization Quantiles

MVT1tumorcells_control_1week_rep1MVT1tumorcells_control_1week_rep2MVT1tumorcells_control_2week_rep1MVT1tumorcells_control_2week_rep2MVT1tumorcells_GW2580treated_2week_rep1MVT1tumorcells_GW2580treated_2week_rep2 (0.054978) (0.108032) (0.415523) (0.145009)[ min (0.193183) ] (0.0832745)[ medium ] [ max ] CEM 1 Acaa2 1571.6 2181.4 3362.3 P ( S | Z, I ) = 1.00 Hadhb 3795.8 4231.3 4736.9 Mean Corr = 0.93093 Mecr 394.9 422.5 481.4 Acadvl 1959.2 2390.5 2893.7 Etfdh 1035.9 1143.3 1488.1 Etfb 3783.9 4104.1 4362.2 Hadha 1351.8 1636.8 2103.3 Decr1 2120.9 2692.9 2864.7 CEM 1 + Ndufv1 3195.6 3764.3 4400.7 Top 10 Genes Etfa 5126.9 5465.2 6131.9 Hadh 1679.4 2491.7 3080.2 Atp5a1 18508.3 20500.2 21320.3 Suclg1 4218.9 4494.8 5012.2

Null module Ppt2 Ppt1 GEO Series "GSE45028" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 22 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE45028 Status: Public on Jul 01 2014 Title: Expression data from NOD and C57BL/6 mouse pancreas CD8α- Dendritic Cells (DCs) under steady-state and after in-vitro LPS stimulation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Abstract Two major dendritic cell (DC) subsets have been described in the islets of mice: The immunogenic CD8α-CD11b+ DCs and the tolerogenic CD8α+CD103+ DCs. We have recently reported on reduced numbers of the minor population of tolerogenic CD8α+CD103+ DCs in the pancreas of 5 week old pre-diabetic non-obese diabetic (NOD) mice. Aim: To analyze also the larger subset of CD11c+CD8α- DCs isolated from the pancreas of pre-diabetic NOD mice 1) for maturation and tolerance inducing molecules found abnormally expressed on CD8α+CD103+ DCs, and 2) for genome-wide gene expression to further elucidate abnormalities in underlying gene expression networks. Methods: CD11c+CD8α- DCs were isolated from 5 week old C57BL/6 and NOD pancreas. Expression of cell surface markers including CD86, CCR5, CD11b, CD103, Clec9a, CD24 and CD200R3 were measured by FACS. Genome-wide gene expression by microarray was assessed during the steady state and after in vitro LPS stimulation. Results: The steady state pancreatic CD11c+ CD8α- DCs during the pre-diabetic stage showed: 1) A reduced expression of several gene networks important for the prime functions of the cell, such as for cell renewal, immune stimulation and immune tolerance induction, for migration and for the provision of growth factors for beta cell regeneration. This general deficiency state was corroborated by a reduced in vivo proliferation (BrdU incorporation) of the cells and the reduced expression in FACS analysis of CD86, CCR5, CD103, Clec9a, CD24 and CD200R3 on the cells. 2) A hyper reactivity of these cells to LPS correlated with an enhanced pro-inflammatory state characterized by altered expression of a number of classical pro-inflammatory factors and cytokines. Conclusion: The NOD CD11c+CD8α- DCs seem to be Janus-faced depending on the conditions: Deficient in steady state with reduced immune stimulation capabilities also for tolerance induction; over-inflammatory with a molecular profile suggesting a preferential stimulatory capacity for Th1 cells when encountering a Pathogen-Associated Molecular Pattern (PAMP) in the form of LPS.

We used microarray gene expression analysis to explain the abnormal expression of several cell surface markers involved in tolerace, migration and maturation in the steady-state and to measure the effect of a PAMP such as LPS

Overall design: We isolated RNA from FACS sorted CD11c+CD8α- DCs in 10 pooled pancreases from pre-diabetic NOD and non-diabetic C57BL/6 mice at 5 weeks. In addition, we treated in another experiment the isolated pancreas DCs with LPS (and PBS), incubated for 18h and measured gene expression. We compared gene expression between strains NOD vs C57BL/6 under steady-state and after in-vitro LPS/PBS stimulation.

Background corr dist: KL-Divergence = 0.0365, L1-Distance = 0.0850, L2-Distance = 0.0118, Normal std = 0.7351

0.543 Kernel fit Pairwise Correlations Normal fit

Density 0.271

0.000 CEM 1

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

Pre-normalization Quantiles

C57BL6C57BL6 pancreasC57BL6 pancreas CD8α-DCC57BL6 pancreas CD8α-DC rep1NODpancreas pancreas CD8α-DC(0.0803594) rep4NOD CD8α-DC(0.0721839) pancreas rep5 NODCD8α-DC (0.056211) pancreas rep6 C57BL6 CD8α-DC rep1 (0.0656358) C57BL6 (0.0844167)CD8α-DCpancreas rep4C57BL6 pancreas(0.0599991) CD8α-DCrep6C57BL6 pancreas(0.0690751) CD8α-DC PBSNOD pancreas CD8α-DCrep pancreas PBS NOD1 (0.0223176) CD8α-DCrep pancreas PBS NODCD8α-DC2 (0.0155693) rep pancreas PBS NODCD8α-DC3 (0.0317191) PBS rep pancreas C57BL6 CD8α-DC4rep (0.0175846) PBS 1 (0.027494) C57BL6 CD8α-DC reppancreas PBS 2 (0.0432773)C57BL6 reppancreas PBSCD8α-DC 3 (0.0627112)NOD reppancreas CD8α-DC 4 pancreas (0.0370954)LPSNOD CD8α-DCrep pancreas LPS 2NODCD8α-DC (0.0296203) rep pancreas LPS 3NODCD8α-DC (0.0650735) LPSrep pancreas 4CD8α-DCrep (0.0101577) LPS 1 (0.0493998) CD8α-DCrep LPS 2 (0.0349163) rep LPS 3 (0.0363412) [rep min 4 (0.0288418) ] [ medium ] [ max ] CEM 1 Acaa2 120.8 203.6 791.0 P ( S | Z, I ) = 1.00 Hadhb 616.5 802.7 2067.6 Mean Corr = 0.94869 Mecr 237.8 330.7 667.8 Acadvl 1286.6 1659.9 3061.5 Etfdh 610.9 787.5 1367.2 Etfb 664.7 1006.6 2681.6 Hadha 1256.1 1883.6 2381.8 Decr1 329.5 436.9 1114.9 CEM 1 + Ndufv1 692.5 945.0 1875.5 Top 10 Genes Etfa 2460.9 3427.8 4876.9 Hadh 101.8 165.0 1359.1 Atp5a1 1822.8 2231.0 3564.6 Suclg1 254.9 454.2 1169.5

Null module Ppt2 Ppt1 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, (0.0123631) 0mg/kg/daydose) 3,(high 1 Block RepliverPFOA, (0.00693886) 0mg/kg/daydose) 3,(high 3 Block ReplungPFOA, (0.0162193) 0mg/kg/daydose) 4,(high 3, Block Rep PFOA,liver (0.0168291) 5mg/kg/daydose) 4, (high4, Block Rep PFOA,lung (0.0113847)5mg/kg/day dose) 5, (high4, Block Rep PFOA,liver (0.0101266)5mg/kg/day dose)5, (high5, Block Rep PFOA,lung (0.0118271)5mg/kg/day dose) 1, (high5, Block Rep PFOA,liver (0.0163229)5mg/kg/day dose)1, (high5, Block Rep PFOA,lung (0.0168369)5mg/kg/day dose) 2, (high5, Block Rep PFOA,liver (0.023356)5mg/kg/day dose)2, (high1, Block Rep PFOA,lung (0.0112631)5mg/kg/day dose) 3, (high1, Block Rep PFOA,liver (0.0224859)5mg/kg/day dose)3, (high2, Block Rep PFOA,lung (0.0118045)5mg/kg/day dose) 4, (high2, Block Rep PFOA,liver (0.0141208)10mg/kg/day dose)4, (high3, Block Rep PFOA,lung (0.0116273)10mg/kg/day dose) 5, (high3, BlockRep liver PFOA, (0.0267947)10mg/kg/day dose)5, (high4, Block lung RepPFOA, (0.0111688)10mg/kg/day dose) (high1,4, Blockliver RepPFOA, (0.0299976)10mg/kg/day dose) (high1, 2, Block Rep PFOA,lung (0.0125767)10mg/kg/day dose) 2, (high2, Block Rep PFOA,liver (0.0161827)10mg/kg/day dose)2, (high1, Block Rep PFOA,lung10mg/kg/day (0.00865595) dose) 3, (high1, Block Rep PFOA,liver10mg/kg/day (0.0119361) dose)3, (high3, Block Rep PFOA,lung10mg/kg/day (0.0110455) dose) 4, (high3, Block Rep PFOA,liver0mg/kg/day (0.0142024) dose)4, (high4, Block Rep PFOA,lung0mg/kg/day (0.0117629) dose) 5, (high4, PFOA, BlockRep liver0mg/kg/day (0.0269132) dose)5, (high 5, RepPFOA,Block lung0mg/kg/day (0.010999) 1,dose) (highBlock5, RepPFOA, liver0mg/kg/day (0.0146386) 1, dose) 5 (high Block ReplungPFOA,0mg/kg/day (0.0185679) 2,dose)(low 5 Block RepliverPFOA, dose)0mg/kg/day (0.0152455) 2,(low 1 Block ReplungPFOA, (0.0129817) dose)0mg/kg/day 3,(low 1 Block RepliverPFOA, (0.00384427) dose)0mg/kg/day 3,(low 2 Block ReplungPFOA, (0.0108476) dose)0mg/kg/day 4,(low 2, Block Rep PFOA, liver(0.0135971) dose)1mg/kg/day 4, (low4, Block Rep PFOA, lung(0.0189981) dose)1mg/kg/day 5, (low4, Block Rep PFOA,liver (0.0235101) dose)1mg/kg/day 5, (low3, Block Rep PFOA,lung (0.0211433) dose)1mg/kg/day 1, (low3, Block Rep PFOA,liver (0.0119298) dose)1mg/kg/day 1, (low5, Block Rep PFOA,liver (0.0167451) dose)1mg/kg/day 1, (low2, Block Rep PFOA,lung (0.0164813) dose)1mg/kg/day 2, (low2, Block Rep PFOA,liver (0.020538) dose)1mg/kg/day 2, (low3, Block Rep PFOA,lung (0.0145121) dose)1mg/kg/day 3, (low3, Block Rep PFOA,liver (0.0172146) dose)3mg/kg/day 3, (low4, Block Rep PFOA,lung (0.0114599) dose)3mg/kg/day 4, (low4, Block Rep PFOA,liver (0.0164557) dose)3mg/kg/day 4, (low1, Block Rep PFOA,lung (0.0161812) dose)3mg/kg/day 1, (low1, Block Rep PFOA,liver (0.011451) dose)3mg/kg/day 1, (low3, Block Rep PFOA,lung (0.0326802) dose)3mg/kg/day 2, (low3, Block Rep PFOA,liver (0.10166) dose)3mg/kg/day 2, (low1, Block Rep PFOA,lung (0.0141225) dose)3mg/kg/day 3, (low1, Block Rep PFOA,liver (0.0217203) dose)3mg/kg/day 3, (low5, Block Rep PFOA,lung (0.0140239) dose)3mg/kg/day 4, (low5, Block Rep PFOA,liver (0.0149732) dose) 4, (low4, Block Rep PFOA,lung (0.0122914) dose) 5, (low4, BlockRep liver (0.0154821) dose) 5, (low2, Block lung (0.0186364) dose)[ (low2,min liver (0.0178537) dose) (low ] (0.0131714) dose) (0.0113)[ medium ] [ max ] CEM 1 Acaa2 2990.8 13709.5 20475.6 P ( S | Z, I ) = 1.00 Hadhb 2656.7 9832.3 26380.9 Mean Corr = 0.92197 Mecr 226.5 799.1 1352.0 Acadvl 2052.8 7775.6 21913.9 Etfdh 1210.6 5016.8 16545.6 Etfb 3741.8 9574.2 19273.2 Hadha 2060.9 5331.6 17404.9 Decr1 1820.9 6818.3 23901.7 CEM 1 + Ndufv1 2493.3 3789.8 5750.1 Top 10 Genes Etfa 2923.3 9709.6 15787.1 Hadh 3955.1 11535.4 20879.7 Atp5a1 15786.3 20256.8 30988.3 Suclg1 2317.6 5378.5 10141.9

Null module Ppt2 Ppt1 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 (0.0467919)liver-hypoxia-2hours-rep 2 (0.040144)liver-hypoxia-2hours-rep 3 (0.0354659)liver-hypoxia-2hours-rep 4 (0.0367019)liver-hypoxia-2hours-rep 1 (0.029479)liver-hypoxia-2hours-rep 2 (0.0296639)liver-hypoxia-2hours-rep 3 (0.0389684)liver-hypoxia-2hours-rep 4 (0.0353418)liver-hypoxia-2hours-rep 5 (0.0321987)liver-vehicle-2hours-rep 6 (0.0257458)liver-vehicle-2hours-rep 7 (0.0271514)liver-vehicle-2hours-rep 8 (0.0311764)liver-vehicle-2hours-rep 5 (0.0392585)bone 6 (0.0358594) marrow-vehicle-2hours-repbone 7 (0.0386917) marrow-vehicle-2hours-repbone 8 (0.0397383) marrow-vehicle-2hours-repbone marrow-hypoxia-2hours-repbone 1 (0.0213927)marrow-hypoxia-2hours-repbone 2 (0.0161111)marrow-hypoxia-2hours-repbone 3 (0.018914)marrow-hypoxia-2hours-repspleen-vehicle-2hours-rep 1 (0.0224734)spleen-vehicle-2hours-rep 2 (0.0201038)spleen-vehicle-2hours-rep 3 (0.0168499)spleen-vehicle-2hours-rep 41 (0.0185401)(0.0111589)spleen-hypoxia-2hours-rep 2 (0.0149378)spleen-hypoxia-2hours-rep 3 (0.0202823)spleen-hypoxia-2hours-rep 4 (0.0124858)spleen-hypoxia-2hours-rep 1 (0.0121046)spleen-vehicle-2hours-rep 2 (0.02507)spleen-hypoxia-2hours-rep 3 (0.016628)spleen-hypoxia-2hours-rep 4 (0.0179497)spleen-vehicle-2hours-rep 5 (0.0186635)spleen-vehicle-2hours-rep 7 (0.0260856)spleen-vehicle-2hours-rep 8 (0.0151779)spleen-hypoxia-2hours-rep 6 (0.0202387)spleen-hypoxia-2hours-rep 7 (0.0189836) 8 (0.0175098) 5 (0.0299977) 6 (0.0259643)[ min ] [ medium ] [ max ] CEM 1 Acaa2 1024.8 1629.5 19144.8 P ( S | Z, I ) = 1.00 Hadhb 2069.9 2633.5 8832.8 Mean Corr = 0.96498 Mecr 221.9 336.9 1004.9 Acadvl 1066.4 1553.3 13071.8 Etfdh 782.0 1207.3 10796.9 Etfb 1949.5 4422.0 16584.0 Hadha 1636.2 2539.2 7824.4 Decr1 801.5 1173.3 9615.9 CEM 1 + Ndufv1 1812.3 3098.4 6698.5 Top 10 Genes Etfa 2062.4 3233.1 18850.1 Hadh 1276.6 1763.6 12371.0 Atp5a1 8018.8 13546.4 28693.0 Suclg1 1708.7 2453.3 10254.3

Null module Ppt2 Ppt1 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 (0.0384278)Brain-Yellow1Liver-Slightly_Mottled1 (0.0246852) (0.031699)Kidney-Slightly_Mottled1Brain-Slightly_Mottled1Liver-Mottled1 (0.0511538)Kidney-Mottled1 (0.00812438) Brain-Mottled1(0.04182) (0.0307149)Liver-Heavily_Mottled1 (0.0159752) Kidney-Heavily_Mottled1(0.0446982)Brain-Heavily_Mottled1Liver-Pseudo_Ag1 (0.0470939)Kidney-Pseudo_Ag1 (0.0452054)Brain-Pseudo_Ag1 (0.0324985) (0.0410732)Liver-Yellow2 (0.00468589)Kidney-Yellow2 (0.0518595) (0.0267336)Brain-Yellow2Liver-Slightly_Mottled2 (0.00129994) (0.0512791)Kidney-Slightly_Mottled2Brain-Slightly_Mottled2Liver-Mottled2 (0.0219805)Kidney-Mottled2 (0.00506471) Brain-Mottled2(0.00884641) (0.0401517)Liver-Heavily_Mottled2 (0.0223637) Kidney-Heavily_Mottled2(0.0471322)Brain-Heavily_Mottled2Liver-Pseudo_Ag2 (0.120523)Kidney-Pseudo_Ag2 (0.00137044)Brain-Pseudo_Ag2 (0.0551442) (0.0229362) (0.0213003) (0.0441589)[ min ] [ medium ] [ max ] CEM 1 Acaa2 195.3 3303.7 11389.6 P ( S | Z, I ) = 1.00 Hadhb 1497.8 6378.7 10384.2 Mean Corr = 0.90048 Mecr 131.3 413.9 652.4 Acadvl 725.0 5132.8 12206.7 Etfdh 459.4 3529.6 8128.0 Etfb 1128.4 11438.6 24218.0 Hadha 725.1 4348.6 10231.8 Decr1 530.0 5321.1 11354.7 CEM 1 + Ndufv1 3758.4 6357.2 13016.0 Top 10 Genes Etfa 984.9 8580.1 17253.4 Hadh 918.0 8788.4 14654.4 Atp5a1 7263.2 15429.8 25498.4 Suclg1 2802.1 8764.2 14640.6

Null module Ppt2 Ppt1 GEO Series "GSE8949" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 20 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8949 Status: Public on Dec 12 2007 Title: Gene expression changes in mouse aorta during activation of or interference with PPAR gamma signaling. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20018933 Summary & Design: Summary: Ligand-mediated activation of the nuclear hormone receptor PPAR gamma lowers blood pressure and improves glucose tolerance in humans. Two naturally occurring mutations (P467L, V290M) in the ligand binding domain of PPAR gamma have been described in humans that lead to severe insulin resistance and hypertension. Experimental evidence suggests that these mutant versions of PPAR gamma act in a dominant negative fashion. To better understand the molecular mechanisms underlying PPAR gamma action in the vasculature, we determined the gene expression patterns in mouse aorta in response to activation or interference with the PPAR gamma signaling pathway.

Keywords: time course, dose response

Overall design: To assess the response to PPAR gamma interference, we used adult mice containing a dominant negative form of PPAR gamma. These mice have a targeted P465L mutation, which is equivalent to the P467L mutant, described in human patients. Wild-type littermates were used as the genetic control. The PPAR gamma signaling pathway was activated by administration of rosiglitazone for either 2 or 14 days to adult mice (C57BL/6J strain) at a dose of 3 or 10 mg/kg/day via the food. Control mice were fed standard mouse chow. For the microarray hybridizations, 2-3 biological replicates from each experimental group were used. Biological replicates were RNA pooled from 8 different mouse aortas. All the microarray procedures were conducted at the University of Iowa DNA Core facility using standard Affymetrix protocols. In brief, approximately 3 ug of total RNA was used as input to a one-step amplification procedure to generate biotin-labeled RNA fragments for hybridization to the Affymetrix GeneChip Mouse Genome 430 2.0 array.

Background corr dist: KL-Divergence = 0.2580, L1-Distance = 0.0580, L2-Distance = 0.0084, Normal std = 0.2981

1.338 Kernel fit Pairwise Correlations Normal fit

Density 0.669

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 Aorta,Mouse Control_for_Rosiglitazone_A Aorta,Mouse Control_for_Rosiglitazone_B Aorta,Mouse Control_for_Rosiglitazone_C Aorta,Mouse Rosiglitazone_dose3_time2_A Aorta,Mouse (0.0135152)Rosiglitazone_dose3_time2_B Aorta,Mouse (0.0535762)Rosiglitazone_dose3_time2_C Aorta,Mouse (0.0489609)Rosiglitazone_dose3_time14_A Aorta,Mouse Rosiglitazone_dose3_time14_B Aorta,Mouse(0.142129) Rosiglitazone_dose3_time14_C Aorta,Mouse(0.0605654) Rosiglitazone_dose10_time2_A Aorta,Mouse(0.0138277) Rosiglitazone_dose10_time2_B Aorta,Mouse (0.0845541) Rosiglitazone_dose10_time2_C Aorta,Mouse (0.0557633) Rosiglitazone_dose10_time14_A Aorta,Mouse (0.00897377) Rosiglitazone_dose10_time14_B Aorta,Mouse (0.0304071) Wildtype_for_P465L_PPARG_KI_A Aorta,Mouse (0.0809742) Wildtype_for_P465L_PPARG_KI_B Aorta,Mouse (0.0218007) Wildtype_for_P465L_PPARG_KI_C Aorta,Mouse (0.0345367) P465L_PPARG_KI_A Aorta,Mouse (0.0228778) P465L_PPARG_KI_B Aorta, (0.0756438) P465L_PPARG_KI_C (0.130522) (0.0259374) (0.0206954) (0.0277265)[ min (0.0470133) ] [ medium ] [ max ] CEM 1 Acaa2 1560.6 2502.5 5720.0 P ( S | Z, I ) = 1.00 Hadhb 4461.7 7658.5 16478.4 Mean Corr = 0.89617 Mecr 312.5 484.9 953.5 Acadvl 3177.3 4803.5 8673.2 Etfdh 1675.0 2732.6 4743.7 Etfb 3066.0 6208.9 11989.3 Hadha 2113.9 3102.6 5510.5 Decr1 2348.8 3768.9 6390.0 CEM 1 + Ndufv1 2521.8 3323.4 5333.9 Top 10 Genes Etfa 3427.9 5745.6 8581.2 Hadh 3076.8 5486.5 9156.4 Atp5a1 8357.7 10695.2 15646.7 Suclg1 2900.4 4770.1 8461.5

Null module Ppt2 Ppt1 GEO Series "GSE43145" 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=GSE43145 Status: Public on Dec 27 2012 Title: Expression data of mouse gastric tumors (TNF KO-Gan and BALB/c-Gan mice ) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Gan mice express Wnt1, Ptgs2, and Ptges, which develop inflammation-associated gastric tumors (Oshima et al, Gastroenterology 131: 1086, 2006). We examined the role of TNF-alpha in tumorigenesis by construction of TNF-/- Gan mice. We also examined genetic background difference in tumor phenotype by changing Gan mouse background from C57BL/6(B6) to BALB/c.

Microarray analyses were performed to examine changes of expression profiles in tumors by TNF gene disruption or by changing genetic background.

Overall design: Total RNA was prepared from B6 Gan mice (n=3: Gan1-Gan3), B6-Gan TNF-/- mice (n=3: Gan(TNF KO)1-Gan(TNF KO)3), BALB-Gan mice (n=3: Gan(BALB/c)1-Gan(BALB/c)3), and wid-type normal glandular stomach (n=3: WT1-WT3). We used Affymetrix microarrays for hybridization, and examined expression profiles.

Background corr dist: KL-Divergence = 0.0952, L1-Distance = 0.0238, L2-Distance = 0.0009, Normal std = 0.4532

0.880 Kernel fit Pairwise Correlations Normal fit

Density 0.440

0.000 CEM 1

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

Pre-normalization Quantiles

WT1 (0.111443)WT2 (0.228418)WT3 (0.179344)Gan1 (0.109493)Gan2 (0.0186104)Gan3 (0.0479571)Gan(TNFGan(TNF KO)1 Gan(TNF(0.0107561) KO)2 Gan(BALB/c)1(0.0443774) KO)3 Gan(BALB/c)2(0.0875481) (0.0496146)Gan(BALB/c)3 (0.0318234) (0.0806139) [ min ] [ medium ] [ max ] CEM 1 Acaa2 2357.0 3148.9 4103.4 P ( S | Z, I ) = 1.00 Hadhb 6136.7 7435.5 12493.1 Mean Corr = 0.89622 Mecr 412.7 526.4 858.0 Acadvl 3074.9 3511.6 4505.3 Etfdh 2481.6 3048.9 5037.0 Etfb 4067.8 4693.5 6106.0 Hadha 1166.8 1514.8 2198.7 Decr1 1628.5 2650.7 3307.9 CEM 1 + Ndufv1 4430.1 4769.1 8739.2 Top 10 Genes Etfa 4144.6 5763.1 9697.1 Hadh 5935.5 7357.9 10075.2 Atp5a1 15510.4 17268.3 23698.3 Suclg1 5515.0 7094.8 8343.8

Null module Ppt2 Ppt1 GEO Series "GSE42473" 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=GSE42473 Status: Public on Dec 04 2012 Title: PGC-1 alpha isoforms and muscle hypertrophy Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23217713 Summary & Design: Summary: An alternative promoter of the PGC-1alpha gene gives rise to three new PGC-1alpha isoforms refered to as PGC-1a2 (A2), PGC-1a3 (A3) and PGC-1a4 (A4). The proximal PGC-1 alpha promotor transcribes the canonical PGC-1 alpha which is refered to as PGC-1a1 (A1).G1/G2/G3 samples refer to the Green fluorescent protein (GFP) control samples used in this experiment. Forced expression of the PGC-1a4 isoform results in muslce hypertrophy associated with increased IGF-1 signaling and repression of myostatin signaling.

Overall design: Mouse primary myoblasts isolated from C57BL/6 mice were differentiated in vitro. Fully differentiated myotubes were transduced with adenoviral vectors expressing GFP (as control) or each of the PGC-1alpha isoforms originating from the proximal or alternative promotor.

Background corr dist: KL-Divergence = 0.1210, L1-Distance = 0.0285, L2-Distance = 0.0011, Normal std = 0.4209

0.965 Kernel fit Pairwise Correlations Normal fit

Density 0.482

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

WtPMC_A1_1WtPMC_A1_2 (0.158653)WtPMC_A1_3 (0.189396)WtPMC_A2_1 (0.249805)WtPMC_A2_2 (0.0337429)WtPMC_A2_3 (0.0262952)WtPMC_A3_1 (0.0311577)WtPMC_A3_2 (0.0432113)WtPMC_A3_3 (0.0586282)WtPMC_A4_1 (0.0236817)WtPMC_A4_2 (0.00988657)WtPMC_A4_3 (0.0449821)WtPMC_G1 (0.0319133)WtPMC_G2 (0.0618296)WtPMC_G3 (0.0132779) (0.0235401) [ min ] [ medium ] [ max ] CEM 1 Acaa2 1962.3 2303.5 4137.3 P ( S | Z, I ) = 1.00 Hadhb 4490.6 5312.2 10582.3 Mean Corr = 0.89442 Mecr 239.5 306.5 464.6 Acadvl 2301.9 2786.0 6656.8 Etfdh 1597.8 2018.1 5697.3 Etfb 4913.7 5047.7 9067.8 Hadha 3427.5 3904.5 6859.0 Decr1 551.5 630.0 915.0 CEM 1 + Ndufv1 5443.0 5926.8 9645.1 Top 10 Genes Etfa 3631.4 4071.0 9326.0 Hadh 1906.9 2296.4 3652.9 Atp5a1 15699.7 17094.6 24227.7 Suclg1 4851.7 5623.5 10598.6

Null module Ppt2 Ppt1 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, (0.0274422)0mg/kg/day rep1 lungPFOS, (0.0239974)0mg/kg/day rep2 liverPFOS, (0.0322237)0mg/kg/day rep2 lungPFOS, (0.0150432)0mg/kg/day rep3 liverPFOS, (0.0459233)0mg/kg/day rep3 lungPFOS, (0.0214881)0mg/kg/day rep4 liverPFOS, (0.0258509)5mg/kg/day rep4 lungPFOS, (0.0425431)5mg/kg/day rep5 liverPFOS, (0.0334186)5mg/kg/day rep5 lungPFOS, (0.0187302)5mg/kg/day rep1 liverPFOS, (0.0299613)5mg/kg/day rep1 lungPFOS, (0.0426911)5mg/kg/day rep2 liverPFOS, (0.0209638)5mg/kg/day rep2 lungPFOS, (0.0243943)5mg/kg/day rep3 liverPFOS, (0.0305155)5mg/kg/day rep3 lungPFOS, (0.0258917)5mg/kg/day rep4 liverPFOS, (0.024976)10mg/kg/day rep4 lungPFOS, (0.0416904)10mg/kg/day rep5 liver PFOS, (0.0372987)10mg/kg/day rep5 lungPFOS, (0.0533353)10mg/kg/day rep1 liverPFOS, 10mg/kg/day(0.0230872) rep1 lungPFOS, 10mg/kg/day(0.0526625) rep2 liverPFOS, 10mg/kg/day(0.0312082) rep2 lungPFOS, 10mg/kg/day(0.0292317) rep3 liverPFOS, 10mg/kg/day(0.0260283) rep3 lungPFOS, 10mg/kg/day(0.039503) rep4 liverPFOS, (0.0264575) rep4 lungPFOS, (0.0572512) rep5 liver (0.0516988) rep5 [(0.0444927) min ] [ medium ] [ max ] CEM 1 Acaa2 2178.7 10573.7 13662.6 P ( S | Z, I ) = 1.00 Hadhb 2050.5 8669.9 14780.9 Mean Corr = 0.97291 Mecr 183.1 650.0 823.0 Acadvl 1499.9 5611.8 10315.1 Etfdh 968.5 3969.1 8189.8 Etfb 2612.5 7578.0 11780.1 Hadha 1963.7 5787.0 10662.3 Decr1 1752.8 6520.5 15664.9 CEM 1 + Ndufv1 1984.2 3472.9 4185.0 Top 10 Genes Etfa 2797.8 9680.8 12828.4 Hadh 3711.3 10697.0 12368.1 Atp5a1 13144.2 18043.8 20796.7 Suclg1 2226.3 5090.4 7266.7

Null module Ppt2 Ppt1 GEO Series "GSE50865" 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=GSE50865 Status: Public on Sep 13 2013 Title: Expression Data For BRD4 Inhibition Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24373973 Summary & Design: Summary: BRD4 Inhibition of spindle cell malignant peripheral nerve sheath tumor (sMPNST) tumor cells

Overall design: Cells were treated with Brd4 shRNA (3 days) or 500 nM JQ1 (2 days) before RNA isolation

Background corr dist: KL-Divergence = 0.1079, L1-Distance = 0.0335, L2-Distance = 0.0015, Normal std = 0.4420

0.928 Kernel fit Pairwise Correlations Normal fit

Density 0.464

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

sMPNST_shCONTROL_3day_rep1sMPNST_shCONTROL_3day_rep2sMPNST_shCONTROL_3day_rep3sMPNST_shBrd4.552_3day_rep1sMPNST_shBrd4.552_3day_rep2 (0.0677572)sMPNST_shBrd4.552_3day_rep3 (0.0354858)sMPNST_Vehicle_2day_rep1 (0.0460455)sMPNST_Vehicle_2day_rep2 (0.126381)sMPNST_Vehicle_2day_rep3 (0.0572599)sMPNST_JQ1_2day_rep1 (0.0438411) (0.135811)sMPNST_JQ1_2day_rep2 (0.104648)sMPNST_JQ1_2day_rep3 (0.0556046) (0.157262) (0.0696281) (0.100274)[ min ] [ medium ] [ max ] CEM 1 Acaa2 825.2 1198.7 1388.3 P ( S | Z, I ) = 1.00 Hadhb 3516.0 4449.3 5315.6 Mean Corr = 0.88373 Mecr 466.4 722.4 848.7 Acadvl 730.8 860.6 2270.8 Etfdh 1360.5 1489.0 2334.3 Etfb 2074.8 2918.8 3561.0 Hadha 1049.9 1272.5 1772.4 Decr1 287.6 426.1 508.1 CEM 1 + Ndufv1 3531.1 3858.0 5070.8 Top 10 Genes Etfa 2910.7 3827.0 4741.2 Hadh 4433.3 5038.2 5887.7 Atp5a1 11083.1 11916.1 12572.8 Suclg1 5166.3 5501.1 6212.9

Null module Ppt2 Ppt1 GEO Series "GSE54581" 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=GSE54581 Status: Public on Jun 02 2014 Title: Selective mRNA translation during eIF2 phosphorylation induces expression of IBTKalpha Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24648495 Summary & Design: Summary: Disruption of protein folding in the endoplasmic reticulum triggers the Unfolded Protein Response (UPR), a transcriptional and translational control network designed to restore protein homeostasis. Central to the UPR is PERK phosphorylation of the alpha subunit of eIF2 (eIF2~P), which represses global translation coincident with preferential translation of mRNAs, such as ATF4 and CHOP, that serve to implement the UPR transcriptional regulation. In this study, we used sucrose gradient ultracentrifugation and a genome-wide microarray approach to measure changes in mRNA translation during ER stress. Our analysis suggests that translational efficiencies vary across a broad range during ER stress, with the majority of transcripts being either repressed or resistant to eIF2~P, while a notable cohort of key regulators are subject to preferential translation. From this latter group, we identify IBTKa as being subject to both translation and transcriptional induction during eIF2~P in both cell lines and a mouse model of ER stress. Translational regulation of IBTKalpha mRNA involves the stress-induced relief of two inhibitory uORFs in the 5'-leader of the transcript. Depletion of IBTKalpha by shRNA reduced viability of cultured cells coincident with increased caspase 3/7 cleavage, suggesting that IBTKalpha is a key regulator in determining cell fate during the UPR.

We used a genome-wide microarray approach to determine how individual mRNAs were differentially translated during endoplasmic reticulum stress.

Overall design: Please note that the treatment plus fractionation based on association with different numbers of ribosomes did yield different populations of mRNAs, which resulted in considerable variation in normalized data across the samples.

Background corr dist: KL-Divergence = 0.1148, L1-Distance = 0.0307, L2-Distance = 0.0019, Normal std = 0.4200

0.950 Kernel fit Pairwise Correlations Normal fit

Density 0.475

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 MEFs, biologicalControl MEFs, biologicalControl MEFs, rep 1 biologicalControl MEFs,(0.0359767) rep 1, biologicalControl MEFs, frac rep 1-4 1, biologicalControl MEFs, frac (0.23349) rep 5-8 1, biologicalControl MEFs, frac (0.0456386) rep 9-14 2 biologicalControl MEFs,(0.0788343) rep(0.00243981) 2, biologicalControl MEFs, frac rep 1-4 2, biologicalControl MEFs, frac (0.0185855) rep 5-8 2, biologicalControl MEFs, frac (0.047601) rep 9-14 3 biologicalStressed MEFs,(0.0604205) rep(0.0220034) 3, biologicalStressed fracMEFs, rep 1-4 3,Stressed biological fracMEFs,(0.019323) rep 5-8 3,Stressed biological fracMEFs,(0.0399637) rep 9-14Stressed 1 biological MEFs,(0.0505197) (0.0124817) repStressed 2 biological MEFs,(0.0781702) replStressed 2,biological MEFs, frac replStressed 1-4 2,biological MEFs, frac (0.0239877)replStressed 5-8 2,biological MEFs, frac (0.0561864)rep 9-143 biological MEFs,(0.0671056) repl (0.0134648) 3,biological frac repl 1-4 3, frac (0.0231566)repl [5-8 3, min frac (0.0567304) 9-14 ] (0.0139203) [ medium ] [ max ] CEM 1 Acaa2 395.0 739.9 1380.4 P ( S | Z, I ) = 1.00 Hadhb 907.9 1885.8 2676.9 Mean Corr = 0.87502 Mecr 301.3 656.3 1090.1 Acadvl 405.2 766.5 1594.6 Etfdh 923.9 1377.4 2413.8 Etfb 827.6 1944.6 3030.4 Hadha 327.0 751.7 1385.4 Decr1 321.9 989.7 1555.1 CEM 1 + Ndufv1 1189.3 3579.6 6662.8 Top 10 Genes Etfa 1775.6 3535.0 6080.9 Hadh 1381.4 3160.8 4549.7 Atp5a1 6042.2 11928.2 16733.1 Suclg1 1144.5 4109.4 5015.0

Null module Ppt2 Ppt1 GEO Series "GSE15914" 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=GSE15914 Status: Public on Oct 01 2009 Title: Interleukin-7 promotes monocyte/macrophage arrest on endothelial cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21804111 Summary & Design: Summary: Background: It is recognized that atherosclerosis can regresses at least in animal models. However, little is known about the mechanisms. We induced regression of advanced atherosclerosis in apolipoprotein E deficient (APOE­/­) mice and studied underlying mechanisms. Unexpectedly, our study led to the role of interleukin-7 (IL-7) in atherogenesis.

Methods and Results: We treated APOE­/­ mice fed a high cholesterol diet for 30 weeks to induce advanced lesions with a helper-dependent adenoviral vector expressing human apoE3 (HDAd-gE3), and analyzed the regression of atherosclerosis after 41 weeks. Using microarray analysis, we identified IL-7 as one of most significantly affected genes by lowering cholesterol. To answer why IL-7 is downregulated by reduced cholesterol, we studied effects of IL-7 on endothelial cells (ECs). Our major findings were (1) long-term lowering cholesterol induced regression of advanced atherosclerosis. (2) Microarray analysis identified multiple signaling pathways affected by lowering cholesterol. (3) Correction for multiple testing revealed that IL-7 expression was downregulated, whereas gamma-sarcoglycan and ˆ´–-actin were upregulated. (4) Oxidized LDL upregulated IL-7 expression in macrophages but not in aorta ECs or smooth muscle cells. (5) IL-7 increased the expression of cell adhesion molecules and chemokine in ECs and promoted monocyte adhesion to ECs. (6) Systemic elevation of IL-7 induced inflammatory response and recruited monocyte/macrophage to the lesions without increasing plasma cholesterol.

Conclusion: Our finding suggest that IL-7 inflames endothelium and triggers the adhesion/recruitment of monocyte/macrophages to the atherosclerotic lesions and thus plays a direct role in development of atherosclerosis.

Key Words: arteriosclerosis, gene therapy, hypercholesterolemia, interleukins, cell adhesion molecules

Overall design: 12039: E3: vector control

Background corr dist: KL-Divergence = 0.0908, L1-Distance = 0.0240, L2-Distance = 0.0008, Normal std = 0.4532

0.880 Kernel fit Pairwise Correlations Normal fit

Density 0.440

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

Baylor/Oka/LiBaylor/Oka/Li etBaylor/Oka/Li al/12031 etBaylor/Oka/Li al/12039 (0.139094) etBaylor/Oka/Li al/12043 (0.178278) etBaylor/Oka/Li al/12046 (0.0121861) etBaylor/Oka/Li al/12047 (0.12948) etBaylor/Oka/Li al/12048 (0.239375) etBaylor/Oka/Li al/12051 (0.0122405) et al/12053 (0.026085) et al/12054 (0.00398462) (0.259277)[ min ] [ medium ] [ max ] CEM 1 Acaa2 4493.0 5725.2 6523.8 P ( S | Z, I ) = 1.00 Hadhb 5184.9 6070.6 6530.2 Mean Corr = 0.88040 Mecr 462.1 707.5 847.5 Acadvl 4623.0 5667.8 6352.7 Etfdh 2773.8 3277.5 3972.1 Etfb 5558.8 7018.4 8336.7 Hadha 1174.4 1545.3 2006.7 Decr1 4141.3 4975.0 5669.4 CEM 1 + Ndufv1 3312.4 4247.7 4800.9 Top 10 Genes Etfa 4933.0 5880.7 6608.8 Hadh 4625.7 5501.3 5925.0 Atp5a1 6020.7 6643.5 7579.2 Suclg1 3139.6 3709.8 4169.7

Null module Ppt2 Ppt1 GEO Series "GSE14753" 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=GSE14753 Status: Public on Feb 10 2009 Title: Mammary tumors from K14-cre; ApcCKO/+ mice vs control mammary glands Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19197353 Summary & Design: Summary: Many components of Wnt/β-catenin signaling pathway also play critical roles in mammary tumor development. To study the role of Apc in mammary tumorigensis, we introduced conditional Apc mutations specifically into two different mammary epithelial populations using K14-Cre (progenitor) and WAP-cre (lactaing luminal) transgenic mice. Only the K14-cre mediated Apc heterozygosity developed mammary adenocarcinomas demonstrating histological and molecular heterogeneity, suggesting the progenitor cell origin of these tumors. These tumors harbored truncation mutation in a very defined region in the remaining wild-type allele of Apc that would retain some down-regulating activity of β-catenin signaling. Our results suggest that not only the epithelial origin but also a certain Apc mutations are selected to achieve a specific level of β-catenin signaling optimal for mammary tumor development.

Overall design: We have compared 3 mammary tumors from K14-cre; ApcCKO/+ mice with 3 control mammary glands.

Background corr dist: KL-Divergence = 0.0282, L1-Distance = 0.0235, L2-Distance = 0.0007, Normal std = 0.6907

0.582 Kernel fit Pairwise Correlations Normal fit

Density 0.291

0.000 CEM 1

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

Pre-normalization Quantiles

control controlmammary controlmammary gland, mammary biological gland,mammary biological tumor,gland, replicatemammary biologicaltumor, replicate 1 (0.264289) biologicaltumor, replicate 2 (0.195498) biological replicate 31 (0.148385)(0.118122) replicate 2[ (0.107182)min 3 (0.166525) ] [ medium ] [ max ] CEM 1 Acaa2 1256.3 1631.5 3251.7 P ( S | Z, I ) = 1.00 Hadhb 5235.3 7466.4 17950.2 Mean Corr = 0.93709 Mecr 389.3 607.8 917.5 Acadvl 2451.0 3643.7 8185.6 Etfdh 1737.3 2334.6 4735.0 Etfb 2777.7 4313.6 7135.9 Hadha 2518.3 3669.4 4720.0 Decr1 1867.0 4337.6 8311.6 CEM 1 + Ndufv1 3990.3 4661.3 6901.5 Top 10 Genes Etfa 4850.5 6697.0 10627.0 Hadh 3579.8 6519.6 11565.7 Atp5a1 8722.5 12691.9 14296.8 Suclg1 2834.1 5196.9 8558.3

Null module Ppt2 Ppt1 GEO Series "GSE6623" 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=GSE6623 Status: Public on Jan 25 2007 Title: FoxO are critical mediators of hematopoietic stem cell resistance to physiologic oxidative stress Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17254970 Summary & Design: Summary: To investigate the role of FoxO transcription factors as mediators of hematopoietic stem cell resistance to oxidative stress.

Keywords: Hematopoietic stem cells, myeloid progenitors, oxidative stress, ROS, Affymetrix Mouse Genome 430 2.0

Overall design: Study the effect of the deficiency of FoxO1, FoxO3, and FoxO4 in murine bone marrow hematopoietic stem cells and myeloid progenitors on expression of genes involved in reactive oxygen species (ROS) metabolism.

Background corr dist: KL-Divergence = 0.0999, L1-Distance = 0.0390, L2-Distance = 0.0024, Normal std = 0.4543

0.913 Kernel fit Pairwise Correlations Normal fit

Density 0.456

0.000 CEM 1

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

Pre-normalization Quantiles

Wild typeWild LSK type (1)Wild LSK(0.0240995) type (2)FoxO LSK(0.308884) deficient (3)FoxO (0.0544846) deficient FoxOLSK (4) deficient Wild LSK(0.115157) type(5) Wild LSK(0.0406579) myeloid type(6)Wild (0.0437999) myeloid progenitors typeFoxO myeloid progenitors deficientFoxO (7) progenitors(0.0737065) deficient FoxOmyeloid (8) (0.0922954) deficient myeloid (9)progenitors (0.0415563) myeloid progenitors (10) progenitors (0.0925248) (11)[ min(0.0288716) (12) (0.0839618) ] [ medium ] [ max ] CEM 1 Acaa2 281.5 730.1 935.7 P ( S | Z, I ) = 1.00 Hadhb 1277.6 1824.4 2211.5 Mean Corr = 0.87037 Mecr 70.5 176.5 299.5 Acadvl 495.6 658.1 1056.1 Etfdh 725.9 1281.5 1475.7 Etfb 128.1 3254.4 4702.0 Hadha 76.1 242.9 374.0 Decr1 1294.2 1862.5 2032.3 CEM 1 + Ndufv1 482.4 2072.1 2761.8 Top 10 Genes Etfa 1663.2 2676.7 3197.0 Hadh 3873.5 5002.3 6612.6 Atp5a1 5574.7 8839.9 9915.2 Suclg1 933.5 1924.4 2369.8

Null module Ppt2 Ppt1 GEO Series "GSE8199" 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=GSE8199 Status: Public on Jul 10 2007 Title: E18.5 Estrogen-related Receptor gamma Knockout Mouse Heart Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17618853 Summary & Design: Summary: 3 ventricles from E18.5 male mice were pooled for each array. Three arrays per genotype.

Title: ERRγ Directs and Maintains the Transition to Oxidative Metabolism in the Post-Natal Heart

Abstract: At birth the heart undergoes a critical metabolic switch to transition from a predominant dependence on carbohydrates during fetal life to a greater dependence on postnatal oxidative metabolism. This remains the principle metabolic state throughout life; although pathologic conditions such as heart failure and cardiac hypertrophy reactivate components of the fetal genetic program to increase carbohydrate utilization. Disruption of the ERRγ gene, which is expressed at high levels in the fetal and postnatal mouse heart, blocks this switch resulting in lactatemia, electrocardiographic (ECG) abnormalities and death during the first week of life. Genomic ChIP-on-chip and expression analysis at E18.5 clearly identifies ERRγ as both a direct and indirect regulator of a nuclear-encoded mitochondrial genetic network that coordinates the postnatal metabolic transition. These findings reveal an unexpected and essential molecular genetic component of the oxidative metabolic gene program in the heart and highlight ERRγ in the study of cardiac hypertrophy and failure.

Keywords: ChIP-on-chip, electrocardiography, fetal gene program, OXPHOS, PGC-1a, sodium current, Single time point (E18.5) to compare genotype differences

Overall design: Fetal mice were collected by caesarean secation. Hearts were stored in RNALater (Qiagen)

Background corr dist: KL-Divergence = 0.1030, L1-Distance = 0.0254, L2-Distance = 0.0011, Normal std = 0.4331

0.921 Kernel fit Pairwise Correlations Normal fit

Density 0.461

0.000 CEM 1

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

Pre-normalization Quantiles

E18.5 ERRgE18.5 +/+ ERRgE18.5 heart, +/+ ERRg E18.5biological heart, +/+ ERRg E18.5biological heart, rep +/- ERRg 1 E18.5biological heart,(0.0233561) rep +/- ERRg 2biologicalE18.5 heart,(0.346204) rep +/- ERRg 3biologicalE18.5 heart,(0.131582) rep -/- ERRg1 biological E18.5 heart,(0.0355479) rep -/- ERRg2biological heart,(0.0683451) rep -/- 3biological heart,(0.0570567) rep 1 biological (0.119507) rep 2 (0.101106)[ repmin 3 (0.117295) ] [ medium ] [ max ] CEM 1 Acaa2 9607.1 11451.4 15684.1 P ( S | Z, I ) = 1.00 Hadhb 12313.2 13042.0 14407.5 Mean Corr = 0.86160 Mecr 621.2 766.5 996.1 Acadvl 8683.1 9968.4 11922.0 Etfdh 8773.2 9232.1 10651.4 Etfb 13414.0 14994.2 18348.2 Hadha 7574.3 9041.2 10586.7 Decr1 5037.3 5465.3 6128.9 CEM 1 + Ndufv1 16626.6 18159.8 19548.3 Top 10 Genes Etfa 12125.7 12958.8 14841.8 Hadh 9708.5 11007.1 12238.4 Atp5a1 42415.6 45962.2 51395.2 Suclg1 12258.2 13201.1 16457.2

Null module Ppt2 Ppt1 GEO Series "GSE56162" 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=GSE56162 Status: Public on Jun 30 2014 Title: Differential effects of maternal high protein diets on liver transcriptomes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: The objective of this study was to test if maternal high protein diet during pregnancy or lactation, imposes different transient or persistently imprinted effects on the liver transcriptome of offspring

Overall design: Livers from 4 to 5 animals (one animal per litter) at days 21 and 150 of of each dietary group were combined to 3 pools each, and processed for microarray analysis.

Background corr dist: KL-Divergence = 0.2001, L1-Distance = 0.0369, L2-Distance = 0.0028, Normal std = 0.3341

1.194 Kernel fit Pairwise Correlations Normal fit

Density 0.597

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 d21Liver control d21Liver controldiet d21 biologicalLiver controldiet d150 biologicalLiver rep1diet control d150 biologicalLiver(0.0186684) rep2 controldiet d150 Liver(0.165419) biological rep3 controldiet d21 Liver(0.140473) biological high rep1diet d21 proteinLiver biological(0.0155053) high rep2 d21 proteinLiverdiet (0.0690329) high rep3 during d150 proteinLiverdiet (0.0113798) high pregnancyduring d150 Liverdiet protein high pregnancyduring d150Liver biological proteindiet high pregnancy d21duringLiver biological proteindiet high rep1 pregnancyd21during proteinLiver biological(0.0509983)diet high rep2 pregnancyd21during proteinLiverdiet (0.0362836) biological high rep3 during pregnancyd150 proteinLiverdiet (0.0238179) biological high lactationduringrep1 d150 Liverdiet protein biological(0.101316) high lactationduringrep2 d150biological proteindiet (0.0594252) high lactationrep3 duringbiological proteindietrep1 (0.0837232) lactation during biological(0.027385) dietrep2 lactationduring (0.0334928) biological[ rep3 min lactation (0.0284658) biological rep4 ] biological(0.0213777) rep5 (0.0556806) rep6[ medium (0.0575561) ] [ max ] CEM 1 Acaa2 9376.2 13955.9 18723.4 P ( S | Z, I ) = 1.00 Hadhb 10455.7 14086.7 20400.3 Mean Corr = 0.85793 Mecr 335.8 557.5 903.4 Acadvl 10591.3 13835.3 17256.6 Etfdh 8830.2 12524.2 18041.8 Etfb 14597.9 17281.3 23011.8 Hadha 2030.4 4177.3 4958.4 Decr1 8335.5 10315.6 14430.8 CEM 1 + Ndufv1 3849.6 5823.6 8184.6 Top 10 Genes Etfa 10937.5 14168.5 16352.7 Hadh 12129.5 15021.1 19567.5 Atp5a1 11170.4 14391.2 16844.8 Suclg1 10949.0 12825.6 15412.4

Null module Ppt2 Ppt1 GEO Series "GSE8679" 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=GSE8679 Status: Public on Jan 11 2008 Title: Gene expression in mouse white adipose tissue Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17878318 Summary & Design: Summary: Trans-10, Cis-12 conjugated linoleic acid (t10c12 CLA) causes fat loss in mouse white adipose tissue (WAT). The early transcriptome changes in WAT were analyzed using high-density microarrays to better characterize the signaling pathways responding to t10c12 CLA. Their gene expression responses between 4 to 24 hr after treatment showed a common set of early gene expression changes indicative of an integrated stress response (ISR).

Keywords: control/treatment time course

Overall design: Mouse WAT RNA for each time point was isolated from two control and two treatment samples for analysis on four microarrays. The two control and two treatment samples consisted of RP tissues from 5 pooled mice for each sample, requiring a total of twenty mice for the four samples taken at each time point.

Background corr dist: KL-Divergence = 0.1214, L1-Distance = 0.0366, L2-Distance = 0.0027, Normal std = 0.4127

1.019 Kernel fit Pairwise Correlations Normal fit

Density 0.510

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 whitemouse adipose whitemouse adipose tissue,whitemouse adipose CLAtissue,whitemouse fed, adipose CLAtissue,whitemouse T1, fed,biological adipose LAtissue,whitemouse T1, fed biological adipose (control), LAtissue, whitemouserep1 fed (0.300691)adipose (control), CLAtissue, whitemouserep2 T1, fed, biological (0.0264295)adipose CLAtissue,whitemouse T2,T1, fed,biological adipose LAtissue, whitemouserep1 T2, fed biological (0.0547582)adipose (control), LAtissue, whitemouserep1rep2 fed (0.0487014)(0.0504967)adipose (control), CLAtissue, whiterep2 T2, fed, biological (0.0633942)adipose CLAtissue, T3,T2, fed,biological LAtissue, rep1 T3, fed biological (0.017033) (control),LA [rep1rep2 fedmin (0.112219)(0.0959523) (control), rep2 T3, ] biological(0.159151) T3, biological rep1[ (0.0170046)medium rep2 (0.0541689) ] [ max ] CEM 1 Acaa2 896.1 3322.4 5292.8 P ( S | Z, I ) = 1.00 Hadhb 7748.9 13817.8 17928.8 Mean Corr = 0.85107 Mecr 790.8 1283.8 2077.1 Acadvl 5101.2 7046.7 7932.6 Etfdh 4107.2 5635.7 6215.3 Etfb 5169.3 11442.0 15997.8 Hadha 2661.8 4114.7 6306.5 Decr1 6949.8 11332.3 13129.3 CEM 1 + Ndufv1 2470.2 4475.1 6846.5 Top 10 Genes Etfa 8894.9 13123.1 14045.5 Hadh 11822.7 16605.4 19133.1 Atp5a1 6982.8 16444.0 25562.4 Suclg1 3302.0 7174.0 8403.9

Null module Ppt2 Ppt1 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(0.0107187)weeks Mammary35 type8 wild(0.0352315)weeks Mammary36 type8 tumor(0.0646676)weeks Mammary37 8Mammary1 tumor(0.0415049)weeks 8Mammary2 tumor(0.0166731)weeks (0.0693932) 8Mammary3 tumorweeks (0.012878) 12Mammary4 tumor weeks (0.01286) 12Mammary5 tumorweeks (0.0252211)12 Mammary6 tumorweeks (0.0132622)12 Mammary7 tumorweeks (0.0104835)12 Mammary8 tumorweeks (0.00903688)16 Mammary9 tumorweeks (0.0284155)16 Mammary10 tumorweeks (0.0214672)16 Mammary11 tumorweeks (0.0112612)16 Mammary13 tumorweeks (0.0503751)16 Mammary14 tumorweeks (0.0173268)20 Mammary15 tumorweeks (0.0166564)20 Mammary32 tumorweeks (0.00678524)20 Mammary22 tumorweeks (0.0559453)20 Mammary23 tumorweeks (0.0728528) Mammary24 tumor (0.126009) Mammary31 (0.132826) (0.138149)[ min ] [ medium ] [ max ] CEM 1 Acaa2 779.3 3106.1 5183.0 P ( S | Z, I ) = 1.00 Hadhb 1094.1 12384.8 18224.2 Mean Corr = 0.85277 Mecr 258.1 1016.4 1238.5 Acadvl 1236.1 5892.1 8691.4 Etfdh 1067.8 4380.8 6793.2 Etfb 1076.8 9100.0 11072.5 Hadha 623.3 3129.3 5004.0 Decr1 848.7 7100.2 8629.6 CEM 1 + Ndufv1 1762.4 5448.4 7453.9 Top 10 Genes Etfa 3484.1 10100.5 12244.3 Hadh 1094.0 9128.3 11574.7 Atp5a1 6213.9 13895.9 18330.9 Suclg1 1270.1 5825.1 8632.0

Null module Ppt2 Ppt1 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 (0.00710668) miceK5˛N˛†cat 2 tumor (0.0108022) miceK5˛N˛†cat 3 tumor (0.00996557) miceK5˛N˛†cat 4 tumor (0.0169564) miceK5˛N˛†cat 5 tumor (0.0128766) miceK5˛N˛†cat 6 tumor (0.0172227) miceK5˛N˛†cat 7 tumor (0.00919896) miceK5˛N˛†cat 8 tumor (0.0181554) miceK5˛N˛†cat 9 tumor (0.00916714) miceK5˛N˛†cat 10 tumor (0.0237195)smallK5˛N˛†cat 11 hyperplasia (0.0175441)smallK5˛N˛†cat hyperplasia small 1K5˛N˛†cat (0.0216421) hyperplasia small 2K5˛N˛†cat (0.00906954) hyperplasia small 3K5˛N˛†cat (0.0424064) hyperplasia Large 4K5˛N˛†cat (0.0842954) hyperplasia Large 5K5˛N˛†cat (0.0498352) hyperplasia Large 1K5˛N˛†cat (0.00796129) hyperplasia Large 2Control (0.000768083) hyperplasia Large 3Control mice (0.00743524) hyperplasia 1 4Control (0.0968039)mice (0.00364372) 2 5Control (0.0532961)mice (0.00359344) 3 sorted (0.0688261)mice 4 basal sorted(0.0219653) cells basalsorted Control cells basalsorted Control mice cells basalsorted 1 Control (0.0369493)mice cells basalsorted 2 K5creL/L (0.0350489)mice cells basal 3 K5creL/L(0.0572539) micecells K5creL/L1 (0.0641221)mice 2 (0.0464)mice[ min3 (0.135969) ] [ medium ] [ max ] CEM 1 Acaa2 489.9 1460.3 4466.9 P ( S | Z, I ) = 1.00 Hadhb 2539.8 5434.6 15547.9 Mean Corr = 0.86760 Mecr 222.3 455.1 1357.1 Acadvl 1517.5 3157.5 7865.4 Etfdh 852.1 1877.8 5210.0 Etfb 1371.4 2564.4 10525.3 Hadha 1471.8 3367.0 8621.5 Decr1 372.6 1602.1 10156.9 CEM 1 + Ndufv1 1191.9 3248.2 6989.6 Top 10 Genes Etfa 2410.2 4938.0 9962.0 Hadh 663.6 2737.3 13375.0 Atp5a1 3104.2 10109.2 18530.2 Suclg1 390.5 2452.9 6181.0

Null module Ppt2 Ppt1 GEO Series "GSE13693" 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=GSE13693 Status: Public on Feb 06 2009 Title: Gene expression profiling of normal mouse myeloid cell populations Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19200802 Summary & Design: Summary: Normal myeloid lineage cell populations (C57BL/6 mice, aged 4-10 weeks, male or female) with three distinct immunophenotypes were prospectively isolated and characterized. In preparation for FACS sorting, bone marrow cells were separated into c-kit+ and c-kit- fractions using an AutoMACS device. C-kit+ cells were further fractionated based on Gr1 and Mac1 expression, and absence of lineage antigen expression (B220, TER119, CD3, CD4, CD8 and IL7Rα), by cell sorting. C-kit+ Gr1+ Mac1lo/- and c-kit+ Gr1+ Mac1+ displayed cytologic features of undifferentiated hematopoietic cells or myeloblasts, whereas c-kit- Gr1+ Mac1+ cells were mature neutrophils.

Overall design: See summary.

Background corr dist: KL-Divergence = 0.0176, L1-Distance = 0.0380, L2-Distance = 0.0018, Normal std = 0.8108

0.500 Kernel fit Pairwise Correlations Normal fit

Density 0.250

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

NORMALNORMAL BM NEUTROPHILS_2NORMAL BM NEUTROPHILS_1NORMAL BM NEUTROPHILS_3NORMAL (0.104426)MYELOBLASTS_CD117POS_GR1+_MAC1-_1NORMAL (0.371732)MYELOBLASTS_CD117POS_GR1+_MAC1-_2NORMAL (0.127537)MYELOBLASTS_CD117POS_GR1+_MAC1-_3NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_2NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_1 MYELOBLASTS_CD117POS_GR1+_MAC1+_3 (0.114133) (0.112401)[ min(0.113259) (0.0151536)] (0.0185067)[ (0.0228524) medium ] [ max ] CEM 1 Acaa2 376.5 1433.0 2395.8 P ( S | Z, I ) = 1.00 Hadhb 1513.5 3351.1 4885.6 Mean Corr = 0.96202 Mecr 24.2 222.8 435.9 Acadvl 1587.9 1738.8 2350.1 Etfdh 537.1 1460.9 1916.5 Etfb 1020.6 7034.1 7865.6 Hadha 126.7 295.4 436.2 Decr1 52.8 1089.8 1691.8 CEM 1 + Ndufv1 708.6 4105.4 5291.4 Top 10 Genes Etfa 483.9 3108.1 4505.1 Hadh 28.8 655.4 1487.1 Atp5a1 3046.1 9996.5 12890.8 Suclg1 2264.7 6013.8 6408.6

Null module Ppt2 Ppt1 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 (0.0101719) age-controlheart-30 replicate3diet-biological months of (0.042124) age-controlheart-30 replicate4 months diet-biologicalof (0.0335262) age-controlheart-30 replicate5 months diet-biologicalof (0.0416943) age-controlheart-30 months replicate1diet-biologicalof (0.0150927) age-controlheart-30 months replicate2diet-biologicalof age-CR(0.0213384)heart-30 months replicate3diet-biologicalof age-CR(0.0153802)diet-biologicalheart-30 months replicate4of age-CR(0.0137014)diet-biologicalheart-30 months replicate5of age-CR(0.0455258)replicate1diet-biologicalheart-30 months of age-CR(0.0198571)replicate2diet-biologicalheart-30 (0.0154267) months of age-resveratrolreplicate3diet-biologicalheart-30 (0.0223204) months of age-resveratrolreplicate4heart-30 (0.0239321) months of age-resveratrol replicate5diet-biologicalgastrocnemius-5 (0.0227923) months of age-resveratrol diet-biologicalgastrocnemius-5 (0.0906935) of age, replicate1diet-biologicalgastrocnemius-5 resveratrolmonths replicate2diet-biologicalgastrocnemius-5 (0.00877234) months of replicate3age-controldiet-biologicalgastrocnemius-5 (0.012499) months of replicate4age-controlgastrocnemius-30 (0.0154299) months diet-biologicalof age-controlreplicate5gastrocnemius-30 (0.0140069) months diet-biologicalof age-controlgastrocnemius-30 (0.0303224) replicate1diet-biological ofmonths age-controlgastrocnemius-30 replicate2diet-biological months of (0.0118316) age-controlgastrocnemius-30 replicate3diet-biological months of (0.0154726) age-controlgastrocnemius-30 replicate4 months diet-biologicalof (0.0155122) age-controlgastrocnemius-30 replicate5 months diet-biologicalof (0.0122828) age-controlgastrocnemius-30 months replicate1diet-biologicalof (0.00355857) age-controlgastrocnemius-30 months replicate2diet-biologicalof age-CR(0.00484177)gastrocnemius-30 months replicate3diet-biologicalof age-CR(0.00807084)gastrocnemius-30diet-biological months replicate4of age-CR(0.00582597)gastrocnemius-30diet-biological months replicate5of age-CR(0.00527969)gastrocnemius-30replicate1diet-biological months of age-CR(0.00397771)gastrocnemius-30replicate2diet-biological (0.0247999) months of age-resveratrolgastrocnemius-30replicate3diet-biological (0.014279) months of age-resveratrolneocortex-5replicate4 (0.0040514) months of age-resveratrol neocortex-5replicate5diet-biological (0.0216707) months of months age-resveratrol neocortex-5diet-biological (0.0140328) of months of age, neocortex-5 replicate1diet-biologicalage-control resveratrol months of neocortex-5 replicate2diet-biologicalage-control (0.00960687) months diet-biologicalof neocortex-30 replicate3age-controldiet-biological (0.0027779) months diet-biologicalof neocortex-30 replicate4age-control (0.0104903) replicate1diet-biological ofmonthsneocortex-30 replicate5age-control (0.00490025) replicate2diet-biological months ofneocortex-30 (0.00876358) age-control (0.00445064) replicate3diet-biological months ofneocortex-30 (0.0158022) age-control replicate4 months diet-biologicalofneocortex-30 (0.0149898) age-control replicate5 months diet-biologicalofneocortex-30 (0.00961519) age-control months replicate1diet-biologicalofneocortex-30 (0.0180011) age-control months replicate2diet-biologicalofneocortex-30 age-CR(0.0130568) months replicate3diet-biologicalofneocortex-30 age-CR(0.0139048)diet-biological months replicate4ofneocortex-30 age-CR(0.0125657)diet-biological months replicate5ofneocortex-30 age-CR(0.0120442)replicate1diet-biological months ofneocortex-30 age-CR(0.0157813)replicate2diet-biological (0.0202541) months ofneocortex-30 age-resveratrolreplicate3diet-biological (0.012455) months ofneocortex-30 age-resveratrolreplicate4 (0.0160382) months of age-resveratrol replicate5diet-biological (0.0129303) months of age-resveratrol diet-biological (0.0124613) of age, replicate1diet-biological resveratrol[ minreplicate2diet-biological (0.0158832) replicate3 diet-biological] (0.0111173) replicate4 (0.0149496) [replicate5 medium(0.0119324) (0.0251333) ] [ max ] CEM 1 Acaa2 348.2 2659.0 16669.2 P ( S | Z, I ) = 1.00 Hadhb 2035.2 12975.1 59685.2 Mean Corr = 0.82642 Mecr 200.3 395.3 716.7 Acadvl 1183.0 9500.9 30005.2 Etfdh 846.6 7052.3 22034.9 Etfb 1179.7 10853.9 34755.5 Hadha 735.9 4609.8 27863.1 Decr1 476.5 4825.7 22280.1 CEM 1 + Ndufv1 5509.7 11818.4 32242.1 Top 10 Genes Etfa 1187.8 10486.2 26685.0 Hadh 1002.7 15148.4 35206.5 Atp5a1 10686.4 34678.1 59745.3 Suclg1 4439.4 14578.6 20941.6

Null module Ppt2 Ppt1 GEO Series "GSE51432" 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=GSE51432 Status: Public on May 28 2014 Title: β-Cryptoxanthin suppresses inflammatory gene expression in diet-induced nonalcoholic steatohepatitis in mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24858832 Summary & Design: Summary: To evaluate the effect of β-cryptoxanthin on diet-induced NASH, we fed a high-cholesterol and high-fat diet (CL diet) with or without 0.003% β-cryptoxanthin to C56BL/6J mice for 12 weeks. After feeding, β-cryptoxanthin attenuated fat accumulation, increases in Kupffer and activated stellate cells, and fibrosis in CL diet-induced NASH in the mice.

Comprehensive gene expression analysis showed that although β-cryptoxanthin histochemically reduced steatosis, it was more effective in inhibiting inflammatory gene expression change in NASH. β-Cryptoxanthin reduced the alteration of expression of genes associated with cell death, inflammatory responses, infiltration and activation of macrophages and other leukocytes, quantity of T cells, and free radical scavenging. However, it showed little effect on the expression of genes related to cholesterol and other lipid metabolism. The expression of markers of M1 and M2 macrophages, T helper cells, and cytotoxic T cells was significantly induced in NASH and reduced by β-cryptoxanthin. β-Cryptoxanthin suppressed the expression of lipopolysaccharide (LPS)-inducible and/or TNFα-inducible genes and the antioxidant enzyme glutathione peroxidase 1 in NASH. Thus, β-cryptoxanthin suppresses inflammation and the resulting fibrosis probably by primarily suppressing the increase and activation of macrophages and other immune cells. Reducing oxidative stress is likely to be a major mechanism of inflammation and injury suppression in the livers of mice with NASH.

Overall design: Eight-week old male C57BL/6J mice were fed for 12 weeks on a CRF-1 standard chow (control), a high-cholesterol and high-fat diet (CL diet; 38.23% CRF-1, 60% cocoa butter, 1.25% cholesterol, 0.5% sodium cholate) or a CL diet containing 0.003% β-cryptoxanthin.

Background corr dist: KL-Divergence = 0.2148, L1-Distance = 0.0482, L2-Distance = 0.0053, Normal std = 0.3222

1.238 Kernel fit Pairwise Correlations Normal fit

Density 0.619

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_controlliver_control diet_repliver_control diet_rep 1liver_control (0.117847) diet_rep 2liver_control (0.0347135) diet_rep 3liver_CL (0.0544508) diet_rep 4liver_CL (0.0500009)diet_rep 5liver_CL (0.045836)diet_rep 1 (0.0872353)liver_CL diet_rep 2 (0.137554)liver_CL diet_rep 3 (0.0046541)liver_CL diet_rep 4 (0.0576166)liver_CL diet_0.005% 5 (0.107393)liver_CL diet_0.005% β-cryptoxanthin_repliver_CL diet_0.005% β-cryptoxanthin_repliver_CL diet_0.005% β-cryptoxanthin_rep diet_0.005% 1 β-cryptoxanthin_rep (0.031716) 2 β-cryptoxanthin_rep (0.0336277) 3 [(0.0381939) min 4 (0.106382) ] 5 (0.0927784)[ medium ] [ max ] CEM 1 Acaa2 14758.2 17876.4 21046.5 P ( S | Z, I ) = 1.00 Hadhb 11968.3 14744.2 20163.0 Mean Corr = 0.82279 Mecr 399.0 498.0 640.4 Acadvl 12335.2 14011.8 17847.2 Etfdh 10028.3 12191.5 15421.9 Etfb 11560.5 15099.7 18090.8 Hadha 5259.5 5959.0 8836.4 Decr1 11451.8 14506.2 19152.0 CEM 1 + Ndufv1 5850.7 7318.2 9213.3 Top 10 Genes Etfa 10486.0 15349.3 19475.2 Hadh 13297.6 16583.9 18186.8 Atp5a1 16751.1 19172.0 27802.9 Suclg1 9949.1 13469.7 17285.6

Null module Ppt2 Ppt1 GEO Series "GSE17297" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 32 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17297 Status: Public on Jul 24 2009 Title: Mndal, a new interferon-inducible family member, suppresses cell growth and may modify plasmacytoma susceptibility Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19654412 Summary & Design: Summary: Mndal, a new interferon-inducible family member, is highly polymorphic, suppresses cell growth and may modify plasmacytoma susceptibility.

The human HIN-200 gene cluster and its mouse counterpart, the Interferon inducible-200 (Ifi200) family, both on Chr 1, are associated with several diseases, including solid tumors and lupus. Our study was initiated to identify the modifier gene(s) encoded by the Pctm locus, in which mouse B cell plasmacytomas induced by pristane are associated with heterozygosity of Chr 1 genes near the Ifi200 cluster.

A screen for differentially expressed genes in granulomatous tissues induced by pristane in resistant and susceptible strains identified a new Ifi200 member whose expression was 1000-fold higher in the strain carrying the resistant allele of Pctm, and was the most highly expressed Ifi200 gene. The gene, designated Mndal (for MNDA-like, myeloid nuclear differentiation antigen like), was absent in the susceptible genome, as were genomic sequences upstream of Ifi203, the gene adjacent to Mndal. Ectopic expression of MNDAL suppressed cell growth, which, together with the disease susceptibility of heterozygotes at the Pctm locus, suggests that Mndal, perhaps with Ifi203, acts as a tumor suppressor and display(s) haplo-insufficiency. Mndal is highly polymorphic among inbred mouse strains, as it is absent in 10/24 strains. This polymorphism may have implications for other disease modifiers mapping to the same region.

Overall design: Using institutionally approved animal protocols, mice were given 0.5 ml TMPD intraperitoneally. Three and 18 days later, total RNA was extracted from mesentery of experimental/control animals, using TRIzol (Invitrogen). Labeled aRNA prepared from 1 ´g of RNA (MessageAmpII aRNA Amplification kit, Ambion protocols) was hybridized to mouse genome 430 2.0 array chips, processed on Workstation 450, and analyzed with Gene Chip Operating Software (GCOS; Affymetrix). Differential expression was assessed by ANOVA (Partek Genomics Suite).

Background corr dist: KL-Divergence = 0.1512, L1-Distance = 0.0349, L2-Distance = 0.0026, Normal std = 0.3805

1.048 Kernel fit Pairwise Correlations Normal fit

Density 0.524

0.000 CEM 1

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

Pre-normalization Quantiles

BALB/cBALB/c d18 (bmsnmix1)BALB/c d18 (bmsnmix2)BALB/c d18 (0.0586624) (bmsnmix3)BALB/c d18 (0.0199191) (bmsnmix4)BALB/c control (0.0175529)BALB/c control(bmsnmix6) (0.0396972)BALB/c control(bmsnmix7) (0.0272613)DBA control(bmsnmix8) d18 (0.0777965)DBA (bmsnmix9) (119msn) d18 (0.0289236)DBA (120msn) (0.0166279) d18 (0.0239926)DBA (123msn) (0.0644695) controlDBA (0.0384121) control(121msn)DBA control(122msn) BALB/c(0.0526814) (124-5msn) BALB/c (0.0547661)d3 (187msn)BALB/c d3 (0.0372812) (190msn) (0.0270253)BALB/c d3 (191msn) (0.0143461)BALB/c control (0.047668)BALB/c control(198msn)CDF1-p3 control(199msn) (0.0293306)CDF1-p3 (200msn) (177msn) (0.0154479)CDF1-p3 (178msn) (0.014708) (0.016701)CDF1-c (179msn) (0.0222969) CDF1-c(195msn) (0.027586) CDF1-c(196msn) (0.00798457) DBA(197msn) (0.0256756) d3DBA (183msn) (0.0162645) d3DBA (184msn) (0.0249143) d3DBA (185msn) (0.0131104) controlDBA (0.010025) control(201msn)DBA control(202msn) (0.0654066) (203msn) (0.0139727) (0.0494924)[ min ] [ medium ] [ max ] CEM 1 Acaa2 1127.6 2560.6 3441.8 P ( S | Z, I ) = 1.00 Hadhb 3494.9 10294.4 17505.6 Mean Corr = 0.82070 Mecr 317.1 700.0 2349.4 Acadvl 2223.0 3873.4 7904.1 Etfdh 930.9 2716.4 4801.3 Etfb 5141.9 7908.3 12456.1 Hadha 2348.9 4444.6 7444.6 Decr1 2098.5 6022.0 12779.3 CEM 1 + Ndufv1 2907.0 4893.4 7516.7 Top 10 Genes Etfa 3017.0 8930.2 12305.2 Hadh 1863.4 7990.2 14326.2 Atp5a1 9013.5 13640.5 19409.2 Suclg1 2320.9 4900.7 7122.1

Null module Ppt2 Ppt1 GEO Series "GSE13707" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 20 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13707 Status: Public on Nov 22 2008 Title: Effect of an anti-myostatin antibody on skeletal muscle gene expression in mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19141683 Summary & Design: Summary: More than 2,000 genes appear to be upregulated or downregulated in skeletal muscle of mice with constitutive knockout of myostatin (Steelman et al., FASEB J 20:580-2, 2006). This study was done to determine whether inhibition of myostatin activity in mature mice has similar effects on the pattern of gene expression.

Keywords: Differential expression in treated and control mice

Overall design: Ten samples from JA16 antibody-treated mice were compared with 10 samples from saline-treated mice

Background corr dist: KL-Divergence = 0.1434, L1-Distance = 0.0544, L2-Distance = 0.0058, Normal std = 0.4029

1.055 Kernel fit Pairwise Correlations Normal fit

Density 0.527

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_Saline_01Muscle_Saline_02Muscle_Saline_03 (0.0132553)Muscle_Saline_04 (0.0389709)Muscle_Saline_05 (0.0173379)Muscle_Saline_06 (0.0361988)Muscle_Saline_07 (0.0335643)Muscle_Saline_08 (0.0223627)Muscle_Saline_09 (0.112401)Muscle_Saline_10 (0.0542589)Muscle_JA16_01 (0.141685)Muscle_JA16_02 (0.0172998)Muscle_JA16_03 (0.0250564)Muscle_JA16_04 (0.0366186)Muscle_JA16_05 (0.0864195)Muscle_JA16_06 (0.0350159)Muscle_JA16_07 (0.0232554)Muscle_JA16_08 (0.0339266)Muscle_JA16_09 (0.0274751)Muscle_JA16_10 (0.153405) (0.0538801) (0.0376132) [ min ] [ medium ] [ max ] CEM 1 Acaa2 2663.0 6114.6 9352.7 P ( S | Z, I ) = 1.00 Hadhb 5713.8 7688.1 12044.8 Mean Corr = 0.81972 Mecr 206.8 423.1 1622.7 Acadvl 4643.8 8268.1 10835.9 Etfdh 1691.9 2779.9 4876.0 Etfb 5608.2 8409.9 14251.6 Hadha 1536.9 2221.8 3186.6 Decr1 3125.5 4231.5 6698.0 CEM 1 + Ndufv1 7762.1 10979.5 14406.3 Top 10 Genes Etfa 5088.1 6816.8 8823.8 Hadh 5168.7 7256.1 9966.3 Atp5a1 13139.6 16571.8 21529.7 Suclg1 7251.9 9577.2 11582.9

Null module Ppt2 Ppt1 GEO Series "GSE46646" 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=GSE46646 Status: Public on Dec 13 2013 Title: IQGAP2 knockout model of hepatocellular carcinoma Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23951254 Summary & Design: Summary: Whole body knockout mice lacking IQ-motif containing GTPase-activating protein 2 (IQGAP2) develop spontaneous hepatocellular carcinoma (HCC) at the age of 12 months and older (Schmidt et al., 2008). Hepatic transcript expression profiles were obtained for IQGAP2 knockout and wild-type control mice of two age groups, 6- and 24-month-old. Liver samples from 24-month-old IQGAP2 knockout mice were HCC tumors, livers from all other groups were tumor-free. Results provide insights into the potential role of IQGAP2 as a liver-specific tumor suppressor.

Overall design: Transcript profiles of four groups of mouse livers (N = 3 in each group) were compared using Affymetrix GeneChip® Mouse Genome 430 2.0 Array. The groups included livers from 6- and 24-month-old wild-type (WT) mice and 6- and 24-month-old (KO) Iqgap2-/- mice.

Background corr dist: KL-Divergence = 0.1090, L1-Distance = 0.0294, L2-Distance = 0.0016, Normal std = 0.4252

0.938 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

KnockoutKnockout mouseKnockout atmouse 6 months,Knockout atmouse 6 months,Knockout biological atmouse 6 months,Knockout biological atmouse replicate 24Wild-type months,biological atmouse replicate 241 (0.0859696)Wild-type months, biologicalmouseat replicate 242 (0.0843779)Wild-type months, biologicalatmouse 6replicate 3 months, (0.0699379)Wild-type biologicalatmouse 6replicate months,1Wild-type biological(0.0131302) atmouse 6replicate months,2Wild-type biological(0.120543) atmouse replicate 24 3 months, biological(0.0821551) atmouse replicate 241 (0.104055) months, biological at replicate 242 (0.259954) months, biological replicate 3 (0.0488963)[ biologicalmin replicate 1 (0.0228209) ]replicate 2 (0.0450805) 3 (0.0630799)[ medium ] [ max ] CEM 1 Acaa2 12881.8 16704.7 20270.6 P ( S | Z, I ) = 1.00 Hadhb 5389.4 9533.7 10937.6 Mean Corr = 0.83288 Mecr 505.0 954.7 1254.2 Acadvl 11205.5 13464.7 15331.9 Etfdh 4579.2 8030.6 9028.4 Etfb 11706.9 15273.2 17991.4 Hadha 4661.1 7842.1 9304.0 Decr1 2531.8 6778.1 9393.4 CEM 1 + Ndufv1 4899.8 6731.5 7903.0 Top 10 Genes Etfa 10072.2 13547.3 16953.9 Hadh 10324.9 14298.8 17242.3 Atp5a1 13061.6 24031.2 27477.5 Suclg1 4952.4 8486.1 9776.9

Null module Ppt2 Ppt1 GEO Series "GSE38574" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 32 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38574 Status: Public on Jun 08 2012 Title: Gene expression data from Ldlr-/-, Apob100/100, Mttp flox/flox Mx1-Cre mice at different stages of atherosclerosis development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18369455 Summary & Design: Summary: Gene expression profiles from the aortic arch of Ldlr-/-Apob100/100 Mttpflox/flox Mx1-Cre mice at different stages of atherosclerosis development

Overall design: Total RNAs from the aortic arch were collected at different time points during atherosclerosis development (10, 20, 30, 40, 50, and 60 weeks of age), 4-7 mice per time point.

Background corr dist: KL-Divergence = 0.3656, L1-Distance = 0.0660, L2-Distance = 0.0123, Normal std = 0.2582

1.545 Kernel fit Pairwise Correlations Normal fit

Density 0.772

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

Week 10Week 1 aortic 10Week 2 arch aortic 10 (0.0491764)Week 3 arch aortic 10 (0.0111651)Week 4 arch aortic 10 (0.0139735)Week 5 arch aortic 10 (0.0352068)Week 6 arch aortic 10 (0.0268055)Week 7 arch aortic 20 (0.0163225)Week 1 arch aortic 20 (0.0263114)Week 2 arch aortic 20 (0.0262847)Week 3 arch aortic 20 (0.00572897)Week 4 arch aortic 20 (0.0138638)Week 5 arch aortic 30 (0.0479701)Week 1 arch aortic 30 (0.0260076)Week 2 arch aortic 30 (0.0380251)Week 3 arch aortic 30 (0.00740028)Week 4 arch aortic 30 (0.0369318)Week 5 arch aortic 30 (0.0164001)Week 6 arch aortic 40 (0.0972404)Week 1 arch aortic 40 (0.00254113)Week 2 arch aortic 40 (0.0415897)Week 3 arch aortic 40 (0.0362103)Week 4 arch aortic 40 (0.0373904)Week 5 arch aortic 50 (0.0188902)Week 1 arch aortic 50 (0.0179394)Week 2 arch aortic 50 (0.00838562)Week 3 arch aortic 50 (0.0381868)Week 4 arch aortic 50 (0.0310415)Week 5 arch aortic 60 (0.022918)Week 1 arch aortic 60 (0.00825863)Week 2 arch aortic 60 (0.173654)Week 3 arch aortic 60 (0.0164564) 4 arch aortic (0.0360479) arch (0.0156758)[ min ] [ medium ] [ max ] CEM 1 Acaa2 4284.7 11408.9 27302.2 P ( S | Z, I ) = 1.00 Hadhb 10572.6 19997.0 36504.5 Mean Corr = 0.81069 Mecr 536.3 1382.8 3401.0 Acadvl 12516.2 22254.8 39921.0 Etfdh 1636.7 4381.7 10205.9 Etfb 6893.8 16991.9 28995.8 Hadha 715.3 1748.2 8125.3 Decr1 7972.1 15017.6 27575.4 CEM 1 + Ndufv1 10551.6 17178.0 30256.1 Top 10 Genes Etfa 6096.1 11562.0 17347.4 Hadh 7090.2 12914.2 26005.0 Atp5a1 12830.2 19307.6 39776.4 Suclg1 6646.7 18012.9 30765.3

Null module Ppt2 Ppt1 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 (0.0469391)min,MHS+MG, Breplica 30 (0.0572183) min,MHS+MG, C 30replica (0.113985) min,MHS+MG, 30Areplica (0.224786)min,MHS+MG, 240Breplica (0.106438) min,MHS+MG, 240C replica (0.0540066) min,MHS+MG, 240 Areplica (0.0914104)min,MHS+MG, 480 Breplica (0.0205054)min,MHS+MG, 480 Creplica (0.0892996)min, 480 Areplica (0.0669806)min, Breplica (0.0814469) C (0.0469831)[ min ] [ medium ] [ max ] CEM 1 Acaa2 1263.1 2155.5 3613.3 P ( S | Z, I ) = 1.00 Hadhb 3294.0 6005.8 9540.4 Mean Corr = 0.83352 Mecr 519.6 806.4 1282.5 Acadvl 1679.9 2194.7 3008.6 Etfdh 1013.7 1628.1 1943.8 Etfb 2048.4 3693.4 6243.5 Hadha 2911.4 4414.7 6510.8 Decr1 9.0 73.1 216.2 CEM 1 + Ndufv1 4004.3 7592.0 8513.6 Top 10 Genes Etfa 2566.7 4200.2 6216.8 Hadh 1149.2 2493.3 2906.4 Atp5a1 14697.3 19491.2 26039.9 Suclg1 2144.2 4472.7 6747.4

Null module Ppt2 Ppt1 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 (0.0679325) mice (0.170232) (sample3) (knockout) (sample4)] mice (0.162412) mice (0.10667) (sample5)[ (sample6) medium (0.0662217) (0.426532) ] [ max ] CEM 1 Acaa2 5030.7 6398.4 6730.5 P ( S | Z, I ) = 1.00 Hadhb 5783.9 7231.9 7650.8 Mean Corr = 0.90909 Mecr 1044.4 1746.4 2356.0 Acadvl 5779.6 8017.6 8477.5 Etfdh 3098.4 4718.5 5094.1 Etfb 3815.2 5892.2 6538.1 Hadha 1743.4 2802.1 2986.0 Decr1 4236.4 6525.5 6742.3 CEM 1 + Ndufv1 3389.2 4776.6 5460.1 Top 10 Genes Etfa 6009.8 8375.7 8659.6 Hadh 6773.9 8106.7 8477.6 Atp5a1 6125.6 7210.9 7778.6 Suclg1 6333.7 8282.8 8308.7

Null module Ppt2 Ppt1 GEO Series "GSE11684" 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=GSE11684 Status: Public on Nov 10 2009 Title: Expression data from Perk wild-type and knockout mouse liver perfused without or with 2,5-di-tert-butylhydroquinone Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19509078 Summary & Design: Summary: In eukaryotes, regulation of mRNA translation enables a fast, localized and finely tuned expression of gene products. Within the translation process, the first stage of translation initiation is most rigorously modulated by the actions of eukaryotic initiation factors (eIFs) and their associated proteins. These 11 eIFs catalyze the joining of the tRNA, mRNA and rRNA into a functional translation complex. Their activity is influenced by a wide variety of extra- and intracellular signals, ranging from global, such as hormone signaling and unfolded proteins, to specific, such as single amino acid imbalance and iron deficiency. Their action is correspondingly comprehensive, in increasing or decreasing recruitment and translation of most cellular mRNAs, and specialized, in targeting translation of mRNAs with regulatory features such as a 5 terminal oligopyrimidine tract (TOP), upstream open reading frames (uORFs), or an internal ribosomal entry site (IRES). In mammals, two major pathways are linked to targeted mRNA translation. The target of rapamycin (TOR) kinase induces translation of TOP and perhaps other subsets of mRNAs, whereas a family of eIF2 kinases does so with mRNAs containing uORFs or an IRES. TOR targets translation of mRNAs that code for proteins involved in translation, an action compatible with its widely accepted role in regulating cellular growth. The four members of the eIF2 kinase family increase translation of mRNAs coding for stress response proteins such as transcription factors and chaperones. Though all four kinases act on one main substrate, eIF2, published literature demonstrates both common and unique effects by each kinase in response to its specific activating stress. This suggests that the activated eIF2 kinases regulate the translation of both a global and a specific set of mRNAs. Up to now, few studies have attempted to test such a hypothesis; none has been done in mammals.

We use array analysis to determine the global mRNA shift into polysomes following a stress response, and to compare the translational response following activation of GCN2 versus PERK, two of the four eIF2alpha kinases.

Keywords: stress response, comparative genomic

Overall design: Perk wild-type or knockout mouse liver were perfused without or with 2,4-di-tert-butylhydroquinone (tBuHQ) for RNA extraction and hybridization of Affymetrix microarrays. RNA was extracted from unfractionated liver samples and polysome fraction of samples separated on sucrose density gradient. To minimize biological variations, we pooled RNA from two perfused liver samples to use in each array analysis. The conditions were total and polysome fraction of Perk+/+, -tBuHQ or +tBuHQ; total and polysome fraction of Perk-/-, -tBuHQ or +tBuHQ. Each array analysis was done in duplicate.

Background corr dist: KL-Divergence = 0.2098, L1-Distance = 0.0435, L2-Distance = 0.0042, Normal std = 0.3267

1.221 Kernel fit Pairwise Correlations Normal fit

Density 0.611

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

Unfractionated,Unfractionated,Unfractionated, Perk wild-typeUnfractionated, Perk wild-typeUnfractionated, liver,Perk wild-type-tBuHQ,Unfractionated, liver,Perk wild-type-tBuHQ, Unfractionated,biological liver,Perk knockout+tBuHQ, Unfractionated,biological liver,Perk rep1 knockout+tBuHQ,Polysome, biological(0.0405043)Perkliver, rep2 knockout-tBuHQ,Polysome, biological(0.0498166)Perkliver, Perkrep1 knockout-tBuHQ, Polysome,biological liver,(0.0752456)wild-type Perkrep2 +tBuHQ, Polysome,biological liver,(0.0541524)wild-type rep1liver,Perk +tBuHQ,Polysome, biological(0.17285) wild-type-tBuHQ, rep2liver,PerkPolysome, biological(0.0627138) wild-type-tBuHQ, biological liver,Perkrep1Polysome, knockout(0.0253279)+tBuHQ, biological liver,Perkrep2 rep1Polysome, knockout(0.0257251)+tBuHQ, biological(0.0475765)Perkliver, rep2 knockout-tBuHQ, biological(0.0190854)Perkliver, rep1 knockout-tBuHQ, biological liver,(0.0296678) rep2 +tBuHQ, biological liver,(0.0264459) rep1[ +tBuHQ,min biological(0.187846) rep2 biological(0.0792393)] rep1 (0.0897155) rep2[ (0.0140879) medium ] [ max ] CEM 1 Acaa2 12130.2 20962.1 26294.3 P ( S | Z, I ) = 1.00 Hadhb 9710.6 14041.5 19887.0 Mean Corr = 0.79370 Mecr 990.0 1880.5 2665.2 Acadvl 10654.1 19569.5 23515.8 Etfdh 7220.4 10886.3 15703.2 Etfb 13881.8 24573.8 32653.3 Hadha 3962.2 6817.1 8110.8 Decr1 7206.5 11691.4 16577.0 CEM 1 + Ndufv1 7046.6 10803.6 15831.2 Top 10 Genes Etfa 11257.2 18378.1 23882.3 Hadh 10674.0 16133.2 21587.7 Atp5a1 24076.3 31069.3 38684.1 Suclg1 6913.3 12240.1 17374.4

Null module Ppt2 Ppt1