第16回千葉カルシウム代謝研究会

Gene ontology term enrichments for RNA-Seq data from differentiated TSC2 deletion cell lines and microarray data of patient SEGAs (related to Fig. 2f). (XLSX 27.7 kb

Additional file 1: of Boolean regulatory network reconstruction using literature based knowledge with a genetic algorithm optimization method

Methods. Detailed description of the methods. (PDF 1329 kb

Epithelial cell injury characterization (upper panel) and fibroblast activation (lower panel) in an <i>in vitro</i> reconstructed microenvironment.

<p>(<b>A</b>) Scheme of the reconstructed microenvironment and workflow analysis of the cisplatin-injured proximal tubular epithelial cells HKC-8 cells and of the WS-1 dermal fibroblasts. (<b>B</b>) Cell viability and (<b>C</b>) apoptosis analysis. Cisplatin-treated proximal tubular epithelial cells HKC-8 cells showed decreased cell viability and increased apoptosis. (<b>D</b>). Cell cycle analysis showed that HKC-8 cells treated with cisplatin high dose (40 µM) were blocked in G2/M phase at 24, 48 and 72 h, whereas cells treated with the low dose (20 µM) reverted at 72 h to a condition similar to control. Cytokine release analysis with (<b>E</b>) IL-6 and (<b>F</b>) RANTES levels. Cisplatin-treated HKC-8 cells produced increased amounts of IL-6 and RANTES. (<b>G</b>) Gene-level analysis results for selected genes showing a stronger response to Ciplatin high dose (CisHigh) than to Ciplatin low dose (CisLow). Expression levels on a logarithmic scale are shown as a heat map: no detectable expression is indicated by black color, increasing expression levels are indicated by brighter shades of yellow. Note that several genes show up twice in the figure because they are represented by multiple probes on the Illumina chip. While the measured values do not necessarily agree, the overall trend of up-regulation is the same. (<b>H</b>) Gene-level analysis was complemented by a network-level approach using Gene Set Enrichment Analysis against the Pathway Commons collection of gene regulatory networks (<a href="http://www.pathwaycommons.org" target="_blank">www.pathwaycommons.org</a>). Cisplatin treated cells (L: low, H: high) were compared to controls (C), and renal clear cell carcinoma (RCC) cells were compared to “normal adjacent” tissue (GEO accession number GSE781; as this data set is based on a different expression array technology, we did not compare expression levels of individual genes for this analysis). The heat map shows FDR-corrected q values on a logarithmic scale for up-regulated (red shades) and down-regulated networks (green shades), black indicating no change. An FDR-corrected q value of 0.01 corresponds to an absolute score of 4.6 on this scale. Please, note that the RCC dataset (last column) does not imply any involvement of the networks shown here. (<b>I–L</b>) RT-PCR analysis and mRNA levels of the (<b>I</b>) <i>Acta2</i> gene (encoding alpha smooth muscle actin) (<b>J</b>) <i>TGF-b1</i>gene (encoding transforming growth factor beta 1), (<b>K</b>) <i>COL1A1</i> gene (encoding collagen-1α1) and (<b>L</b>) ID-1 gene (encoding Inhibitor of differentiation 1). Retrieved WS-1 dermal fibroblasts showed increased level for key fibrotic markers α-SMA, TGF-β1 and Collagen 1α1 and decreased level of ID-1 when epithelial cells HK-C8 cells were layered on top. Gene expression profile for the same gene in absence of HK-C8 cells can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056575#pone.0056575.s002" target="_blank">Figure S2B</a>-E. n.s. = not statistically different, * = p<0.05, ** = p<0.001.</p

Additional file 4 of Detect tissue heterogeneity in gene expression data with BioQC

Supplementary Document 3. This document can also be assessed on the BioQC website under [29] respectively. (ZIP 325 kb

Additional file 8: Table S5. of Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model

Gene set enrichment analysis of ribosome profiling data (related to Fig. 3d). (XLSX 11.1 kb

Additional file 9: Table S6. of Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model

Gene ontology term enrichments for ribosome profiling data (related to Fig. 3f). (XLSX 11 kb

Additional file 2: Figure S2. of Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model

Loss of TSC2 triggers expression changes related to inflammatory response, metabolism, and neuronal function. (PDF 1.15 mb

Additional file 1: Figure S1. of Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model

Deregulated expression of neuronal and glial markers in the absence of TSC2. (PDF 2.73 mb

Additional file 10: Table S7. of Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model

RNA-Seq and ribosome profiling data of differentiated TSC2 wild-type and homozygous deletion cell lines treated with mTOR inhibitors (related to Fig. 4). (XLSB 7.52 mb

Additional file 11: Table S8. of Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model

Gene sets and associated genes that show after mTOR treatment a reversal of the change in expression detected in untreated TSC2 deletion cells (related to Fig. 4b). (XLSX 25.8 kb