In C. elegans, ablation of germline stem cells (GSCs) extends lifespan, but also increases fat accumulation and alters lipid metabolism, raising the intriguing question of how these effects might be related. Here we show that a lack of GSCs results in a broad transcriptional reprogramming, in which the conserved detoxification regulator SKN-1/Nrf increases stress resistance, proteasome activity, and longevity. SKN-1 also activates diverse lipid metabolism genes and reduces fat storage, thereby alleviating the increased fat accumulation caused by GSC absence. Surprisingly, SKN-1 is activated by signals from this fat, which appears to derive from unconsumed yolk that was produced for reproduction. We conclude that SKN-1 plays a direct role in maintaining lipid homeostasis, in which it is activated by lipids. This SKN-1 function may explain the importance of mammalian Nrf proteins in fatty liver disease, and suggests that particular endogenous or dietary lipids might promote health through SKN-1/Nrf. Overall design: Samples were prepared from ~5,000 synchronized, L1 arrested day-one adult animals cultured at 25°C. Worms were synchronized by sodium hypochlorite (bleach) treatment, as previously described (Porta-de-la-Riva et al., 2012). Bleach solution (9 mL ddH2O; 1 mL 1 N NaOH; 4 mL Clorox bleach) was freshly prepared before each experiment. Worms were bleached for 5 minutes, washed 5x in M9, and arrested at the L1 stage at 25°C in M9 containing 10 µg/mL cholesterol. Feeding RNAi was started at the L1 stage. This approach only partially reduces skn-1 function, but allows analysis of larger samples than would be feasible with skn-1 mutants, which are sterile (Bowerman et al., 1992). Because these animals were not treated with FUdR, the WT adults contained an intact germline and eggs. As is explained in the Results section, we therefore confined our analysis to genes that were overrepresented in glp-1(ts) animals, which lack eggs and most of the germline, and established a high-confidence cutoff for genes that were upregulated by GSC absence as opposed to simply being expressed specifically in somatic tissues. RNA was extracted using the same protocol for qRT-PCR samples. Purified RNA samples were DNase treated and assigned a RIN quality score using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Only matched samples with high RIN scores were sent for sequencing. Single read 50 bp RNA sequencing with poly(A) enrichment was performed at the Dana-Farber Cancer Institute Center for Computational Biology using a HiSeq 2000 (Illumina, San Diego, CA). FASTQ output files were aligned to the WBcel235 (Feb 2014) C. elegans reference genome using STAR (Dobin et al., 2013). These files have been deposited at the Gene Expression Omnibus (GEO) with the accession number GSE63075. Samples averaged 75% mapping of sequence reads to the reference genome. Differential expression analysis was performed using a custom R and Bioconductor RNA-seq pipeline (http://bioinf.wehi.edu.au/RNAseqCaseStudy/) (Gentleman et al., 2004; Anders et al., 2013; R Core Team, 2014). Quantification of mapped reads in the aligned SAM output files was performed using featureCounts, part of the Subread package (Liao et al., 2013, 2014). We filtered out transcripts that didn't have at least one count per million reads in at least two samples. Quantile normalization and estimation of the mean-variance relationship of the log-counts was performed by voom (Law et al., 2014). Linear model fitting, empirical Bayes analysis and differential expression analysis was then conducted using limma (Smyth, 2005). To identify genes that are upregulated in a SKN-1-dependent manner by GSC loss, we sought genes for which glp-1(ts) expression was higher than WT, and for which glp-1(ts);skn-1(-) expression was reduced relative to glp-1(ts). To test for this pattern, if a gene's expression change was higher in the comparison of glp-1(ts) vs. WT and lower in the comparison of glp-1(ts);skn-1(-) vs. glp-1(ts), then we calculated the minimum (in absolute value) of the t-statistics from these two comparisons, and assessed the significance of this statistic by comparing to a null distribution derived by applying this procedure to randomly generated t-statistics. We corrected for multiple testing in this and the differential expression analysis using the false discovery rate (FDR) (Benjamini and Hochberg, 1995). Heatmaps were generated using heatmap.2 in the gplots package (Warnes et al., 2014). Functional annotations and phenotypes were obtained from Wormbase build WS246. SKN-1 transcription factor binding site analysis of hits was conducted with biomaRt, GenomicFeatures, JASPAR, MotifDb, motifStack, MotIV, and Rsamtools (Sandelin et al., 2004; Durinck et al., 2005; Durinck et al., 2009; Lawrence et al., 2013; Ou et al., 2013; Mercier and Gottardo, 2014; Shannon, 2014). JASPAR analysis was performed with the SKN-1 matrix MA0547.1 using 2 kb upstream sequences obtained from Ensembl WBcel235 (Staab et al., 2013). modENCODE SKN-1::GFP ChIP-seq analysis of hits was performed using biomaRt, ChIPpeakAnno, IRanges, and multtest (Durinck et al., 2005; Durinck et al., 2009; Gerstein et al., 2010; Zhu et al., 2010; Niu et al., 2011; Lawrence et al., 2013). SKN-1::GFP ChIP-seq peaks were generated by Michael Snyder's lab. We used the peak data generated from the first 3 larval stages: L1 (modENCODE_2622; GSE25810), L2 (modENCODE_3369), and L3 (modENCODE_3838; GSE48710). Human ortholog matching was performed using Wormbase, Ensembl, and OrthoList (Shaye and Greenwald, 2011). Gene lists were evaluated for functional classification and statistical overrepresentation with Database for Annotation, Visualization and Integrated Discovery (DAVID) version 6.7 (Dennis et al., 2003).
Lipid-mediated regulation of SKN-1/Nrf in response to germ cell absence.
Cell line, Subject
View SamplesThis study was performed to identify gene expression differences in not otherwise specified soft tissue sarcomas (NOS, malignant fibrous histiocytomas) and correlate them to histological findings and the clinical course. RNA was isolated and differential gene expression was analysed by the microarray technique.
Malignant fibrous histiocytoma--pleomorphic sarcoma, NOS gene expression, histology, and clinical course. A pilot study.
Sex
View SamplesGSE2240 contains two different experimental subsets:
Functional profiling of human atrial and ventricular gene expression.
No sample metadata fields
View SamplesWe used microarrays to detail the global program of gene expression during early hESC differentiation to mesendoderm using FBS, with and without RUNX1 depletion.
Transient RUNX1 Expression during Early Mesendodermal Differentiation of hESCs Promotes Epithelial to Mesenchymal Transition through TGFB2 Signaling.
Specimen part, Cell line
View SamplesThe onset and progression of breast cancer are linked to genetic and epigenetic changes that alter the normal programming of cells. Epigenetic modifications of DNA and histones contribute to chromatin structure that results in the activation or repression of gene expression. Several epigenetic pathways have been shown to be highly deregulated in cancer cells. Targeting specific histone modifications represents a viable strategy to prevent oncogenic transformation, tumor growth or metastasis. Methylation of histone H3 lysine 4 has been extensively studied and shown to mark genes for expression; however this residue can also be acetylated and the specific function of this alteration is less well known. To define the relative roles of histone H3 methylation (H3K4me3) and acetylation (H3K4ac) in breast cancer, we determined genomic regions enriched for both marks in normal-like (MCF10A), transformed (MCF7) and metastatic (MDA-MB-231) cells using a genome-wide ChIP-Seq approach. Our data revealed a genome-wide gain of H3K4ac associated with both early and late breast cancer cell phenotypes, while gain of H3K4me3 was predominantly associated with late stage cancer cells. Enrichment of H3K4ac was overrepresented at promoters of genes associated with cancer-related phenotypic traits, such as estrogen response and epithelial-to-mesenchymal transition pathways. Our findings highlight an important role for H3K4ac in predicting epigenetic changes associated with early stages of transformation. In addition, our data provide a valuable resource for understanding epigenetic signatures that correlate with known breast cancer-associated oncogenic pathways. Overall design: RNA-Seq of cell lines MCF10A, MCF7 and MDA-MB-231.
Histone H3 lysine 4 acetylation and methylation dynamics define breast cancer subtypes.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Genomic occupancy of Runx2 with global expression profiling identifies a novel dimension to control of osteoblastogenesis.
Specimen part
View SamplesOsteogenesis is a highly regulated developmental process and continues during the turnover and repair of mature bone. Runx2, the master regulator of osteoblastogenesis, directs a transcription program essential for bone formation through both genetic and epigenetic mechanisms. While individual Runx2 gene targets have been identified, further insights into the broad spectrum of Runx2 functions required for osteogenesis are needed. By performing genome-wide characterization of Runx2 binding at the three major stages of osteoblast differentiation: proliferation, matrix deposition and mineralization, we identified Runx2-dependent regulatory networks driving bone formation. Using chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) over the course of these stages, we discovered close to 80,000 significantly enriched regions of Runx2 binding throughout the mouse genome. These binding events exhibited distinct patterns during osteogenesis, and were associated with proximal promoters as well as a large percentage of Runx2 occupancy in non-promoter regions: upstream, introns, exons, transcription termination site (TTS) regions, and intergenic regions. These peaks were partitioned into clusters that are associated with genes in complex biological processes that support bone formation. Using Affymetrix expression profiling of differentiating osteoblasts depleted of Runx2, we identified novel Runx2 targets including Ezh2, a critical epigenetic regulator; Crabp2, a retinoic acid signaling component; Adamts4 and Tnfrsf19, two remodelers of extracellular matrix. We demonstrated by luciferase assays that these novel biological targets are regulated by Runx2 occupancy at non-promoter regions. Our data establish that Runx2 interactions with chromatin across the genome reveal novel genes, pathways and transcriptional mechanisms that contribute to the regulation of osteoblastogenesis.
Genomic occupancy of Runx2 with global expression profiling identifies a novel dimension to control of osteoblastogenesis.
Specimen part
View SamplesThe goal of this study was to determine the differential expression of specific genes within the papilloma tissues themselves and to characterize the array of host genes that might be important in the pathophysiology of recurrent respiratory papillomatosis.
Immune dysregulation and tumor-associated gene changes in recurrent respiratory papillomatosis: a paired microarray analysis.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Identifying Nuclear Matrix-Attached DNA Across the Genome.
Specimen part, Cell line
View SamplesWe used microarrays to detail the global programme of gene expression during early hESC differentiation to Mesendoderm using FBS.
Lineage-Specific Early Differentiation of Human Embryonic Stem Cells Requires a G2 Cell Cycle Pause.
Sex, Cell line, Time
View Samples