a tab delimited flat file (SDRF file) describing the experimental details for human timecourse samples for the standard protocol of the HeliScopeCAGE protocol

List of DRA (http://trace.ddbj.nig.ac.jp/dra/index_e.html) accession numbers of the FANTOM5 samples, sequences and genomic coordinations. Files are in tab-delimited format, which includes * Library ID * FFID * BioSamples accession number * DRA experiment accession number * DRA run accession numbers * DRA analysis accession number for genomic coordination (BAM file) * DRA analysis accession number for CTSS (BED file) * Experiment method (CAGE/RNA-Seq/sRNA-Seq)

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

Sample information (SDRF file) for human, including their details and details of their RNA extractions

The data set includes:1) "Celltype_enriched.txt" files separated by ";" that contain genes significantly enriched in one cell type compared to other three analyzed hWAT cell types according to the analysis described in R markdown file:http://figshare.com/s/509ea9441af442a735acAdjusted p-value <0.05 for all pairwise comparisons, moderated F-statistics p-value <0.05 (from R package/bioconductor package Limma). 2) "Celltype_enriched_collected.txt" files separated by ";". These files contain tables that include mean expression of the gene in a fraction where it is enriched, log fold change (logFC) and adjusted P values (adj.P.val) compared to each of other fractions. Minimal logFC and maximal adj.P.Val against other fractions are included as separate columns to enable easy sorting of the data in search for best expressed, best enriched or most specific genes. 3) R-code used to generate "Celltype_enriched_collected.txt" tables is provided. 4) In addition, a table with 100 highest-ranked genes from each fraction (based on highest logFC_min and lowest adj.P.val_max) is also included ("Selected_enriched_genes_all_fractions" - separated by tab).

List of DRA (http://trace.ddbj.nig.ac.jp/dra/index_e.html) accession numbers of the FANTOM5 samples, sequences and genomic coordinations. Files are in tab-delimited format, which includes * Library ID * FFID * BioSamples accession number * DRA experiment accession number * DRA run accession numbers * DRA analysis accession number for genomic coordination (BAM file) * DRA analysis accession number for CTSS (BED file) * Experiment method (CAGE/RNA-Seq/sRNA-Seq)

Although the mechanisms linking obesity to insulin resistance (IR) and type 2 diabetes (T2D) are not entirely understood, it is likely that alterations of adipose tissue function are involved. The aim of this study was to identify new genes controlling insulin sensitivity in adipocytes from obese women with either insulin resistant (OIR) or sensitive (OIS) adipocytes. Insulin sensitivity was first determined by measuring lipogenesis in isolated adipocytes from abdominal subcutaneous white adipose tissue (WAT) in a large observational study. Lipogenesis was measured under conditions where glucose transport was the rate limiting step and reflects in vivo insulin sensitivity. We then performed microarray-based transcriptome profiling on subcutaneous WAT specimen from a subgroup of 9 lean, 21 OIS and 18 obese OIR women. We could identify 432 genes that were differentially expressed between the OIR and OIS group (FDR ≤5%). These genes are enriched in pathways related to glucose and amino acid metabolism, cellular respiration, and insulin signaling, and include genes such as SLC2A4, AKT2, as well as genes coding for enzymes in the mitochondria respiratory chain. Two IR-associated genes, KLF15 encoding a transcription factor and SLC25A10 encoding a dicarboxylate carrier, were selected for functional evaluation in adipocytes differentiated in vitro. Knockdown of KLF15 and SLC25A10 using siRNA inhibited insulin-stimulated lipogenesis in adipocytes. Transcriptome profiling of siRNA-treated cells suggested that KLF15 might control insulin sensitivity by influencing expression of PPARG, PXMP2, AQP7, LPL and genes in the mitochondrial respiratory chain. Knockdown of SLC25A10 had only modest impact on the transcriptome, suggesting that it might directly influence insulin sensitivity in adipocytes independently of transcription due to its important role in fatty acid synthesis. In summary, this study identifies novel genes associated with insulin sensitivity in adipocytes in women independently of obesity. KFL15 and SLC25A10 are inhibitors of insulin-stimulated lipogenesis under conditions when glucose transport is the rate limiting step.

CAGE peak based expression table (RLE normalized) for human samples

White adipose tissue (WAT) can develop into several phenotypes with different pathophysiological impact on type 2 diabetes. To better understand the adipogenic process, the transcriptional events that occur during in vitro differentiation of human adipocytes were investigated and the findings linked to WAT phenotypes. Single-molecule transcriptional profiling provided a detailed map of the expressional changes of genes, enhancers, and long noncoding RNAs, where different types of transcripts share common dynamics during differentiation. Common signatures include early downregulated, transient, and late induced transcripts, all of which are linked to distinct developmental processes during adipogenesis. Enhancers expressed during adipogenesis overlap significantly with genetic variants associated with WAT distribution. Transiently expressed and late induced genes are associated with hypertrophic WAT (few but large fat cells), a phenotype closely linked to insulin resistance and type 2 diabetes. Transcription factors that are expressed early or transiently affect differentiation and adipocyte function and are controlled by several well-known upstream regulators such as glucocorticosteroids, insulin, cAMP, and thyroid hormones. Taken together, our results suggest a complex but highly coordinated regulation of adipogenesis.

a tab delimited flat file (SDRF file) describing the experimental details for mouse tissue samples for the low quantity version of the HeliScopeCAGE protocol

a tab delimited flat file (SDRF file) describing the experimental details for mouse quality control samples for the standard protocol of the HeliScopeCAGE protocol

Regulation of adipose tissue stem cells (ASCs) and adipogenesis impact the development of excess body fat-related metabolic complications. Animal studies have suggested the presence of distinct subtypes of ASCs with different differentiation properties. In addition, ASCs are becoming the biggest source of mesenchymal stem cells used in therapies, which requires deep characterization. Using unbiased single cell transcriptomics we aimed to characterize ASC populations in human subcutaneous white adipose tissue (scWAT). The transcriptomes of 574 single cells from the WAT total stroma vascular fraction (SVF) of four healthy women were analyzed by clustering and t-distributed stochastic neighbor embedding visualization. The identified cell populations were then mapped to cell types present in WAT using data from gene expression microarray profiling of flow cytometry-sorted SVF. Cells clustered into four distinct populations: three adipose tissue-resident macrophage subtypes and one large, homogeneous population of ASCs. While pseudotemporal ordering analysis indicated that the ASCs were in slightly different differentiation stages, the differences in gene expression were small and could not distinguish distinct ASC subtypes. Altogether, in healthy individuals, ASCs seem to constitute a single homogeneous cell population that cannot be subdivided by single cell transcriptomics, suggesting a common origin for human adipocytes in scWAT.

Genes used for first-level (Supplemental table 1) and second-level (Supplemental table 2) clustering. (XLSX 132 kb)

Sample information (SDRF file) for human, including their details and details of their RNA extractions

Current worldwide figures suggest that obesity is pandemic. Understanding the underlying molecular mechanisms would help develop viable anti-obesity therapies. Here, we assess the influence of obesity-induced inflammation on white adipocyte cyclic guanosine monophosphate (cGMP) signaling, which is beneficial for adipocyte differentiation and thermogenesis. We find that murine gonadal and not inguinal fat is prone to obesity-induced inflammation. Correspondingly, the cGMP cascade is dysregulated in gonadal but not in inguinal fat of obese mice. Analysis of two independent human cohorts reveals a defective cGMP pathway only in visceral fat of obese subjects. Congruently, cGMP signaling is dysregulated in tumor necrosis factor α (TNF-α)-treated primary white adipocytes. TNF-α-mediated suppression of sGCβ1 is mediated via NF-κB, whereas PKG is repressed by JNK signaling. Additionally, TNF-α-activated JNK signaling suppresses PPARγ and aP2. Taken together, the intensity of obesity-induced inflammation dictates the amplitude of cGMP signaling dysregulation in white adipocytes through distinct pathways.

Obesity affects gene expression and metabolism of white adipose tissue (WAT), which results in insulin resistance (IR) and type 2 diabetes. However, WAT is a heterogeneous organ containing many cell types that might respond differently to obesity-induced changes. We performed flow cytometry sorting and RNA expression profiling by microarray of major WAT cell types (adipocytes, CD45-/CD31-/CD34+ progenitors, CD45+/CD14+ monocytes/ macrophages, CD45+/CD14- leukocytes), which allowed us to identify genes enriched in specific cell fractions. Additionally, we included adipocytes and adipocyte progenitor cells obtained from lean and obese individuals. Taken together, we provide a detailed gene expression atlas of major human adipose tissue resident cell types for clinical/basic research and using this dataset provide lists of cell-type specific genes that are of interest for metabolic research.

Context: Cardiometabolic complications in obesity may be linked to white adipose tissue (WAT) dysfunction. Transcriptomic studies of Sc WAT have reported that CCL18, encoding the CC chemokine ligand 18 (CCL18), is increased in obesity/insulin resistance but its functional role is unknown.Objective: Our objectives were to determine if CCL18 is secreted from Sc WAT and if secreted and/or serum levels associate with metabolic phenotypes. We also planned to define the primary cellular source and if CCL18 exerts effects on adipocytes.Design: This is a cohort study.Setting: The study took place in an outpatient academic clinic.Participants: A total of 130 obese women scheduled for bariatric surgery and 35 nonobese controls were included.Methods: Insulin sensitivity was assessed by hyperinsulinemic euglycemic clamp or homeostasis model assessment. CCL18 was analyzed in serum/WAT incubates by ELISA. Effects of recombinant CCL18 was determined in cultures of primary human adipocytes and the monocyte cell line THP-1 differentiated into M0/M1/M2 macrophages.Main Outcome Measure: Association with metabolic risk factors was measured.Results: CCL18 was secreted from WAT and the levels correlated positively with insulin resistance, Adult Treatment Panel III risk score and plasma triglycerides, independent of body mass index and better than other established adipocytokines. In 80 obese women, S-CCL18 levels were significantly higher in insulin resistant compared with insulin sensitive subjects. In WAT CCL18 mRNA was expressed in macrophages and correlated positively with immune-related genes, particularly those enriched in M2 macrophages. While CCL18 increased cyto-/chemokine expression in M0/M2-THP-1 cells, human adipocytes showed no responses in vitro.Conclusions: Circulating and WAT-secreted CCL18 correlates with insulin resistance and metabolic risk score. Because CCL18 is macrophage-specific and associates with adipose immune gene expression, it may constitute a marker of WAT inflammation.

OBJECTIVE Although long-term weight regain may occur after bariatric surgery, many patients are protected against relapse or development of type 2 diabetes. The study objective was to investigate whether this involves beneficial changes in adipose function. RESEARCH DESIGN AND METHODS Forty-nine obese women were investigated before and 2 and 5 years after Roux-en-Y gastric bypass (RYGB). At the 5-year follow-up, 30 subjects were pairwise matched for BMI and age to 30 control women. Clinical parameters and fine-needle biopsies from subcutaneous abdominal adipose tissue were obtained; fat cell size and number, lipolysis, adiponectin, and proinflammatory protein secretion were determined. RESULTS After 2 years, BMI decreased from 43 to 29 kg/m2, which was accompanied by improvements in insulin sensitivity (HOMA of insulin resistance [HOMA-IR]), increased circulating and adipose secreted adiponectin, and decreased adipose lipolysis and fat cell size but no change in adipocyte number. Between 2 and 5 years after surgery, BMI had increased to 31 kg/m2. This was associated with slightly increased HOMA-IR and unaltered circulating or adipose secreted adiponectin but higher secretion of tumor necrosis factor-α and increased lipolysis and number of fat cells but no change in adipocyte size. All these parameters, except lipolysis, were significantly more favorable compared with those in matched control subjects. Furthermore, the relationship between HOMA-IR and circulating adiponectin was less steep than in control subjects. CONCLUSIONS RYGB improves long-term insulin sensitivity and adipose phenotypes beyond the control state despite weight regain. Postoperative beneficial alterations in adipose function may be involved in the diabetes-protective effect of bariatric surgery.

Although it is generally accepted that cellular differentiation requires changes to transcriptional networks, dynamic regulation of promoters and enhancers at specific sets of genes has not been previously studied en masse. Exploiting the fact that active promoters and enhancers are transcribed, we simultaneously measured their activity in 19 human and 14 mouse time courses covering a wide range of cell types and biological stimuli. Enhancer RNAs, then messenger RNAs encoding transcription factors, dominated the earliest responses. Binding sites for key lineage transcription factors were simultaneously overrepresented in enhancers and promoters active in each cellular system. Our data support a highly generalizable model in which enhancer transcription is the earliest event in successive waves of transcriptional change during cellular differentiation or activation.