Integrated analysis of transcript level regulation of metabolism during human adipocyte differentiation [ChIP-Seq]
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ABSTRACT: Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network. Illumina HT12 V3.0 microarrays: LXR ligand activation with 1 microM T0901317 for 4 h in SGBS day 10 differentiated adipocytes (6 samples, treatment vs control, in triplicate) This submission represents transcriptome component of study.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network. Illumina Solexa sequencing: Six samples in total. Two ChIP-seq samples were prepared using an antibody against H3K4me3 active TSS chromatin marker from human SGBS preadipocyte and day 10 differentiated SGBS adipocyte cells. From day 10 differentiated SGBS cells additional three samples were prepared using an antibody against PPARg, CEBPa and LXRa to determine their genome-wide binding. One input control sample is included.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network. Illumina HT12 microarrays: Time series of differentiation (20 samples, 7 time points in duplicate or triplicate) This is the Illumina Gene Expression part of the study.
Project description:Here, we have focused on studying the link between metabolic changes driven by the differentiation into mature adipocytes of a human preadipocyte cell line (SGBS) and their regulation, through a combined experimental and computational approach. By collecting data on gene expression, PPARg, CEBPa, LXR and H3K4me3 genome-wide ChIP-seq profles and transcriptome-wide microRNA target identification for miR-27a, miR29a and miR-222, and using constraint-based modeling to estimate metabolic reaction activity, we obtained a comprehensive set of information highlighting how epigenetic, transcriptional and post-transcriptional regulation impacts the metabolic network. Illumina HT12 V4.0 microarrays: Transcriptome analysis 24 hours following overexpression of indicated microRNAs or control siRNAs on indicated time points of differentiation (D0 or D4 + 24 hours) (7 conditions in triplicate, total of 21 samples + siLamin transfection as positive control in duplicate) This submission represents transcriptome component of study.
Project description:Human SGBS preadipocytes were differentiated into adipocytes, and human iPSCs were differentiated into hypothalamic neurons. Cells were collected for ATAC-seq at several differentiation stages. The differentiations were performed in one biological replicate, with two technical replicates (different wells of the differentiation that were also processed individually during library preparation). SGBS Day0: Represents the preadipocyte state. SGBS Day2: Represents immature adipocytes. SGBS Day8: Represents early mature adipocytes. SGBS Day16: Represents mature adipocytes. Hypothalamic Day 12: Represents early hypothalamic neurons. Hypothalamic Day 16: Represents mid hypothalamic neurons. Hypothalamic Day 27: Represents mature hypothalamic neurons.
Project description:Human SGBS preadipocytes were differentiated into adipocytes, and human iPSCs were differentiated into hypothalamic neurons. Cells were collected for RNA-seq at several differentiation stages. The differentiations were performed in one biological replicate, with three technical replicates (different wells of the differentiation that were also processed individually during library preparation). SGBS Day0: Represents the preadipocyte state. SGBS Day2: Represents immature adipocytes. SGBS Day8: Represents early mature adipocytes. SGBS Day16: Represents mature adipocytes. Hypothalamic Day 12: Represents early hypothalamic neurons. Hypothalamic Day 16: Represents mid hypothalamic neurons. Hypothalamic Day 27: Represents mature hypothalamic neurons.