Genome-wide analysis of gene expression during adipogenesis in human adipose-derived stromal cells reveals novel patterns of gene expression during adipocyte differentiation

Ambele, Melvin Anyasi; Dessels, Carla; Durandt, Chrisna

doi:10.1016/j.scr.2016.04.011

Cited by 109 publications

(118 citation statements)

References 40 publications

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“…), which validates its identification in this study since the microarray data in our previous study (Ambele et al. ) that were used here were generated from relatively late passage ASCs. Nfat1 (Nfatc2) (600490) transcriptionally activates the adipocyte‐specific gene aP2 to mediate adipocyte differentiation in 3T3‐L1 cells (Ho et al.…”

Section: Resultssupporting

confidence: 84%

“…To better understand adipogenesis in humans, we have used human adipose‐derived stromal/stem cells (ASCs) to study adipogenic differentiation at multiple time points, ranging from early‐ to late‐stage adipogenesis, to identify novel molecular players that could contribute to our understanding of human adipogenesis across the entire process (Ambele et al. ). A well‐designed 21‐day time‐course of in vitro adipogenic differentiation, using ASCs at a relatively high passage number, in which the rate of differentiation was accurately determined (Durandt et al.…”

Section: Introductionmentioning

confidence: 99%

“…), previously reported the differential expression of genes that encode TFs known to play a role in adipogenesis, such as PPARG , CEBP's , FOXO1A (136533), KLF15 , FOXD1 (601091), E2F7 (612046), FOXP1 (605515), HMGA1 (600701), KLF2 , JUN (165160), KLF16 (606139), GATA6 (601656), KLF12 (607531), FOXM1 (602341) and STAT4 (600558) (Ambele et al. ). In this study, we sought to employ computational methods to conduct an in silico analysis to identify the upstream candidate regulators that might constitute the regulatory network of TFs potentially responsible for driving changes in the expression of these differentially expressed downstream TFs and other genes during adipogenesis in ASCs.…”

Section: Introductionmentioning

confidence: 99%

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Identification of transcription factors potentially involved in human adipogenesis in vitro

Ambele

Pepper

2017

Molec Gen & Gen Med

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BackgroundIncreased adiposity in humans leads to obesity, which is a major risk factor for cardiovascular disease, type 2 diabetes, and cancer. We previously conducted an extensive unbiased in vitro transcriptomic analysis of adipogenesis, using human adipose‐derived stromal cells (ASCs). Here, we have applied computational methods to these data to identify transcription factors (TFs) that constitute the upstream gene regulatory networks potentially, driving adipocyte formation in human ASCs.MethodsWe used Affymetrix Transcription Analysis Console™ v3.0 for calculating differentially expressed genes. MATCH™ and F‐MATCH™ algorithms for TF identification. STRING v10 to predict protein–protein interactions between TFs.ResultsA number of TFs that were reported to have a significant role in adipogenesis, as well as novel TFs that have not previously been described in this context, were identified. Thus, 32 upstream TFs were identified, with most belonging to the C2H2‐type zinc finger and HOX families, which are potentially involved in regulating most of the differentially expressed genes observed during adipocyte differentiation. Furthermore, 17 important upstream TFs were found to have increased regulatory effects on their downstream target genes and were consistently up‐regulated during the differentiation process. A strong hypothetical functional interaction was observed among these TFs, which supports their common role in the downstream regulation of gene expression during adipogenesis.ConclusionOur results support several previous findings on TFs involved in adipogenesis and thereby validate the comprehensive and systematic in silico approach described in this study. In silico analysis also allowed for the identification of novel regulators of adipocyte differentiation.

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Section: Resultssupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of transcription factors potentially involved in human adipogenesis in vitro

Ambele

Pepper

2017

Molec Gen & Gen Med

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“…ZBTB16 also plays a role in the regulation of hematopoietic stem cell fate and homeostasis [17]. In addition, comparative epigenomic and transcriptome studies suggest ZBTB16 gene to be a new candidate modulator of adipogenesis regulating fat development [18,19]. In brown fat and muscle, ZBTB16 has been uncovered regulating thermogenic program [20].…”

Section: Introductionmentioning

confidence: 99%

ZBTB16 Overexpression Enhances White Adipogenesis and Induces Brown-Like Adipocyte Formation of Bovine White Intramuscular Preadipocytes

Wei

Zhang

Zheng

et al. 2018

Cell Physiol Biochem

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Background/Aims: Our study aims to characterize functions of ZBTB16 gene in the process of intramuscular fat (IMF) deposition and metabolism of bovine, thereby providing insights into mechanisms for the use of ZBTB16 in fat management. Methods: Primary preadipocytes derived from bovine IMF tissue were isolated and used as the in vitro cell model. An adenovirus Ad-ZBTB16 was transfected into bovine preadipocytes to overexpress the ZBTB16 gene. By using real-time quantitative PCR (RT-qPCR), western blotting, Oil Red-O staining, glycerol-3-phosphate dehydrogenase (GPDH) activity assay, and cell counting kit-8 (CCK-8) test, adipogenic and proliferative signals in adipocytes were monitored to investigate effects of ZBTB16 on adipogenesis of bovine preadipocytes. Results: After transfection, mRNA and protein levels of ZBTB16 gene were significantly increased. Enhanced ZBTB16 significantly promoted preadipocyte differentiation, as evidenced by accelerated lipid accumulation, enhanced GPDH activity, consistently increased mRNA expressions of adipogenic key transcription factors PPARγ, C/EBPα, FABP4, and ADIPOQ, and markedly increased protein expressions of PPARγ and FABP4. No difference was observed concerning proliferation of preadipocytes after treatment with Ad-ZBTB16. Furthermore, relative mRNA levels of brown adipocyte selective genes (PRDM16, UCP1, Cidea, Cox8b, and PGC-1α) and beige adipocyte selective genes (CD137, TMEM26, and Tbx1) as well as UCP1 protein expression were significantly increased by Ad-ZBTB16. Meanwhile, Ad-ZBTB16 treatment remarkably induced mitochondrial biogenesis and increased relative mitochondrial DNA (mtDNA) copy number in bovine adipocytes. Conclusion: These results suggest that ZBTB16 overexpression can promote white adipogenesis and induce brown-like adipocyte formation for bovine white intramuscular preadipocytes.

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“…In the HRG induced GRN, NFE2, SMARCA4, FOSL2, ZNF263 and MXI1 were found to be the largest junctions. Among these, NFE2 and MXI1 were also found to large hubs, whereas SMARA4, FOSL2 and ZNF263 were previously shown to play important role in mammary cell differentiation727374.…”

Section: Resultsmentioning

confidence: 94%

BGRMI: A method for inferring gene regulatory networks from time-course gene expression data and its application in breast cancer research

Iglesias-Martinez

Kölch

Santra

2016

Sci Rep

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Reconstructing gene regulatory networks (GRNs) from gene expression data is a challenging problem. Existing GRN reconstruction algorithms can be broadly divided into model-free and model–based methods. Typically, model-free methods have high accuracy but are computation intensive whereas model-based methods are fast but less accurate. We propose Bayesian Gene Regulation Model Inference (BGRMI), a model-based method for inferring GRNs from time-course gene expression data. BGRMI uses a Bayesian framework to calculate the probability of different models of GRNs and a heuristic search strategy to scan the model space efficiently. Using benchmark datasets, we show that BGRMI has higher/comparable accuracy at a fraction of the computational cost of competing algorithms. Additionally, it can incorporate prior knowledge of potential gene regulation mechanisms and TF hetero-dimerization processes in the GRN reconstruction process. We incorporated existing ChIP-seq data and known protein interactions between TFs in BGRMI as sources of prior knowledge to reconstruct transcription regulatory networks of proliferating and differentiating breast cancer (BC) cells from time-course gene expression data. The reconstructed networks revealed key driver genes of proliferation and differentiation in BC cells. Some of these genes were not previously studied in the context of BC, but may have clinical relevance in BC treatment.

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Genome-wide analysis of gene expression during adipogenesis in human adipose-derived stromal cells reveals novel patterns of gene expression during adipocyte differentiation

Cited by 109 publications

References 40 publications

Identification of transcription factors potentially involved in human adipogenesis in vitro

Identification of transcription factors potentially involved in human adipogenesis in vitro

ZBTB16 Overexpression Enhances White Adipogenesis and Induces Brown-Like Adipocyte Formation of Bovine White Intramuscular Preadipocytes

BGRMI: A method for inferring gene regulatory networks from time-course gene expression data and its application in breast cancer research

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