Literature DB >> 20948521

Comprehensive human adipose tissue mRNA and microRNA endogenous control selection for quantitative real-time-PCR normalization.

Matt J Neville1, Jenny M Collins, Anna L Gloyn, Mark I McCarthy, Fredrik Karpe.   

Abstract

The accurate quantification of cellular and tissue mRNA and microRNA content is reliant upon the selection of stable endogenous control transcripts for normalizing quantitative real-time-PCR (qRT-PCR) data. Using the combination of unbiased and informed approaches and a wide range of human adipose tissues and cells, we sought to identify invariant control transcripts for mRNA and microRNA. A total of 26 mRNA transcript candidates were selected from the literature. MicroRNA candidates were selected from a microRNA-microarray (Agilent, n = 22 tissues), and together with candidates from the literature resulted in 14 different microRNAs. The variability of these mRNA and microRNA transcripts were then tested in a large (n = 180) collection of a variety of human adipose tissues and cell samples. Phosphoglycerate kinase-1 (PGK1) and peptidylprolyl isomerase A (PPIA) were identified as the most stable mRNAs across all tissues and panels. MiR-103 was overall the most stable microRNA transcript across all biological backgrounds. Several proposed and commonly used normalization transcripts were found to be highly variable. We then tested the effect on expression of two established adipocyte-related transcripts (fatty acid binding protein 4 (FABP4) and microRNA-145 (miR-145)), either normalized to the optimal or a commonly used controls transcript. This test clearly indicated that spurious results could arise from using less stable control transcripts for mRNA and microRNA qRT-PCR.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20948521      PMCID: PMC4623139          DOI: 10.1038/oby.2010.257

Source DB:  PubMed          Journal:  Obesity (Silver Spring)        ISSN: 1930-7381            Impact factor:   5.002


  18 in total

1.  A new mathematical model for relative quantification in real-time RT-PCR.

Authors:  M W Pfaffl
Journal:  Nucleic Acids Res       Date:  2001-05-01       Impact factor: 16.971

2.  Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Authors:  K J Livak; T D Schmittgen
Journal:  Methods       Date:  2001-12       Impact factor: 3.608

3.  Evaluation of reference genes for studies of gene expression in human adipose tissue.

Authors:  Britt G Gabrielsson; Louise E Olofsson; Anders Sjögren; Margareta Jernås; Anna Elander; Malin Lönn; Mats Rudemo; Lena M S Carlsson
Journal:  Obes Res       Date:  2005-04

4.  Identification of depot-specific human fat cell progenitors through distinct expression profiles and developmental gene patterns.

Authors:  Tamara Tchkonia; Marc Lenburg; Thomas Thomou; Nino Giorgadze; Garrett Frampton; Tamar Pirtskhalava; Andrew Cartwright; Mark Cartwright; John Flanagan; Iordanes Karagiannides; Norman Gerry; R Armour Forse; Yourka Tchoukalova; Michael D Jensen; Charalabos Pothoulakis; James L Kirkland
Journal:  Am J Physiol Endocrinol Metab       Date:  2006-09-19       Impact factor: 4.310

5.  Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies.

Authors:  Carmela Tricarico; Pamela Pinzani; Simonetta Bianchi; Milena Paglierani; Vito Distante; Mario Pazzagli; Stephen A Bustin; Claudio Orlando
Journal:  Anal Biochem       Date:  2002-10-15       Impact factor: 3.365

6.  IPO8 and FBXL10: new reference genes for gene expression studies in human adipose tissue.

Authors:  Carmen Hurtado del Pozo; Rosa M Calvo; Gregorio Vesperinas-García; Javier Gómez-Ambrosi; Gema Frühbeck; Ramón Corripio-Sánchez; Miguel A Rubio; Maria-Jesus Obregon
Journal:  Obesity (Silver Spring)       Date:  2009-10-29       Impact factor: 5.002

7.  Proteomic analysis of human adipose tissue after rosiglitazone treatment shows coordinated changes to promote glucose uptake.

Authors:  Meftun Ahmed; Matt J Neville; Mariola J Edelmann; Benedikt M Kessler; Fredrik Karpe
Journal:  Obesity (Silver Spring)       Date:  2009-06-25       Impact factor: 5.002

8.  Expression of fatty-acid-handling proteins in human adipose tissue in relation to obesity and insulin resistance.

Authors:  K Gertow; K H Pietiläinen; H Yki-Järvinen; J Kaprio; A Rissanen; P Eriksson; A Hamsten; R M Fisher
Journal:  Diabetologia       Date:  2004-05-28       Impact factor: 10.122

9.  De novo lipogenesis and stearoyl-CoA desaturase are coordinately regulated in the human adipocyte and protect against palmitate-induced cell injury.

Authors:  Jennifer M Collins; Matt J Neville; Michael B Hoppa; Keith N Frayn
Journal:  J Biol Chem       Date:  2009-12-23       Impact factor: 5.157

10.  MicroRNAs induced during adipogenesis that accelerate fat cell development are downregulated in obesity.

Authors:  Huangming Xie; Bing Lim; Harvey F Lodish
Journal:  Diabetes       Date:  2009-02-02       Impact factor: 9.461

View more
  50 in total

Review 1.  The role of microRNAs in adipocyte differentiation.

Authors:  Rong Zhang; Di Wang; Zhuying Xia; Chao Chen; Peng Cheng; Hui Xie; Xianghang Luo
Journal:  Front Med       Date:  2013-04-21       Impact factor: 4.592

2.  De novo lipogenesis in the differentiating human adipocyte can provide all fatty acids necessary for maturation.

Authors:  Jennifer M Collins; Matt J Neville; Katherine E Pinnick; Leanne Hodson; Bente Ruyter; Theo H van Dijk; Dirk-Jan Reijngoud; Mark D Fielding; Keith N Frayn
Journal:  J Lipid Res       Date:  2011-06-15       Impact factor: 5.922

3.  IL-6 and TNF-α induced obesity-related inflammatory response through transcriptional regulation of miR-146b.

Authors:  Chunmei Shi; Lijun Zhu; Xiaohui Chen; Nan Gu; Ling Chen; Lu Zhu; Lei Yang; Lingxia Pang; Xirong Guo; Chenbo Ji; Chunmei Zhang
Journal:  J Interferon Cytokine Res       Date:  2014-01-15       Impact factor: 2.607

4.  SIRT1 and SIRT7 expression in adipose tissues of obese and normal-weight individuals is regulated by microRNAs but not by methylation status.

Authors:  A Kurylowicz; M Owczarz; J Polosak; M I Jonas; W Lisik; M Jonas; A Chmura; M Puzianowska-Kuznicka
Journal:  Int J Obes (Lond)       Date:  2016-08-02       Impact factor: 5.095

5.  Influence of adenovirus 36 seropositivity on the expression of adipogenic microRNAs in obese subjects.

Authors:  Víctor Manríquez; Alvaro Gutierrez; Alexis Morales; Roberto Brito; Monica Pavez; Jorge Sapunar; Luis Fonseca; Víctor Molina; Eugenia Ortiz; Maria Ines Barra; Camila Reimer; Maria Charles; Constance Schneider; Alvaro Cerda
Journal:  Int J Obes (Lond)       Date:  2020-08-22       Impact factor: 5.095

6.  Evaluating the potential of housekeeping genes, rRNAs, snRNAs, microRNAs and circRNAs as reference genes for the estimation of PMI.

Authors:  Chunyan Tu; Tieshuai Du; Chengchen Shao; Zengjia Liu; Liliang Li; Yiwen Shen
Journal:  Forensic Sci Med Pathol       Date:  2018-04-24       Impact factor: 2.007

7.  Modulation of hsa-miR-26b levels following adipokine stimulation.

Authors:  Guangfeng Xu; Chenbo Ji; Chunmei Shi; Hailong Fu; Lingling Zhu; Lu Zhu; Lulian Xu; Ling Chen; Yueying Feng; Yaping Zhao; Xirong Guo
Journal:  Mol Biol Rep       Date:  2012-12-30       Impact factor: 2.316

Review 8.  MicroRNA regulatory networks in human adipose tissue and obesity.

Authors:  Peter Arner; Agné Kulyté
Journal:  Nat Rev Endocrinol       Date:  2015-03-03       Impact factor: 43.330

9.  The biological effects of hsa-miR-1908 in human adipocytes.

Authors:  Lei Yang; Chun-mei Shi; Ling Chen; Ling-xia Pang; Guang-feng Xu; Nan Gu; Li-jun Zhu; Xi-rong Guo; Yu-hui Ni; Chen-bo Ji
Journal:  Mol Biol Rep       Date:  2014-11-25       Impact factor: 2.316

10.  Exploration of the R code-based mathematical model for PMI estimation using profiling of RNA degradation in rat brain tissue at different temperatures.

Authors:  Jianlong Ma; Hui Pan; Yan Zeng; Yehui Lv; Heng Zhang; Aimin Xue; Jieqing Jiang; Kaijun Ma; Long Chen
Journal:  Forensic Sci Med Pathol       Date:  2015-09-12       Impact factor: 2.007

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.