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Detection and Quantification of GPCR mRNA: An Assessment and Implications of Data from High-Content Methods
[Image: see text] G protein-coupled receptors (GPCRs) are the largest family of membrane receptors and targets for approved drugs. The analysis of GPCR expression is, thus, important for drug discovery and typically involves messenger RNA (mRNA)-based methods. We compared transcriptomic complementar...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6796235/ https://www.ncbi.nlm.nih.gov/pubmed/31646252 http://dx.doi.org/10.1021/acsomega.9b02811 |
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author | Sriram, Krishna Wiley, Shu Z. Moyung, Kevin Gorr, Matthew W. Salmerón, Cristina Marucut, Jordin French, Randall P. Lowy, Andrew M. Insel, Paul A. |
author_facet | Sriram, Krishna Wiley, Shu Z. Moyung, Kevin Gorr, Matthew W. Salmerón, Cristina Marucut, Jordin French, Randall P. Lowy, Andrew M. Insel, Paul A. |
author_sort | Sriram, Krishna |
collection | PubMed |
description | [Image: see text] G protein-coupled receptors (GPCRs) are the largest family of membrane receptors and targets for approved drugs. The analysis of GPCR expression is, thus, important for drug discovery and typically involves messenger RNA (mRNA)-based methods. We compared transcriptomic complementary DNA (cDNA) (Affymetrix) microarrays, RNA sequencing (RNA-seq), and quantitative polymerase chain reaction (qPCR)-based TaqMan arrays for their ability to detect and quantify expression of endoGPCRs (nonchemosensory GPCRs with endogenous agonists). In human pancreatic cancer-associated fibroblasts, RNA-seq and TaqMan arrays yielded closely correlated values for GPCR number (∼100) and expression levels, as validated by independent qPCR. By contrast, the microarrays failed to identify ∼30 such GPCRs and generated data poorly correlated with results from those methods. RNA-seq and TaqMan arrays also yielded comparable results for GPCRs in human cardiac fibroblasts, pancreatic stellate cells, cancer cell lines, and pulmonary arterial smooth muscle cells. The magnitude of mRNA expression for several Gq/11-coupled GPCRs predicted cytosolic calcium increase and cell migration by cognate agonists. RNA-seq also revealed splice variants for endoGPCRs. Thus, RNA-seq and qPCR-based arrays are much better suited than transcriptomic cDNA microarrays for assessing GPCR expression and can yield results predictive of functional responses, findings that have implications for GPCR biology and drug discovery. |
format | Online Article Text |
id | pubmed-6796235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-67962352019-10-23 Detection and Quantification of GPCR mRNA: An Assessment and Implications of Data from High-Content Methods Sriram, Krishna Wiley, Shu Z. Moyung, Kevin Gorr, Matthew W. Salmerón, Cristina Marucut, Jordin French, Randall P. Lowy, Andrew M. Insel, Paul A. ACS Omega [Image: see text] G protein-coupled receptors (GPCRs) are the largest family of membrane receptors and targets for approved drugs. The analysis of GPCR expression is, thus, important for drug discovery and typically involves messenger RNA (mRNA)-based methods. We compared transcriptomic complementary DNA (cDNA) (Affymetrix) microarrays, RNA sequencing (RNA-seq), and quantitative polymerase chain reaction (qPCR)-based TaqMan arrays for their ability to detect and quantify expression of endoGPCRs (nonchemosensory GPCRs with endogenous agonists). In human pancreatic cancer-associated fibroblasts, RNA-seq and TaqMan arrays yielded closely correlated values for GPCR number (∼100) and expression levels, as validated by independent qPCR. By contrast, the microarrays failed to identify ∼30 such GPCRs and generated data poorly correlated with results from those methods. RNA-seq and TaqMan arrays also yielded comparable results for GPCRs in human cardiac fibroblasts, pancreatic stellate cells, cancer cell lines, and pulmonary arterial smooth muscle cells. The magnitude of mRNA expression for several Gq/11-coupled GPCRs predicted cytosolic calcium increase and cell migration by cognate agonists. RNA-seq also revealed splice variants for endoGPCRs. Thus, RNA-seq and qPCR-based arrays are much better suited than transcriptomic cDNA microarrays for assessing GPCR expression and can yield results predictive of functional responses, findings that have implications for GPCR biology and drug discovery. American Chemical Society 2019-09-30 /pmc/articles/PMC6796235/ /pubmed/31646252 http://dx.doi.org/10.1021/acsomega.9b02811 Text en Copyright © 2019 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Sriram, Krishna Wiley, Shu Z. Moyung, Kevin Gorr, Matthew W. Salmerón, Cristina Marucut, Jordin French, Randall P. Lowy, Andrew M. Insel, Paul A. Detection and Quantification of GPCR mRNA: An Assessment and Implications of Data from High-Content Methods |
title | Detection and Quantification of GPCR mRNA: An Assessment
and Implications of Data from High-Content Methods |
title_full | Detection and Quantification of GPCR mRNA: An Assessment
and Implications of Data from High-Content Methods |
title_fullStr | Detection and Quantification of GPCR mRNA: An Assessment
and Implications of Data from High-Content Methods |
title_full_unstemmed | Detection and Quantification of GPCR mRNA: An Assessment
and Implications of Data from High-Content Methods |
title_short | Detection and Quantification of GPCR mRNA: An Assessment
and Implications of Data from High-Content Methods |
title_sort | detection and quantification of gpcr mrna: an assessment
and implications of data from high-content methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6796235/ https://www.ncbi.nlm.nih.gov/pubmed/31646252 http://dx.doi.org/10.1021/acsomega.9b02811 |
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