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Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis

BACKGROUND: Diabetic nephropathy (DN) is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape det...

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Autores principales: Cohen, Clemens D., Lindenmeyer, Maja T., Eichinger, Felix, Hahn, Alexander, Seifert, Martin, Moll, Anton G., Schmid, Holger, Kiss, Eva, Gröne, Elisabeth, Gröne, Hermann-Josef, Kretzler, Matthias, Werner, Thomas, Nelson, Peter J.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2493035/
https://www.ncbi.nlm.nih.gov/pubmed/18698414
http://dx.doi.org/10.1371/journal.pone.0002937
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author Cohen, Clemens D.
Lindenmeyer, Maja T.
Eichinger, Felix
Hahn, Alexander
Seifert, Martin
Moll, Anton G.
Schmid, Holger
Kiss, Eva
Gröne, Elisabeth
Gröne, Hermann-Josef
Kretzler, Matthias
Werner, Thomas
Nelson, Peter J.
author_facet Cohen, Clemens D.
Lindenmeyer, Maja T.
Eichinger, Felix
Hahn, Alexander
Seifert, Martin
Moll, Anton G.
Schmid, Holger
Kiss, Eva
Gröne, Elisabeth
Gröne, Hermann-Josef
Kretzler, Matthias
Werner, Thomas
Nelson, Peter J.
author_sort Cohen, Clemens D.
collection PubMed
description BACKGROUND: Diabetic nephropathy (DN) is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A) by standard Robust Multi-array Analysis (RMA). Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID) showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis). This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI) is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.
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spelling pubmed-24930352008-08-13 Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis Cohen, Clemens D. Lindenmeyer, Maja T. Eichinger, Felix Hahn, Alexander Seifert, Martin Moll, Anton G. Schmid, Holger Kiss, Eva Gröne, Elisabeth Gröne, Hermann-Josef Kretzler, Matthias Werner, Thomas Nelson, Peter J. PLoS One Research Article BACKGROUND: Diabetic nephropathy (DN) is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A) by standard Robust Multi-array Analysis (RMA). Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID) showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis). This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI) is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease. Public Library of Science 2008-08-13 /pmc/articles/PMC2493035/ /pubmed/18698414 http://dx.doi.org/10.1371/journal.pone.0002937 Text en Cohen et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Cohen, Clemens D.
Lindenmeyer, Maja T.
Eichinger, Felix
Hahn, Alexander
Seifert, Martin
Moll, Anton G.
Schmid, Holger
Kiss, Eva
Gröne, Elisabeth
Gröne, Hermann-Josef
Kretzler, Matthias
Werner, Thomas
Nelson, Peter J.
Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis
title Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis
title_full Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis
title_fullStr Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis
title_full_unstemmed Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis
title_short Improved Elucidation of Biological Processes Linked to Diabetic Nephropathy by Single Probe-Based Microarray Data Analysis
title_sort improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2493035/
https://www.ncbi.nlm.nih.gov/pubmed/18698414
http://dx.doi.org/10.1371/journal.pone.0002937
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