Gene expression analysis reveals a gene set discriminatory to different metals in soil.

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Environmental pollution is a worldwide problem, and metals are the largest group of contaminants in soil. Microarray toxicogenomic studies with ecologically relevant organisms, such as springtails, supplement traditional ecotoxicological research but are presently rather descriptive. Classifier analysis, a more analytical application of the microarray technique, is able to predict biological classes of unknown samples. We used the uncorrelated shrunken centroid method to classify gene expression profiles of the springtail Folsomia candida exposed to soil spiked with six different metals (barium, cadmium, cobalt, chromium, lead, and zinc). We identified a gene set (classifier) of 188 genes that can discriminate between six different metals present in soil, which allowed us to predict the correct classes for samples of an independent test set with an accuracy of 83% (error rate = 0.17). This study shows further that in order to apply classifier analysis to actual contaminated field soil samples, more insight and information is needed on the transcriptional responses of soil organisms to different soil types (properties) and mixtures of contaminants. © The Author 2010. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.
Original languageEnglish
Pages (from-to)34-40
JournalToxicological Sciences
Volume115
Issue number1
DOIs
Publication statusPublished - 2010

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Gene expression
Soil
Genes
Metals
Soils
Gene Expression
Classifiers
Microarrays
Toxicogenetics
Impurities
Environmental Pollution
Candida
Chromium
Barium
Cobalt
Cadmium
Transcriptome
Zinc
Pollution
Research

Cite this

@article{75f07db0ea9c4bc38b276a9e3c217678,
title = "Gene expression analysis reveals a gene set discriminatory to different metals in soil.",
abstract = "Environmental pollution is a worldwide problem, and metals are the largest group of contaminants in soil. Microarray toxicogenomic studies with ecologically relevant organisms, such as springtails, supplement traditional ecotoxicological research but are presently rather descriptive. Classifier analysis, a more analytical application of the microarray technique, is able to predict biological classes of unknown samples. We used the uncorrelated shrunken centroid method to classify gene expression profiles of the springtail Folsomia candida exposed to soil spiked with six different metals (barium, cadmium, cobalt, chromium, lead, and zinc). We identified a gene set (classifier) of 188 genes that can discriminate between six different metals present in soil, which allowed us to predict the correct classes for samples of an independent test set with an accuracy of 83{\%} (error rate = 0.17). This study shows further that in order to apply classifier analysis to actual contaminated field soil samples, more insight and information is needed on the transcriptional responses of soil organisms to different soil types (properties) and mixtures of contaminants. {\circledC} The Author 2010. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.",
author = "B. Nota and R.A. Verweij and D. Molenaar and B. Ylstra and {van Straalen}, N.M. and D. Roelofs",
year = "2010",
doi = "10.1093/toxsci/kfq043",
language = "English",
volume = "115",
pages = "34--40",
journal = "Toxicological Sciences",
issn = "1096-6080",
publisher = "Oxford University Press",
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}

Gene expression analysis reveals a gene set discriminatory to different metals in soil. / Nota, B.; Verweij, R.A.; Molenaar, D.; Ylstra, B.; van Straalen, N.M.; Roelofs, D.

In: Toxicological Sciences, Vol. 115, No. 1, 2010, p. 34-40.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Gene expression analysis reveals a gene set discriminatory to different metals in soil.

AU - Nota, B.

AU - Verweij, R.A.

AU - Molenaar, D.

AU - Ylstra, B.

AU - van Straalen, N.M.

AU - Roelofs, D.

PY - 2010

Y1 - 2010

N2 - Environmental pollution is a worldwide problem, and metals are the largest group of contaminants in soil. Microarray toxicogenomic studies with ecologically relevant organisms, such as springtails, supplement traditional ecotoxicological research but are presently rather descriptive. Classifier analysis, a more analytical application of the microarray technique, is able to predict biological classes of unknown samples. We used the uncorrelated shrunken centroid method to classify gene expression profiles of the springtail Folsomia candida exposed to soil spiked with six different metals (barium, cadmium, cobalt, chromium, lead, and zinc). We identified a gene set (classifier) of 188 genes that can discriminate between six different metals present in soil, which allowed us to predict the correct classes for samples of an independent test set with an accuracy of 83% (error rate = 0.17). This study shows further that in order to apply classifier analysis to actual contaminated field soil samples, more insight and information is needed on the transcriptional responses of soil organisms to different soil types (properties) and mixtures of contaminants. © The Author 2010. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.

AB - Environmental pollution is a worldwide problem, and metals are the largest group of contaminants in soil. Microarray toxicogenomic studies with ecologically relevant organisms, such as springtails, supplement traditional ecotoxicological research but are presently rather descriptive. Classifier analysis, a more analytical application of the microarray technique, is able to predict biological classes of unknown samples. We used the uncorrelated shrunken centroid method to classify gene expression profiles of the springtail Folsomia candida exposed to soil spiked with six different metals (barium, cadmium, cobalt, chromium, lead, and zinc). We identified a gene set (classifier) of 188 genes that can discriminate between six different metals present in soil, which allowed us to predict the correct classes for samples of an independent test set with an accuracy of 83% (error rate = 0.17). This study shows further that in order to apply classifier analysis to actual contaminated field soil samples, more insight and information is needed on the transcriptional responses of soil organisms to different soil types (properties) and mixtures of contaminants. © The Author 2010. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.

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DO - 10.1093/toxsci/kfq043

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EP - 40

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