Gene expression profiles of Hyalella azteca populations with different pyrethroid sensitivities
Ontology highlight
ABSTRACT:
ORGANISM(S): Hyalella azteca
SUBMITTER: Helen Poynton
PROVIDER: E-GEOD-48943 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:The goal of the study was to investigate gene expression differences in Hyalella azteca exposed to pyrethroid insecticides and compare a laboratory strain to a wild population believed to be resistant to the pesticides. H. azteca reared in the laboratory at the University of CA, Berkeley (UCB) were exposed to cyfluthrin, a commerical pyrethroid insecticide for 96-h. A wild population collected from Grayson Creek (GC), CA was reared in the laboratory for several days and also exposed to cyfluthrin. Toxicity testing revealed that GC animals were two orders of magnitude less sensitive to cyfluthrin compared to the laboratory animals with the no observed effect concentration (NOEC) for UCB = 0.4 ng/L and GC= 170 ng/L. Unexposed, control animals and animals exposed to 0.4 ng/L (GC and UCB) or 170 ng/L cyfluthrin were collected following 96-h treatments. Differences in gene expression were measured using a custom Hyalella azteca microarray. Gene expression profiles revealed that laboratory H. azteca responded to cyfluthrin through differential expression of genes involved in neurological system processes. In contract, H. azteca from Grayson Creek showed a pattern of oxidative stress through the differential expression of glutathione-S-transferases, heat shock proteins, and other genes involved in oxidation-reduction processes.
2013-07-17 | GSE48943 | GEO
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64203 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64202 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64205 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64204 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64207 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64206 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64208 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64209 | biostudies-arrayexpress
Project description:Additional toxicity testing and regulation are needed as the number of compounds chronically released into aquatic coastal environments increases. Decision makers require comprehensive and efficient screening tools to detect adverse biological effects and to identify their cause. Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, identifying sub-lethal organismal responses and identifying contaminant classes underlying observed toxicity. Before transcriptomic information is used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps that impact the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories. Estuarine amphipods were exposed to cyfluthrin-spiked or control sediments for 10 days. Two sample types were generated: the first consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the second type consisted of exposed and control whole body amphipods (WB) from which RNA was extracted by each laboratory. A subset of genes were consistently identified as differentially expressed across all laboratories and sample types. Genes with the highest magnitude of differential expression (> 2 fold) were more likely to be consistently identified as differentially expressed across laboratories. Differentially expressed data had a higher degree of concordance across all laboratories (W = 0.7) in samples with similar RNA quality (Ex) when compared to WB samples (W = 0.5). Our results revealed that several factors can affect data comparability including RNA sample preparation, labeling, instrumentation and technical expertise. First dataset: RNA extracts (Ex) derived from whole bodies of 8 controls and 8 cyfluthrin-exposed amphipods were prepared by one single lab and analyzed (i.e., labeling, microarray hybridization and feature extraction) by all 6 laboratories. Second dataset: Each of the 6 labs received 8 control and 8 cyfluthrin-exposed whole body samples (WB) for RNA extraction and microarrays. Lab C was unable to analyze the WB samples and only submitted data for the Ex samples.
2015-01-26 | E-GEOD-64212 | biostudies-arrayexpress