ArticleEnvironmental science and pollution research international2018
Transcriptional changes measured in rice roots after exposure to arsenite-contaminated sediments.
Article in Environmental science and pollution research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Recent Advances in Transcriptome Analysis Within the Realm of Low Arsenic Rice Breeding.Plants (Basel, Switzerland) · 2025Review
- Pan-transcriptomic Profiling Demarcates Serendipita Indica-Phosphorus Mediated Tolerance Mechanisms in Rice Exposed to Arsenic Toxicity.Rice (New York, N.Y.) · 2023Article
- Arsenic Uptake and Accumulation Mechanisms in Rice Species.Plants (Basel, Switzerland) · 2020Review
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5 authors.
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Abstract
Transcriptional analyses are discussed to provide a deeper understanding of the molecular mechanisms underlying toxic effects. Thus, they can complement classic ecotoxicological test methods and potentially allow the identification of biomarkers associated to the exposure of chemical stressors and or adverse biological effects. This feasibility study intended to identify a set of potential gene expression biomarkers for arsenite-exposure in rice roots that could complement the informative value of an existing sediment-contact test with rice. A sediment-contact test with Oryza sativa with the parameters inhibition of root and shoot elongation as phenotypic endpoints was used as basis. Rice plants were exposed to arsenite-spiked sediments. Transcriptomic changes in response to arsenite were observed by means of cDNA-microarray analysis regarding the whole-transcriptome at two sublethal arsenite concentrations. In order to identify candidate biomarker genes, differentially expressed genes were identified. Arsenite-induced differentially expressed genes were significantly associated with gene ontology (GO)-terms that indicated a general stress response. Of the differentially expressed genes, five genes were selected and their expression was measured at seven arsenite concentrations by means of qPCR in order to obtain their expression profiles. Three candidate biomarker genes showed a dose-dependent upregulation, while two showed no clear dose-dependent expression. The expression of all candidate biomarkers was also assessed in rice plants grown on two arsenic-contaminated natural sediments, but only one biomarker gene showed the expected upregulation.
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