Transcriptomics in ecotoxicology

Abstract

The emergence of analytical tools for high-throughput screening of biomolecules has revolutionized the way in which toxicologists explore the impact of chemicals or other stressors on organisms. One of the most developed and routinely applied high-throughput analysis approaches is transcriptomics, also often referred to as gene expression profiling. The transcriptome represents all RNA molecules, including the messenger RNA (mRNA), which constitutes the building blocks for translating DNA into amino acids to form proteins. The entirety of mRNA is a mirror of the genes that are actively expressed in a cell or an organism at a given time. This in turn allows one to deduce how organisms respond to changes in the external environment. In this article we explore how transcriptomics is currently applied in ecotoxicology and highlight challenges and trends.

Figure

The transcriptome (RNA) is a mirror of the genes that are actively expressed in a cell or organism at a given time, providing information on how organisms respond to chemicals or other stressors in the environment

Fig. 1

Ecotoxicology relies upon the integration of knowledge across different levels of biological organization. Any impact of a chemical on an organism is initiated at the level of the cell, where a chemical elicits a small-scale biomolecular response within a short period of time. Thousands of molecules (e.g. genes, proteins) may be involved in such a response, calling for integrative technologies that allow one to measure the biomolecular response in its entirety. The responses on the cellular level will translate to higher-effect levels on a larger time and spatial scale if they are not compensated by cellular protective mechanisms

Fig. 2

Transcript or gene expression (messenger RNA) analysis can be done in two distinct ways. In the targeted approaches, transcripts are quantified on the basis of prior knowledge of relevant gene sequences by polymerase chain reaction (PCR)-based methods or with reporter systems. These techniques are easy to apply and can be run on many samples (high sample throughput), yet yield information on only a few genes. In contrast, non-targeted approaches do not require a prior selection of genes and provide information for a large or the entire set of transcripts in each sample. The amount of data obtained and the costs involved are a bottleneck to applying transcriptomics for high sample throughput. Transcriptomics can guide the selection of targets and the targeted approaches support the verification of transcriptome data, in particular with regard to transcript regulation in response to chemical concentration and time where many samples are required to achieve the necessary resolution. Abbreviations: cDNA-AFLP complementary DNA–amplified fragment length polymorphism, SAGE serial analysis of gene expression, MPSS massive parallel signature sequencing