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Applications of Toxicogenomic Technologies to Predictive Toxicology and Risk Assessment
FIGURE 2-1 Hierarchical relationships of DNA, RNA, proteins, and metabolites.
criptomics. In contrast to microarrays for transcriptomics, technologies for proteomics and metabolomics are limited by the huge range of analyte concentrations involved (at least six orders of magnitude), because all existing instrumentation favors the detection of more abundant species over those that are less abundant. This fundamental problem limits essentially all proteomic and metabolomic analyses to subsets of the complete collections of proteins and metabolites, respectively. Despite this limitation, proteomic and metabolomic approaches have fundamentally advanced the understanding of the mechanisms of toxicity and adaptation to stress and injury.
The core technologies for toxicogenomics are evolving rapidly, and this is making toxicogenomic approaches increasingly powerful and cost-effective. Several key aspects of technology development will drive toxicogenomics in the next decade:
New sequencing technologies offer the prospect of cost-effective individual whole-genome sequencing and comprehensive genotype analysis.
Array-based whole-genome scanning for variations in individual genes, known as single nucleotide polymorphisms (SNPs), will dramatically increase throughput for genotyping in population studies.
Advances in NMR and MS instrumentation will enable high-sensitivity analyses of complex collections of metabolites and proteins and quantitative metabolomics and proteomics.
New bioinformatic tools, database resources, and statistical methods will integrate data across technology platforms and link phenotypes and toxicogenomic data.