Conventional concepts of points of departure for adverse effects (e.g., NOAEL/LOAEL) do not translate directly to gene expression data. The benchmark dose approach offers a robust alternative method, and has been adapted to transcriptomics. Benchmark Dose is a data driven mathematical approach to determine a dose at which a significant change in response is detected. It is applicable to continuous data such as gene expression data where changes in the abundance of gene transcripts can be detected for all genes expressed in a cell using fluorescence detection (as in microarray technology) or via counts of sequenced transcripts per gene (as with RNA-Seq or BioSpyder’s TempO-Seq ligation system).
Chemicals with different potencies lead to apical effects at different exposure levels (i.e., have different points of departure, POD). It has been similarly established that compounds with lower points of departure also induce transcriptomic changes at lower concentrations. This observation has led to the concept of the transcriptomic point of departure as a proxy for compound toxicity. The impact of a compound on the transcriptome can be quantitatively determined and used to compare potency (Figure). We are using this concept with clients in applications related to compound screening and down-selection. There are also potential applications in product stewardship, such as alternatives assessment.
Key Takeaways:
- Transcriptomic analysis offers greater sensitivity and accuracy in assessing chemical toxicity compared to traditional methods, enabling early detection of molecular changes and identification of affected genes and pathways.
- A variety of techniques, such as RNA sequencing (RNA-Seq), microarray analysis, and quantitative PCR (qPCR), are employed in transcriptomic analysis, providing valuable insights into gene expression levels and transcription factors.
- Transcriptomic biomarkers, which are specific genes or groups of genes indicative of a disease or condition, can help develop targeted treatments and improve drug safety assessments.
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Want to learn more? Take a look at:
- Toward More Efficient Safety Testing Through Development Of An Internal Threshold Of Toxicological Concern
- Using Short-Term In Life Transcriptomic Studies To More Effectively Assess Dose Responses And Modes Of Action
The Role of Transcriptomics in Compound Toxicity Assessment
Discover the significance of transcriptomics in assessing compound toxicity by unveiling molecular-level changes upon chemical exposure.
By analyzing gene expression levels in cells or tissues, we can pinpoint the pathways and mechanisms affected by the chemical. Harness this knowledge to identify potential toxicity indicators and devise more precise toxicity testing methods.
Transcriptomic Points of Departure for Chemical Risk Assessment
Transcriptomic points of departure (PoD) serve as statistical benchmarks to determine the safe exposure levels of a drug. By examining gene expression changes in the presence of a chemical and identifying the lowest concentration causing such alterations, transcriptomic PoD is established.
This method outperforms traditional toxicity measurements, which rely on observing adverse effects on whole organisms, as it boasts greater sensitivity and accuracy.
What Are Transcriptomic Points Of Departure And How Are They Determined?
Transcriptomic points of departure (PoD) enable toxicologists to identify the minimal drug concentration that alters gene expression. This can be achieved by examining mRNA levels within a cell or tissue.
Determining a transcriptome’s PoD involves a multi-step process.
- First, cells or tissues are subjected to varying chemical concentrations in a dose-response experiment.
- Next, RNA is extracted from the cells or tissues to observe gene expression changes.
The PoD represents the lowest concentration that triggers a statistically significant alteration in gene expression. Benchmark dose modeling refines this process by applying a statistical model to the dose-response data.
Contrary to histopathology, transcriptomic PoD offers a more precise approach to measuring exposure. It allows for the detection of early molecular events and the investigation of chemical impacts on genes and networks.
Applications Of Transcriptomic Points Of Departure In Chemical Risk Assessment
When assessing a drug’s potential hazards, transcriptomic PoD offers various applications. It enables the evaluation of chemical toxicity with complex or unknown mechanisms and aids in the identification of potential biomarkers for more targeted toxicity testing.
Furthermore, transcriptomic PoD assists in determining drug safety and establishing more precise exposure limits.
Comparison Of Transcriptomic Points Of Departure With Traditional Toxicity Testing Methods
Compared to traditional toxicity testing methods, transcriptomic points of departure (PoD) offer superior sensitivity and accuracy. Conventional approaches, which typically involve observing the harmful effects of substances on whole organisms like rodents, often fail to detect subtle or early molecular changes induced by a drug.
In contrast, transcriptomic research identifies alterations in gene expression levels upon chemical exposure, even at low doses. This technique uncovers early molecular shifts that might go unnoticed in standard histopathological evaluations.
Moreover, transcriptomic PoD reveals the genes and pathways affected by chemical exposure, providing insights into the chemical’s mode of action and enabling the development of more targeted treatments.
FAQs
What are the methods of transcriptomic analysis?
Transcriptomic analysis methods measure gene expression levels in cells or tissues exposed to chemicals or other stimuli. Popular techniques include microarray analysis, quantitative PCR (qPCR), RNA sequencing (RNA-Seq), and reverse transcription PCR (RT-PCR).
What are the five techniques involved in transcriptome analysis?
Transcriptome analysis encompasses five techniques: microarray analysis, RNA-Seq, serial analysis of gene expression (SAGE), expressed sequence tag (EST) sequencing, and differential display PCR.
What sequencing strategy is used for this transcriptomics?
RNA-Seq is a widely utilized sequencing strategy in transcriptomics, enabling the separation and sequencing of RNA molecules in a sample to identify and measure transcripts.
Which of the following is a widely used method for transcriptome analysis?
RNA sequencing (RNA-Seq) is a common way to study the transcriptome.
What methods identify transcription factors?
Transcription factors can be identified through chromatin immunoprecipitation (ChIP) and yeast one-hybrid (Y1H) assays.
Which one of the following techniques can be used for the analysis of the transcription product?
Reverse transcription PCR (RT-PCR) is a technique employed for analyzing transcription products.
What is a transcriptomic biomarker?
Transcriptomic biomarkers are genes or groups of genes whose expression levels indicate the state of a disease or condition.
What is transcriptomics vs proteomics?
While both transcriptomics and proteomics are -omics fields that study gene expression, proteomics focuses on proteins, and transcriptomics on RNA transcripts.
What is the difference between genomic and transcriptomic data?
Genomic data encompasses an organism’s entire DNA code, whereas transcriptomic data refers to the RNA transcripts expressed in specific cells or tissues.
What is the difference between transcriptomic and metabolomic?
Transcriptomic analysis concentrates on RNA transcripts, while metabolomic analysis targets small molecules called metabolites within a biological system.