Method for predicting embryonic development toxicity of chemicals based on dose-effect simplified transcriptome

Abstract

The invention discloses a calculation method for predicting the embryonic development toxicity of chemicals based on dose-effect simplified transcriptome, and belongs to the field of predictive toxicology. According to the calculation method, high-throughput testing data is systematically integrated for grading calculation to predict the embryonic toxicity of the chemicals and identify the key toxicity mechanism of the chemicals. In the calculation method, relevant evidence between key events (KE) is taken as the basis, and the high-throughput molecular testing data like the dose-effect simplified transcriptome is utilized to conduct activation grading calculation on an adverse outcome pathway (AOP) related to zebra fish development. The calculation method is more efficient and sensitive than a traditional embryonic development toxicity test and realizes efficient toxicity prediction based on the chemical toxication mechanism; by determining the influence of the low-dose chemicals on the early embryo transcriptional level, the developmental toxicity effect in a longer life stage can be predicted, the toxication mechanism of the chemicals can be identified, and the chemicals with different toxication modes can be distinguished.

Description

technical field [0001] The invention belongs to the field of predictive toxicology, and in particular relates to a method for predicting embryonic developmental toxicity of chemicals based on dose-effect simplified transcriptome. Background technique [0002] Chemical risk management urgently needs a method to accurately predict chemical toxicity based on the mechanism of toxicity by systematically integrating high-throughput test data. There are many kinds of chemicals in the world, and the number of new chemicals is increasing rapidly. The inefficient traditional in vivo toxicity testing methods are far from meeting the needs of current chemical testing, and there is a lack of toxicity data for a large number of chemicals. In order to solve this difficult problem of chemical management, alternative testing methods have developed rapidly in recent years, such as in vitro testing and omics, which can provide rich information on the molecular mechanism of chemical toxicity. ...

AI Technical Summary

Problems solved by technology

[0008] Aiming at the problem that the prediction accuracy of chemical toxicity in the prior art is not high, and it is impossible to distinguish different toxicity model chemicals, this study aims to establish a way to integrate high-throughput test data to score zebrafish development-related AOPs The method can not only accurately predict the toxic effects of chemicals on zebrafish embryonic development, but also distinguish chemicals with different modes of action, so as to identify the key toxicity mechanism of chemicals

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