Bioinformatics Methods for Transcriptome Analysis on Teratogenesis Testing.

Area of Science:

• Developmental toxicology
• Bioinformatics
• Genomics

Background:

• Teratogenesis testing faces challenges with current in vitro and in vivo models.
• Human embryonic cell-based test systems combined with omics strategies, like transcriptomics, offer solutions.
• Analyzing gene expression data from microarray and RNA-seq requires significant computational and bioinformatics expertise.

Purpose of the Study:

• To present a bioinformatics pipeline for processing microarray and RNA-seq data.
• To assist researchers in interpreting transcriptome results, including differential gene expression and enrichment analysis.
• To address specific challenges in teratogenesis research, such as time-course analysis.

Main Methods:

• Development of a computational pipeline for transcriptomic data processing.
• Integration of microarray and RNA-seq data analysis.
• Inclusion of statistical interpretation and visualization methods.
• Discussion of programming codes and user-friendly tools for accessibility.

Main Results:

• The pipeline facilitates the interpretation of key transcriptome analysis outputs.
• It provides methods to overcome common difficulties in transcriptomic data processing.
• Demonstrates application in teratogenesis studies, including time-course analysis.

Conclusions:

• The presented pipeline democratizes transcriptome analysis for teratogenesis research.
• It empowers researchers across various fields to interpret gene expression data effectively.
• The tool aids in understanding the impact of potential teratogens on embryonic development.