Interspecies Gene Name Extrapolation--A New Approach

Area of Science:

• Bioinformatics
• Genomics
• Toxicology

Background:

• Animal models are crucial for studying environmental factor effects on human health using omics technologies.
• Microarray data from animal models often lacks human gene name annotation, hindering analysis.

Purpose of the Study:

• To develop and validate a novel bioinformatics pipeline for pig-to-human gene name extrapolation.
• To enhance the utility of animal model microarray data in omics research.

Main Methods:

• Single-color gene expression microarray analysis of pig tissues (duodenum, spleen) exposed to zearalenone and Escherichia coli.
• Bioinformatics pipeline involving file format modification, data alignment, and command-line tools for gene name mapping.

Main Results:

• The developed pipeline achieved an average pig-to-human gene name extrapolation yield of 58.34%.
• This yield is substantially higher than the 3.64% obtained with simpler methods.

Conclusions:

• The new bioinformatics pipeline offers a more effective solution for gene annotation challenges in animal model omics data.
• This approach is valuable for researchers in the omics era dealing with cross-species gene identification.