iMARS--mutation analysis reporting software: an analysis of spontaneous cII mutation spectra

Area of Science:

• Toxicology
• Genetics
• Molecular Biology

Background:

• Assessing chemical mutagenicity requires understanding spontaneous mutation rates and types in control test systems.
• Current mutation-spectra analysis is time-consuming and labor-intensive.
• Establishing baseline spontaneous mutation data is crucial for accurate chemically induced mutation detection.

Purpose of the Study:

• To introduce iMARS, a comprehensive package for mutation-spectrum analysis.
• To demonstrate iMARS's utility by analyzing spontaneous base substitutions in transgenic rodent models (Big Blue Mouse, MutaMouse, Big Blue Rat) using the cII gene assay.
• To establish a baseline reference for spontaneous mutation studies in these models.

Main Methods:

• Development of iMARS, a mutation-spectrum analysis package utilizing routine methodologies and visualization tools.
• Analysis of spontaneous base substitutions in the cII gene of transgenic rodents.
• Assessment of mutation distribution, types, sequence context, and hotspot identification.

Main Results:

• Significant variations in spontaneous mutation spectra were observed within and between Big Blue Mouse, MutaMouse, and Big Blue Rat models.
• G:C-->A:T transitions and G:C-->T:A transversions were the most frequent spontaneous base substitutions.
• Big Blue Mouse exhibited more variation in mutation distribution, type, and sequence context compared to MutaMouse and Big Blue Rat. Twenty-eight mutation hotspots were identified, often in CG, GA/TC, GG, and GC dinucleotides.

Conclusions:

• iMARS provides a valuable tool for comprehensive mutation spectrum analysis, simplifying the assessment of mutation distribution, type, and hotspots.
• Spontaneous mutation spectra show considerable variation across different transgenic rodent models, necessitating careful consideration when comparing results.
• The findings offer a critical baseline for future mutation studies and aid in distinguishing true chemically induced mutations from background noise.