Consensus genetic structuring and typological value of markers using multiple co-inertia analysis.

Area of Science:

• Population genetics
• Statistical genetics
• Bioinformatics

Background:

• Analyzing population genetic structure with weakly congruent markers requires specialized methods.
• Multivariate statistical approaches are crucial for uncovering consensus genetic structuring.

Purpose of the Study:

• To present and evaluate a novel multivariate method for analyzing consensus genetic structuring.
• To assess the efficiency of individual genetic markers in population structuring.

Main Methods:

• Principal Component Analysis for Allelic Frequencies (%PCA) for single-marker analysis.
• Multiple Co-Inertia Analysis (MCOA) to reveal commonalities and build a reference structure.
• Calculation of a typological value for each marker to quantify its structuring efficiency.

Main Results:

• The proposed method effectively reveals consensus genetic structures.
• Marker efficiency, measured by typological value, varies significantly among markers.
• Marker efficiency is context-dependent, differing across distinct population collections.

Conclusions:

• The developed multivariate method is efficient for analyzing population genetic structure with weakly congruent markers.
• Marker selection based on typological value is critical for reliable population structure analysis.
• The reliability of genetic studies depends on marker quality, not solely on the number of markers used.