Inference of population structure using multilocus genotype data: dominant markers and null alleles

Area of Science:

• Population genetics
• Molecular ecology
• Genomics

Background:

• Dominant markers like amplified fragment length polymorphisms (AFLPs) are cost-effective for surveying genetic variation across numerous loci.
• Genotypic uncertainty, null alleles, and challenges in genotype calling for polyploids limit the applicability of traditional population structure analysis methods.
• Accurate population structure inference is crucial for understanding evolutionary processes and informing conservation strategies.

Purpose of the Study:

• To develop a straightforward method for handling genotypic ambiguity in population structure analyses.
• To apply this novel approach to amplified fragment length polymorphism (AFLP) data from whitefish populations.
• To provide a robust tool for researchers working with dominant markers and complex genetic data.

Main Methods:

• Development of a statistical approach to account for uncertainty in genotype data derived from dominant markers.
• Application of the method to amplified fragment length polymorphism (AFLP) data.
• Utilizing the 'structure' software version 2.2 for implementing the new analytical approach.

Main Results:

• The developed method successfully accounts for genotypic ambiguity inherent in dominant marker data.
• The approach was effectively applied to AFLP data, demonstrating its utility in real-world population studies.
• The 'structure' software version 2.2 now incorporates this enhanced capability for population genetics research.

Conclusions:

• The presented simple approach effectively addresses genotypic ambiguity in population structure studies using dominant markers.
• This method enhances the reliability of statistical analyses, particularly for organisms where genotype calling is challenging.
• The implementation in 'structure' software provides a valuable, accessible tool for the population genetics community.