QST-FST comparisons with unbalanced half-sib designs

Area of Science:

• Evolutionary genetics
• Population genetics
• Quantitative genetics

Background:

• Quantitative trait differentiation (QST) measures genetic variation among populations for specific traits.
• Comparing QST with neutral genetic differentiation (FST) helps infer local adaptation.
• Previous statistical methods for QST vs. FST comparison were limited to balanced datasets and paternal half-sib families.

Purpose of the Study:

• To extend statistical methods for comparing QST and FST.
• To accommodate maternal half-sib families, common in plant breeding.
• To enable analysis of unbalanced datasets in population genetics studies.

Main Methods:

• Development of a simulation resampling approach for statistical testing.
• Extension of existing methods to include maternal half-sib relationships.
• Adaptation of the method to handle unbalanced data structures.
• Implementation of the extended approach in the R package QstFstComp.

Main Results:

• The new method statistically compares QST and FST for maternal half-sib families.
• The approach successfully handles unbalanced datasets, increasing applicability.
• The R package QstFstComp provides a user-friendly tool for these analyses.

Conclusions:

• The extended method provides a robust framework for detecting local adaptation using QST and FST.
• This advancement is particularly valuable for plant science and breeding programs.
• The QstFstComp R package democratizes advanced population genetic analyses.