Disentangling pooled triad genotypes for association studies.

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Trio-based genetic association studies are robust to population structure and can assess complex genetic effects.
• Limited DNA specimens and high genotyping costs can be significant challenges in these studies.

Purpose of the Study:

• To propose and evaluate a cost-effective case-parents design using pooled DNA specimens for genetic association studies.
• To reduce the number of required genotyping assays while maintaining statistical power.

Main Methods:

• Randomly partitioning case-parent triads into pooling sets and creating pooled DNA from mothers, fathers, and offspring.
• Utilizing maximum-likelihood estimation via log-linear modeling and the expectation-maximization algorithm.
• Assessing offspring and maternal genetic effects, accommodating genotyping errors and missing genotypes.

Main Results:

• The proposed pooling strategy significantly reduces genotyping costs and conserves limited specimens.
• Power calculations indicate only modest reductions in statistical power for detecting genetic effects, especially with low genotyping error rates.
• The method effectively assesses offspring and maternal genetic effects.

Conclusions:

• Pooled DNA case-parents designs offer an economical and efficient approach for genetic association studies with limited specimens.
• This strategy provides a viable alternative to individual genotyping, balancing cost reduction with acceptable power.
• The method is robust to genotyping errors and missing data, enhancing its practical applicability.