A model-based 'varimax' sampling strategy for a heterogeneous population.

Area of Science:

• Population genetics
• Human genetics
• Forensic genetics

Background:

• Sampling strategies aim to improve sample homogeneity and reduce confounding errors.
• Karachi, Pakistan's largest city, served as a model for population sampling.
• Minimizing variation within population groups is crucial for accurate genetic studies.

Purpose of the Study:

• To develop and validate a sampling strategy for heterogeneous urban populations.
• To assess gene diversity and admixture levels in different ethnic groups within Karachi.
• To establish an optimal model for sampling diverse populations.

Main Methods:

• Blood groups (ABO, Rh) and Short Tandem Repeat (STR) loci (CSF1PO, TPOX, TH01) were analyzed in 3000 individuals.
• Participants were categorized into five ethnic groups: Balochi, Muhajir, Pathan, Punjabi, and Sindhi.
• An admixture index was developed to quantify genetic mixing at parental and grandparental levels.

Main Results:

• Significant differences in blood group and STR loci distribution were observed among ethnic groups.
• Higher gene diversity was found in a sub-population model compared to an agglomerated population.
• Gene diversity was significantly higher in models with no parental admixture than in admixture models.

Conclusions:

• A sub-population model with no parental admixture is justified for sampling Karachi's heterogeneous population.
• This strategy minimizes confounding errors and enhances sample homogeneity.
• The findings provide a validated approach for genetic sampling in diverse urban settings.