The whole genome tagSNP selection and transferability among HapMap populations

Area of Science:

• Genetics
• Bioinformatics

Background:

• Marker selection is critical for the success of association studies.
• Tagging SNPs (tSNPs) identified via HapMap data offer a potential approach for marker selection.

Purpose of the Study:

• To determine the number of tSNPs required for whole-genome association analysis across diverse HapMap populations (CEPH, Nigerian, Chinese, Japanese).
• To evaluate the effectiveness of tSNP sets from one population in describing markers from other populations.
• To quantify the additional tSNPs needed to cover markers across different populations.

Main Methods:

• Utilized HapMap data to identify tagging SNPs (tSNPs).
• Calculated the number of tSNPs necessary for genome-wide association studies in distinct HapMap populations.
• Assessed the proportion of markers adequately described by tSNP sets from one population within others.
• Determined the number of supplementary tSNPs required for comprehensive marker coverage across populations.

Main Results:

• The study presents the specific number of tSNPs needed for genome-wide association analysis across CEPH, Nigerian, Chinese, and Japanese HapMap populations.
• It quantifies the degree to which tSNP sets from one population can represent markers in another.
• The research identifies the number of additional tSNPs required to ensure complete marker description across different populations.

Conclusions:

• The findings provide essential data for selecting optimal tSNP sets for association studies in diverse populations.
• Understanding cross-population tSNP applicability is vital for efficient and accurate genome-wide association studies.
• This research aids in designing future association studies by informing marker selection strategies.