Population-specific genetic variation in large sequencing data sets: why more data is still better.

Area of Science:

• Genomics
• Population Genetics
• Bioinformatics

Background:

• The Rotterdam Study is a population-based cohort with extensive longitudinal phenotyping.
• Existing large-scale sequencing efforts may not fully capture population-specific genetic diversity.

Purpose of the Study:

• To generate and release a comprehensive whole-exome sequencing dataset from the Rotterdam Study.
• To provide a valuable control dataset for genetic variant interpretation.
• To highlight the presence of population-specific variants in next-generation sequencing data.

Main Methods:

• Whole-exome sequencing of 2628 participants from the Rotterdam Study.
• Identification and characterization of single-nucleotide variants and short insertions/deletions.
• Comparison of generated variants with existing large sequencing databases (ExAC, ESP, 1000G, UK10K, GoNL, DECODE).

Main Results:

• A dataset comprising 669,737 single-nucleotide variants and 24,019 short insertions/deletions was generated.
• The dataset contains a significant number of population-specific variants not found in other major sequencing efforts.
• The data enables extensive interpretation of genetic variants in relation to clinical outcomes.

Conclusions:

• Next-generation sequencing data sets, like the one from the Rotterdam Study, are crucial for identifying population-specific genetic variants.
• This dataset serves as a vital control resource for genetic research.
• Understanding population-specific variants is essential for comprehensive genetic association studies and personalized medicine.