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Whole-genome scan, in a complex disease, using 11,245 single-nucleotide polymorphisms: comparison with
Sally John1, Neil Shephard, Guoying Liu
1University of Manchester, Manchester, United Kingdom.
American Journal of Human Genetics
|May 22, 2004
Summary
Single-nucleotide polymorphisms (SNPs) offer superior precision in whole-genome linkage analysis for complex diseases like rheumatoid arthritis (RA) compared to microsatellites. This study highlights SNPs' higher information content for more accurate locus detection and gene mapping.
Area of Science:
- Genetics
- Genomics
- Medical Genetics
Background:
- Single-nucleotide polymorphisms (SNPs) are theoretically valuable for linkage analysis but lack direct whole-genome comparison with microsatellites in complex diseases.
- Rheumatoid arthritis (RA) is a complex disease where identifying genetic susceptibility loci is crucial for understanding pathogenesis.
Purpose of the Study:
- To directly compare the utility of whole-genome single-nucleotide polymorphism (SNP) scans versus microsatellite scans for linkage analysis in rheumatoid arthritis (RA).
- To evaluate the impact of SNP density and information content on the precision and power of linkage analysis for complex diseases.
Main Methods:
- Conducted a whole-genome scan of 11,245 SNPs across 157 families with multiple RA cases.
- Compared SNP scan results with a 10-cM microsatellite scan in the same cohort.
- Assessed the effect of varying SNP density (11,245 SNPs vs. 3,300 SNPs) on linkage detection.
Main Results:
- The SNP scan identified the major RA susceptibility locus, HLA*DRB1, with a more precise 31-cM interval compared to the 50-cM interval from the microsatellite scan.
- Four additional loci were detected by the SNP scan at nominal significance (P<.05) that were missed by the microsatellite scan.
- Higher information content of SNPs was the primary driver of improved detection and precision, with reduced SNP density significantly impacting results.
Conclusions:
- Dense SNP maps are highly effective for linkage analysis in complex diseases, even when parental DNA is unavailable, offering greater precision than microsatellites.
- SNP-based linkage analysis substantially reduces the resources needed for gene mapping and provides a foundation for subsequent association studies.
- The findings underscore the importance of marker density and information content in maximizing the power of genomewide scans for complex genetic traits.