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SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis.

Constantine CC, Gurrin LC, McLaren CE, Bahlo M, Anderson GJ, Vulpe CD, Forrest SM, Allen KJ, Gertig DM, HealthIron Investigato - BMC Med. Genet. (2008)

Bottom Line: We contrasted results from two tag SNP selection algorithms, LDselect and Tagger.We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing.A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data.

View Article: PubMed Central - HTML - PubMed

Affiliation: The Centre for Molecular, Environmental, Genetic and Analytic (MEGA) Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia. ccconsta@uci.edu

ABSTRACT

Background: We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis.

Methods: We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform.

Results: Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays.

Conclusion: A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.

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Related in: MedlinePlus

Pattern of linkage disequilibrium across six genes and five population samples using Haploview default settings (with blocks removed).
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Figure 5: Pattern of linkage disequilibrium across six genes and five population samples using Haploview default settings (with blocks removed).

Mentions: Table 6 lists the number of tag SNP and total number of SNPs with MAF ≥ 3% for 14 genes resequenced by NHLBI across five population samples. The ratio of tag to total SNPs is low for genes within which there is substantial LD (e.g. FLVCR). The number of tag SNPs required is higher for African populations due to both the higher total number of SNPs and lower LD for most genes (as shown by higher ratios of tag SNPs to total SNPs). The final column uses multiPopTagSelect [12] to choose a minimal union of population-specific tag SNPs to capture SNP variation across all five populations. Figure 5 shows the pattern of linkage disequilibrium across five populations for the six genes which had more than 40 SNPs in each population. There is substantial variation in LD patterns both across genes and across populations which likely represents admixture variability throughout the genome.


SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis.

Constantine CC, Gurrin LC, McLaren CE, Bahlo M, Anderson GJ, Vulpe CD, Forrest SM, Allen KJ, Gertig DM, HealthIron Investigato - BMC Med. Genet. (2008)

Pattern of linkage disequilibrium across six genes and five population samples using Haploview default settings (with blocks removed).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2289803&req=5

Figure 5: Pattern of linkage disequilibrium across six genes and five population samples using Haploview default settings (with blocks removed).
Mentions: Table 6 lists the number of tag SNP and total number of SNPs with MAF ≥ 3% for 14 genes resequenced by NHLBI across five population samples. The ratio of tag to total SNPs is low for genes within which there is substantial LD (e.g. FLVCR). The number of tag SNPs required is higher for African populations due to both the higher total number of SNPs and lower LD for most genes (as shown by higher ratios of tag SNPs to total SNPs). The final column uses multiPopTagSelect [12] to choose a minimal union of population-specific tag SNPs to capture SNP variation across all five populations. Figure 5 shows the pattern of linkage disequilibrium across five populations for the six genes which had more than 40 SNPs in each population. There is substantial variation in LD patterns both across genes and across populations which likely represents admixture variability throughout the genome.

Bottom Line: We contrasted results from two tag SNP selection algorithms, LDselect and Tagger.We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing.A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data.

View Article: PubMed Central - HTML - PubMed

Affiliation: The Centre for Molecular, Environmental, Genetic and Analytic (MEGA) Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia. ccconsta@uci.edu

ABSTRACT

Background: We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis.

Methods: We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform.

Results: Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays.

Conclusion: A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.

Show MeSH
Related in: MedlinePlus