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1.
Nat Genet ; 45(2): 197-201, 2013 Feb.
Article in English | MEDLINE | ID: mdl-23263489

ABSTRACT

Insulin secretion has a crucial role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5-5%) and rare (MAF < 0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip. We identified low-frequency coding variants associated with fasting proinsulin concentrations at the SGSM2 and MADD GWAS loci and three new genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1 and PAM. We also show that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs both nearby and megabases away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.


Subject(s)
Exome/genetics , Genetic Variation , Insulin/genetics , Insulin/metabolism , Adaptor Proteins, Signal Transducing , Amidine-Lyases/genetics , Cytoskeletal Proteins , Death Domain Receptor Signaling Adaptor Proteins/genetics , Fasting/blood , Finland , Gene Frequency , Genetics, Population , Genotype , Guanine Nucleotide Exchange Factors/genetics , Humans , Insulin Secretion , Intracellular Signaling Peptides and Proteins/genetics , Male , Mixed Function Oxygenases/genetics , Molecular Sequence Annotation , Proinsulin/blood , Tumor Suppressor Proteins/genetics
2.
Am J Hum Genet ; 73(2): 271-84, 2003 Aug.
Article in English | MEDLINE | ID: mdl-12844283

ABSTRACT

Recent advances in technologies for high-throughout single-nucleotide polymorphism (SNP)-based genotyping have improved efficiency and cost so that it is now becoming reasonable to consider the use of SNPs for genomewide linkage analysis. However, a suitable screening set of SNPs and a corresponding linkage map have yet to be described. The SNP maps described here fill this void and provide a resource for fast genome scanning for disease genes. We have evaluated 6,297 SNPs in a diversity panel composed of European Americans, African Americans, and Asians. The markers were assessed for assay robustness, suitable allele frequencies, and informativeness of multi-SNP clusters. Individuals from 56 Centre d'Etude du Polymorphisme Humain pedigrees, with >770 potentially informative meioses altogether, were genotyped with a subset of 2,988 SNPs, for map construction. Extensive genotyping-error analysis was performed, and the resulting SNP linkage map has an average map resolution of 3.9 cM, with map positions containing either a single SNP or several tightly linked SNPs. The order of markers on this map compares favorably with several other linkage and physical maps. We compared map distances between the SNP linkage map and the interpolated SNP linkage map constructed by the deCode Genetics group. We also evaluated cM/Mb distance ratios in females and males, along each chromosome, showing broadly defined regions of increased and decreased rates of recombination. Evaluations indicate that this SNP screening set is more informative than the Marshfield Clinic's commonly used microsatellite-based screening set.


Subject(s)
Chromosome Mapping , Polymorphism, Single Nucleotide , Alleles , DNA/genetics , Female , Gene Frequency , Genetic Testing , Genome, Human , Genotype , Humans , Male
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