Dataset Information

Detecting local haplotype sharing and haplotype association.

ABSTRACT: A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.

SUBMITTER: Xu H

PROVIDER: S-EPMC4096364 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Detecting local haplotype sharing and haplotype association.

Xu Hanli H Guan Yongtao Y

Genetics 20140508 3

A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model ...[more]

PMID: 24812308

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Project description:Age at first egg (AFE) and egg number (EN) are economically important traits related to egg production, as they directly influence the benefits of the poultry industry, but the molecular genetic research that affects those traits in laying ducks is still sparse. Our objective was to identify the genomic regions and candidate genes associated with AFE, egg production at 43 weeks (EP43w), and egg production at 66 weeks (EP66w) in a Shaoxing duck population using genome-wide association studies (GWASs) and haplotype-sharing analysis. Single-nucleotide polymorphism (SNP)-based genetic parameter estimates showed that the heritability was 0.15, 0.20, and 0.22 for AFE, EP43w, and EP66w, respectively. Subsequently, three univariate GWASs for AFE, EP43w, and EP66w were carried out independently. Twenty-four SNPs located on chromosome 25 within a 0.01-Mb region that spans from 4.511 to 4.521 Mb were associated with AFE. There are two CIs that affect EP43w, i.e., twenty-five SNPs were in strong linkage disequilibrium region spanning from 3.186 to 3.247 Mb on chromosome 25, a region spanning from 4.442 to 4.446 Mb on chromosome 25, and two interesting genes, ACAD8 and THYN1, that may affect EP43w in laying ducks. There are also two CIs that affect EP66w, i.e., a 2.412-Mb region that spans from 127.497 to 129.910 Mb on chromosome 2 and a 0.355-Mb region that spans from 4.481 to 4.837 Mb on chromosome 29, and CA2 and GAMT may be the putative candidate genes. Our study also found some haplotypes significantly associated with these three traits based on haplotype-sharing analysis. Overall, this study was the first publication of GWAS on egg production in laying ducks, and our findings will be helpful to provide some candidate genes and haplotypes to improve egg production performance based on breeding in laying duck. Additionally, we learned from a method called bootstrap test to verify the reliability of a GWAS with small experimental samples that users can access at https://github.com/xuwenwu24/Bootstrap-test.

Dataset Information

Detecting local haplotype sharing and haplotype association.

Publications

Detecting local haplotype sharing and haplotype association.

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