Literature DB >> 15483647

Pedigree linkage disequilibrium mapping of quantitative trait loci.

Ruzong Fan1, Christie Spinka, Lei Jin, JeeSun Jung.   

Abstract

In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme (ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.

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Year:  2005        PMID: 15483647     DOI: 10.1038/sj.ejhg.5201301

Source DB:  PubMed          Journal:  Eur J Hum Genet        ISSN: 1018-4813            Impact factor:   4.246


  10 in total

1.  Association testing in a linked region using large pedigrees.

Authors:  Rita M Cantor; Gary K Chen; Päivi Pajukanta; Kenneth Lange
Journal:  Am J Hum Genet       Date:  2005-01-18       Impact factor: 11.025

2.  Combined linkage and association mapping of quantitative trait loci by multiple markers.

Authors:  Jeesun Jung; Ruzong Fan; Lei Jin
Journal:  Genetics       Date:  2005-03-31       Impact factor: 4.562

3.  Association studies of dormancy and cooking quality traits in direct-seeded indica rice.

Authors:  Sunayana Rathi; K Pathak; R N S Yadav; B Kumar; R N Sarma
Journal:  J Genet       Date:  2014-04       Impact factor: 1.166

4.  High-resolution association mapping of quantitative trait loci: a population-based approach.

Authors:  Ruzong Fan; Jeesun Jung; Lei Jin
Journal:  Genetics       Date:  2005-09-19       Impact factor: 4.562

5.  Longitudinal association analysis of quantitative traits.

Authors:  Ruzong Fan; Yiwei Zhang; Paul S Albert; Aiyi Liu; Yuanjia Wang; Momiao Xiong
Journal:  Genet Epidemiol       Date:  2012-09-10       Impact factor: 2.135

6.  Association of the calcium-sensing receptor gene with blood pressure and urinary calcium in African-Americans.

Authors:  Jeesun Jung; Tatiana M Foroud; George J Eckert; Leah Flury-Wetherill; Howard J Edenberg; Xiaoling Xuei; Syed-Adeel Zaidi; J Howard Pratt
Journal:  J Clin Endocrinol Metab       Date:  2008-12-09       Impact factor: 5.958

7.  PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size.

Authors:  Kristina Allen-Brady; Jathine Wong; Nicola J Camp
Journal:  BMC Bioinformatics       Date:  2006-04-18       Impact factor: 3.169

8.  A quantitative linkage score for an association study following a linkage analysis.

Authors:  Tao Wang; Robert C Elston
Journal:  BMC Genet       Date:  2006-01-20       Impact factor: 2.797

9.  Favorable alleles mining for gelatinization temperature, gel consistency and amylose content in Oryza sativa by association mapping.

Authors:  Hui Wang; Shangshang Zhu; Xiaojing Dang; Erbao Liu; Xiaoxiao Hu; Moaz Salah Eltahawy; Imdad Ullah Zaid; Delin Hong
Journal:  BMC Genet       Date:  2019-03-19       Impact factor: 2.797

10.  Polymorphisms of the IGF1R gene and their genetic effects on chicken early growth and carcass traits.

Authors:  Mingming Lei; Xia Peng; Min Zhou; Chenglong Luo; Qinghua Nie; Xiquan Zhang
Journal:  BMC Genet       Date:  2008-11-07       Impact factor: 2.797

  10 in total

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