Covariance between relatives for a marked quantitative trait locus

Wang, T; Fernando, R. L.; Beek, S. van der; Grossman, Michael; Arendonk, Jam van

doi:10.1186/1297-9686-27-3-251

Cited by 100 publications

(40 citation statements)

References 14 publications

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“…The matrix Z estimated with the algorithm outlined here gives 0.5 ZZ' equal to the IBD matrix obtained from the single point algorithm developed by Wang et al [27]. A fully detailed description of the algorithm is given in Methods.…”

Section: Resultsmentioning

confidence: 99%

“…An element l (for l = 1,...,2 f ) in row 2 i -1 is the probability that the paternally inherited QTL allele is identical to the l :th allele in the base generation, and an element l ( l = 1,...,2 f ) in row 2 i is the corresponding probability for the maternally inherited QTL allele. Thus the first 2 f columns in W are the same as the first 2 f columns of the gametic IBD matrix (as defined in [27])…”

Section: Methodsmentioning

confidence: 99%

“…The first step is based on the concept of probability of descent of a gamete ( PDQ ij ) as defined in [27]. The PDQ matrix of size 2 × 4 gives the probabilities for the two alleles (row i ) being inherited from the four possible parental alleles (column j ).…”

Section: Methodsmentioning

confidence: 99%

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Separation of base allele and sampling term effects gives new insights in variance component QTL analysis

Rönnegård

Carlborg

2007

BMC Genet

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Background: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix).

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis

Rönnegård

Carlborg

2007

BMC Genet

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show abstract

“…Deterministic methods [17,18] only use informative markers (where marker phase can be inferred without uncertainty) and therefore only uses part of the available information, whereas iterative methods [15,16] provide better precision in IBD estimation, but also higher computational demand. However, if haplotypes are estimated by an independent routine, and included in the input data, it can increase the amount of information available for the deterministic algorithm.…”

Section: Methodsmentioning

confidence: 99%

Fine mapping and replication of QTL in outbred chicken advanced intercross lines

et al. 2011

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BackgroundLinkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.MethodsWe have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.ResultsFive of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.ConclusionsOur results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.

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“…As for the covariances, these were computed using the algorithm of Wang et al [26]. The final covariance matrix G is:…”

Section: Illustrationsmentioning

confidence: 99%

Linear models for joint association and linkage QTL mapping

Legarra

Fernando

2009

Genet Sel Evol

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BackgroundPopulational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure.ResultsWe herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission) average of the substitution effects of founders' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component) model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided.ConclusionThe linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward.

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Covariance between relatives for a marked quantitative trait locus

Cited by 100 publications

References 14 publications

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis

Fine mapping and replication of QTL in outbred chicken advanced intercross lines

Linear models for joint association and linkage QTL mapping

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