Power and Precision of Alternate Methods for Linkage Disequilibrium Mapping of Quantitative Trait Loci

Zhao, Honghua; Fernando, Rohan L.; Dekkers, Jack C. M.

doi:10.1534/genetics.106.066480

Cited by 69 publications

(106 citation statements)

References 34 publications

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“…Such an analytical approach has also been applied in association studies in human and animal genetics (Sham et al 2000;Purcell et al 2003;Wang 2008;Teyssèdre et al 2012). Alternatively, the estimation of power has also been addressed through simulation studies (see, for instance, Yu et al 2006;H. Zhao et al 2007;Stich and Melchinger 2009;Erbe et al 2010;MacLeod et al 2010;Bradbury et al 2011).…”

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confidence: 99%

Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium

et al. 2014

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Association mapping has permitted the discovery of major QTL in many species. It can be applied to existing populations and, as a consequence, it is generally necessary to take into account structure and relatedness among individuals in the statistical model to control false positives. We analytically studied power in association studies by computing noncentrality parameter of the tests and its relationship with parameters characterizing diversity (genetic differentiation between groups and allele frequencies) and kinship between individuals. Investigation of three different maize diversity panels genotyped with the 50k SNPs array highlighted contrasted average power among panels and revealed gaps of power of classical mixed models in regions with high linkage disequilibrium (LD). These gaps could be related to the fact that markers are used for both testing association and estimating relatedness. We thus considered two alternative approaches to estimating the kinship matrix to recover power in regions of high LD. In the first one, we estimated the kinship with all the markers that are not located on the same chromosome than the tested SNP. In the second one, correlation between markers was taken into account to weight the contribution of each marker to the kinship. Simulations revealed that these two approaches were efficient to control false positives and were more powerful than classical models.

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confidence: 99%

Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium

et al. 2014

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“…To our knowledge, earlier studies have all considered haplotype a fixed effect in the model (e.g. Zhao et al, 2007;Pryce et al, 2010). There were two significant modeling differences in this study compared to Sahana et al (2010) who used nearly the same datasets to compare several associations of mapping methods and models: (1) fitting haplotype effects as random in the model, and (2) modeling genetic relationship within study samples.…”

Section: Discussionmentioning

confidence: 94%

“…Conflicting reports, however, are available (Zhao et al, 2007). The discrepancies in the results of these studies could be due to several factors influencing the LD between markers and the LD between markers and QTLs: marker density, effective population size, generations of random mating, QTL allele frequency, QTL position relative to observed marker positions, and if one of the Strategies for haplotype-based association mapping in a complex pedigreed population J. Boleckova 1,2 , O. F. Christensen 1 , P. Sørensen 1 , G. Sahana markers is a causative mutation that affects gene products (Cargill et al, 1999;Zhao et al, 2007;Pei et al, 2009). Furthermore, imprecise modeling of the genetic relation within the study sample may cause spurious associations, i.e.…”

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confidence: 99%

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Strategies for haplotype-based association mapping in a complex pedigreed population

Boleckova¹,

Christensen²,

Sørensen³

et al. 2012

CZECH J ANIM SCI

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AbStrAct:In association mapping, haplotype-based methods are generally regarded to provide higher power and increased precision than methods based on single markers. For haplotype-based association mapping most studies use a fixed haplotype effect in the model. However, an increase in haplotype length raises the number of parameters in the model, resulting in low accuracy of the estimates especially for the low-frequency haplotypes. Modeling of haplotype effects can be improved if they are assumed to be random effects, as only one parameter, i.e. haplotype variance, needs to be estimated compared to estimating the effects of all different haplotypes in a fixed haplotype model. Using simulated data, we investigated statistical models where haplotypes were fitted either as a fixed or random effect and we compared them for the power, precision, and type I error. We investigated five haplotype lengths of 2, 4, 6, 10 and 20. The simulated data resembled the Danish Holstein cattle pedigree representing a complex relationship structure and QTL effects of different sizes were simulated. We observed that the random haplotype models had high power and very low type I error rates (after the Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. Haplotype length of 4 to 6 gave the best results for random model in the present study. Though the present study was conducted on data structure more frequent in livestock, our findings on random vs. fixed haplotype effects in association mapping models are applicable to data from other species with a similar pedigree structure.

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“…gnets.ncsu.edu/data/website/dgrp2.tgeno), replacing any reported sequence within the GRR with our own long-read sequence data. We then calculated a multiallelic extension of r 2 (Hill and Robertson 1968), which provides an accurate metric of LD among multiallelic loci (Zhao et al 2007). The analysis was performed using our data coded either as entire haplotypes (and therefore highly multiallelic), or as a series of SNPs and indels from alignment of the haplotypes.…”

Section: Linkage Disequilibrium Analysismentioning

confidence: 99%

Variation and evolution of the glutamine-rich repeat region of Drosophila Argonaute-2

Palmer

Obbard

2016

Preprint

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RNA interference pathways mediate biological processes through Argonaute-family proteins, which bind small RNAs as guides to silence complementary target nucleic acids . In insects and crustaceans Argonaute-2 silences viral nucleic acids, and therefore acts as a primary effector of innate antiviral immunity. Although the function of the major Argonaute-2 domains, which are conserved across most Argonautefamily proteins, are known, many invertebrate Argonaute-2 homologs contain a glutamine-rich repeat (GRR) region of unknown function at the N-terminus . Here we combine long-read amplicon sequencing of Drosophila Genetic Reference Panel (DGRP) lines with publicly available sequence data from many insect species to show that this region evolves extremely rapidly and is hyper-variable within species. We identify distinct GRR haplotype groups in Drosophila melanogaster, and suggest that one of these haplotype groups has recently risen to high frequency in a North American population. Finally, we use published data from genome-wide association studies of viral resistance in D. melanogaster to test whether GRR haplotypes are associated with survival after virus challenge. We find a marginally significant association with survival after challenge with Drosophila C Virus in the DGRP, but we were unable to replicate this finding using lines from the Drosophila Synthetic Population Resource panel. KEYWORDS

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Power and Precision of Alternate Methods for Linkage Disequilibrium Mapping of Quantitative Trait Loci

Cited by 69 publications

References 34 publications

Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium

Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium

Strategies for haplotype-based association mapping in a complex pedigreed population

Variation and evolution of the glutamine-rich repeat region of Drosophila Argonaute-2

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