scholarly journals Fine Mapping of Quantitative Trait Loci Using Linkage Disequilibria With Closely Linked Marker Loci

Genetics ◽  
2000 ◽  
Vol 155 (1) ◽  
pp. 421-430 ◽  
Author(s):  
T H E Meuwissen ◽  
M E Goddard
Keyword(s):  
Quantitative Trait Loci ◽  
Fine Mapping ◽  
Quantitative Trait ◽  
Mapping Method ◽  
Linkage Disequilibrium Mapping ◽  
Effective Population ◽  
Marker Haplotype ◽  
Trait Loci ◽  
Marker Loci ◽  
Dense Marker

Abstract A multimarker linkage disequilibrium mapping method was developed for the fine mapping of quantitative trait loci (QTL) using a dense marker map. The method compares the expected covariances between haplotype effects given a postulated QTL position to the covariances that are found in the data. The expected covariances between the haplotype effects are proportional to the probability that the QTL position is identical by descent (IBD) given the marker haplotype information, which is calculated using the genedropping method. Simulation results showed that a QTL was correctly positioned within a region of 3, 1.5, or 0.75 cM in 70, 62, and 68%, respectively, of the replicates using markers spaced at intervals of 1, 0.5, and 0.25 cM, respectively. These results were rather insensitive to the number of generations since the QTL occurred and to the effective population size, except that 10 generations yielded rather poor estimates of the QTL position. The position estimates of this multimarker disequilibrium mapping method were more accurate than those from a single marker transmission disequilibrium test. A general approach for identifying QTL is suggested, where several stages of disequilibrium mapping are used with increasingly dense marker spacing.

Bayesian Mapping of Multiple Quantitative Trait Loci From Incomplete Inbred Line Cross Data

Genetics ◽  
1998 ◽  
Vol 148 (3) ◽  
pp. 1373-1388
Author(s):  
Mikko J Sillanpää ◽  
Elja Arjas
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Backcross Progeny ◽  
Random Variable ◽  
Interval Mapping ◽  
Mapping Method ◽  
Structure Mapping ◽  
Standard Interval ◽  
Trait Loci

Abstract A novel fine structure mapping method for quantitative traits is presented. It is based on Bayesian modeling and inference, treating the number of quantitative trait loci (QTLs) as an unobserved random variable and using ideas similar to composite interval mapping to account for the effects of QTLs in other chromosomes. The method is introduced for inbred lines and it can be applied also in situations involving frequent missing genotypes. We propose that two new probabilistic measures be used to summarize the results from the statistical analysis: (1) the (posterior) QTL-intensity, for estimating the number of QTLs in a chromosome and for localizing them into some particular chromosomal regions, and (2) the location wise (posterior) distributions of the phenotypic effects of the QTLs. Both these measures will be viewed as functions of the putative QTL locus, over the marker range in the linkage group. The method is tested and compared with standard interval and composite interval mapping techniques by using simulated backcross progeny data. It is implemented as a software package. Its initial version is freely available for research purposes under the name Multimapper at URL http://www.rni.helsinki.fi/~mjs.

scholarly journals A Rank-Based Nonparametric Method for Mapping Quantitative Trait Loci in Outbred Half-Sib Pedigrees: Application to Milk Production in a Granddaughter Design

Genetics ◽  
1998 ◽  
Vol 149 (3) ◽  
pp. 1547-1555 ◽  
Author(s):  
Wouter Coppieters ◽  
Alexandre Kvasz ◽  
Frédéric Farnir ◽  
Juan-Jose Arranz ◽  
Bernard Grisart ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Real Data ◽  
Interval Mapping ◽  
Mapping Method ◽  
Residual Variance ◽  
Data Set ◽  
Wilcoxon Rank Sum Test ◽  
Holstein Friesian ◽  
Trait Loci

Abstract We describe the development of a multipoint nonparametric quantitative trait loci mapping method based on the Wilcoxon rank-sum test applicable to outbred half-sib pedigrees. The method has been evaluated on a simulated dataset and its efficiency compared with interval mapping by using regression. It was shown that the rank-based approach is slightly inferior to regression when the residual variance is homoscedastic normal; however, in three out of four other scenarios envisaged, i.e., residual variance heteroscedastic normal, homoscedastic skewed, and homoscedastic positively kurtosed, the latter outperforms the former one. Both methods were applied to a real data set analyzing the effect of bovine chromosome 6 on milk yield and composition by using a 125-cM map comprising 15 microsatellites and a granddaughter design counting 1158 Holstein-Friesian sires.

Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle1

2009 ◽  
Vol 87 (1) ◽  
pp. 37-45 ◽  
Author(s):  
E. L. Sherman ◽  
J. D. Nkrumah ◽  
C. Li ◽  
R. Bartusiak ◽  
B. Murdoch ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Fine Mapping ◽  
Feed Intake ◽  
Quantitative Trait ◽  
Feed Efficiency ◽  
Trait Loci

scholarly journals Fine-mapping quantitative trait loci affecting murine external ear tissue regeneration in the LG/J by SM/J advanced intercross line

Heredity ◽  
2014 ◽  
Vol 112 (5) ◽  
pp. 508-518 ◽  
Author(s):  
J M Cheverud ◽  
H A Lawson ◽  
K Bouckaert ◽  
A V Kossenkov ◽  
L C Showe ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Tissue Regeneration ◽  
Fine Mapping ◽  
Quantitative Trait ◽  
External Ear ◽  
Advanced Intercross Line ◽  
Trait Loci

Joint Linkage and Linkage Disequilibrium Mapping of Quantitative Trait Loci in Natural Populations

Genetics ◽  
2002 ◽  
Vol 160 (2) ◽  
pp. 779-792 ◽  
Author(s):  
Rongling Wu ◽  
Chang-Xing Ma ◽  
George Casella
Keyword(s):  
Linkage Disequilibrium ◽  
Quantitative Trait Loci ◽  
Linkage Analysis ◽  
Quantitative Trait ◽  
Genome Mapping ◽  
Linkage Disequilibrium Mapping ◽  
Allelic Association ◽  
Mapping Strategy ◽  
Trait Loci ◽  
New Strategy

AbstractLinkage analysis and allelic association (also referred to as linkage disequilibrium) studies are two major approaches for mapping genes that control simple or complex traits in plants, animals, and humans. But these two approaches have limited utility when used alone, because they use only part of the information that is available for a mapping population. More recently, a new mapping strategy has been designed to integrate the advantages of linkage analysis and linkage disequilibrium analysis for genome mapping in outcrossing populations. The new strategy makes use of a random sample from a panmictic population and the open-pollinated progeny of the sample. In this article, we extend the new strategy to map quantitative trait loci (QTL), using molecular markers within the EM-implemented maximum-likelihood framework. The most significant advantage of this extension is that both linkage and linkage disequilibrium between a marker and QTL can be estimated simultaneously, thus increasing the efficiency and effectiveness of genome mapping for recalcitrant outcrossing species. Simulation studies are performed to test the statistical properties of the MLEs of genetic and genomic parameters including QTL allele frequency, QTL effects, QTL position, and the linkage disequilibrium of the QTL and a marker. The potential utility of our mapping strategy is discussed.

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