			Home About us Contact

QTL Detection (qtl + detection)

Distribution by Scientific Domains

Life Sciences	60%

Selected Abstracts

A score for Bayesian genome screening

GENETIC EPIDEMIOLOGY, Issue 3 2003
E. Warwick Daw
Abstract Bayesian Monte Carlo Markov chain (MCMC) techniques have shown promise in dissecting complex genetic traits. The methods introduced by Heath ([1997], Am. J. Hum. Genet. 61:748,760), and implemented in the program Loki, have been able to localize genes for complex traits in both real and simulated data sets. Loki estimates the posterior probability of quantitative trait loci (QTL) at locations on a chromosome in an iterative MCMC process. Unfortunately, interpretation of the results and assessment of their significance have been difficult. Here, we introduce a score, the log of the posterior placement probability ratio (LOP), for assessing oligogenic QTL detection and localization. The LOP is the log of the posterior probability of linkage to the real chromosome divided by the posterior probability of linkage to an unlinked pseudochromosome, with marker informativeness similar to the marker data on the real chromosome. Since the LOP cannot be calculated exactly, we estimate it in simultaneous MCMC on both real and pseudochromosomes. We investigate empirically the distributional properties of the LOP in the presence and absence of trait genes. The LOP is not subject to trait model misspecification in the way a lod score may be, and we show that the LOP can detect linkage for loci of small effect when the lod score cannot. We show how, in the absence of linkage, an empirical distribution of the LOP may be estimated by simulation and used to provide an assessment of linkage detection significance. Genet Epidemiol 24:181,190, 2003. © 2003 Wiley-Liss, Inc. [source]

Comparison of estimated breeding values, daughter yield deviations and de-regressed proofs within a whole genome scan for QTL

JOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 6 2001
H. Thomsen
An important issue in quantitative trait loci (QTL) detection is the use of phenotypic measurement as a dependent variable. Daughter yield deviations (DYDs) as the unit of choice are not available for all traits of interest. The use of de-regressed proofs (DRPFs) of estimated breeding values (EBVs) is an alternative to using daughter yield deviations. The objective of this study was to examine possible differences between DYDs and DRPFs within the use of QTL detection. The pedigree used was part of the granddaughter design of the German QTL effort. Consisting marker maps for livestock species were derived from all available data of 16 German Holstein paternal half-sib families with a total of 872 sires. The number of progeny ranged from 19 to 127. A whole genome scan was performed using weighted and unweighted multimarker regression with DYDs, DRPFs and EBVs as dependent variables for the traits milk, fat and protein yields. Results were compared with respect to the number of QTL detected. A similar number of QTL was detected with DRPFs and DYDs. Also, when dependent variables were weighted according to the variance of the trait, a higher number of QTL was detected at the desired level of significance as compared to using unweighted variables. Vergleich von Zuchtwerten, Daughter Yield Deviation und deregressierten Zuchtwerten bei der Genomanalyse zum Nachweis für QTL Ein bedeutender Einflussfaktor in der QTL-Analyse (QTL: Genorte für quantitativemarkmale) ist die Wahl der abhängigen Leistungsvariablen. Da Daughter Yield Deviations (DYDs) aber nicht für jedes Leistungsmerkmal zur Verfügung stehen, sollte untersucht werden, ob die De-regression von Zuchtwerten als alternative Variable in der QTL Analyse verwendet werden kann. Für die Untersuchung wurde ein Teil des Tiermaterials verwendet, das im Rahmen des Genomanalyseprojektes der Arbeitsgemeinschaft Deutscher Rinderzüchter untersucht wurde. Es standen 872 Bullen aus 16 väterlichen Halbgeschwisterfamilien der Rasse Deutsche Holsteins zur Verfügung. Die Zahl der Nachkommen pro Familie variierte von 19 bis 127. Unter Verwendung eines gewichteten als auch ungewichteten Multi-Marker Regressionsansatzes wurde ein Genomscan für die Leistungsmerkmale Milch-kg, Fett-kg und Eiweiss-kg durchgeführt, wobei als abhängige Variablen Zuchtwerte (EBV), Daughter Yield Deviations (DYD) und de-regressierte Zuchtwerte (DRPF) verwendet wurden. Die De-regression wurde auf der Basis der effektiven Töchterzahl, der Heritabilität des Merkmals und der additiv genetischen Verwandtschaftsmatrix durchgeführt. Alle Ergebnisse wurden in Hinblick auf die Anzahl der entdeckten QTL verglichen. Es zeigten sich dabei keine wesentlichen Unterschiede bei der Verwendung von DYDs und DRPFs. Die Rate der QTL Entdeckungen war bei beiden verwendeten Zuchtwerten annähernd gleich. Über den Vergleich unterschiedlicher Leistungsvariablen hinaus wurden die Ergebnisse der ungewichteten und gewichteten Analyse einander gegenübergestellt. Es konnte gezeigt werden, dass bei einer Gewichtung des Merkmals die Rate der QTL-Entdeckungen bei einem bestimmten Signifikanzniveau deutlich höher ist. [source]

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

ANIMAL GENETICS, Issue 2 2009
G. Le Mignon
Summary Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F2 crosses between two divergently selected ,Fat' and ,Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F2 offspring produced by 10 F1 sires and 85 F1 dams. AF and BM traits were measured on F2 animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F0, F1 and F2 birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F2 design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the ,Fat' nor the ,Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations. [source]

Efficiency of quantitative trait loci-assisted selection in correlations between identified and residual genotypes

ANIMAL SCIENCE JOURNAL, Issue 1 2008
Ching Y. LIN
ABSTRACT This study quantified the efficiency of quantitative traits loci (QTL)-assisted selection in the presence of correlations (,qr) between identified (q) and residual (r) genotypes. Two levels of heritability (h2 = 0.1 or 0.3), two levels of correlation (,qr = ,0.3 or 0.3) and five proportions of genetic variance explained by QTL detected (= 0.1, 0.2, 0.4, 0.6 or 0.8) were combined to give 20 scenarios in all. QTL-assisted selection placed a larger index weight on the QTL genotype than on the phenotype in 17 of 20 scenarios, yielding a greater response in the QTL genotype than in residual genotype. Although QTL-assisted selection was superior to phenotypic selection in all 20 scenarios, QTL-assisted selection showed a greater advantage over phenotypic selection when ,qr was positive than when ,qr was negative. Doubling the proportion of detected QTL variance to genetic variance does not result in a twofold increase in the genetic response to QTL-assisted selection, suggesting that economic returns diminish for each additional cost of detecting extra QTL. The correlation between q and r would make the interpretation (or prediction) of QTL effects difficult and QTL-assisted selection strategy must consider the joint effect of q and r. When q and r are not independent, a failure to account for ,qr in QTL-assisted selection would underestimate the genetic responses when ,qr is positive, but overestimate the genetic responses when ,qr is negative. Estimation bias is more serious at high heritability than at low heritability. Accounting for ,qr would improve the efficiency of QTL-assisted selection and the accuracy of QTL detection. The generalized procedure developed in this study allows for quantifying the efficiency of QTL-assisted selection and assessing estimation bias for ignoring the correlation between q and r for all possible combinations of h2, ,qr, and . [source]

Nonparametric Functional Mapping of Quantitative Trait Loci

BIOMETRICS, Issue 1 2009
Jie Yang
Summary Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples. [source]