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PubMed1997

Joint segregation and linkage analysis of a quantitative trait compared to separate analyses.

Our goal was to determine the degree to which joint segregation and linkage analysis leads to increased efficiency for estimating the recombination fraction and to greater power for detecting linkage, compared to separate analyses. We concentrated on the quantitative phenotype Q2 and analyzed linkage with a tightly linked marker, a loosely linked marker, and eight unlinked markers, the latter chosen to evaluate false positive rates. We considered both nuclear-family and extended-pedigree data, using the 200 replicates of each provided to GAW participants. We found joint analysis to be consistently more efficient, with relative efficiencies for the tightly linked marker of 1.16 and 1.06 in extended pedigrees and nuclear families, respectively. These relative efficiencies translated into modest but consistent gains in power to detect linkage. Both methods appear to produce unbiased parameter estimates and similar false positive rates.

Computer Simulation↗
PubMed1998

Efficiency of multistage marker-assisted selection in the improvement of multiple quantitative traits.

The application of marker-assisted selection (MAS) to breeding programmes depends on its relative cost and the expected economic return compared to conventional phenotypic selection. The relative efficiency of MAS can be increased through a two-stage selection scheme or through marker-based, multiple-trait improvement. However, the effectiveness of these alternatives has not been quantified. In this study, we evaluate the efficiency of MAS relative to conventional phenotypic selection and marker-only selection in multistage selection for the improvement of multiple traits. We further incorporate the costs of obtaining measurements on phenotypic characters and marker loci into the objective function to evaluate the efficiency of MAS with respect to the gain per unit cost. Deterministic analyses indicate that excluding costs, multiple-trait MAS can be used to increase the aggregate breeding values in quantitative characters and is expected to be more effective than conventional selection or single-trait MAS. Two-stage MAS has a slightly reduced gain because of culling in the first stage. If the objective function is to maximize the gain per unit cost, multiple-trait MAS is inferior to phenotypic selection in most of the selection schemes investigated when the cost ratio (r) of obtaining measurements on phenotypic characters to scoring marker loci is less than unity (r < or = 1.0) and the heritability (h2) is greater than 0.3. The efficiency of MAS increases as r increases and h2 decreases. For MAS to be more effective, it is necessary to decrease further the cost associated with molecular marker assays.

Chromosome Mapping↗
PubMed2005

Mapping quantitative trait loci for milk production and genetic polymorphisms of milk proteins in dairy sheep.

In this paper, we present recent advances in the molecular dissection of complex traits in dairy sheep and discuss their possible impact on breeding schemes. In the first step, we review the literature data on genetic polymorphisms and the effects of sheep alphas1-casein and beta-lactoglobulin loci. It is concluded that the results are rather inconsistent and cannot be used in dairy sheep selection. In a second step, we describe the strategy implemented in France, Italy and Spain taking advantage of the genetic maps for QTL detection. These studies were part of a European project, called "genesheepsafety", which investigated both milk production and functional traits. Preliminary QTL results are presented for production traits.

Animals↗
PubMed2001

Potential gain from optimizing multigeneration selection on an identified quantitative trait locus.

The potential extra response that can be obtained from the optimal use of a known QTL in selection by optimizing weights in an index of breeding value for the QTL and polygenic EBV was investigated for a range of parameters. Optimal strategies were derived for a deterministic model of simultaneous selection on a QTL and polygenic effects using optimal control theory. Responses over 10 generations to the following selection strategies were compared: 1) standard QTL selection, with QTL weights equal to 1, 2) optimal QTL selection, 3) stepwise single-generation optimal QTL selection, and 4) non-QTL selection based on phenotype. Cumulative discounted response with discount rates of 10 or 30% per generation were evaluated and used as objective for optimal selection strategies. Optimal selection balanced the conflict between short- and long-term responses and gave greater cumulative discounted response than standard QTL selection of up to 20%, but less than 5% for most cases. Discount rate had limited impact. For a QTL with an additive effect of one polygenic standard deviation, cumulative discounted response from optimal QTL selection was less than 5% greater than response for non-QTL selection for most cases. Exceptions were traits with low heritability and recessive QTL at low frequency, for which extra response was up to 55% greater. Stepwise optimal selection resulted in less cumulative discounted response than standard QTL selection for QTL with negative dominance. The benefit of optimal over stepwise optimal selection was limited (less than 4%) for most cases, except for overdominant QTL. These results indicate that optimizing selection on an identified QTL can result in greater responses to selection but that extra responses tend to be limited for the situations studied here of single-stage purebred selection on a single QTL for a trait observed on both sexes.

Animals↗
PubMed2003

The phenomenology of niche evolution via quantitative traits in a 'black-hole' sink.

Previous studies of adaptive evolution in sink habitats (in which isolated populations of a species cannot persist deterministically) have highlighted the importance of demographic constraints in slowing such evolution, and of immigration in facilitating adaptation. These studies have relied upon either single-locus models or deterministic quantitative genetic formulations. We use individual-based simulations to examine adaptive evolution in a 'black-hole' sink environment where fitness is governed by a polygenic character. The simulations track both the number of individuals and their multi-locus genotypes, and incorporate, in a natural manner, both demographic and genetic stochastic processes. In agreement with previous studies, our findings reveal the central parts played by demographic constraints and immigration in adaptation within a sink (adaptation is more difficult in environments with low absolute fitness, and higher immigration can accelerate adaptation). A novel finding is that there is a 'punctuational' pattern in adaptive evolution in sink environments. Populations typically stay maladapted for a long time, and then rapidly shift into a relatively adapted state, in which persistence no longer depends upon recurrent immigration.

Animals↗
PubMed1999

Method to detect genotype-environment interactions for quantitative trait loci in association studies.

Khoury et al. (Am J Hum Genet 1988;42:89-95 and Am J Epidemiol 1993;137:1241-50) presented an epidemiologic approach to examine genotype-environment interaction in situations where the disease is either present or absent. In this article, the author extends the approach of Khoury et al. to quantitative outcome variables. This extension is relevant for diseases that are extremes on a continuum or when continuous risk factors are studied. To account for a possible admixture of subgroups in the sample, tests for genotype-environment interaction are discussed for designs with parents as controls as well as without parents as controls. Assuming two environmental conditions, the author demonstrates how the power of these tests can be calculated and used to estimate the sample sizes needed to detect genotype-environment interaction in a variety of conditions. In addition, he analyzes simulated data to demonstrate the detection of different mechanisms of genotype-environment interaction and to study the effectiveness of this approach to identify the correct mechanism. Finally, extensions to multiple environmental conditions and designs with multiple subjects per family are discussed.

Analysis of Variance↗
PubMed2006

Quantitative trait associated microarray gene expression data analysis.

Selection on phenotypes may cause genetic change. To understand the relationship between phenotype and gene expression from an evolutionary viewpoint, it is important to study the concordance between gene expression and profiles of phenotypes. In this study, we use a novel method of clustering to identify genes whose expression profiles are related to a quantitative phenotype. Cluster analysis of gene expression data aims at classifying genes into several different groups based on the similarity of their expression profiles across multiple conditions. The hope is that genes that are classified into the same clusters may share underlying regulatory elements or may be a part of the same metabolic pathways. Current methods for examining the association between phenotype and gene expression are limited to linear association measured by the correlation between individual gene expression values and phenotype. Genes may be associated with the phenotype in a nonlinear fashion. In addition, groups of genes that share a particular pattern in their relationship to phenotype may be of evolutionary interest. In this study, we develop a method to group genes based on orthogonal polynomials under a multivariate Gaussian mixture model. The effect of each expressed gene on the phenotype is partitioned into a cluster mean and a random deviation from the mean. Genes can also be clustered based on a time series. Parameters are estimated using the expectation-maximization algorithm and implemented in SAS. The method is verified with simulated data and demonstrated with experimental data from 2 studies, one clusters with respect to severity of disease in Alzheimer's patients and another clusters data for a rat fracture healing study over time. We find significant evidence of nonlinear associations in both studies and successfully describe these patterns with our method. We give detailed instructions and provide a working program that allows others to directly implement this method in their own analyses.

Animals↗
PubMed2003

Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon.

A BC(2)F(2) population developed from an interspecific cross between Oryza sativa (cv IR64) and O. rufipogon (IRGC 105491) was used in an advanced backcross QTL analysis to identify and introduce agronomically useful genes from this wild relative into the cultivated gene pool. The objectives of this study were: (1) to identify putative yield and yield component QTLs that can be useful to improve the elite cultivar IR64; (2) to compare the QTLs within this study with previously reported QTLs in rice as the basis for identifying QTLs that are stable across different environments and genetic backgrounds; and (3) to compare the identified QTLs with previously reported QTLs from maize to examine the degree of QTL conservation across the grass family. Two hundred eighty-five families were evaluated in two field environments in Indonesia, with two replications each, for 12 agronomic traits. A total of 165 markers consisting of 131 SSRs and 34 RFLPs were used to construct the genetic linkage map. By employing interval mapping and composite interval mapping, 42 QTLs were identified. Despite its inferior performance, 33% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield and yield components in the IR64 background. Twenty-two QTLs (53.4%) were located in similar regions as previously reported rice QTLs, suggesting the existence of stable QTLs across genetic backgrounds and environments. Twenty QTLs (47.6%) were exclusively detected in this study, uncovering potentially novel alleles from the wild, some of which might improve the performance of the tropical indica variety IR64. Additionally, several QTLs for plant height, grain weight, and flowering time detected in this study corresponded to homeologous regions in maize containing previously detected maize QTLs for these traits.

Base Sequence↗
PubMed2001

Quantitative trait loci for upper thermal tolerance in outbred strains of rainbow trout (Oncorhynchus mykiss).

The expression of three putative QTL for upper thermal tolerance (UTT) was examined in two strains of outbred rainbow trout unselected for this trait using simple-sequence repeat (SSR; microsatellite) markers associated with UTT in backcrosses of lines selected on this trait. Two-way diallel lots in the third generation of an outbred pedigree were exposed to an acute thermal challenge. QTL detection was performed separately by each second-generation parent within each diallel lot, incorporating the effects of full sib families and correlated traits. Inheritance of different alleles at the SSR Ssa20.19NUIG from the sire 93-32-1 was strongly associated with the thermal tolerance of his half sib progeny, explaining 7.5% of their phenotypic variance in this trait. A hierarchical linear model incorporating allelic inheritance from all four grandsires of the experimental diallels (in addition to family specific and covariate trait effects) was also used to detect associations between the SSR and thermal tolerance in their third-generation grandprogeny. Ssa20.19NUIG was strongly associated with thermal tolerance in the grandprogeny of the grandsire G(0)SVM2. The generally stronger marker-trait associations found in male parents may be partially due to reduced chromosomal recombination rates in male salmonids compared to females. These results indicate the effects of a QTL on a fitness-related trait in unselected populations of rainbow trout.

Alleles↗