scholarly journals The effects of selection on linkage analysis for quantitative traits.

Genetics ◽  
1992 ◽  
Vol 132 (4) ◽  
pp. 1177-1185 ◽  
Author(s):  
M J Mackinnon ◽  
M A Georges
Keyword(s):  
Allele Frequency ◽  
Quantitative Trait ◽  
Recombination Rate ◽  
Quantitative Traits ◽  
Sample Selection ◽  
Complex Function ◽  
Substitution Effect ◽  
Marker Locus ◽  
Animal Populations ◽  
Allele Substitution

Abstract The effects of within-sample selection on the outcome of analyses detecting linkage between genetic markers and quantitative traits were studied. It was found that selection by truncation for the trait of interest significantly reduces the differences between marker genotype means thus reducing the power to detect linked quantitative trait loci (QTL). The size of this reduction is a function of proportion selected, the magnitude of the QTL effect, recombination rate between the marker locus and the QTL, and the allele frequency of the QTL. Proportion selected was the most influential of these factors on bias, e.g., for an allele substitution effect of one standard deviation unit, selecting the top 80%, 50% or 20% of the population required 2, 6 or 24 times the number of progeny, respectively, to offset the loss of power caused by this selection. The effect on power was approximately linear with respect to the size of gene effect, almost invariant to recombination rate, and a complex function of QTL allele frequency. It was concluded that experimental samples from animal populations which have been subjected to even minor amounts of selection will be inefficient in yielding information on linkage between markers and loci influencing the quantitative trait under selection.

scholarly journals A classical setting for associations between markers and loci affecting quantitative traits

1999 ◽  
Vol 74 (3) ◽  
pp. 271-277 ◽  
Author(s):  
DAHLIA M. NIELSEN ◽  
B. S. WEIR
Keyword(s):  
Genetic Marker ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Genetic Variance ◽  
Genetic Model ◽  
Marker Locus ◽  
Multiple Alleles ◽  
Classical Setting ◽  
Tests Of Association ◽  
Trait Locus

We examine the relationships between a genetic marker and a locus affecting a quantitative trait by decomposing the genetic effects of the marker locus into additive and dominance effects under a classical genetic model. We discuss the structure of the associations between the marker and the trait locus, paying attention to non-random union of gametes, multiple alleles at the marker and trait loci, and non-additivity of allelic effects at the trait locus. We consider that this greater-than-usual level of generality leads to additional insights, in a way reminiscent of Cockerham's decomposition of genetic variance into five terms: three terms in addition to the usual additive and dominance terms. Using our framework, we examine several common tests of association between a marker and a trait.

scholarly journals Selection in backcross programmes

2005 ◽  
Vol 360 (1459) ◽  
pp. 1503-1511 ◽  
Author(s):  
Frédéric Hospital
Keyword(s):  
Molecular Markers ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Recurrent Parent ◽  
Breeding Scheme ◽  
Animal Populations ◽  
Trait Loci ◽  
Donor Parent ◽  
Genetic Value

Backcrossing is a well-known and long established breeding scheme where a characteristic is introgressed from a donor parent into the genomic background of a recurrent parent. The various uses of backcrossing in modern genetics, particularly with the help of molecular markers, are reviewed here. Selection in backcross programmes is used to either improve the genetic value of plant and animal populations or fine map quantitative trait loci. Both cases are helpful in our understanding of the genetic bases of quantitative traits variation.

scholarly journals Inferring Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 457-467 ◽  
Author(s):  
Z W Luo ◽  
S H Tao ◽  
Z-B Zeng
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Random Mating ◽  
Natural Populations ◽  
Polymorphic Marker ◽  
Marker Locus ◽  
Model Parameters ◽  
Phenotypic Variance ◽  
Wide Range ◽  
Trait Locus

Abstract Three approaches are proposed in this study for detecting or estimating linkage disequilibrium between a polymorphic marker locus and a locus affecting quantitative genetic variation using the sample from random mating populations. It is shown that the disequilibrium over a wide range of circumstances may be detected with a power of 80% by using phenotypic records and marker genotypes of a few hundred individuals. Comparison of ANOVA and regression methods in this article to the transmission disequilibrium test (TDT) shows that, given the genetic variance explained by the trait locus, the power of TDT depends on the trait allele frequency, whereas the power of ANOVA and regression analyses is relatively independent from the allelic frequency. The TDT method is more powerful when the trait allele frequency is low, but much less powerful when it is high. The likelihood analysis provides reliable estimation of the model parameters when the QTL variance is at least 10% of the phenotypic variance and the sample size of a few hundred is used. Potential use of these estimates in mapping the trait locus is also discussed.

scholarly journals Consequences of Recombination Rate Variation on Quantitative Trait Locus Mapping Studies: Simulations Based on the Drosophila melanogaster Genome

Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 581-588
Author(s):  
Mohamed A F Noor ◽  
Aimee L Cunningham ◽  
John C Larkin
Keyword(s):  
Quantitative Trait Locus ◽  
Drosophila Melanogaster ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Recombination Rate ◽  
Genome Project ◽  
Gene Density ◽  
Rate Variation ◽  
Trait Locus ◽  
Recombination Rate Variation

Abstract We examine the effect of variation in gene density per centimorgan on quantitative trait locus (QTL) mapping studies using data from the Drosophila melanogaster genome project and documented regional rates of recombination. There is tremendous variation in gene density per centimorgan across this genome, and we observe that this variation can cause systematic biases in QTL mapping studies. Specifically, in our simulated mapping experiments of 50 equal-effect QTL distributed randomly across the physical genome, very strong QTL are consistently detected near the centromeres of the two major autosomes, and few or no QTL are often detected on the X chromosome. This pattern persisted with varying heritability, marker density, QTL effect sizes, and transgressive segregation. Our results are consistent with empirical data collected from QTL mapping studies of this species and its close relatives, and they explain the “small X-effect” that has been documented in genetic studies of sexual isolation in the D. melanogaster group. Because of the biases resulting from recombination rate variation, results of QTL mapping studies should be taken as hypotheses to be tested by additional genetic methods, particularly in species for which detailed genetic and physical genome maps are not available.

scholarly journals Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

Genetics ◽  
1989 ◽  
Vol 121 (1) ◽  
pp. 185-199 ◽  
Author(s):  
E S Lander ◽  
D Botstein
Keyword(s):  
Dna Markers ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Human Genetics ◽  
Substantial Reduction ◽  
Interval Mapping ◽  
Genetic Dissection ◽  
Linkage Maps ◽  
Phenotypic Effect ◽  
Length Polymorphisms

Abstract The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.

scholarly journals R/qtlcharts: interactive graphics for quantitative trait locus mapping

2014 ◽  
Author(s):  
Karl W Broman
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait Locus Mapping ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
R Package ◽  
High Dimensional ◽  
Interactive Graphics ◽  
Phenotype Data ◽  
Trait Locus ◽  
Locus Mapping

Every data visualization can be improved with some level of interactivity. Interactive graphics hold particular promise for the exploration of high-dimensional data. R/qtlcharts is an R package to create interactive graphics for experiments to map quantitative trait loci (QTL; genetic loci that influence quantitative traits). R/qtlcharts serves as a companion to the R/qtl package, providing interactive versions of R/qtl's static graphs, as well as additional interactive graphs for the exploration of high-dimensional genotype and phenotype data.

scholarly journals The Theory and Applications of Measuring Broad-Range and Chromosome-Wide Recombination Rate from Allele Frequency Decay around a Selected Locus

2020 ◽  
Vol 37 (12) ◽  
pp. 3654-3671
Author(s):  
Kevin H -C Wei ◽  
Aditya Mantha ◽  
Doris Bachtrog
Keyword(s):  
Genetic Distance ◽  
Allele Frequency ◽  
Recombination Rate ◽  
High Throughput Sequencing ◽  
Genetic Material ◽  
Cost Effective ◽  
Genetic Distances ◽  
Recombination Rates ◽  
Marker Selection ◽  
Cost Effective Approach

Abstract Recombination is the exchange of genetic material between homologous chromosomes via physical crossovers. High-throughput sequencing approaches detect crossovers genome wide to produce recombination rate maps but are difficult to scale as they require large numbers of recombinants individually sequenced. We present a simple and scalable pooled-sequencing approach to experimentally infer near chromosome-wide recombination rates by taking advantage of non-Mendelian allele frequency generated from a fitness differential at a locus under selection. As more crossovers decouple the selected locus from distal loci, the distorted allele frequency attenuates distally toward Mendelian and can be used to estimate the genetic distance. Here, we use marker selection to generate distorted allele frequency and theoretically derive the mathematical relationships between allele frequency attenuation, genetic distance, and recombination rate in marker-selected pools. We implemented nonlinear curve-fitting methods that robustly estimate the allele frequency decay from batch sequencing of pooled individuals and derive chromosome-wide genetic distance and recombination rates. Empirically, we show that marker-selected pools closely recapitulate genetic distances inferred from scoring recombinants. Using this method, we generated novel recombination rate maps of three wild-derived strains of Drosophila melanogaster, which strongly correlate with previous measurements. Moreover, we show that this approach can be extended to estimate chromosome-wide crossover interference with reciprocal marker selection and discuss how it can be applied in the absence of visible markers. Altogether, we find that our method is a simple and cost-effective approach to generate chromosome-wide recombination rate maps requiring only one or two libraries.

Variation at CPE but not CEBPA appears to be associated with intramuscular fat deposition in the longissimus muscle of cattle

2009 ◽  
Vol 49 (7) ◽  
pp. 558 ◽  
Author(s):  
William Barendse ◽  
Rowan J. Bunch ◽  
Blair E. Harrison
Keyword(s):  
Substitution Effect ◽  
Intramuscular Fat ◽  
High Linkage Disequilibrium ◽  
Substitution Effects ◽  
Phenotypic Variance ◽  
Nucleotide Polymorphisms ◽  
Allele Substitution Effect ◽  
Single Nucleotide ◽  
Enhancer Binding Protein ◽  
Allele Substitution

An important step in the localisation of quantitative trait loci is the confirmation of trait-marker associations in independent studies. In this report, we test three single nucleotide polymorphisms (SNP) of two genes for associations to intramuscular fat (IMF) measurements in cattle. We genotyped SNP of carboxypeptidase E (CPE) and ccaat/enhancer binding protein, α (CEBPA) in a sample of a total of 813 cattle of taurine, composite and indicine breeds. All three polymorphisms showed significant differences between breeds, with the widest range found in CEBPA:g.271A > C where the A allele frequency ranged from P = 0.07 in Brahman to 0.88 in Shorthorn. The taurine breeds showed high linkage disequilibrium between the pair of CPE SNP, with all four breeds showing r2 = 1.0. The Brahman and Santa Gertrudis showed r2 ≤ 0.17. Both CPE:g.445C > T and CPE:g.601C > T SNP showed significant allele substitution effects to IMF in animals of taurine ancestry, with an allele substitution effect of α = 0.22, P = 0.020 for CPE:g.445C > T, explaining 0.4% of the phenotypic variance.

scholarly journals The use of selection experiments for detecting quantitative trait loci

1997 ◽  
Vol 69 (3) ◽  
pp. 227-232 ◽  
Author(s):  
L. OLLIVIER ◽  
L. A. MESSER ◽  
M. F. ROTHSCHILD ◽  
C. LEGAULT
Keyword(s):  
Quantitative Trait ◽  
Marker Locus ◽  
Frequency Change ◽  
Gene Frequencies ◽  
Marker Allele ◽  
Gene Effects ◽  
Selection Experiments ◽  
Frequency Changes ◽  
Combined Selection ◽  
Number Of Individuals

Gene frequency changes following selection may reveal the existence of gene effects on the trait selected. Loci for the selected quantitative trait (SQTL) may thus be detected. Additionally, one can estimate the average effect (α) of a marker allele associated with an SQTL from the allele frequency change (Δq) due to selection of given intensity (i). In a sample of unrelated individuals, it is optimal to select the upper and lower 27% for generating Δq in order to estimate α. For a given number of individuals genotyped, this estimator is 0·25i2 times more efficient than the classical estimator of α, based on the regression of the trait on the genotype at the marker locus. The method is extended to selection criteria using information from relatives, showing that combined selection considerably increases the efficiency of estimation for traits of low heritability. The method has been applied to the detection of SQTL in a selection experiment in which the trait selected was pig litter size averaged over the first four parities, with i=3. Results for four genes are provided, one of which yielded a highly significant effect. The conditions required for valid application of the method are discussed, including selection experiments over several generations. Additional advantages of the method can be anticipated from determining gene frequencies on pooled samples of blood or DNA.

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