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Multiple Allele Traits01:49

Multiple Allele Traits

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...

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Linear models for joint association and linkage QTL mapping.

Andrés Legarra1, Rohan L Fernando

  • 1INRA, UR631, BP 52627, 31326 Castanet Tolosan, France. andres.legarra@toulouse.inra.fr

Genetics, Selection, Evolution : GSE
|October 1, 2009
PubMed
Summary

A new linear model theory enhances quantitative trait loci (QTL) mapping by combining populational and within-family linkage, offering accurate QTL allele effects across general pedigrees. This approach simplifies computations compared to existing methods.

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Area of Science:

  • Quantitative genetics
  • Statistical genomics
  • Bioinformatics

Background:

  • Populational and within-family linkage are key for QTL mapping and marker-assisted selection.
  • Combining both linkage types improves QTL localization accuracy.
  • Existing models face limitations in complexity or applicability to specific family structures.

Purpose of the Study:

  • To present a linear model theory for estimating additive QTL allele effects in general pedigrees.
  • To account for linkage disequilibrium between QTLs and markers.
  • To provide a robust framework for QTL mapping using dense marker maps.

Main Methods:

  • Developed linear model theory based on association analysis in founders.
  • Incorporated transmission probabilities for descendant QTL effects.
  • Allowed for non-complete linkage disequilibrium.
  • Presented Haley-Knott type regression and a general mixed model for different pedigrees.
  • Compared regression method performance with an Identity By Descent (IBD) method via simulation.

Main Results:

  • The linear model effectively estimates additive QTL effects in general pedigrees.
  • The model accommodates linkage disequilibrium between QTLs and markers.
  • The Haley-Knott type regression offers a simple, implementable approach for half-sib families.
  • The general mixed model handles complex pedigrees.
  • Simulations showed comparable accuracies to IBD methods, with IBD exhibiting a bias towards the region's center.

Conclusions:

  • Linear model theory provides a versatile and computationally simple framework for QTL mapping with dense marker data.
  • The proposed methods offer accurate QTL localization.
  • The framework is readily extendable to genomic selection and multi-QTL mapping.