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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Published on: June 21, 2018

Computer simulation of marker-assisted selection utilizing linkage disequilibrium.

W Zhang¹, C Smith

¹Center for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, N1G 2W1, Guelph, Ontario, Canada.

TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik

|November 9, 2013

Summary

Marker-assisted selection (MAS) effectively boosts genetic gain when combined with conventional breeding methods. Higher initial linkage disequilibrium between markers and quantitative trait loci (QTL) improves MAS efficacy, approaching direct QTL selection with close linkage.

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Area of Science:

Quantitative genetics
Animal and plant breeding
Genomic selection

Background:

Marker-assisted selection (MAS) leverages linkage disequilibrium (LD) between genetic markers and quantitative trait loci (QTL) for improved breeding outcomes.
Understanding the impact of initial LD levels and population structure on MAS effectiveness is crucial for optimizing selection strategies.

Purpose of the Study:

To evaluate the efficacy of MAS utilizing LD for genetic gain in simulated populations.
To compare MAS with conventional best linear unbiased prediction (BLUP) and a combined selection approach.

Main Methods:

Simulated four base populations (F2, F5, F10, F20) with varying initial LD levels.
Implemented selection based on marker-QTL associations (MAS), BLUP, and a combined (COMB) strategy.
Varied parameters including heritability, initial LD, and QTL effect distribution across a simulated genome.

Main Results:

Initial LD significantly influenced MAS genetic gain, with higher LD yielding greater responses (F2>F5>F10>F20).
Conventional BLUP often produced higher genetic gains than MAS alone, but the COMB approach yielded substantially greater responses.
MAS selection reduced LD over generations, and closer marker-QTL proximity enhanced LD for selection.

Conclusions:

MAS is most effective when initial linkage disequilibrium is high and can be significantly enhanced when combined with BLUP.
Future improvements in MAS rely on detecting markers in closer proximity to QTLs, potentially enabling selection equivalent to direct QTL analysis.
The study highlights the importance of population structure and LD management in maximizing genetic gains through marker-assisted breeding.