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Theory of genome-wide association for QTL detection

Code: 9781786767806
Henk Bovenhuis, Wageningen University and Research, The Netherlands; Frédéric Farnir, Liège University, Belgium; and Pascale Le Roy, French National Institute for Agricultural Research, France

Chapter synopsis: To identify the regions on the genome that influence traits, Genome Wide Association Study (GWAS) uses the information of Linkage Disequilibrium (LD) between a QTL and neighboring genetic markers. LD is created by mutations and recombinations, but populations mixture also generates gametic phase disequilibrium at the genome level. Commonly GWAS are performed using a mixed model. The statistical model contains the unknown SNP effect and interest is in estimating this effect based on the sample obtained from the population, and testing its significance. Instead of analyzing one SNP at a time, it is also possible to include all SNP simultaneously in the model. It is common to control the overall type 1 error rate to avoid false positives. A single SNP GWAS analysis of egg weight in layers illustrates this chapter on the theory of GWAS for QTL detection. In conclusion, GWAS advantages and limitations are discussed.

DOI: £25.00
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Table of contents 1 Introduction 2 Principles of genome-wide association studies (GWAS) 3 Statistical methods 4 Using a genome-wide association study (GWAS) for QTL detection in poultry 5 Conclusion 6 References

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