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Optimization of sampling designs for pedigrees and association studies.

Olivier David1, Arnaud Le Rouzic2, Christine Dillmann3

  • 1Université Paris-Saclay, INRAE, MaIAGE, 78350, Jouy-en-Josas, France.

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|April 20, 2021
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Summary

Optimizing sampling in genetic studies improves statistical analysis precision. This research introduces stratified sampling and D-optimality, considering mutation effects for pedigrees and enhancing joint estimation for association studies.

Keywords:
Bayesian statisticsgenetic algorithmhigh-dimensional statisticsoptimal designsquantitative genetics

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Area of Science:

  • Quantitative genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Phenotyping related individuals is crucial for understanding genotype-phenotype relationships.
  • Accurate estimation of breeding values and locus effects relies on precise statistical analysis.
  • When complete phenotyping is infeasible, strategic population sampling is essential.

Purpose of the Study:

  • To develop and evaluate optimized sampling designs for genetic studies.
  • To improve the precision of statistical analyses in pedigree and association studies.
  • To investigate the impact of mutation and genetic architecture on sampling strategies.

Main Methods:

  • Development of stratified sampling and D-optimality methods.
  • Application of sampling designs to pedigree data across multiple generations.
  • Evaluation of sampling strategies for association studies with varying genetic architectures.

Main Results:

  • Optimized sampling for pedigrees must account for mutation, prioritizing later generations with larger mutation effects.
  • Sampling designs enhance joint estimation of breeding values and locus effects, particularly with small sample sizes and simple genetic architectures.
  • For traits controlled by few loci, optimized designs resemble classical regression models, favoring homozygous individuals.

Conclusions:

  • Optimized sampling designs are critical for efficient genetic studies when not all individuals can be phenotyped.
  • Mutation effects significantly influence optimal pedigree sampling strategies.
  • The effectiveness of optimized designs in association studies depends on sample size and the complexity of the trait's genetic architecture.