ArticleGenetics2015
Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.
Article in Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Strength of selection potentiates distinct adaptive responses in an evolution experiment with outcrossing yeast.G3 (Bethesda, Md.) · 2026Article
- The Genetic Architecture of Venom Resistance: A Novel Approach to Target Identification and Coevolutionary Discovery.Molecular biology and evolution · 2026Article
- Leveraging low-cost short-read sequencing: revolutionizing complex trait genetics.Molecular biology and evolution · 2026Article
- Article
- A Path Integral Approach for Allele Frequency Dynamics Under Polygenic Selection.bioRxiv : the preprint server for biology · 2024Article
- Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping.Genetics, selection, evolution : GSE · 2023Article
- Natural alleles at theProceedings. Biological sciences · 2022Article
- Highly Parallel Genomic Selection Response in Replicated Drosophila melanogaster Populations with Reduced Genetic Variation.Genome biology and evolution · 2021Article
- Adaptation and correlated fitness responses over two time scales in Drosophila suzukii populations evolving in different environments.Journal of evolutionary biology · 2021Article
- Complex pleiotropic genetic architecture of evolved heat stress and oxidative stress resistance in the nematode Caenorhabditis remanei.G3 (Bethesda, Md.) · 2021Article
- Novel Genomic Regions Associated with Intramuscular Fatty Acid Composition in Rabbits.Animals : an open access journal from MDPI · 2020Article
- The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics.Evolution letters · 2020Article
- The Effects of Quantitative Trait Architecture on Detection Power in Short-Term Artificial Selection Experiments.G3 (Bethesda, Md.) · 2020Article
- Low concordance of short-term and long-term selection responses in experimental Drosophila populations.Molecular ecology · 2020Article
- Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments.G3 (Bethesda, Md.) · 2019Article
- Next-generation forward genetic screens: using simulated data to improve the design of mapping-by-sequencing experiments in Arabidopsis.Nucleic acids research · 2019Article
- Optimizing the Power to Identify the Genetic Basis of Complex Traits with Evolve and Resequence Studies.Molecular biology and evolution · 2019Article
- Benchmarking software tools for detecting and quantifying selection in evolve and resequencing studies.Genome biology · 2019Article
- Rare genetic variation and balanced polymorphisms are important for survival in global change conditions.Proceedings. Biological sciences · 2019Article
- An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice.eLife · 2019Article
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Authors and funding
2 authors.
Funding
Abstract
Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50-100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.