Analysis of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in STRUCTURE, ADMIXTURE, FASTSTRUCTURE and INSTRUCT under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, STRUCTURE was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown dosage or dominant markers). Still, since STRUCTURE was comparatively slow, the much faster but less powerful FASTSTRUCTURE provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, for large numbers of loci (>1000) with known dosage k-means clustering was superior to FASTSTRUCTURE in terms of power and speed. We conclude that STRUCTURE is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.
- MeSH
- Diploidy MeSH
- Genetic Variation genetics MeSH
- Genetic Markers genetics MeSH
- Genotype MeSH
- Polymorphism, Single Nucleotide genetics MeSH
- Microsatellite Repeats genetics MeSH
- Ploidies * MeSH
- Genetics, Population statistics & numerical data MeSH
- Cluster Analysis MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
We consider a one-dimensional population genetics model for the advance of an advantageous gene. The model is described by the semilinear Fisher equation with unbalanced bistable non-Lipschitzian nonlinearity f(u). The "nonsmoothness" of f allows for the appearance of travelling waves with a new, more realistic profile. We study existence, uniqueness, and long-time asymptotic behavior of the solutions u(x, t), [Formula: see text]. We prove also the existence and uniqueness (up to a spatial shift) of a travelling wave U. Our main result is the uniform convergence (for [Formula: see text]) of every solution u(x, t) of the Cauchy problem to a single travelling wave [Formula: see text] as [Formula: see text]. The speed c and the travelling wave U are determined uniquely by f, whereas the shift [Formula: see text] is determined by the initial data.
- MeSH
- Humans MeSH
- Mathematical Concepts MeSH
- Models, Genetic * MeSH
- Nonlinear Dynamics MeSH
- Population Dynamics statistics & numerical data MeSH
- Genetics, Population statistics & numerical data MeSH
- Models, Statistical MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
