Rare sex or out of reach equilibrium? The dynamics of F IS in partially clonal organisms.

BACKGROUND: Partially clonal organisms are very common in nature, yet the influence of partial asexuality on the temporal dynamics of genetic diversity remains poorly understood. Mathematical models accounting for clonality predict deviations only for extremely rare sex and only towards mean inbreeding coefficient [Formula: see text]. Yet in partially clonal species, both F IS < 0 and F IS > 0 are frequently observed also in populations where there is evidence for a significant amount of sexual reproduction. Here, we studied the joint effects of partial clonality, mutation and genetic drift with a state-and-time discrete Markov chain model to describe the dynamics of F IS over time under increasing rates of clonality. RESULTS: Results of the mathematical model and simulations show that partial clonality slows down the asymptotic convergence to F IS = 0. Thus, although clonality alone does not lead to departures from Hardy-Weinberg expectations once reached the final equilibrium state, both negative and positive F IS values can arise transiently even at intermediate rates of clonality. More importantly, such "transient" departures from Hardy Weinberg proportions may last long as clonality tunes up the temporal variation of F IS and reduces its rate of change over time, leading to a hyperbolic increase of the maximal time needed to reach the final mean [Formula: see text] value expected at equilibrium. CONCLUSION: Our results argue for a dynamical interpretation of F IS in clonal populations. Negative values cannot be interpreted as unequivocal evidence for extremely scarce sex but also as intermediate rates of clonality in finite populations. Complementary observations (e.g. frequency distribution of multiloci genotypes, population history) or time series data may help to discriminate between different possible conclusions on the extent of clonality when mean [Formula: see text] values deviating from zero and/or a large variation of F IS over loci are observed.

Untangling the hedge: Genetic diversity in clonally and sexually transmitted genomes of European wild roses, Rosa L.

While European wild roses are abundant and widely distributed, their morphological taxonomy is complicated and ambiguous. In particular, the polyploid Rosa section Caninae (dogroses) is characterised by its unusual meiosis, causing simultaneous clonal and sexual transmission of sub-genomes. This hemisexual reproduction, which often co-occurs with vegetative reproduction, defies the standard definition of species boundaries. We analysed seven highly polymorphic microsatellite loci, scored for over 2 600 Rosa samples of differing ploidy, collected across Europe within three independent research projects. Based on their morphology, these samples had been identified as belonging to 21 dogrose and five other native rose species. We quantified the degree of clonality within species and at individual sampling sites. We then compared the genetic structure within our data to current rose morpho-systematics and searched for hemisexually co-inherited sets of alleles at individual loci. We found considerably fewer copies of identical multi-locus genotypes in dogroses than in roses with regular meiosis, with some variation recorded among species. While clonality showed no detectable geographic pattern, some genotypes appeared to be more widespread. Microsatellite data confirmed the current classification of subsections, but they did not support most of the generally accepted dogrose microspecies. Under canina meiosis, we found co-inherited sets of alleles as expected, but could not distinguish between sexually and clonally inherited sub-genomes, with only some of the detected allele combinations being lineage-specific.

Software Choice and Sequencing Coverage Can Impact Plastid Genome Assembly-A Case Study in the Narrow Endemic Calligonum bakuense.

Most plastid genome sequences are assembled from short-read whole-genome sequencing data, yet the impact that sequencing coverage and the choice of assembly software can have on the accuracy of the resulting assemblies is poorly understood. In this study, we test the impact of both factors on plastid genome assembly in the threatened and rare endemic shrub Calligonum bakuense. We aim to characterize the differences across plastid genome assemblies generated by different assembly software tools and levels of sequencing coverage and to determine if these differences are large enough to affect the phylogenetic position inferred for C. bakuense compared to congeners. Four assembly software tools (FastPlast, GetOrganelle, IOGA, and NOVOPlasty) and seven levels of sequencing coverage across the plastid genome (original sequencing depth, 2,000x, 1,000x, 500x, 250x, 100x, and 50x) are compared in our analyses. The resulting assemblies are evaluated with regard to reproducibility, contig number, gene complement, inverted repeat length, and computation time; the impact of sequence differences on phylogenetic reconstruction is assessed. Our results show that software choice can have a considerable impact on the accuracy and reproducibility of plastid genome assembly and that GetOrganelle produces the most consistent assemblies for C. bakuense. Moreover, we demonstrate that a sequencing coverage between 500x and 100x can reduce both the sequence variability across assembly contigs and computation time. When comparing the most reliable plastid genome assemblies of C. bakuense, a sequence difference in only three nucleotide positions is detected, which is less than the difference potentially introduced through software choice.

Interpretation and approximation tools for big, dense Markov chain transition matrices in population genetics.

BACKGROUND: Markov chains are a common framework for individual-based state and time discrete models in evolution. Though they played an important role in the development of basic population genetic theory, the analysis of more complex evolutionary scenarios typically involves approximation with other types of models. As the number of states increases, the big, dense transition matrices involved become increasingly unwieldy. However, advances in computational technology continue to reduce the challenges of "big data", thus giving new potential to state-rich Markov chains in theoretical population genetics. RESULTS: Using a population genetic model based on genotype frequencies as an example, we propose a set of methods to assist in the computation and interpretation of big, dense Markov chain transition matrices. With the help of network analysis, we demonstrate how they can be transformed into clear and easily interpretable graphs, providing a new perspective even on the classic case of a randomly mating, finite population with mutation. Moreover, we describe an algorithm to save computer memory by substituting the original matrix with a sparse approximate while preserving its mathematically important properties, including a closely corresponding dominant (normalized) eigenvector. A global sensitivity analysis of the approximation results in our example shows that size reduction of more than 90 % is possible without significantly affecting the basic model results. Sample implementations of our methods are collected in the Python module mamoth. CONCLUSION: Our methods help to make stochastic population genetic models involving big, dense transition matrices computationally feasible. Our visualization techniques provide new ways to explore such models and concisely present the results. Thus, our methods will contribute to establish state-rich Markov chains as a valuable supplement to the diversity of population genetic models currently employed, providing interesting new details about evolution e.g. under non-standard reproductive systems such as partial clonality.