The Site Frequency/Dosage Spectrum of Autopolyploid Populations

Effects of polyploidization and their evolutionary implications are revealed by heritable polyploidy in the haplodiploid wasp Nasonia vitripennis

Recurrent polyploidization occurred in the evolutionary history of most Eukaryota. However, how neopolyploid detriment (sterility, gigantism, gene dosage imbalances) has been overcome and even been bridged to evolutionary advantage (gene network diversification, mass radiation, range expansion) is largely unknown, particularly for animals. We used the parasitoid wasp Nasonia vitripennis, a rare insect system with heritable polyploidy, to begin addressing this knowledge gap. In Hymenoptera the sexes have different ploidies (haploid males, diploid females) and neopolyploids (diploid males, triploid females) occur for various species. Although such polyploids are usually sterile, those of N. vitripennis are reproductively capable and can even establish stable polyploid lines. To assess the effects of polyploidization, we compared a long-established polyploid line, the Whiting polyploid line (WPL) and a newly generated transformer knockdown line (tKDL) for fitness traits, absolute gene expression, and cell size and number. WPL polyploids have high male fitness and low female fecundity, while tKDL polyploids have poor male mate competition ability and high fertility. WPL has larger cells and cell number reduction, but the tKDL does not differ in this respect. Expression analyses of two housekeeping genes indicated that gene dosage is linked to sex irrespective of ploidy. Our study suggests that polyploid phenotypic variation may explain why some polyploid lineages thrive and others die out; a commonly proposed but difficult-to-test hypothesis. This documentation of diploid males (tKDL) with impaired competitive mating ability; triploid females with high fitness variation; and hymenopteran sexual dosage compensation (despite the lack of sex chromosomes) all challenges general assumptions on hymenopteran biology. We conclude that polyploidization is dependent on the duplicated genome characteristics and that genomes of different lines are unequally suited to survive diploidization. These results demonstrate the utility of N. vitripennis for delineating mechanisms of animal polyploid evolution, analogous to more advanced polyploid plant models.

Quantitative evaluation of nonlinear methods for population structure visualization and inference

Population structure (also called genetic structure and population stratification) is the presence of a systematic difference in allele frequencies between subpopulations in a population as a result of nonrandom mating between individuals. It can be informative of genetic ancestry, and in the context of medical genetics, it is an important confounding variable in genome-wide association studies. Recently, many nonlinear dimensionality reduction techniques have been proposed for the population structure visualization task. However, an objective comparison of these techniques has so far been missing from the literature. In this article, we discuss the previously proposed nonlinear techniques and some of their potential weaknesses. We then propose a novel quantitative evaluation methodology for comparing these nonlinear techniques, based on populations for which pedigree is known a priori either through artificial selection or simulation. Based on this evaluation metric, we find graph-based algorithms such as t-SNE and UMAP to be superior to principal component analysis, while neural network-based methods fall behind.

Natural variation and improved genome annotation of the emerging biofuel crop field pennycress (Thlaspi arvense)

The Brassicaceae family comprises more than 3,700 species with a diversity of phenotypic characteristics, including seed oil content and composition. Recently, the global interest in Thlaspi arvense L. (pennycress) has grown as the seed oil composition makes it a suitable source for biodiesel and aviation fuel production. However, many wild traits of this species need to be domesticated to make pennycress ideal for cultivation. Molecular breeding and engineering efforts require the availability of an accurate genome sequence of the species. Here, we describe pennycress genome annotation improvements, using a combination of long- and short-read transcriptome data obtained from RNA derived from embryos of 22 accessions, in addition to public genome and gene expression information. Our analysis identified 27,213 protein-coding genes, as well as on average 6,188 biallelic SNPs. In addition, we used the identified SNPs to evaluate the population structure of our accessions. The data from this analysis support that the accession Ames 32872, originally from Armenia, is highly divergent from the other accessions, while the accessions originating from Canada and the United States cluster together. When we evaluated the likely signatures of natural selection from alternative SNPs, we found 7 candidate genes under likely recent positive selection. These genes are enriched with functions related to amino acid metabolism and lipid biosynthesis and highlight possible future targets for crop improvement efforts in pennycress.

Model-based genotype and ancestry estimation for potential hybrids with mixed-ploidy

Non-random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed-ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, called entropy, which can use low-depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed-ploidy individuals (including sex chromosomes and autosomes within individuals). Our analysis of simulated data illustrated the trade-off between sequencing depth and genome coverage and found lower error associated with low-depth sequencing across a larger fraction of the genome than with high-depth sequencing across a smaller fraction of the genome. The model has high accuracy and sensitivity as verified with simulated data and through analysis of admixture among populations of diploid and tetraploid Arabidopsis arenosa.