GENETICS

The P-element, a DNA transposon, has independently invaded two Drosophila species, accompanied by rapid evolution of suppression. In the germline, suppression is mediated primarily by maternally expressed piRNAs, a class of regulatory small RNAs associated with PIWI proteins. The offspring of females that lack P-element-specific piRNAs and males that contain P-elements suffer a syndrome of deleterious phenotypes, including sterility, genome rearrangements, gonadal atrophy, and mutations, while the offspring of the reciprocal cross are normal. These effects, collectively termed hybrid dysgenesis, have been investigated primarily in female D. melanogaster. Here, we study hybrid dysgenesis in male D. simulans. Using an attached-X chromosome stock, we generated genetically identical F1 males that differed only in maternal suppression of the P-element. Using targeted sequencing of P-element breakpoints, we show that P-element transposition is elevated in dysgenic males and confirm a preference for insertion near origins of replication. Using transcriptomics, we show that dysgenic males have elevated P-element expression and reduced splicing suppression, with patterns of gene expression suggesting the loss of mature sperm cells. Fertility assays show higher rates of male sterility but otherwise modest effects on fertility. In conjunction with the transcriptomic data, small RNA sequencing confirms that the piRNA pathway functions in testes. Our results suggest that the P-element may spread more readily through males than females, as transposition rates are similar while fertility defects are less severe in males.

Biobank-scale datasets now routinely include hundreds of thousands to millions of individuals, and as sample sizes grow, close relatives become increasingly prevalent. The convention in population genetics has been to remove close relatives prior to inference, effectively treating them as a nuisance parameter. However, the consequences of this practice for demographic inference, and specifically for estimates of recent effective population size (Ne), have not been rigorously evaluated. Here, we benchmark IBDNe and HapNe-IBD, two widely-used methods for inferring recent Ne from identity-by-descent (IBD) segments, under a range of demographic histories and relative sampling schemes. We show that when individuals are randomly ascertained, retaining all relatives produces the least biased Ne estimates; in contrast, removing even second-degree relatives inflates recent Ne and induces oscillatory artifacts that "ripple", leading to biased estimates up to ten generations into the past. We demonstrate that this ripple effect arises because close relatives contribute IBD segments that are assigned by the model to a range of ancestral ages beyond their true TMRCA, meaning their removal creates signal deficits across multiple generations simultaneously. We further show that deliberately oversampling close relatives produces severe downward bias in recent Ne. To support these analyses, we develop an open-source IBD simulation pipeline using msprime that generates realistic IBD segments under arbitrary demographic histories and Wright-Fisher pedigrees. We provide practical guidelines for IBD simulation schemes incorporating pedigrees and argue that, in the biobank era, retaining close relatives is generally the best practice for IBD-based Ne inference.

The Saccharomyces cerevisiae Pch2 protein is a conserved meiotic AAA+ ATPase whose activity must be tightly regulated to ensure proper chromosome dynamics during meiotic prophase I. Its function relies on remodeling the HORMA-domain protein Hop1, promoting conformational transitions that are essential for chromosome axis organization, checkpoint signaling, and recombination control. Here, we identify threonine 428 (T428), located within a conserved threonine-glutamine (TQ) putative phosphorylation motif, as a critical regulatory residue of Pch2. We found that, in zip1{Delta} cells, the meiotic recombination checkpoint response is partially or completely abolished in the pch2-T428A and pch2-T428D mutants, respectively. Both mutations alter Pch2 subcellular localization, leading to its increased nuclear accumulation; however, forced nuclear exclusion of Pch2-T428A, but not Pch2-T428D, restores the zip1{Delta} meiotic block, indicating an additional effect of the T428D substitution on checkpoint function beyond subcellular distribution. Analysis in synapsis-proficient strains reveals that this residue also plays a critical role in coordinating Hop1 chromosomal enrichment with Mek1 activation along the synaptonemal complex. In contrast to pch2{Delta} or the ATPase-defective pch2-E399Q mutant, introduction of a negative charge at the 428 position uncouples Hop1 accumulation from its phosphorylation, preventing Mek1 activation despite robust Hop1 association with meiotic chromosomes. These findings support emerging models in which Pch2 regulates Hop1 to control not only its chromosomal abundance, but also the maintenance of sufficient levels of Hop1 in a phosphorylation-competent conformation, thereby ensuring proper checkpoint signaling and faithful meiotic progression.

Maternally transmitted Wolbachia often cause cytoplasmic incompatibility (CI), a sperm modification that kills host embryos lacking the endosymbiont. CI produces defects in paternal chromosome replication, condensation, and segregation during the first zygotic cell cycle, but a significant fraction of embryos progress normally through this and subsequent cycles and only exhibit defects at later developmental stages. These results, together with documented CI-induced epigenetic chromatin modifications, suggest heritable chromatin modifications are responsible for the developmentally delayed defects. Here, we conducted a Position-Effect Variegation (PEV) screen in Drosophila melanogaster using In(1)wm4to test for persistent effects on heterochromatin-mediated silencing in adults that survived CI. We show that Wolbachia acts as a variegation suppressor, or Su(var), increasing eye pigment when present in CI-inducing fathers, a reproducible effect observed across several maternal genotypes that differed in CI strength. That is, passage of the In(1)wm4through Wolbachia-infected males limits the spread of heterochromatin into the neighboring euchromatin in the progeny. This effect is consistent with disruption of heterochromatin establishment at the mid-blastula transition, when stochastic spreading of heterochromatin determines whether the displaced white gene is silenced. Surprisingly, maternal Wolbachia did not revert the PEV modification, and in one genotype, Wolbachia increased suppression. Together, our results demonstrate that Wolbachia-mediated chromatin effects persist to adulthood, are not corrected by CifA-dependent rescue, and can be compounded by maternal Wolbachia. These findings establish that rescue is incomplete at the level of heterochromatin-mediated silencing and suggest that CI-specific and constitutive Wolbachia chromatin effects may operate through at least partially independent pathways.

The origin recognition complex (ORC) selects origins of replication and directs the loading of the Mcm2-7 replicative helicase at these sites. Five of the six ORC subunits are related to the AAA+ family of ATPases. Although functions for ATP hydrolysis by Cdc6 and the Mcm2-7 complex have been described, the essential role of ORC ATP hydrolysis remains unclear. We performed a genetic screen in Saccharomyces cerevisiae for suppressors of the lethal phenotype of the orc4-R267A allele, which disrupts ORC ATP hydrolysis in vitro. We identified six causative mutations, five of which are distributed across different ORC subunits. The suppressor mutations in Orc1 and Orc4, but not the other ORC subunits, increase the in vitro helicase loading activity of ATPase-defective ORC (ORC4R). Allele specificity studies showed the alleles specifically suppress defects at ATPase interfaces within the ORC-Cdc6 complex. The sixth allele is a mutation in TOA2, a subunit of the TFIIA general transcription factor. Mutations in the general transcription factors TBP and TFIIB, and the large subunit of RNA Polymerase II also suppressed the orc4-R267A lethality, suggesting that reducing transcription is sufficient for suppression. Our study identifies multiple ways to suppress the lethal phenotype of an ATPase defective ORC allele and reveals a connection between ORC ATP hydrolysis and transcription.

Standard genome-wide association studies (GWASs) are vulnerable to confounding factors, including stratification, assortative mating, and dynastic effects. Family studies such as sibling-based GWAS (sib-GWAS) mitigate such confounding and are becoming the tool of choice for teasing apart direct genetic effects--causal effects of ones genotype on ones own phenotype-- from other factors. However, due in part to their smaller sample sizes, sib-GWAS allelic effect estimates are substantially more variable than standard (i.e., population-based) GWAS estimates. The quantification of this uncertainty is essential for many uses of sib-GWAS, including polygenic scoring, causal inference (e.g., Mendelian randomization), disentangling direct from indirect familial effects, and measuring assortative mating. Here, we investigate sources of uncertainty in sib-GWAS allelic effect estimators. We study their impacts on the biases of three uncertainty measurement methods, including two that are commonly used and a new resampling-based approach we propose. We find that heterogeneity in allelic effects or heteroskedasticity across families (e.g., due to variation in genetic backgrounds or environments) can bias existing methods, and that this bias is more severe for small samples and rare variants. In contrast, the resampling-based approach we propose is approximately unbiased under all scenarios we considered. We validate our theoretical predictions, as well as the importance of effect heterogeneity and heteroskedasticity, using simulations and empirical analysis in the UK Biobank. In sum, this study helps understand the sources of uncertainty in family-based genotype-phenotype association studies and provides a robust method to estimate uncertainty.

Using an abstract computational model of multicellular development, I show that the deleterious effects of gene expression noise on development are heavily buffered by increased ploidy, both from haploid to diploid cells and from diploid to tetraploid ones. Because the development of large multicellular organisms requires at least millions of individual cell divisions and many specifications of cell fate, it is likely impossible for large organisms to sufficiently control expression noise so as to prevent all noise-related errors in fate determination. However, for any given level of noise tolerance, cells of higher ploidy are less likely to suffer fate determination failure, potentially giving an explanation for the preference for larger organisms to have diploid somatic phases. Ploidy, however, is not the only potential mechanism by which differences in noise tolerance might influence hybrid vigor. Diploid hybrids can also display developmental robustness due to the removal of allelic correlations in expression noise. If we flip this perspective, noise-related disruption of development provides a neutral source of inbreeding depression, whereby sequence similarity throughout the genome induces correlated gene expression noise, reducing developmental robustness and pushing diploids back in the direction of haploid developmental fidelity.

Loop extrusion has been clearly shown to be insufficient as a mechanism to explain TAD formation, leaving a large gap in our understanding of how the specificity of TAD boundary interactions and inter-TAD chromosomal interactions are determined. Many TAD binding proteins have been implicated in boundary interactions, including the gypsy transposon boundary binding protein Su(Hw). How these proteins generate the often specific and orientation-dependent boundary interactions that underpin chromosomal architecture is largely unknown. Here, we investigate the role of the single Su(Hw) binding site located in each of the boundaries that flank the Drosophila eve locus, homie and nhomie. We show that Su(Hw), which binds hundreds of sites throughout the Drosophila genome, plays a large role in the highly selective and orientation-specific interactions of homie and nhomie. Despite its outsized role in the binding strength and stability of these interactions, other boundary binding proteins are implicated as the primary determinants of the specificity of the interactions. These studies provide an important example of the need to more fully investigate how strength and specificity of TAD boundary interactions are separately encoded in this important class of genome architectural elements.

A sudden reduction in population size increases the rate of genetic drift, reducing variability and increasing the mean level of homozygosity. The resulting increased exposure of recessive or partially recessive, strongly deleterious alleles to selection against homozygotes may lead to their being purged from the population, potentially allowing mean fitness to increase after an initial decline, and accelerating the decline in inbreeding depression associated with reduced variability. However, detailed population genetic theory on the effects of population bottlenecks on mean fitness and inbreeding depression remains limited. We develop a theoretical framework for small, randomly mating populations founded from a large population near mutation-selection-drift equilibrium, using both simulations and approximate analytical predictions. These provide quantitative predictions for the dynamics of the populations mean fitness and level of inbreeding depression following a bottleneck. In particular, we derive an approximate expression for the time needed for mean fitness to recover after an initial decline; such a recovery requires selection to be sufficiently strong relative to drift and mutations to be sufficiently recessive. In contrast, weakly deleterious mutations cause reductions in mean fitness and inbreeding depression that are similar in size to those predicted from increases in neutral homozygosity.

Yeast responding to acute stress reallocate cellular resources, in part via the Environmental Stress Response (ESR) that induces stress-defense genes while repressing ribosome-biogenesis and growth genes. The purpose and regulation of coordinated induction and repression is incompletely understood, but both responses are influenced by ESR transcription factors Msn2 and Msn4 (Msn2/4). Here we used single-cell microscopy and transcriptomic analysis to investigate the role of upstream regulator Pde2 in ESR regulation and post-stress fitness. Loss of PDE2 weakened and shortened Msn2 activation following salt stress and produced muted induction of Msn2/4 targets, similar to a msn2{triangleup}msn4{triangleup} strain. In contrast, Pde2 had at most a minor impact on ESR repressor Dot6, yet was important for repression of its targets beyond Msn2/4 influence. Consistent with our recent resource-reallocation model, pde2{triangleup} cells had normal or faster post-stress growth rates, despite weaker activation of the ESR. We discuss implications for ESR regulation and function.

Conventional LD measures such as r2 perform poorly in the rare common regime, particularly in asymmetric configurations such as nested haplotype structure. Because r2 is symmetric and quadratic, it removes directional structure in two ways: squaring discards the sign, or phase, retained by the signed LD coefficient D, while symmetric normalization hides the asymmetry between the conditional probabilities P(A|B) and P(B|A). Although D recovers the phase, it is locus symmetric and unnormalized; its magnitude is hard to compare across frequency regimes and it does not by itself express which way the asymmetry runs. We therefore analyze the conditional-probability asymmetry {Delta} = P(A|B) - P(B|A), together with r2 and D, as distinct scalar functions on the haplotype simplex under the Fisher information metric. The conditional probabilities P(A|B) and P(B|A) are bounded in [0, 1], directly express carrier-set inclusion, and are more readily visualized than D. Moreover, their difference admits the exact decomposition {Delta} = M + C into a marginal frequency term M and an LD-coupled term C. Prior work has characterized either the mathematical behavior of LD normalizations across allele-frequency space or the Fisher geometry of the haplotype simplex, but not their connection. We bridge this gap by showing that the geometric structure of the simplex explains why LD measures disagree in the rare common regime and why symmetric normalizations such as r2 lose directional information. We show that the fixed-frequency leaf is intrinsically anisotropic, positively curved, and frequency-dependent under the Fisher metric. These geometric predictions are tested empirically , in phased 1000 Genomes data1 and a two locus Wright Fisher model, in a companion paper (Ichikawa, preprint); the present note develops the geometry itself. Keywords: linkage disequilibrium; Fisher information metric; haplotype simplex; rare variant; conditional-probability asymmetry; nested haplotype structure

As whole-genome and whole-exome datasets increase in size, they uncover alleles at lower and lower frequencies in the population. Samples of rare alleles often include recurrent mutations, where derived alleles are identical by state and not by descent. As a result, the site frequency spectrum (SFS) becomes challenging to analyze because it is strongly dependent on the mutation rate. To overcome this hurdle, we define the single mutation frequency spectrum (SMFS), which is the frequency spectrum of alleles descendant from a single mutational event. For rare alleles, the SFS with recurrent mutation is then a weighted sum of the convolutions of the SMFS with itself. This simple, yet powerful, model decouples recurrent mutation from the population genetic processes giving rise to the SMFS, such as genetic drift and selection. We show how both forward-in-time and backward-in-time models with recurrent mutations can be recast in terms of the SMFS. We then develop a method for combinatorial hierarchic estimation of the SMFS (which we name CHES). We apply this simple, yet robust, method to a human exome sequencing dataset to show that the SMFS with recurrent mutation can account for SFS differences between low and high mutation rate sites. The inferred SMFS shows an approximate scaling law with allele frequencies inconsistent with both a constant population size and an exponentially growing population model. Lastly, we use our model to compare the expected and observed proportions of missense and stop-gain mutations in the human exome, using this disparity to infer the strength of selection on these classes of mutations. Our combined results show how the SMFS can explain the dependency of the SFS on the mutation rate and how it reflects human demographic and evolutionary history.

Genetic influences on gene expression are an important source of variation in complex traits. Conflicting results have been reported about the concordance of genetic effects on mRNA abundance vs. protein levels, ranging from high agreement to a predominance of effects that are specific to mRNA or protein. Here, we integrated 13 published datasets of genetic variation in mRNA or protein collected in the same cross of two strains of the yeast Saccharomyces cerevisiae. These highly replicated data allowed us to gauge the overall agreement between the genetics of mRNA and protein and search for individual loci whose effects on these two gene products are reproducibly different. Overall, genetic effects were highly correlated across all datasets. mRNA and protein showed similar genetic architectures. Pairwise agreement between loci from mRNA datasets and loci from protein datasets was indistinguishable from agreement between loci from datasets of the same gene product. Trans-acting hotspots with effects on numerous genes affected mRNA and protein similarly. There were no hotspots that exclusively affected mRNA or protein across datasets. A small number of loci did show reproducibly different effects on mRNA or protein of individual genes. Collectively, these results show that, with a few notable exceptions, genetic effects on mRNA and protein are largely concordant.

Synthetic Genetic Array (SGA) analysis comprises the high-throughput crossing of a query deletion strain against a genome-wide deletion library to score fitness interactions in thousands of double mutants. SGAs have produced comprehensive genetic interaction maps in yeasts and have emerged as a leading platform for pharmacogenomics: mapping genetic modifiers of drug response, identifying synthetic lethal targets and illuminating mechanisms of drug action and resistance. We have previously demonstrated that in fission yeast, the ade6 mutant is functionally neutral relative to the parental library and can serve as a standard negative control for SGA screens. Here, while we confirm our previous observation, we show that this neutrality fails under pharmacological stress. Using Torin1, an ATP-competitive TOR kinase inhibitor, we demonstrate that the ade6 SGA fitness profile diverges from that of the parental library in a dose-dependent and genomically widespread manner. At 2 M Torin1 only 12.2% of scored genes exceed a 1.5-fold fitness difference between backgrounds; at 3 M this proportion rises to 43.2% -a 3.5-fold increase driven by qualitative reorganisation of the genetic interaction landscape rather than simple scaling of pre-existing differences. Gene ontology analysis of divergent genes implicates autophagy, iron starvation responses, central carbon metabolism, and vesicle trafficking, consistent with TOR-regulated nutrient adaptation being differentially affected by the ade6-M210/M216 point mutations in the library versus the ade6 null in the SGA control. Our results have implications in fission yeast and beyond and we propose solutions towards reliable retrieval of genetic interactions.

Linkage disequilibrium between two biallelic loci is usually summarized by scalar association measures such as r2 and D'. These measures quantify how visible an allelic association is to a symmetric LD scan, but they do not directly represent the topology of carrier sets: whether the carriers of one variant are contained within, partially overlap with, or are disjoint from the carriers of the other. This distinction is structural. On the haplotype-frequency simplex, carrier-set inclusion corresponds to a boundary face where one haplotype class is absent. In the rare-common regime, a nested rare variant is further constrained by the ceiling r2 [≤] pA/pB, so that complete carrier-set inclusion can remain nearly invisible to r2. Here, as a companion to the Fisher-geometry preprint 1, we examine the empirical and dynamic behavior of this carrier-set topology. In 1000 Genomes Phase 3, across 156,604,320 SNP pairs from the MHC and NEGR1 regions, pairs on the | D' |= 1 boundary span a wide range of r2 and | C |. Within fixed r2 strata, r2 poorly distinguishes nested from non-nested carrier-set configurations, with AUROC values of approximately 0.54-0.62, whereas the boundary-sensitive normalization | D' | separates them much more effectively, with AUROC values of approximately 0.90-0.92. The empirical data also obey the predicted r2 [≤] pA/pB ceiling. We then introduce a temporal axis using a two-locus Wright-Fisher model on the same simplex. Carrier-set topology evolves through three motions relative to the | D' |= 1 boundary: formation or persistence, in which recombination suppression establishes and maintains inclusion without requiring selection; visibility change, in which selection or drift moves r2 along the boundary while preserving the inclusion relation; and breaking, in which a recombination pulse introduces the previously absent haplotype and dissolves inclusion. A fourth mode, specificity erosion, expands the partner carrier set while preserving inclusion, thereby lowering P(A | B) while keeping P(B | A) and | D' | equal to one. This mode shows that asymmetric conditional probabilities are best understood as diagnostic coordinates for carrier-set topology, not as the primary object itself. Together, these results show that topology and visibility are separable axes of LD structure. Conventional r2-based scans and carrier-set topology scans therefore answer complementary, not interchangeable, questions.

Gene duplication typically fails to confer a selective advantage to an organism, prompting their removal from a population. In the rare instance that duplication either does not incur a fitness cost or it enhances fitness, gene families can form through repeating the duplication process. While the function of gene duplicates has been studied in detail, little work has explored how repeated duplication impacts paralog redundancy and may restrict the emergence of new paralogs or novel function. Here, we constructed a panel of single deletion mutants for each of the 14 members of the <em>Candida albicans</em> telomere-associated (<em>TLO</em>) gene family to test the redundancy in molecular and biological function among paralogs from a lineage-specific expansion. Tlo proteins function as interchangeable subunits of the Mediator transcriptional regulatory complex and have the potential to alter gene expression and an array of cellular responses. Redundancy was the most common outcome, being observed for approximately 80% of the phenotypic assays in strains lacking single <em>TLO </em>genes. However, mutants for all 14 paralogs displayed non-redundant functions in phenotypes ranging from carbon utilization to <em>in vivo</em> virulence. Analysis of gene expression in single <em>TLO </em>mutants found similar trends in redundancy, and loss of single <em>TLO</em>s disproportionately affected genes involved in filamentation, adhesion, redox reactions, and transporter activity at the cell surface. Importantly, sequence divergence between paralogs positively correlated with the frequency of altered phenotypes in single <em>TLO </em>mutants, indicating the acquisition of non-redundant function with increased evolutionary distance. Double mutants lacking two <em>TLO</em> genes produced both positive and negative synergistic phenotypes, suggesting that crosstalk or coordinated regulation is common among paralogs. Together, this study demonstrates that recently emergent paralogs acquire non-redundant functions despite often retaining redundancy with other gene family members to form a highly interconnected functional network.

We present Nemo 2.4, an advanced forward-time individual-based simulation framework designed to model the complex eco-evolutionary dynamics and genetic basis of quantitative traits. This tool addresses current challenges in evolutionary quantitative genetics by providing unprecedented flexibility and computational efficiency. Nemo 2.4's modular architecture allows researchers to design custom life cycles by combining specialized Life Cycle Event (LCE) modules, from reproduction and dispersal to selection, crossing, and phenotype expression. The software supports diverse population models, including both Wright-Fisher (WF) and non-WF dynamics, spatially explicit models, and varying demography. Nemo 2.4 handles a wide range of genetic architectures, including both multi-allelic Quantitative Trait Loci (QTL) for general trait studies, and dense di-allelic Quantitative Trait Nucleotides (QTN) implemented with highly optimized bit-wise data structures. Crucially, it allows the simulation of QTNs on comprehensive genetic maps that incorporate other genetic elements, providing genomic-scale resolution. Key biological complexities are integrated natively: the model accommodates modular pleiotropy, dominance, and pairwise epistasis across multiple traits, facilitating the study of complex genotype-phenotype mappings. Furthermore, Nemo 2.4 models phenotypic plasticity through reaction norms and incorporates underlying liability thresholds, enabling the simulation of environmental influences on trait evolution with various forms of selection (e.g., Gaussian, linear, truncation). Due to its compiled design and memory-efficient data representations for large numbers of loci, Nemo provides a robust platform for running high-throughput simulations critical for testing theoretical predictions in polygenic adaptation and understanding evolutionary responses to changing environments.

The Gene Version Iteration Hypothesis (GVIH) proposes that mutant genes may originate from the Y chromosome, traverse through the X chromosome to autosomes, undergo interchromosomal transfer, and potentially return to the Y chromosome via the X chromosome. This hypothetical closed transmission loop may facilitate the storage, screening, and elimination of different versions of mutant genes. The hypothesis comprises five core propositions: (1) Mutation reservoir: The Y chromosome may serve as a specialized carrier for generating mutant genes, characterized by elevated mutation rates, reduced gene density, and accelerated evolutionary dynamics; (2) Closed-loop transmission: Mutant genes may follow a unidirectional pathway Y[-&gt;]X[-&gt;]autosomes[-&gt;]X[-&gt;]Y, forming a complete transmission circuit; (3) Coexistence of multiple versions: A single functional gene may exist in multiple versions across different chromosomes, constituting a dynamic gene version library; (4) Reproductive screening: Environmentally adaptive gene versions may persist across generations and potentially migrate to upstream chromosomes, while maladaptive versions may be eliminated; (5) Terminal elimination: Gene versions reaching the Y chromosome may undergo elimination processes, potentially preventing version monopolization and maintaining evolutionary dynamics. This hypothesis provides a novel framework for understanding adaptive evolution at the genetic level. If empirically validated, it may offer new insights into the molecular mechanisms underlying certain genetic phenomena and evolutionary processes.

Whole genome duplication is a common mutation in eukaryotes with far-reaching phenotypic effects. The resulting morphological, physiological, and fitness consequences and how they affect the survival probability of newly polyploid lineages are intensively studied, but very little is known about the effect of genome doubling on the short-term evolvability of populations. Understanding the effect of polyploidization on the adaptive potential of populations is of crucial importance to predict the future of polyploid populations. In this paper, I investigate the immediate consequences of genome doubling on the genetic variance of populations. To do so, I performed numerical iterations and simulations of how the genetic variance of a quantitative trait changes after polyploidization, under different genetic architectures (additivity, dominance, and epistasis). I found that genetic variance generally decreases after genome doubling. Non-additive gene actions can make autotetraploid populations genetically more diverse than their diploid progenitors in rare cases, notably with overdominance and directional epistasis. By collecting estimates from the agronomic literature, I found that both dominance and epistatic variance contribute to the genetic variance of polyploid populations. These results bring new insights into the adaptive potential of newly formed tetraploid populations, and call for further experimental investigations of how polyploidization is associated with a short-term decrease in evolvability.

Polycomb Repressive Complex 2 (PRC2) is a conserved epigenetic regulator that represses gene expression through methylation of histone H3 lysine 27 (H3K27me3). In animals, plants, and some fungi, PRC2-directed facultative heterochromatin plays essential roles in development and cellular differentiation. Here, we show that the replication-dependent histone chaperone Chromatin Assembly Factor 1 (CAF-1) is required for proper structure and function of facultative heterochromatin in the model fungus Neurospora crassa. Loss of CAF-1 causes widespread transcriptional misregulation, particularly within PRC2-repressed regions, and leads to redistribution of H3K27me3, reduced ASH1-dependent H3K36 methylation, and accumulation of chromatin marks associated with active transcription. CAF-1 was not required for repressive histone methylation within constitutive heterochromatin. A double mutant lacking both CAF-1 and PRC2 components displayed a synergistic silencing defect, suggesting these complexes make distinct contributions to facultative heterochromatin. Together, our findings indicate that CAF-1 works in concert with PRC2 to silence transcription within N. crassa facultative heterochromatin domains.