The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Protein structures play an important role in bioinformatics, such as in predicting gene function or validating gene model annotation. However, determining protein structure was, until now, costly and time-consuming, which resulted in a structural biology bottleneck. With the release of such programs AlphaFold and ESMFold, this bottleneck has been reduced by several orders of magnitude, permitting protein structural comparisons of entire genomes within reasonable timeframes. MaizeGDB has leveraged this technological breakthrough by offering several new tools to accelerate protein structural comparisons between maize and other plants as well as human and yeast outgroups. MaizeGDB also offers bulk downloads of these comparative protein structure data, along with predicted functional annotation information. In this way, MaizeGDB is poised to assist maize researchers in assessing functional homology, gene model annotation quality, and other information unavailable to maize scientists even a few years ago.

Nikolai K. Koltzoff (Koltsov) (1872-1940) is one of the key figures in Russian biology. He essentially initiated Russian physicochemical biology and established a large scientific school in the area. Among his disciples, there are the geneticists B.L. Astaurov, S.S. Chetverikov, N.P. Dubinin, V.P. Efroimson, I.A. Rapoport, V.V. Sakharov, and N.V. Timofeeff-Ressovsky; histologist G.I. Roskin, experimental surgeon A.G. Lapchinsky, developmental biologist M.M. Zavadovsky, physiologist L.V. Krushinsky, microbiologist S.M. Gershenson, biochemist V.A. Engelhardt, hydrobiologist G.G. Vinberg, cytologist M.A. Peshkov, and many other famous Soviet biologists. He made several fundamental discoveries; the first of them was the discovery of the cytoskeleton (1903). He was the first to formulate the idea of a crystal-like mechanism for copying inherited information (1927) and the principles of epigenetics (as well as the term itself, in 1934; it seems astonishing, but as early as 1915, he hypothesized that the gene methylation might be a mechanism of genetic variability). He started the work which later led his disciples V.V. Sakharov and I.A. Rapoport to the discovery of chemical mutagenesis. His research on sex regulation in silkworms was later successfully continued by B.L. Astaurov. Koltzoff encouraged S.S. Chetverikov, the entomologist, to study the genetics of natural Drosophila populations, which went on to form the basis of the Modern Synthesis reconciling Darwinian evolutionary theory and the Mendelian laws of heredity. Unfortunately, the name of N.K. Koltzoff has almost sunk into oblivion. This is largely due to the fact that mentioning his name was prohibited in the USSR over a long period of time, since he was a staunch opponent of Lysenko. In this paper dedicated to the 150th anniversary of Koltzoff, we briefly describe the milestones of the life and scientific research of this outstanding biologist and his scientific school.

Adult stem cells maintain homeostatic self-renewal through the strategy of either population or single-cell asymmetry, and the former type of stem cells are thought to take passive while the latter ones take active competition for niche occupancy. Although the division ability of stem cells is known to be crucial for their passive competition, whether it is also crucial for active competition is still elusive. Drosophila female germline stem cells are thought to take active competition, and bam mutant germ cells are more competitive than wild-type germline stem cells for niche occupancy. Here we report that either cycB, cycE, cdk2, or rheb null mutation drastically attenuates the division ability and niche occupancy capacity of bam mutant germ cells. Conversely, accelerating their cell cycle by mutating hpo has an enhanced effect. Last but not least, we also determine that E-cadherin, which was proposed to be crucial previously, just plays a mild role in bam mutant germline niche occupancy. Together with previous studies, we propose that division ability plays a unified crucial role in either active or passive competition among stem cells for niche occupancy.

As one of the first model organism knowledgebases, Saccharomyces Genome Database (SGD) has been supporting the scientific research community since 1993. As technologies and research evolve, so does SGD: from updates in software architecture, to curation of novel data types, to incorporation of data from, and collaboration with, other knowledgebases. We are continuing to make steps toward providing the community with an S. cerevisiae pan-genome. Here, we describe software upgrades, a new nomenclature system for genes not found in the reference strain, and additions to gene pages. With these improvements, we aim to remain a leading resource for students, researchers, and the broader scientific community.

Whereas both sperm and egg contribute nuclear genetic material to the zygote in metazoan organisms, the inheritance of other cellular constituents is unequal between the 2 gametes. Thus, 2 copies of the centriole are contributed solely by the sperm to the zygote in most species. Centrioles can have a stereotyped distribution in some asymmetric divisions, but whether sperm-contributed centrioles are distributed in a stereotyped manner in the resulting embryo is not known. Here, we address this question in Caenorhabditis elegans using marked mating experiments, whereby the presence of the 2 sperm-contributed centrioles is monitored in the embryo using the stable centriolar component SAS-4::GFP, as well as GFP::SAS-7. Our analysis demonstrates that the distribution of sperm-contributed centrioles is stochastic in 4-cell stage embryos. Moreover, using sperm from zyg-1 mutant males that harbor a single centriole, we show that the older sperm-contributed centriole is likewise distributed stochastically in the resulting embryo. Overall, we conclude that, in contrast to the situation during some asymmetric cell divisions, centrioles contributed by the male germ line are distributed stochastically in embryos of C. elegans.

Mediation analysis is used in genetic mapping studies to identify candidate gene mediators of quantitative trait loci (QTL). We consider genetic mediation analysis of triplets-sets of three variables consisting of a target trait, the genotype at a QTL for the target trait, and a candidate mediator that is the abundance of a transcript or protein whose coding gene co-locates with the QTL. We show that, in the presence of measurement error, mediation analysis can infer partial mediation even in the absence of a causal relationship between the candidate mediator and the target. We describe a measurement error model and a corresponding latent variable model with estimable parameters that are combinations of the causal effects and measurement errors across all three variables. The relative magnitudes of the latent variable correlations determine whether or not mediation analysis will tend to infer the correct causal relationship in large samples. We examine case studies that illustrate the common failure modes of genetic mediation analysis and demonstrate how to evaluate the effects of measurement error. While genetic mediation analysis is a powerful tool for identifying candidate genes, we recommend caution when interpreting mediation analysis findings.

Common genetic association models for structured populations, including principal component analysis (PCA) and linear mixed-effects models (LMMs), model the correlation structure between individuals using population kinship matrices, also known as genetic relatedness matrices. However, the most common kinship estimators can have severe biases that were only recently determined. Here we characterize the effect of these kinship biases on genetic association. We employ a large simulated admixed family and genotypes from the 1000 Genomes Project, both with simulated traits, to evaluate key kinship estimators. Remarkably, we find practically invariant association statistics for kinship matrices of different bias types (matching all other features). We then prove using statistical theory and linear algebra that LMM association tests are invariant to these kinship biases, and PCA approximately so. Our proof shows that the intercept and relatedness effect coefficients compensate for the kinship bias, an argument that extends to generalized linear models. As a corollary, association testing is also invariant to changing the reference ancestral population of the kinship matrix. Lastly, we observed that all kinship estimators, except for popkin ratio-of-means, can give improper non-positive semidefinite matrices, which can be problematic although some LMMs handle them surprisingly well, and condition numbers can be used to choose kinship estimators. Overall, we find that existing association studies are robust to kinship estimation bias, and our calculations may help improve association methods by taking advantage of this unexpected robustness, as well as help determine the effects of kinship bias in related problems.

Xenbase (https://www.xenbase.org/), the Xenopus model organism knowledgebase, is a web-accessible resource that integrates the diverse genomic and biological data from research on the laboratory frogs Xenopus laevis and Xenopus tropicalis. The goal of Xenbase is to accelerate discovery and empower Xenopus research, to enhance the impact of Xenopus research data, and to facilitate the dissemination of these data. Xenbase also enhances the value of Xenopus data through high-quality curation, data integration, providing bioinformatics tools optimized for Xenopus experiments, and linking Xenopus data to human data, and other model organisms. Xenbase also plays an indispensable role in making Xenopus data interoperable and accessible to the broader biomedical community in accordance with FAIR principles. Xenbase provides annotated data updates to organizations such as NCBI, UniProtKB, Ensembl, the Gene Ontology consortium, and most recently, the Alliance of Genomic Resources, a common clearing house for data from humans and model organisms. This article provides a brief overview of key and recently added features of Xenbase. New features include processing of Xenopus high-throughput sequencing data from the NCBI Gene Expression Omnibus; curation of anatomical, physiological, and expression phenotypes with the newly created Xenopus Phenotype Ontology; Xenopus Gene Ontology annotations; new anatomical drawings of the Normal Table of Xenopus development; and integration of the latest Xenopus laevis v10.1 genome annotations. Finally, we highlight areas for future development at Xenbase as we continue to support the Xenopus research community.

Transcriptome analysis of several animal clades suggests that male reproductive tract gene expression evolves quickly. However, the factors influencing the abundance and distribution of within-species variation, the ultimate source of interspecific divergence, are poorly known. Drosophila melanogaster, an ancestrally African species that has recently spread throughout the world and colonized the Americas in the last roughly 100 years, exhibits phenotypic and genetic latitudinal clines on multiple continents, consistent with a role for spatially varying selection in shaping its biology. Nevertheless, geographic expression variation in the Americas is poorly described, as is its relationship to African expression variation. Here, we investigate these issues through the analysis of two male reproductive tissue transcriptomes [testis and accessory gland (AG)] in samples from Maine (USA), Panama, and Zambia. We find dramatic differences between these tissues in differential expression between Maine and Panama, with the accessory glands exhibiting abundant expression differentiation and the testis exhibiting very little. Latitudinal expression differentiation appears to be influenced by the selection of Panama expression phenotypes. While the testis shows little latitudinal expression differentiation, it exhibits much greater differentiation than the accessory gland in Zambia vs American population comparisons. Expression differentiation for both tissues is non-randomly distributed across the genome on a chromosome arm scale. Interspecific expression divergence between D. melanogaster and D. simulans is discordant with rates of differentiation between D. melanogaster populations. Strongly heterogeneous expression differentiation across tissues and timescales suggests a complex evolutionary process involving major temporal changes in the way selection influences expression evolution in these organs.

The Rat Genome Database (RGD, https://rgd.mcw.edu) has evolved from simply a resource for rat genetic markers, maps, and genes, by adding multiple genomic data types and extensive disease and phenotype annotations and developing tools to effectively mine, analyze, and visualize the available data, to empower investigators in their hypothesis-driven research. Leveraging its robust and flexible infrastructure, RGD has added data for human and eight other model organisms (mouse, 13-lined ground squirrel, chinchilla, naked mole-rat, dog, pig, African green monkey/vervet, and bonobo) besides rat to enhance its translational aspect. This article presents an overview of the database with the most recent additions to RGD's genome, variant, and quantitative phenotype data. We also briefly introduce Virtual Comparative Map (VCMap), an updated tool that explores synteny between species as an improvement to RGD's suite of tools, followed by a discussion regarding the refinements to the existing PhenoMiner tool that assists researchers in finding and comparing quantitative data across rat strains. Collectively, RGD focuses on providing a continuously improving, consistent, and high-quality data resource for researchers while advancing data reproducibility and fulfilling Findable, Accessible, Interoperable, and Reusable (FAIR) data principles.

Long noncoding RNAs (lncRNAs) play important regulatory roles in stem cell self-renewal, pluripotency maintenance, and differentiation. Till now, there is very limited knowledge about how lncRNAs regulate intestinal stem cells (ISCs), and lncRNAs mediating ISC regeneration in Drosophila have yet been characterized. Here, we identify a lncRNA, CR46040, that is essential for the injury-induced ISC regeneration in Drosophila. Loss of CR46040 greatly impairs ISC proliferation in response to tissue damage caused by dextran sulfate sodium (DSS) treatment. We demonstrate that CR46040 is a genuine lncRNA that has two isoforms transcribed from the same transcription start site and works in trans to regulate intestinal stem cells. Mechanistically, CR46040 knock-out flies failed to fully activate JNK, JAK/STAT, and HIPPO signaling pathways after tissue damage, which are required for ISC proliferation after intestinal injury. Moreover, CR46040 knock-out flies are highly susceptible to DSS treatment and enteropathogenic bacteria Erwinia carotovora ssp. carotovora 15 (Ecc15) infection. Our findings characterize, for the first time, a lncRNA that mediates damage-induced ISC proliferation in Drosophila and provide new insights into the functional links among the long noncoding RNAs, ISC proliferation, and tissue homeostasis.

Agro-ecosystems provide environments that are conducive for rapid evolution and dispersal of plant pathogens. Previous studies have demonstrated that hybridization of crop pathogens can give rise to new lineages with altered virulence profiles. Currently, little is known about either the genetics of fungal pathogen hybridization or the mechanisms that may prevent hybridization between related species. The fungus Pyrenophora teres is a global pathogen of barley. The pathogenic fungus P. teres exists as two distinct lineages P. teres f. teres and P. teres f. maculata (Ptt and Ptm, respectively), which both infect barley but produce very distinct lesions and rarely interbreed. Interestingly, Ptt and Ptm can, by experimental mating, produce viable progenies. Here, we addressed the underlying genetics of reproductive barriers of P. teres. We hypothesize that Ptt and Ptm diverged in the past, possibly by adapting to distinct hosts, and only more recently colonized the same host in agricultural fields. Using experimental mating and in planta phenotyping in barley cultivars susceptible to both P. teres forms, we demonstrate that hybrids produce mixed infection phenotypes but overall show inferior pathogenic fitness relative to the pure parents. Based on analyses of 104 hybrid genomes, we identify signatures of negative epistasis between parental alleles at distinct loci (Dobzhansky-Müller incompatibilities). Most DMI regions are not involved in virulence but certain genes are predicted or known to play a role in virulence. These results potentially suggest that divergent niche adaptation-albeit in the same host plant-contributes to speciation in P. teres.

Maintenance of osmotic homeostasis is one of the most aggressively defended homeostatic set points in physiology. One major mechanism of osmotic homeostasis involves the upregulation of proteins that catalyze the accumulation of solutes called organic osmolytes. To better understand how osmolyte accumulation proteins are regulated, we conducted a forward genetic screen in Caenorhabditis elegans for mutants with no induction of osmolyte biosynthesis gene expression (Nio mutants). The nio-3 mutant encoded a missense mutation in cpf-2/CstF64, while the nio-7 mutant encoded a missense mutation in symk-1/Symplekin. Both cpf-2 and symk-1 are nuclear components of the highly conserved 3' mRNA cleavage and polyadenylation complex. cpf-2 and symk-1 block the hypertonic induction of gpdh-1 and other osmotically induced mRNAs, suggesting they act at the transcriptional level. We generated a functional auxin-inducible degron (AID) allele for symk-1 and found that acute, post-developmental degradation in the intestine and hypodermis was sufficient to cause the Nio phenotype. symk-1 and cpf-2 exhibit genetic interactions that strongly suggest they function through alterations in 3' mRNA cleavage and/or alternative polyadenylation. Consistent with this hypothesis, we find that inhibition of several other components of the mRNA cleavage complex also cause a Nio phenotype. cpf-2 and symk-1 specifically affect the osmotic stress response since heat shock-induced upregulation of a hsp-16.2::GFP reporter is normal in these mutants. Our data suggest a model in which alternative polyadenylation of 1 or more mRNAs is essential to regulate the hypertonic stress response.

The detection and avoidance of harmful stimuli are essential animal capabilities. The molecular and cellular mechanisms controlling nociception and its plasticity are conserved, genetically controlled processes of broad biomedical interest given their relevance to understand and treat pain conditions that represent a major health burden. Recent genome-wide association studies (GWAS) have identified a rich set of polymorphisms related to different pain conditions and pointed to many human pain gene candidates, whose connection to the pain pathways is however often poorly understood. Here, we used a computer-assisted Caenorhabditis elegans thermal avoidance analysis pipeline to screen for behavioral defects in a set of 109 mutants for genes orthologous to human pain-related genes. We measured heat-evoked reversal thermosensitivity profiles, as well as spontaneous reversal rate, and compared naïve animals with adapted animals submitted to a series of repeated noxious heat stimuli, which in wild type causes a progressive habituation. Mutations affecting 28 genes displayed defects in at least one of the considered parameters and could be clustered based on specific phenotypic footprints, such as high-sensitivity mutants, nonadapting mutants, or mutants combining multiple defects. Collectively, our data reveal the functional architecture of a network of conserved pain-related genes in C. elegans and offer novel entry points for the characterization of poorly understood human pain genes in this genetic model.

Moths and butterflies (Lepidoptera) have sex chromosome systems with female heterogamety, and 2 models, W-dominance and Z-counting, have been proposed to determine sex. The W-dominant mechanism is well known in Bombyx mori. However, little is known about the Z-counting mechanism in Z0/ZZ species. We investigated whether ploidy changes affect sexual development and gene expression in the eri silkmoth, Samia cynthia ricini (2n = 27♀/28♂, Z0♀/ZZ♂). Tetraploid males (4n = 56, ZZZZ) and females (4n = 54, ZZ) were induced by heat and cold shock, and then, triploid embryos were produced by crosses between diploids and tetraploids. Two karyotypes (3n = 42, ZZZ and 3n = 41, ZZ) were identified in triploid embryos. Triploid embryos with 3 Z chromosomes showed male-specific splicing of the S. cynthia doublesex (Scdsx) gene, whereas 2-Z triploid embryos showed both male- and female-specific splicing. From larva to adult, 3-Z triploids showed a normal male phenotype, except for defects in spermatogenesis. However, abnormal gonads were observed in 2-Z triploids, which showed both male- and female-specific Scdsx transcripts not only in the gonads but also in somatic tissues. Two-Z triploids were thus obviously intersexes, suggesting that sexual development in S. c. ricini depends on the Z:A ratio and not only on the Z number. Moreover, mRNA-seq analyses in embryos showed that relative levels of gene expression are similar between samples with different doses of Z chromosomes and autosome sets. Our results provide the first evidence that ploidy changes disrupt sexual development but have no effect on the general mode of dosage compensation in Lepidoptera.

A broad array of endosymbionts radiate through host populations via vertical transmission, yet much remains unknown concerning the cellular basis, diversity, and routes underlying this transmission strategy. Here, we address these issues, by examining the cellular distributions of Wolbachia strains that diverged up to 50 million years ago in the oocytes of 18 divergent Drosophila species. This analysis revealed 3 Wolbachia distribution patterns: (1) a tight clustering at the posterior pole plasm (the site of germline formation); (2) a concentration at the posterior pole plasm, but with a significant bacteria population distributed throughout the oocyte; and (3) a distribution throughout the oocyte, with none or very few located at the posterior pole plasm. Examination of this latter class indicates Wolbachia accesses the posterior pole plasm during the interval between late oogenesis and the blastoderm formation. We also find that 1 Wolbachia strain in this class concentrates in the posterior somatic follicle cells that encompass the pole plasm of the developing oocyte. In contrast, strains in which Wolbachia concentrate at the posterior pole plasm generally exhibit no or few Wolbachia in the follicle cells associated with the pole plasm. Taken together, these studies suggest that for some Drosophila species, Wolbachia invade the germline from neighboring somatic follicle cells. Phylogenomic analysis indicates that closely related Wolbachia strains tend to exhibit similar patterns of posterior localization, suggesting that specific localization strategies are a function of Wolbachia-associated factors. Previous studies revealed that endosymbionts rely on 1 of 2 distinct routes of vertical transmission: continuous maintenance in the germline (germline-to-germline) or a more circuitous route via the soma (germline-to-soma-to-germline). Here, we provide compelling evidence that Wolbachia strains infecting Drosophila species maintain the diverse arrays of cellular mechanisms necessary for both of these distinct transmission routes. This characteristic may account for its ability to infect and spread globally through a vast range of host insect species.

Danio rerio is a model organism used to investigate vertebrate development. Manipulation of the zebrafish genome and resultant gene products by mutation or targeted knockdown has made the zebrafish a good system for investigating gene function, providing a resource to investigate genetic contributors to phenotype and human disease. Phenotypic outcomes can be the result of gene mutation, targeted knockdown of gene products, manipulation of experimental conditions, or any combination thereof. Zebrafish have been used in various genetic and chemical screens to identify genetic and environmental contributors to phenotype and disease outcomes. The Zebrafish Information Network (ZFIN, zfin.org) is the central repository for genetic, genomic, and phenotypic data that result from research using D. rerio. Here we describe how ZFIN annotates phenotype, expression, and disease model data across various experimental designs, how we computationally determine wild-type gene expression, the phenotypic gene, and how these results allow us to propagate gene expression, phenotype, and disease model data to the correct gene, or gene related entity.

Estrogen signaling exerts a decisive role in female sex determination and differentiation in chicken and fish. Aromatase encoded by Cyp19a1 is the key enzyme that catalyzes the conversion of androgen to estrogen. Correlative analyses implicate the potential involvement of aromatase in reptilian sexual development, however, the direct genetic evidence is lacking. Herein, we found that Cyp19a1 exhibited temperature-dependent sexually dimorphic expression, and located in the medullary somatic cells in early female embryos of the red-eared slider turtle (Trachemys scripta elegans), before the gonad is distinct. To determine the functional role of Cyp19a1 in turtle ovarian determination, we established loss- and gain-of-function models through in ovo lentivirus-mediated genetic manipulation. At female-producing temperature, inhibition of aromatase or knockdown of Cyp19a1 in turtle embryos resulted in female-to-male sex reversal, with the formation of a testis-like structure and a male distribution pattern of germ cells, as well as ectopic expression of male-specific markers (SOX9 and AMH) and disappearance of ovarian regulator FOXL2. On the contrary, overexpression of Cyp19a1 at male-producing temperature led to male-to-female sex reversal. In conclusion, our results suggest that Cyp19a1 is both necessary and sufficient for ovarian determination in the red-eared slider turtle, establishing causality and a direct genetic link between aromatase and reptilian sex determination and differentiation.

The genes that encode ribosomal RNAs are present in several hundred copies in most eukaryotes. These vast arrays of repetitive ribosomal DNA (rDNA) have been implicated not just in ribosome biogenesis, but also aging, cancer, genome stability, and global gene expression. rDNA copy number is highly variable among and within species; this variability is thought to associate with traits relevant to human health and disease. Here we investigate the phenotypic consequences of multicellular life at the lower bounds of rDNA copy number. We use the model Caenorhabditis elegans, which has previously been found to complete embryogenesis using only maternally provided ribosomes. We find that individuals with rDNA copy number reduced to ∼5% of wild type are capable of further development with variable penetrance. Such individuals are sterile and exhibit severe morphological defects, particularly in post-embryonically dividing tissues such as germline and vulva. Developmental completion and fertility are supported by an rDNA copy number ∼10% of wild type, with substantially delayed development. Worms with rDNA copy number reduced to ∼33% of wild type display a subtle developmental timing defect that was absent in worms with higher copy numbers. Our results support the hypothesis that rDNA requirements vary across tissues and indicate that the minimum rDNA copy number for fertile adulthood is substantially less than the lowest naturally observed total copy number. The phenotype of individuals with severely reduced rDNA copy number is highly variable in penetrance and presentation, highlighting the need for continued investigation into the biological consequences of rDNA copy number variation.

Population bottlenecks are commonplace in experimental evolution, specifically in serial passaging experiments where microbial populations alternate between growth and dilution. Natural populations also experience such fluctuations caused by seasonality, resource limitation, or host-to-host transmission for pathogens. Yet, how unlimited growth with periodic bottlenecks influence the adaptation of populations is not fully understood. Here, we study theoretically the effects of bottlenecks on the accessibility of evolutionary paths and on the rate of evolution. We model an asexual population evolving on a minimal fitness landscape consisting of two types of beneficial mutations with the empirically supported trade-off between mutation rate and fitness advantage, in the regime where multiple beneficial mutations may segregate simultaneously. In the limit of large population sizes and small mutation rates, we show the existence of a unique most likely evolutionary scenario, determined by the size of the wild-type population at the beginning and at the end of each cycle. These two key demographic parameters determine which adaptive paths may be taken by the evolving population by controlling the supply of mutants during growth and the loss of mutants at the bottleneck. We do not only show that bottlenecks act as a deterministic control of evolutionary paths but also that each possible evolutionary scenario can be forced to occur by tuning demographic parameters. This work unveils the effects of demography on adaptation of periodically bottlenecked populations and can guide the design of evolution experiments.

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

According to the revisionist interpretation of Mendel's pea crosses, his primary aim was not to study the inheritance of traits. Instead, he was interested in the question raised by Linnaeus as to whether new species could arise from the hybridization of existing species. The genetic interpretation is therefore seen as ahistorical by the revisionists. This view goes back to the 1979 article "Mendel no Mendelian?" by the historian of science R.C. Olby. A closer analysis shows that Olby implicitly assumed Mendel adhered to the unusual strictest species definition for Pisum. However, we argue that Mendel only mentions the hypothetical application of this strict definition in his 1866 paper. Like most of his contemporaries, Mendel accepted variation within species where the differences between varieties and species were a matter of degree. After researching variable hybrids in peas (Pisum; 1854-1863), Mendel also studied constant hybrids in hawkweeds (Hieracium; 1866-1873), which he considered to be new species. There is no debate about the latter, but the matter becomes muddled because Olby lumps Pisum and Hieracium together, despite their having completely different reproduction systems. Based on newly discovered historical sources, we also dispute several other assumptions made by Olby. We do not consider Olby's claim that Mendel conducted the Pisum experiments to investigate species multiplication to be tenable.

Retrotransposons are a class of transposable elements capable of self-replication and insertion into new genomic locations. Across species, the mobilization of retrotransposons in somatic cells has been suggested to contribute to the cell and tissue functional decline that occurs during aging. Retrotransposons are broadly expressed across cell types, and de novo insertions have been observed to correlate with tumorigenesis. However, the extent to which new retrotransposon insertions occur during normal aging and their effect on cellular and animal function remains understudied. Here, we use a single nucleus whole genome sequencing approach in Drosophila to directly test whether transposon insertions increase with age in somatic cells. Analyses of nuclei from thoraces and indirect flight muscles using a newly developed pipeline, Retrofind, revealed no significant increase in the number of transposon insertions with age. Despite this, reducing the expression of two different retrotransposons, 412 and Roo, extended lifespan, but did not alter indicators of health such as stress resistance. This suggests a key role for transposon expression and not insertion in regulating longevity. Transcriptomic analyses revealed similar changes to gene expression in 412 and Roo knockdown flies and highlighted changes to genes involved in proteolysis and immune function as potential contributors to the observed changes in longevity. Combined, our data show a clear link between retrotransposon expression and aging.

Most variants identified in human genome-wide association studies and scans for selection are noncoding. Interpretation of their effects and the way in which they contribute to phenotypic variation and adaptation in human populations is therefore limited by our understanding of gene regulation and the difficulty of confidently linking noncoding variants to genes. To overcome this, we developed a gene-wise test for population-specific selection based on combinations of regulatory variants. Specifically, we use the QX statistic to test for polygenic selection on cis-regulatory variants based on whether the variance across populations in the predicted expression of a particular gene is higher than expected under neutrality. We then applied this approach to human data, testing for selection on 17,388 protein-coding genes in 26 populations from the Thousand Genomes Project. We identified 45 genes with significant evidence (FDR<0.1) for selection, including FADS1, KHK, SULT1A2, ITGAM, and several genes in the HLA region. We further confirm that these signals correspond to plausible population-level differences in predicted expression. While the small number of significant genes (0.2%) is consistent with most cis-regulatory variation evolving under genetic drift or stabilizing selection, it remains possible that there are effects not captured in this study. Our gene-level QX score is independent of standard genomic tests for selection, and may therefore be useful in combination with traditional selection scans to specifically identify selection on regulatory variation. Overall, our results demonstrate the utility of combining population-level genomic data with functional data to understand the evolution of gene expression.

Reduced-representation sequencing (RRS) provides cost-effective and time-saving genotyping platforms. Despite the outstanding advantage of RRS in throughput, the obtained genotype data usually contain a large number of errors. Several error correction methods employing the hidden Markov model (HMM) have been developed to overcome these issues. These methods assume that markers have a uniform error rate with no bias in the allele read ratio. However, bias does occur because of uneven amplification of genomic fragments and read mismapping. In this paper, we introduce an error correction tool, GBScleanR, which enables robust and precise error correction for noisy RRS-based genotype data by incorporating marker-specific error rates into the HMM. The results indicate that GBScleanR improves the accuracy by more than 25 percentage points at maximum compared to the existing tools in simulation data sets and achieves the most reliable genotype estimation in real data even with error-prone markers.

The evolution of gene expression is constrained by the topology of gene regulatory networks, as co-expressed genes are likely to have their expressions affected together by mutations. Conversely, co-expression can also be an advantage when genes are under joint selection. Here, we assessed theoretically whether correlated selection (selection for a combination of traits) was able to affect the pattern of correlated gene expressions and the underlying gene regulatory networks. We ran individual-based simulations, applying a stabilizing correlated fitness function to three genetic architectures: a quantitative genetics (multilinear) model featuring epistasis and pleiotropy, a quantitative genetics model where each genes has an independent mutational structure, and a gene regulatory network model, mimicking the mechanisms of gene expression regulation. Simulations showed that correlated mutational effects evolved in the three genetic architectures as a response to correlated selection, but the response in gene networks was specific. The intensity of gene co-expression was mostly explained by the regulatory distance between genes (largest correlations being associated to genes directly interacting with each other), and the sign of co-expression was associated with the nature of the regulation (transcription activation or inhibition). These results concur to the idea that gene network topologies could partly reflect past selection patterns on gene expression.

The regulation of the initiation of transcription by transcription factors is often assumed to be dependent on specific recognition of DNA-binding sites and nonredundant. However, the redundant induction or rescue of a phenotype by transcription factors, phenotypic nonspecificity, challenges these assumptions. To assess the frequency of phenotypic nonspecificity in the rescue of transcription factor phenotypes, seven transcription factor phenotypes (labial, Deformed, Sex combs reduced, Ultrabithorax, fruitless, doublesex, and apterous) were screened for rescue by the expression of 12, or more, nonresident transcription factors. From 308 assessments of rescue by nonresident transcription factors, 18 rescues were identified across 6 of the 7 transcription factor phenotypes. Seventeen of the 18 rescues were with transcription factors that recognize distinct DNA-binding sites relative to the resident transcription factors. All rescues were nonuniform across pleiotropic transcription factor phenotypes suggesting extensive differential pleiotropy of the rescue. Primarily using RNAi to knockdown expression, and with the exceptions of the requirement of Bric a Brac 1 for female abdominal pigmentation and Myb oncogene-like for wing development, no evidence was found for a role of the other 16 nonresident transcription factor in the transcription factor phenotypes assessed. Therefore, these 16 rescues are likely due to functional complementation and not due to the expression of an epistatic function in the developmental/behavioral pathway. Phenotypic nonspecificity is both differentially pleiotropic and frequent, as on average 1 in 10-20 nonresident transcription factors rescue a phenotype. These observations will be important in future considerations of transcription factors function.

The geographic nature of biological dispersal shapes patterns of genetic variation over landscapes, making it possible to infer properties of dispersal from genetic variation data. Here, we present an inference tool that uses geographically distributed genotype data in combination with a convolutional neural network to estimate a critical population parameter: the mean per-generation dispersal distance. Using extensive simulation, we show that our deep learning approach is competitive with or outperforms state-of-the-art methods, particularly at small sample sizes. In addition, we evaluate varying nuisance parameters during training-including population density, demographic history, habitat size, and sampling area-and show that this strategy is effective for estimating dispersal distance when other model parameters are unknown. Whereas competing methods depend on information about local population density or accurate inference of identity-by-descent tracts, our method uses only single-nucleotide-polymorphism data and the spatial scale of sampling as input. Strikingly, and unlike other methods, our method does not use the geographic coordinates of the genotyped individuals. These features make our method, which we call "disperseNN," a potentially valuable new tool for estimating dispersal distance in nonmodel systems with whole genome data or reduced representation data. We apply disperseNN to 12 different species with publicly available data, yielding reasonable estimates for most species. Importantly, our method estimated consistently larger dispersal distances than mark-recapture calculations in the same species, which may be due to the limited geographic sampling area covered by some mark-recapture studies. Thus genetic tools like ours complement direct methods for improving our understanding of dispersal.

In studying allele-frequency variation across populations, it is often convenient to classify an allelic type as "rare," with nonzero frequency less than or equal to a specified threshold, "common," with a frequency above the threshold, or entirely unobserved in a population. When sample sizes differ across populations, however, especially if the threshold separating "rare" and "common" corresponds to a small number of observed copies of an allelic type, discreteness effects can lead a sample from one population to possess substantially more rare allelic types than a sample from another population, even if the two populations have extremely similar underlying allele-frequency distributions across loci. We introduce a rarefaction-based sample-size correction for use in comparing rare and common variation across multiple populations whose sample sizes potentially differ. We use our approach to examine rare and common variation in worldwide human populations, finding that the sample-size correction introduces subtle differences relative to analyses that use the full available sample sizes. We introduce several ways in which the rarefaction approach can be applied: we explore the dependence of allele classifications on subsample sizes, we permit more than two classes of allelic types of nonzero frequency, and we analyze rare and common variation in sliding windows along the genome. The results can assist in clarifying similarities and differences in allele-frequency patterns across populations.

Sex and recombination can affect the dynamics of transposable elements (TEs) in various ways: while sex is expected to help TEs to spread within populations, the deleterious effect of ectopic recombination among transposons represents a possible source of purifying selection limiting their number. Furthermore, recombination may also increase the efficiency of selection against TEs by reducing selective interference among loci. In order to better understand the effects of recombination and reproductive systems on TE dynamics, this article provides analytical expressions for the linkage disequilibrium among TEs in a classical model in which TE number is stabilized by synergistic purifying selection. The results show that positive linkage disequilibrium is predicted in infinite populations despite negative epistasis, due to the effect of the transposition process. Positive linkage disequilibrium may substantially inflate the variance in the number of elements per genome in the case of partially selfing or partially clonal populations. Finite population size tends to generate negative linkage disequilibrium (Hill-Robertson effect), the relative importance of this effect increasing with the degree of linkage among loci. The model is then extended in order to explore how TEs may affect selection for recombination. While positive linkage disequilibrium generated by transposition generally disfavors recombination, the Hill-Robertson effect may represent a non-negligible source of indirect selection for recombination when TEs are abundant. However, the direct fitness cost imposed by ectopic recombination among elements generally drives the population towards low-recombination regimes, at which TEs cannot be maintained at a stable equilibrium.

The maize female gametophyte is comprised of four cell types: two synergids, an egg cell, a central cell, and a variable number of antipodal cells. In maize, these cells are produced after three rounds of free-nuclear divisions followed by cellularization, differentiation, and proliferation of the antipodal cells. Cellularization of the eight-nucleate syncytium produces seven cells with two polar nuclei in the central cell. Nuclear localization is tightly controlled in the embryo sac. This leads to precise allocation of the nuclei into the cells upon cellularization. Nuclear positioning within the syncytium is highly correlated with their identity after cellularization. Two mutants are described with extra polar nuclei, abnormal antipodal cell morphology, and reduced antipodal cell number, as well as frequent loss of antipodal cell marker expression. Mutations in one of these genes, indeterminate gametophyte2 encoding a MICROTUBULE ASSOCIATED PROTEIN65-3 homolog, shows a requirement for MAP65-3 in cellularization of the syncytial embryo sac as well as for normal seed development. The timing of the effects of ig2 suggests that the identity of the nuclei in the syncytial female gametophyte can be changed very late before cellularization.

Interpopulation improvement for crosses of close populations in crops and livestock depends on the amount of heterosis and the amount of variance of dominance deviations in the hybrids. It has been intuited that the further the distance between populations, the lower the amount of dominance variation and the higher the heterosis. Although experience in speciation and interspecific crosses shows, however, that this is not the case when populations are so distant-here we confine ourselves to the case of not-too-distant populations typical in crops and livestock. We present equations that relate the distance between 2 populations, expressed as Nei's genetic distance or as correlation of allele frequencies, quadratically to the amount of dominance deviations across all possible crosses and linearly to the expected heterosis averaging all possible crosses. The amount of variation of dominance deviations decreases with genetic distance until the point where allele frequencies are uncorrelated, and then increases for negatively correlated frequencies. Heterosis always increases with Nei's genetic distance. These expressions match well and complete previous theoretical and empirical findings. In practice, and for close enough populations, they mean that unless frequencies are negatively correlated, selection for hybrids will be more efficient when populations are distant.

Epigenetic regulation varies with the environment. In the fruit fly Drosophila melanogaster, environmental temperature can affect chromatin-based gene regulation. Genes regulated by the Polycomb group can vary in their transcriptional output in response to changes in temperature, which typically increases with decreasing temperature. Here, we studied temperature-sensitive expression of Polycomb group target genes on a genome-wide scale, as well as temperature-sensitive enrichment of two histone modifications associated with the regulation of Polycomb group target genes, H3K27me3 and H3K4me3. We investigated temperature-sensitivity in adult flies, and possible differences thereof between populations adapted to temperate and tropical climates. Compared to genes not targeted by the Polycomb group, an elevated number of target genes showed higher expression at the lower temperature, as it is typically observed for Polycomb group regulation. Many of the Polycomb group target genes also exhibited temperature-sensitive H3K4me3 enrichment in the same direction, and the H3K4me3 temperature response correlated positively with that of expression. A small set of target sites also showed temperature-sensitive enrichment of H3K27me3, again with a higher proportion corresponding to increased transcriptional activation at the lower temperature. Overall, higher transcriptional activity at lower temperature was less pronounced in males compared to females, and in temperate compared to tropical flies. Possible trans- and cis-acting factors responsible for reduced expression plasticity in temperate flies were identified, including factors belonging to the Trithorax group and insulator binding proteins, respectively.

Differential gene expression between environments often underlies phenotypic plasticity. However, environment-specific expression patterns are hypothesized to relax selection on genes, and thus limit plasticity evolution. We collated over 27 terabases of RNA-sequencing data on Arabidopsis thaliana from over 300 peer-reviewed studies and 200 treatment conditions to investigate this hypothesis. Consistent with relaxed selection, genes with more treatment-specific expression have higher levels of nucleotide diversity and divergence at nonsynonymous sites but lack stronger signals of positive selection. This result persisted even after controlling for expression level, gene length, GC content, the tissue specificity of expression, and technical variation between studies. Overall, our investigation supports the existence of a hypothesized trade-off between the environment specificity of a gene's expression and the strength of selection on said gene in A. thaliana. Future studies should leverage multiple genome-scale datasets to tease apart the contributions of many variables in limiting plasticity evolution.

Over evolutionary timescales, the logic and pattern of cell-type specific gene expression can remain constant, yet the molecular mechanisms underlying such regulation can drift between alternative forms. Here, we document a new example of this principle in the regulation of the haploid-specific genes in a small clade of fungal species. For most ascomycete fungal species, transcription of these genes is repressed in the a/α cell type by a heterodimer of two homeodomain proteins, Mata1 and Matα2. We show that in the species Lachancea kluyveri, most of the haploid-specific genes are regulated in this way, but repression of one haploid-specific gene (GPA1) requires, in addition to Mata1 and Matα2, a third regulatory protein, Mcm1. Model building, based on x-ray crystal structures of the three proteins, rationalizes the requirement for all three proteins: no single pair of the proteins is optimally arranged, and we show that no single pair can bring about repression. This case study exemplifies the idea that the energy of DNA binding can be "shared out" in different ways and can result in different DNA-binding solutions across different genes-while maintaining the same overall pattern of gene expression.

Chromosome breakage plays an important role in the evolution of karyotypes and can produce deleterious effects within a single individual, such as aneuploidy or cancer. Forces that influence how and where chromosomes break are not fully understood. In humans, breakage tends to occur in conserved hotspots called common fragile sites (CFS), especially during replication stress. By following the fate of dicentric chromosomes in Drosophila melanogaster, we find that breakage under tension also tends to occur in specific hotspots. Our experimental approach was to induce sister chromatid exchange in a ring chromosome to generate a dicentric chromosome with a double chromatid bridge. In the following cell division, the dicentric bridges may break. We analyzed the breakage patterns of 3 different ring-X chromosomes. These chromosomes differ by the amount and quality of heterochromatin they carry as well as their genealogical history. For all 3 chromosomes, breakage occurs preferentially in several hotspots. Surprisingly, we found that the hotspot locations are not conserved between the 3 chromosomes: each displays a unique array of breakage hotspots. The lack of hotspot conservation, along with a lack of response to aphidicolin, suggests that these breakage sites are not entirely analogous to CFS and may reveal new mechanisms of chromosome fragility. Additionally, the frequency of dicentric breakage and the durability of each chromosome's spindle attachment vary significantly between the 3 chromosomes and are correlated with the origin of the centromere and the amount of pericentric heterochromatin. We suggest that different centromere strengths could account for this.

The karyotype, or number and arrangement of chromosomes, has varying levels of stability across both evolution and disease. Karyotype changes often originate from DNA breaks near the centromeres of chromosomes, which generally contain long arrays of tandem repeats or satellite DNA. Drosophila virilis possesses among the highest relative satellite abundances of studied species, with almost half its genome composed of three related 7 bp satellites. We discovered a strain of D. virilis that we infer recently underwent three independent chromosome fusion events involving the X and Y chromosomes, in addition to one subsequent fission event. Here, we isolate and characterize the four different karyotypes we discovered in this strain which we believe demonstrates remarkable genome instability. We discovered that one of the substrains with an X-autosome fusion has an X-to-Y chromosome nondisjunction rate 20 × higher than the D. virilis reference strain (21% vs 1%). Finally, we found an overall higher rate of DNA breakage in the substrain with higher satellite DNA compared to a genetically similar substrain with less satellite DNA. This suggests that satellite DNA abundance may play a role in the risk of genome instability. Overall, we introduce a novel system consisting of a single strain with four different karyotypes, which we believe will be useful for future studies of genome instability, centromere function, and sex chromosome evolution.

Evolution is driven by the accumulation of competing mutations that influence survival. A broad form of genetic variation is the amplification or deletion of DNA (≥50 bp) referred to as copy number variation (CNV). In humans, CNV may be inconsequential, contribute to minor phenotypic differences, or cause conditions such as birth defects, neurodevelopmental disorders, and cancers. To identify mechanisms that drive CNV, we monitored the experimental evolution of Saccharomyces cerevisiae populations grown under sulfate-limiting conditions. Cells with increased copy number of the gene SUL1, which encodes a primary sulfate transporter, exhibit a fitness advantage. Previously, we reported interstitial inverted triplications of SUL1 as the dominant rearrangement in a haploid population. Here, in a diploid population, we find instead that small linear fragments containing SUL1 form and are sustained over several generations. Many of the linear fragments are stabilized by de novo telomere addition within a telomere-like sequence near SUL1 (within the SNF5 gene). Using an assay that monitors telomerase action following an induced chromosome break, we show that this region acts as a hotspot of de novo telomere addition and that required sequences map to a region of <250 base pairs. Consistent with previous work showing that association of the telomere-binding protein Cdc13 with internal sequences stimulates telomerase recruitment, mutation of a four-nucleotide motif predicted to associate with Cdc13 abolishes de novo telomere addition. Our study suggests that internal telomere-like sequences that stimulate de novo telomere addition can contribute to adaptation by promoting genomic plasticity.

Numerous studies over the last decade have demonstrated the utility of machine learning methods when applied to population genetic tasks. More recent studies show the potential of deep-learning methods in particular, which allow researchers to approach problems without making prior assumptions about how the data should be summarized or manipulated, instead learning their own internal representation of the data in an attempt to maximize inferential accuracy. One type of deep neural network, called Generative Adversarial Networks (GANs), can even be used to generate new data, and this approach has been used to create individual artificial human genomes free from privacy concerns. In this study, we further explore the application of GANs in population genetics by designing and training a network to learn the statistical distribution of population genetic alignments (i.e. data sets consisting of sequences from an entire population sample) under several diverse evolutionary histories-the first GAN capable of performing this task. After testing multiple different neural network architectures, we report the results of a fully differentiable Deep-Convolutional Wasserstein GAN with gradient penalty that is capable of generating artificial examples of population genetic alignments that successfully mimic key aspects of the training data, including the site-frequency spectrum, differentiation between populations, and patterns of linkage disequilibrium. We demonstrate consistent training success across various evolutionary models, including models of panmictic and subdivided populations, populations at equilibrium and experiencing changes in size, and populations experiencing either no selection or positive selection of various strengths, all without the need for extensive hyperparameter tuning. Overall, our findings highlight the ability of GANs to learn and mimic population genetic data and suggest future areas where this work can be applied in population genetics research that we discuss herein.

tRNA splicing endonuclease (TSEN) has a well-characterized role in transfer RNA (tRNA) splicing but also other functions. For yeast TSEN, these other functions include degradation of a subset of mRNAs that encode mitochondrial proteins and an unknown essential function. In this study, we use yeast genetics to characterize the unknown tRNA-independent function(s) of TSEN. Using a high-copy suppressor screen, we found that sen2 mutants can be suppressed by overexpression of SEN54. This effect was seen both for tRNA-dependent and tRNA-independent functions indicating that SEN54 is a general suppressor of sen2, likely through structural stabilization. A spontaneous suppressor screen identified mutations in the intron-debranching enzyme, Dbr1, as tRNA splicing-independent suppressors. Transcriptome analysis showed that sen2 mutation activates the Gcn4 stress response. These Gcn4 target transcripts decreased considerably in the sen2 dbr1 double mutant. We propose that Dbr1 and TSEN may compete for a shared substrate, which TSEN normally processes into an essential RNA, while Dbr1 initiates its degradation. These data provide further insight into the essential function(s) of TSEN. Importantly, single amino acid mutations in TSEN cause the generally fatal neuronal disease pontocerebellar hypoplasia (PCH). The mechanism by which defects in TSEN cause this disease is unknown, and our results reveal new possible mechanisms.

Studying the signatures of evolution can help to understand genetic processes. Here, we demonstrate how the existence of balancing selection can be used to identify the breeding systems of fungi from genomic data. The breeding systems of fungi are controlled by self-incompatibility loci that determine mating types between potential mating partners, resulting in strong balancing selection at the loci. Within the fungal phylum Basidiomycota, two such self-incompatibility loci, namely HD MAT locus and P/R MAT locus, control mating types of gametes. Loss of function at one or both MAT loci results in different breeding systems and relaxes the MAT locus from balancing selection. By investigating the signatures of balancing selection at MAT loci, one can infer a species' breeding system without culture-based studies. Nevertheless, the extreme sequence divergence among MAT alleles imposes challenges for retrieving full variants from both alleles when using the conventional read-mapping method. Therefore, we employed a combination of read-mapping and local de novo assembly to construct haplotypes of HD MAT alleles from genomes in suilloid fungi (genera Suillus and Rhizopogon). Genealogy and pairwise divergence of HD MAT alleles showed that the origins of mating types predate the split between these two closely related genera. High sequence divergence, trans-specific polymorphism, and the deeply diverging genealogy confirm the long-term functionality and multiallelic status of HD MAT locus in suilloid fungi. This work highlights a genomics approach to studying breeding systems regardless of the culturability of organisms based on the interplay between evolution and genetics.

The advent of CRISPR/Cas9-mediated genome editing has expanded the range of animals amenable to targeted genetic analysis. This has accelerated research in animals not traditionally studied using molecular genetics. However, studying genes essential for reproduction or survival in such animals remains challenging, as they lack the tools that aid genetic analysis in traditional genetic model organisms. We recently introduced the use of distinguishably marked knock-in pairs (DMKPs) as a strategy for rapid and reliable genotyping in such species. Here we show that DMKPs also facilitate the maintenance and study of mutations that cannot be maintained in a homozygous state, a group which includes recessive lethal and sterile mutations. Using DMKPs, we disrupt the zero population growth locus in Drosophila melanogaster and in the dengue vector mosquito Aedes aegypti. In both species, DMKPs enable the maintenance of zero population growth mutant strains and the reliable recovery of zero population growth mutant animals. Male and female gonad development is disrupted in fly and mosquito zero population growth mutants, rendering both sexes sterile. In Ae. aegypti, zero population growth mutant males remain capable of inducing a mating refractory period in wild-type females and of competing with wild-type males for mates, properties compatible with zero population growth serving as a target in mosquito population suppression strategies. DMKP is readily generalizable to other species amenable to CRISPR/Cas9-mediated gene targeting, and should facilitate the study of sterile and lethal mutations in multiple organisms not traditionally studied using molecular genetics.

We construct a reliable estimation method for evolutionary parameters within the Wright-Fisher model, which describes changes in allele frequencies due to selection and genetic drift, from time-series data. Such data exist for biological populations, for example via artificial evolution experiments, and for the cultural evolution of behavior, such as linguistic corpora that document historical usage of different words with similar meanings. Our method of analysis builds on a Beta-with-Spikes approximation to the distribution of allele frequencies predicted by the Wright-Fisher model. We introduce a self-contained scheme for estimating parameters in the approximation, and demonstrate its robustness with synthetic data, especially in the strong-selection and near-extinction regimes where previous approaches fail. We further apply the method to allele frequency data for baker's yeast (Saccharomyces cerevisiae), finding a significant signal of selection in cases where independent evidence supports such a conclusion. We further demonstrate the possibility of detecting time-points at which evolutionary parameters change in the context of a historical spelling reform in the Spanish language.