G3: Genes|Genomes|Genetics

Phosphatidylinositol (PI) phosphates (PIPs) are membrane lipids with crucial roles in intracellular signaling, membrane trafficking and cytoskeletal organization. To perturb PIP function in Drosophila melanogaster sperm development, we previously expressed the Salmonella PIP phosphatase SigD (also known as SopB) under control of a spermatocyte- specific promoter. SigD expression results in reduced levels of plasma membrane PI 4,5-bisphosphate [PI(4,5)P2; henceforth PIP2] and male sterility. Transgenic lines expressing high levels of SigD (SigD-high) exhibit defects in spermatocyte cytokinesis, ciliary transition zone maturation and spermatid elongation, whereas lines expressing low levels of SigD (SigD-low) have defects in nuclear shaping and spermatid cell polarization. To further investigate the role of PIPs during Drosophila sperm development, we conducted a sensitized genetic screen to identify suppressors and enhancers of SigD-low phenotypes. From a screen of 760 chromosomal deficiencies spanning 83.6% of chromosomes 2 and 3, we identified 80 interacting regions that were further narrowed down to 40 individual suppressors. Among the strongest interactors were genes involved in microtubule dynamics, nucleocytoplasmic transport and membrane trafficking. The novel genetic interactions identified by our screen pave the way for further investigation into molecular mechanisms underlying the affected aspects of sperm development.

Enhancing grain carotenoid concentration to increase yellowness and provitamin A content in sorghum (Sorghum bicolor [L.] Moench) is a major breeding objective across sub-Saharan Africa. Carotenoid breeding is constrained by costly post-harvest phenotyping and can be accelerated through genetic markers that capture functional variation in key carotenoid biosynthesis genes. Zeaxanthin epoxidase (ZEP) is a major gene controlling sorghum grain carotenoid accumulation, and SNP-based KASP markers facilitate selection of high-carotenoid grain, although quantitative variation remains among lines carrying the favorable allele. We hypothesized that additional functional variation within ZEP and other carotenoid biosynthesis pathway genes contributes to this variation and can be revealed by a pangenome-informed analysis. Using a 33-member pangenome reference, we characterized sequence and structural variation at ZEP and other key carotenoid biosynthesis genes and applied pangenome-derived genotyping to study marker diversity associated with carotenoid accumulation. Evaluation of ZEP in the pangenome reference revealed previously uncharacterized structural variation that is absent from the BTx623 primary reference genome. A pangenome-based association analysis identified genetic markers associated with the accumulation of carotenoids which were specific to particular pangenome reference members, including in RTx430 and SRN39, both yellow endosperm lines. Machine learning identified markers in ZEP, {beta}-OH, ZDS, and Z-ISO as the most predictive for all carotenoid traits, suggesting a multi-locus genetic architecture underlies the accumulation of carotenoids in sorghum grain. By integrating sorghum pangenomic resources with machine learning, this study establishes a framework for pangenome-accelerated trait discovery and identifies new genetic targets for carotenoid biofortification in sorghum.

In common wheat (Triticum aestivum L.), variation at the Vrn1 and Ppd1 loci changes plant phenology, resulting in differential adaptation useful to breeders. Because the effects of phenology on grain yield are conditional on environmental factors, the incorporation of markers for Vrn1 and Ppd1 alleles into breeding approaches has proven difficult. Historic phenotypic, genotypic, and environmental data can provide insight into the relationship between major phenology alleles and grain yield as mediated by environmental variables. Analyses of eight years of breeding trials (1,038 lines at 219 site-years) determined that weak vrn1 alleles and Ppd1 insensitivity alleles have variable effects. These effects change depending on an environment's winter temperature and latitude, respectively, but the environmentally-driven changes in effect of vrn1 alleles are much more variable than effects of Ppd1 alleles. Mediation analyses showed phenologically-dependent environmental variables are one mechanism through which phenological changes created by vrn1 and Ppd1 variants alter yield across multiple developmental stages. Environmentally-driven relationships between flowering time and yield were modeled to estimate yield allele effects as a function of effects on phenology and environmental variables. Weak winter alleles at vrn1 may play a stabilizing role on yield, due to the correlation of winter conditions that drive larger effects with later-season warm temperatures that penalize later maturity. A better mechanistic understanding of how these loci drive environment-specific yield effects may facilitate utilization of markers for these alleles and improve predictive modeling of yield.

Targeted protein turnover of the transcription factor C/EBP is enhanced by the Tribbles (Trib) pseudokinase family of adaptor proteins, which bind to a conserved degron motif in C/EBP substrate and recruit a cognate COP1 E3 ligase to ubiquitinate C/EBP for degradation. We identified a conserved degron in the Drosophila C/EBP ortholog Slbo and fused this motif to a fluorescent protein (GFP or RFP) under the control of a constitutive promoter. Transgenic flies expressing this fluorescent protein (FP)::degron transgene, which we call the Fluorescent Ubiquitination-based Trbl Turnover Indicator (or FUTTI) sensor, showed reduced levels of fluorescence in response to increased levels of Drosophila Tribbles (Trbl) and conversely, increased levels when Trbl activity was reduced. Mutations in the Trbl conserved pseudokinase substrate binding pocket and in a divergent PEST-like motif in the C-terminal tail region disrupted Trbl activity in the FUTTI assay. These data indicate that FUTTI will be a valuable tool to identify sites of Trbl activity in vivo and the critical features of the protein required for function.

Caraway (Carum carvi L., 2n = 2x = 20) is a medicinal and aromatic plant of the Apiaceae family valued for its essential oil with the major terpenoids carvone and limonene. While the essential oil content represents an important quality trait, low seed shattering and high thousand-grain weight (TGW) are key determinants of seed yield. As molecular tools remain scarce within Apiaceae breeding beyond carrot, we conducted a QTL mapping for these seed-related traits using two previously established F2 populations (Effective N(P1) = 236; N(P2) = 266). In P1 with the non-shattering maternal parent Rekord, QTL mapping revealed at least one shattering locus on LG03 (PVE: 9.9%). In addition, loci associated with essential oil (LG08, 10.5% PVE) and TGW (LG09, 11.1% PVE) were detected. In P2, we identified six essential-oil loci (LG02-06, LG10; combined PVE: 49.2%), with five loci affecting both carvone and limonene, and one (LG03) exclusively limonene. Additionally, a major QTL for TGW mapped to LG02 (PVE: 15.6%). For stalk attachment rate one minor QTL was detected (LG07, 8.5% PVE), while no QTL co-localized with the major shattering locus. To pave the path towards fine-mapping, we designed and validated 26 diagnostic PACE markers covering five key QTLs.

Amongst measures of linkage disequilibrium, the correlation measure r2, due originally to Sewall Wright, has several advantages. Although basically a haploid statistic, it can readily be estimated using covariance and correlation from diploid data. Its population expectation can also be found from probability methods. We show that the probability of linked identity by descent, LIBD, directly estimates the expectation for r2 for Wright-Fisher models. The simplest such model for two loci is the haploid model, where each haplotype is chosen independently from haplotypes of the previous generation. This gives an equilibrium between recombination (recombination frequency c) and drift (population size N) where the expected value of r2 is approximately 1/(1+4Nc). For diploid models, the expectation is similar for low values of c, but contains a term in c2 and rises to double the haploid value for the limiting value of c = 0.5. An increase in r2 is also expected for the model of monogamous mating, as opposed to random mating for each offspring. The expectation for r2 is unaffected by the use of diploid rather than haploid data, an exception being the case of monogamous mating. Computer simulation shows close agreement of r2 with probability expectations, with minor discrepancies observed for unlinked loci. Using the probabilistic definition, r2 can be intuitively understood as a parameter shaping the effective sample size in genome-wide association studies.

Reproductive stage drought disrupts flag leaf metabolism in rice (Oryza sativa), limiting photoassimilate translocation to developing grains and reducing grain yield (GY). How natural variation in this response relates to GY remains poorly understood. This study combines untargeted metabolomics of flag leaves from 271 indica rice accessions grown under well-watered (WW) and reproductive-stage water-limited (WL) field conditions with genome-wide association studies of 89 annotated polar metabolites. A total of 180 metabolite quantitative trait loci (mQTLs) were identified: 93 detected only under WL, 68 only under WW, and 19 under both conditions, indicating a predominant stress-dependent genetic control; mapping of GY itself detected only four marginal QTLs, none overlapping the mQTLs. Four high-density regions (HDRs) of mQTLs were identified: HDR1-1, detected only under WW conditions and associated mainly with raffinose family oligosaccharides; HDR1-2, HDR4, and HDR11, detected only under WL conditions and associated mainly with tricarboxylic acid cycle intermediates and amino acids. After correcting for genetic relatedness, accessions carrying the favourable haplotype at both HDR1-2 and HDR4 yielded 21.5% more under WL conditions than accessions carrying the unfavourable haplotype at both loci and lost 11.4 percentage points less GY to stress. Accessions carrying the favourable haplotype at only one locus showed a comparable reduction in yield loss. Haplotype-guided variant detection against the 3,000 Rice Genomes Project panel identified major-impact variants in candidate genes, including a polyphenol oxidase at HDR1-2 and tandem cytochrome P450s at HDR4. These hubs are promising, metabolically defined targets for breeding drought-resilient rice.

Heavy metal contamination of aquatic environments poses persistent risks to ecosystems and human health. Aquatic macrophytes such as Pistia stratiotes are increasingly used for phytoremediation due to their capacity to accumulate contaminants without displaying symptoms of abiotic stress. However, the molecular mechanisms underlying their metal tolerance remain poorly understood. Metallothioneins (MTs) are cysteine-rich proteins involved in metal binding and detoxification in plants. In this study, genome-wide analysis was performed to identify and characterise candidate MT genes in P. stratiotes and to assess their transcriptional response to copper exposure. Six novel MT genes (PsMT2f, PsMT3a-d, and PsMT4) were identified and classified into MT2, MT3, and MT4 subfamilies based on conserved cysteine motifs and domain architecture. Quantitative real-time PCR showed differential and tissue-specific expression of MT genes in roots and leaves following exposure to copper for up to 4 h. These findings provide the first comprehensive characterisation of the MT gene family in P. stratiotes and demonstrate their potential role in copper tolerance, supporting the application of this species in the phytoremediation of metal-contaminated aquatic systems.

Adult stem cells can survive diverse insults, from ionizing radiation to toxic chemicals. In vertebrates, ABC transporter expression and dye-efflux capacity have been associated with stem-cell protection and multidrug resistance. How compound accumulation differs between adult stem cells and their differentiated daughters within an intact tissue remains poorly understood. Here, we show that adult Drosophila intestinal stem/progenitor cells maintain a distinct low-accumulation state for membrane-permeable compounds and that ABC transporters contribute to this phenotype and to the response to cytotoxic stress. Across nine membrane-permeable probes, stem/progenitor cells accumulated eight at lower levels than differentiated enterocytes. We selected tetramethylrhodamine methyl ester (TMRM), a membrane-permeable fluorescent probe that showed a strong difference in accumulation between stem/progenitor cells and enterocytes, as a quantitative readout for an RNAi screen of all 56 Drosophila ABC-family genes. The screen identified seven candidate transporters whose depletion increased the stem/progenitor-to-enterocyte TMRM fluorescence ratio. Further characterization of one of them, ABCB7, showed that ABCB7-depleted guts contained fewer mitotic cells during cytotoxic drug exposure. These results implicate ABC transporters in lower compound accumulation in Drosophila intestinal stem/progenitor cells and support a role for ABC transporters in their response to cytotoxic challenge.

Understanding how crop wild relatives (CWR) adapt to diverse environments is important both for evolutionary biology and for the development of climate-resilient agriculture. CWR represent an important reservoir of adaptive variation that can be exploited for future crop improvement. To investigate how natural selection has shaped adaptation in these species, we analysed whole-transcriptome data from four diploid wild wheat relatives with contrasting mating systems: the outcrossing species Aegilops speltoides and Aegilops mutica, and the selfing species Aegilops tauschii and Triticum urartu. We combined the imputed McDonald--Kreitman test (MKT) with lineage-specific estimates of divergence obtained from branch-specific models of molecular evolution. This framework reduces biases caused by slightly deleterious mutations and enables adaptive substitutions to be assigned to individual evolutionary lineages. We detected marked differences among species in the prevalence of positive selection. Evidence of adaptive evolution was concentrated in the outcrossing species, whereas few positively selected genes were identified in the selfing species. Comparisons between standard and branch-specific MKT approaches showed that some signals initially inferred as shared among species were reassigned to individual lineages when divergence was estimated on a branch-specific basis, emphasizing the importance of accurately localizing adaptive substitutions. Functional annotation revealed several candidate genes containing domains associated with abiotic and biotic stress responses. Our study provides a framework for detecting positive selection in wild wheat relatives and identifies candidate genes that may contribute to adaptation and represent valuable targets for future functional analyses and wheat improvement programs.

Genetic interactions contribute to phenotypic variation, yet most studies characterize them in a small number of reference backgrounds rather than across natural populations. Studying genetic interactions in Caenorhabditis elegans is facilitated by RNAi by feeding, which enables gene-specific knockdowns across many genetic backgrounds without the need to construct individual mutant lines. However, individually screening hundreds of isolates across many RNAi conditions is laborious. Here, we developed a pooled platform that uses whole-genome sequencing to quantify the fitness of hundreds of genetically distinct C. elegans strains competing in a single flask. We leveraged this platform to evaluate RNAi responses in a pooled population of RNAi-sensitive C. elegans strains and identified two classes of QTL that influence RNAi responses. The first class influences responses to knockdowns of specific genes and is exemplified by a QTL that is specific to knockdown of mig-6. The second class influences general RNAi-response across multiple knockdowns. One QTL in this class localized to the right arm of chromosome III and was detected by both GWA and xQTL mapping, which suggests that a common large-effect variant underlies this QTL. We identified a T96K missense change in the dsRNA receptor SID-2 as the underlying causal variant. The 96K allele resides in the extracellular domain of SID-2 and confers increased RNAi sensitivity relative to the 96T allele. We hypothesize that the 96K allele enables greater uptake of ingested lumenal dsRNA through higher-affinity binding to the dsRNA phosphate backbone. The platform we developed enables systematic mapping of genetic interactions across natural populations at a previously impractical scale.

To reduce health risks for human space exploration, it is important to model the effects of deep-space radiation on biological systems. The budding yeast Saccharomyces cerevisiae is a common model organism in space radiobiology, but little is known about how radiation damage to individual cells translates into the population-level effects that experiments measure. The Agent-Based Model for Microbial Populations Exposed to Radiation (AMMPER) is a spatially explicit agent-based model that simulates the effects of ionizing radiation on S. cerevisiae cells and produces population-level results. Its goal is to improve experiment design and data interpretation. AMMPER-1 demonstrated that agent-based simulations can qualitatively reproduce the effects of proton radiation on the growth rate of wild-type and DNA-repair mutant yeast. Here, we present AMMPER-2, which addresses limitations of the first model and expands its capabilities. AMMPER-2 incorporates the dynamics of the redox dye alamarBlue, a data type commonly generated in spaceflight microbiology experiments, and models the fate of reactive oxygen species in more detail. It also adds an improved graphical interface and runs faster. AMMPER-2 remains easy to execute in Python on a standard personal laptop, providing space biologists a tool to explore experimental conditions, generate hypotheses, and interpret data from microbial space radiation experiments.

Cell differentiation into distinct cell types generates functional specialization in eukaryotic organisms. Many fungal species undergo filamentous growth, where cells differentiate into elongated and adhesive filaments capable of expansion and invasion into new environments. The budding yeast Saccharomyces cerevisiae also undergoes filamentous growth, and the regulatory pathways that control the response have been well characterized; however, the roles essential proteins play in this response have not been systematically explored. To address this gap in understanding, we constructed a collection of 332 temperature-sensitive (ts) alleles in 320 essential genes in a strain background that undergoes filamentous growth (called {Sigma}1278b or Sigma). The ts Sigma collection showed differences in temperature sensitivity compared to a ts laboratory strain collection, revealing unexpected phenotypic diversity in essential alleles across populations of individuals. Screening the ts Sigma collection for phenotypes related to filamentous growth uncovered new phenotypes for >35% of essential alleles. New regulators of the Mitogen-Activated Protein Kinase (MAPK) pathway that regulates filamentous growth (fMAPK) were identified, including Las17, a homolog of Wiskott-Aldrich Syndrome Protein (WASP) in humans. Las17 regulated the fMAPK pathway by promoting delivery of the sensor protein, Sho1, and Rho GTPase Cdc42 to the plasma membrane. Las17 also functioned as a hub coordinating separate parallel aspects of the filamentation response. The widespread roles for essential proteins in regulating a eukaryotic differentiation response suggest broader roles essential proteins than is currently appreciated.

Stressful events are associated with long-term adverse health impacts, but the causal mechanisms linking these exposures to subsequent disease remain poorly understood. One plausible mechanism is persistent changes to hormonal signaling that regulate metabolic homeostasis. Here, we examine the long-term impacts of stress associated with exposure to the 2004 Indian Ocean tsunami on levels of free triiodothyronine (FT3), a circulating measure of biologically active thyroid hormone, using data from the Study of Tsunami Aftermath and Recovery. We measure biomarkers 20 years after the tsunami in a population-representative sample age 35y+ in 2024 who, at the time of the tsunami, were living along the coast of Aceh, Indonesia, the most affected part of the Indian Ocean Basin. Because respondents were first interviewed before the tsunami and subsequently tracked regardless of migration, the sample avoids a major source of selection bias common in long-term disaster studies. We identify the causal effect of tsunami exposure using variation in community-level tsunami mortality, comparing communities within the same sub-district. We find that greater tsunami exposure reduced levels of FT3 20 years later. Exposure also altered relationships between FT3, body composition, and cortisol and increased cardiometabolic risk. These findings identify persistent alteration of thyroid hormone physiology as a potential pathway linking severe stressful exposures to long-term cardiometabolic disease risk.

Forward-in-time population genetic simulations are widely used in evolutionary analyses, but simulating large populations and long genomic regions remains computationally demanding. To reduce this cost, parameter rescaling is widely employed, in which the original evolutionary process is approximated by one with a smaller population size and fewer generations. Recently, several studies using the SLiM simulator have raised concerns about the accuracy of this rescaling approach. In this study, we show that many of the biases reported in these studies can be mitigated by using a different simulation algorithm. These results reveal that the accuracy of parameter rescaling depends on how well the simulation algorithm preserves diffusion-limit properties under rescaling.

The intrinsically disordered tardigrade Dsup protein has garnered attention for its ability to protect cells and organisms from radiation and oxidative stress. Our lab has previously described Dsups protective effect in yeast, finding that, while Dsup expression comes with a fitness cost, it improves survival under many stressors, including the heavy metal cadmium. While Dsups protection against oxidative stress and radiation is well-established, the mechanism by which it protects against other stressors is underinvestigated. To address this knowledge gap, we screened a collection of 4000 yeast deletion mutants expressing Dsup in the presence of three doses of cadmium to identify synergistic/synthetically lethal genes and processes. We find that Dsup broadly buffers many processes/genes at lower levels of cadmium stress but at higher doses, cells shift to buffering specific genes/processes. These results identify host genetic processes that influence Dsups ability to confer cadmium resistance to organisms.

Social genetic effects can substantially influence phenotypes in animals and plants and the study of them is of interest. Group housing in animals for example, in pigs provide an ideal framework for studying interactions among individuals. In animals, the genetic of social effects has been studied by simplifying the underlying interactions for example, by assuming that all the individuals in the group contribute equally to the social environment. This homogeneous behaviour is not observed in real conditions. Here, we address this issue showing that identification of interacting individuals is feasible in pig behaviour during growth, and we propose a model that leads to more accurate modelling of social genetics. Our approach infers the strength of interaction via time interval between visits of animals to automatic feeders. This measure of strength was then used in a reaction norm model to evaluate the genetic determinism of social effects. We also build a framework to transform variance components estimated for a trait continuously measured, such as feed intake per visit, into variance of total or aggregated trait e.g. during the growth period. Including social effects improves the fitting of the models. Visit-based social interaction was highest at short time intervals, decreasing rapidly and becoming negligible after 80 seconds. Variance components for the aggregated trait the total feed intake support the contribution of the social interactions. Our approach allows more precise understanding of social effects through individual feeding events and a measure of interaction strength, and further translates these into in an aggregated phenotype of interest.

Early embryos must mount stress defenses without compromising the developmental programs that drive morphogenesis, but whether genetic background alters this balance remains unclear. We compared cellularizing Drosophila melanogaster embryos from inbred and outcrossed backgrounds under control conditions and after acute or chronic heat-stress. Both backgrounds developed successfully and showed modest transcriptomic differences at 18{degrees}C. Heat stress at 32{degrees}C, however, sharply separated their phenotypic and transcriptional responses. Inbred embryos showed poor larval hatching after acute and chronic heat, and this deficit persisted through adult eclosion. Their transcriptomes exhibited a greater stress-response burden, with enrichment of proteostasis, DNA repair, mitochondrial maintenance, RNA processing, and metabolic remodeling programs. Outcrossed embryos retained substantially greater developmental survival and higher abundance of transcripts associated with development, adhesion, epithelial organization, signaling, transport, sensory responses, and morphogenesis. Background-dependent divergence was greatest during acute heat. Under chronic heat, background-dependent differences were fewer, with most overlapping those seen during acute heat and a smaller set detected only under chronic heat. Transcript-origin analysis further showed that acute outcrossed-biased genes were predominantly maternally derived and showed no enrichment for purely zygotic transcripts, whereas chronic outcrossed-biased genes contained a larger zygotic component. In summary, the less viable inbred background mounted the broader molecular stress signature, whereas the more viable outcrossed background retained greater abundance of development-associated transcripts. These findings identify genetic background as a major determinant of how embryonic heat responses are distributed between molecular stress defense and developmental gene expression.

Phakopsora pachyrhizi, the causal agent of soybean rust, is among the most aggressive and economically impactful pathogens affecting soybean (Glycine max) production worldwide. As a dikaryotic rust fungus, P. pachyrhizi maintains its genetic information as two discrete haplotypes that are sequestered within separate nuclei for most of its life cycle as it reproduces asexually via the production of infectious urediniospores. Previous genomes of three P. pachyrhizi isolates collected in South America revealed a large genome with a high transposable element content, measuring up to 1.25 Gb and 93%, respectively. Although these efforts provided valuable foundational resources, the complexity of the genome resulted in highly fragmented assemblies. Here, we generated a highly contiguous, substantially improved, annotated genome resource from the P. pachyrhizi isolate LA04-1, collected during the initial outbreak of soybean rust in the continental United States in 2004. The assembly is haplotype-phased, with each haplotype assembled into 18 chromosomes totaling 572 Mb and 569 Mb in size. The isolate contains unique mating-type genes and does not share haplotype genomes with any available isolates with whole-genome sequencing datasets. This resource will be valuable to future investigations into the underlying mechanisms of virulence in this important plant pathogen.

Sudden Death Syndrome (SDS), caused by Fusarium virguliforme, can significantly impact soybean yields. To advance the understanding of SDS resistance in plant introductions, we conducted genome-wide association studies (GWAS) on a set of 351 accessions from the USDA Soybean Germplasm Collection. The analysis revealed seven single nucleotide polymorphisms (SNPs) significantly associated with foliar SDS resistance; three significant QTL (on chromosomes 3, 9 and 11) were detected with Fixed and Random Model Circulating Probability Unification (FarmCPU) and four (on chromosomes 5, 6 and two on chromosome 7) with Bayesian-information and Linkage disequilibrium Iterative Nested Keyway (BLINK). Localized linkage disequilibrium blocks were estimated for these regions. Notably, all of them overlapped with regions where QTL associated with SDS resistance had been previously reported and where within, or close to, sequences annotated as implicated in plant defense mechanisms, such as toxin transporters and transcription factors. The architecture of SDS resistance appears quantitative and polygenic, with most loci explaining modest phenotypic variance. Six plant introductions in this study--PI 175188, PI 307889A, PI 323559, PI 578307C, PI 445683, and PI 323558--harbor favorable alleles at all seven loci, providing high-value resources for resistance introgression. This study underscores the value of leveraging the USDA Soybean Germplasm Collection for the discovery of resistance loci and provides a foundation for marker-assisted breeding to enhance SDS resistance in elite soybean lines.