G3 Genes|Genomes|Genetics

Transgenic GAL4 lines are widely used in Drosophila to label and manipulate specific cell types, but the resulting reporter expression patterns do not always represent ongoing driver activity. We generated a collection of neuropeptide T2A-GAL4 knock-ins and characterized their expression by native-fluorescence imaging using UAS-CD8::GFP and a Brp-miRFP680 knock-in, eliminating the need for immunostaining. During characterization of these lines, we observed cases in which adult GFP patterns did not match the on-going GAL4 activity, as well as cases in which GAL4 produced adverse cellular effects. Using temperature-sensitive GAL80, we found that adult GFP expression in certain neurons driven by CCHa2-T2A-GAL4 and Dsk-T2A-GAL4 depended on GAL4 activity before eclosion and was not reproduced by adult-only induction. Several GAL4 lines also showed dominant developmental phenotypes. Heterozygous Burs-T2A-GAL4 animals, for example, displayed wing-expansion defects that were fully suppressed by GAL80. Severe wing defects were not accompanied by a reduction in the number of reporter-labeled neurons before eclosion, but the morphology of these neurons were affected. These observations illustrate how developmental driver history and GAL4-associated cellular effects can influence reporter patterns in the adult nervous system.

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.

The sexual identity of specific tissues can be altered through cell-autonomous manipulation of the sex determination pathway in the nematode Caenorhabditis elegans. Previously described sexually mosaic strains carried multicopy transgenic arrays that are potentially subject to transgene silencing or misexpression artefacts. We used here the CRISPR/Cas9 system to engineer strains in which coding sequences for either a masculinizing agent (FEM-3) or a feminizing agent (intracellular domain of TRA-2) are inserted with a trans-splicing system at the 3 end of endogenous genetic loci that are known to be expressed in either a neuron-specific (rab-3) or gut-specific (elt-2) manner. We validate the tissue-specific sex-transformations induced by these genomic manipulations through expression analysis of known sex-specific genes and through assaying behavioral readouts. These strains may serve the worm community as standard reference tools to study the consequences of tissue-specific sex transformations.

Site-specific recombinases, such as Cre recombinase (Cre) and FLP recombinase (FLPase), are popular tools that enable precise spatiotemporal control over fluorescent reporter genes. However, studies show that increased Cre expression can lead to cytotoxic phenotypes including DNA damage, cell cycle arrest, cell death, and aneuploidy. In contrast, there is little-to-no known cytotoxicity associated with FLPase. FLPase is considered to be the safer, if less efficient, recombinase. To compensate for decreased efficiency, researchers will often increase expression of the FLPase to ensure a complete gene edit. Despite previous evidence that FLPase is nontoxic at high doses, we report that high expression of FLPase from multi-copy extrachromosomal arrays can disrupt synaptic protein trafficking in C. elegans. We discovered several off-target effects of high FLPase expression including mislocalization of the pre-synaptic marker FLPon::mScarlet::SYD-2 and decreased synaptic abundance, transport, and expression of the ionotropic glutamate receptor subunit GLR-1. Neither overexpression of an inactive FLPase, low activity FLPase, nor mCherry under the same promoter elicited these effects. However, single-copy expression of the FLPase construct reliably tags FLPon::mScarlet::SYD-2 and does not lead to these off-target effects. This work supports growing awareness that tyrosine recombinases can become cytotoxic at high doses.

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.

Breedbase ( is a comprehensive, web-based, open-source breeding management and analysis software for plant breeding that was introduced to address gaps with existing software for plant breeding data. Breedbase is continually improved and developed, with new features being added as required by the breeding community. Since its inception, the capabilities of Breedbase were improved to better serve the diverse data modeling needs of additional crops beyond our original ensemble of cassava, banana, yam, sweet potato, tomato, rice, and wheat. We describe here major updates that have been made in the past 4 years, including (1) improved handling of repetitive measurements; (2) a redesigned experimental treatments interface; (3) a more fine-grained user permission system; (4) improved trial quality control workflows; (5) intercropping support; (6) the addition of a decision meeting feature that helps decision makers make the best selection with the available data; (7) transgenics and tracking tools and finally, (8) an improved field layout tool which consolidates several trials in one field. These new features integrate seamlessly with the previous feature set of Breedbase - making it one of the most feature rich breeding management softwares available.

Generating high-quality genome assemblies for small animals with large genomes is complex due to their small body size, DNA contamination, and repetitive elements. Ticks exemplify these complexities, while also being a global health threat to humans, domestic animals, and wildlife. Advances in long-read sequencing platforms now make it feasible to obtain large amounts of raw sequence data from individual specimens, but challenges remain. Key genome workflow challenges include error correction, assembly, transposable element annotation, and chromosome assignment and synteny. Here we examine three individual Dermacentor reticulatus ticks using deep Oxford Nanopore sequencing. Comparing and contrasting bioinformatic tools for raw read and assembly manipulation allows us to identify the parameters that provide a high-quality haploid genome assembly among 38 assemblies. We find Dorado error corrected raw read data from approximately two flow cells are needed, but limiting assembly coverage to 40x produces the highest quality assemblies. Then we examined the effects of optimal workflow parameters on downstream analyses of gene synteny and manual transposable element annotation of the three tick assemblies in comparison to an independent assembly of a fourth D. reticulatus individual from a different country. Gene synteny analysis allows chromosome assignment of scaffolds and transposable element identification was improved markedly with manual curation. Finally, we compared the genetic variation of D. reticulatus across two populations and found similar genetic diversity. Our study provides a clear workflow to obtain high-quality assemblies from Oxford Nanopore sequences and genetic characterization of a species with a large, complex, and repetitive genome.

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.

We present draft genome assemblies for two poneroid ant species with distinctive life history traits: Platythyrea mocquerysi Emery, 1899 (Ponerinae) and Stigmatomma oregonense Wheeler, 1915 (Amblyoponinae). Platythyrea mocquerysi is a Malagasy ant in which larvae produce secretions from a ventral tubercle that are consumed by adults, representing an unusual form of larva-to-adult trophallaxis. Stigmatomma oregonense, a North American "dracula ant," feeds non-lethally on larval haemolymph. Using PacBio HiFi long-read sequencing, we assembled the P. mocquerysi genome (187 Mb, 307 scaffolds, N50 = 5.26 Mb, BUSCO 99.2% complete) and the S. oregonense genome (262 Mb, 1,189 scaffolds, N50 = 0.84 Mb, BUSCO 98.3% complete). These genomes encode 10,860 and 12,354 protein-coding genes, respectively. Repeat content is higher in S. oregonense than in P. mocquerysi, 54.3% against a lower bound of 15.7%. Most of the difference is in unclassified repeats, which we show to be diverged transposable elements. Comparative analysis with two additional poneroid genomes from closely related species reveals that genome size variation across poneroid ants is largely explained by transposable element dynamics, with notable expansions in several gene families including carboxylesterases, serine proteases, and lipid metabolism genes in Amblyoponinae. These genomes provide essential resources for investigating the molecular basis of unconventional brood management strategies in ants.

Dominance is an important and evolvable property of the genotype-phenotype map. A longstanding debate in evolutionary genetics concerns whether dominance is determined primarily by intrinsic properties of alleles at the focal locus or by modifiers elsewhere in the genome. Theoretical models show that second-site modifiers of dominance can evolve under some conditions. However, direct empirical tests of these models are rare because they require holding the focal heterozygous genotype constant while changing the rest of the genome. In the Drosophila montium species subgroup, female pigmentation is a Mendelian trait controlled by a single gene, POU domain motif 3 (pdm3), but the dominance relationships between pdm3 alleles differ among species. Using reciprocal introgressions among three closely related species, we compared females carrying the same Light/Dark pdm3 allele combinations in different homozygous or heterozygous genomic backgrounds and across different temperatures. In both species-pair comparisons, changing genomic background significantly altered the phenotype of identical pdm3 heterozygotes, demonstrating the existence of second-site modifiers of dominance. The effects of dominance modifiers depend on the particular pair of pdm3 alleles and on rearing temperature. These results show that dominance in this system is a genotype-by-genotype-by-environment trait, rather than a fixed attribute of individual alleles. The finding that second-site modifiers can alter dominance by reshaping reaction norms provides a developmental mechanism that links the evolution of dominance to phenotypic plasticity.

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.

Recombination shapes allelic combinations across the genome and plays a central role in adaptation and speciation. While recombination rates are known to vary and evolve, how recombination landscapes diverge between populations and which processes drive this divergence remains poorly understood. Here, we use the Population Recombination Divergence Index (PRDI) to quantify divergence in effective recombination landscapes between seven pairs of populations and species from four percomorph fish lineages (cichlids, sticklebacks, killifish, and clownfish). While accounting for stochasticity and confounders of linkage disequilibrium (LD) -based recombination rate estimates, we find that recombination landscapes diverged substantially in all comparisons. This divergence generally increases with genetic differentiation and divergence time, but the amount of PRDI accumulated per unit of genetic divergence (FST), net nucleotide divergence (da), or divergence time varies markedly among population and species pairs. Comparisons across systems suggest that PRDI accumulation tends to be faster (per unit of FST, da, or divergence time) in pairs with higher inferred gene flow. We also introduce a local version of PRDI (_l) to better characterize genomic heterogeneity in effective recombination divergence. We find that higher inferred gene flow between populations tends to be associated with stronger intragenomic correlation between local FST and _l. Finally, we propose a conceptual framework for investigating how divergent selection and gene flow may interact to shape effective recombination landscape divergence. Our work highlights the heterogeneous dynamics of effective recombination landscape evolution, and motivates further theoretical and empirical efforts to integrate recombination landscape evolution into studies of adaptation and speciation.

Breeding programmes choose genomic prediction models by accuracy rankings, and the metric behind a ranking decides which model wins. Selecting the best genotypes within a trial depends only on the order of the predictions, so a metric that guides the choice must be unchanged by any order-preserving change of the predictions and respond when their order is reversed. Of the 22 official metrics of the Genomes to Fields maize competition, one meets both conditions, the within-environment rank correlation; the within-environment Pearson correlation is protected against rescaling only; and twenty fail, including the root mean squared error that decided the 2022 ranking. Switching between the competitions two official metrics reverses 27 % of team pairs, and an exact decomposition shows why pooled metrics mislead: in three constructed panels, 94-95 % of the attainable square of pooled correlation is carried by the environment means. The accuracy difference a trial can resolve falls as about 3/{surd}N with its N genotype-environment cells: at least 0.03 at the competitions design and 0.04-0.12 once calibrated on real panels, against 0.003 between the first two teams; tests that two correlations differ declare far smaller differences, which do not reliably change selection. In soybean, where the two most accurate methods stand clear of most others by more than the trial resolves, ranking by either within-environment correlation selects better material, 98-99 % of the attainable selection gain in held-out environments against 13-34 % for error-magnitude rankings; in common bean and a Chinese maize population, where the leading methods lie within the resolvable gap, all rules pick material of similar value. GPverdict runs these checks on any programmes cross-validated predictions.

Forward genetics is a powerful approach for gene discovery, but identifying causal mutations becomes difficult when mutants are maintained in heterogeneous populations with uncertain pedigrees. This is exemplified by classical tasselseed (ts) mutants, which have long served as a genetic model for studying sex determination and carpel suppression. Decades of repeated outcrossing to diverse inbred lines have created substantial genetic heterogeneity, limiting the effectiveness of conventional bulked-segregant analysis sequencing (BSA-Seq). To address this, we developed a BSA-Seq framework that integrates flexible experimental designs, multiple reference genomes, and complementary statistical methods tailored for genetically heterogeneous populations. Applying this framework revealed that reference genome selection is critical for mapping success and that Euclidean distance raised to the fourth power (ED4) outperformed homozygosity mapping (HM). Furthermore, the framework enables simultaneous mapping of multiple mutations within a single population, eliminating the need for additional mapping populations. Applying this framework to 26 ts mutant stocks from the Maize Genetics Cooperation Stock Center, we successfully mapped 24 mutants to genomic intervals containing known ts genes, while the remaining mutants mapped to distinct genomic intervals, defining novel candidate regions underlying carpel suppression. Together, these results demonstrate that historical mutant collections represent an underutilized resource for gene discovery and establish a generalizable mapping strategy for unlocking their genetic potential across diverse species.

The sheep research community benefits from a genome assembly that has been refined over the last 15 years. However, the rich diversity of sheep breeds suggests that a single individual genome is not enough to represent the species full genomic content. Third-generation sequencing technologies have recently made it possible to generate high quality assemblies that should enable to elucidate unique and/or complex phenotype determinisms depending on genetic structural variations. In the SeqOccin project, twelve breeds were selected to represent (mostly French) sheep genetic diversity: Basco-Bearnaise, Black Belly, Blanche du Massif Central, Corse, Ile de France, Lacaune, Manech Tete Noire, Noire du Velay, Ouessant, Rambouillet, Vendeen, Soay. High-molecular-weight DNA was extracted from blood samples and subjected to long read whole-genome sequencing. The reads were used to generate de novo assemblies and were aligned onto the public reference to call structural variants. PacBio HiFi and parental Illumina reads were used to assemble phased haplotypes of the Lacaune breed. For the other breeds, PacBio raw (CLR) or ONT reads were generated. Our work demonstrates the feasibility of assembling genomes with a reasonable amount of data and appropriate software packages, delivering one high-quality assembly and 11 standard sheep assemblies that pave the way for pangenome construction and structural variant functional studies.

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.

Genotype-by-environment interactions can complicate plant breeding because genetic effects may vary across weather regimes, locations, and years. Although genomic prediction models can use dense marker data to predict complex crop traits, they often provide limited information about how marker relevance changes across environmental conditions. This study introduces a graph-based framework for estimating environment-associated marker rankings from multi-environment crop trial data. We introduce an attention-based graph neural network that jointly represents SNP markers and weather-based environment vectors as interacting nodes and is designed to learn environment-associated marker rankings from supervised yield data. The model is trained using yield prediction as the supervised objective, and the learned marker-level attention signals are aggregated to estimate marker rankings overall and within groups of similar environments. We evaluate the framework on two genotype-by-environment datasets. In both datasets, we examine whether learned marker rankings are stable across independent training runs and determine the overlap between high-ranked markers and external GWAS references. In a maize dataset with data from 212 different site-years, we rank markers separately within each weather-defined environment cluster and define a global marker set as the markers shared across all clusters. This provides a structured way to examine how marker rankings vary across weather-defined groups and which markers remain important across environments. We further encode each weather variable with a separate LSTM combined by attention, which makes the contribution of individual weather variables readable, and compare the resulting variable ranking against an independent SHAP-based attribution. Genes located near the top-ranked markers are also examined for functional enrichment. Overall, the results suggest that graph-based, environment-conditioned marker attribution may complement genomic prediction as an exploratory tool for studying context-dependent genomic signals in multi-environment trials.

The hybrid grouper 'Yushuban' (Cromileptes altivelis [female] x Epinephelus fuscoguttatus [male]) has shown promising performance in aquaculture trials, yet no complete reference genome has been available for this hybrid. We generated two gapless, telomere-to-telomere (T2T) haplotype-resolved genome assemblies of a single individual by integrating short-read, PacBio HiFi, Oxford Nanopore ultralong-read and Hi-C data. The maternal (Yushu_Calti_1.0) and paternal (Yushu_Efusc_1.0) haplotypes are 1,077.33 Mb and 1,083.36 Mb in length, with N50 values of 45.46 Mb and 45.55 Mb, respectively. Across all platforms, over 99.4% of reads mapped to each assembly, and Merqury-based quality values reached 57.7413 and 59.2068 (PacBio). BUSCO recovered 99.78% and 99.75% of complete core genes. We predicted 27,248 and 27,566 protein-coding genes, of which 98.52% and 99.23% were functionally annotated, and annotated telomeric motifs and repetitive elements (46.12% and 47.18% of each genome). These assemblies fill a gap in grouper genomic resources and provide a foundation for genetic dissection, parental genome comparison and molecular breeding of this hybrid.

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.

A complete reference genome for species with chromosomally-determined separate sexes should contain scaffolds for all sex chromosome homologs. However, sex chromosomes present distinct computational challenges compared to autosomes. Here we present a k-mer based analysis that utilizes whole-genome sequencing of a few sex-identified isolates: Cytogenetics-By-Sequencing (CBS) tools. Unlike other approaches that typically address one aspect of the sex chromosomes, CBS-tools strives to guide users from the discovery of the heterogametic sex through identifying the sex-determination region (SDR). The core of CBS-tools is automated quantification of sex-specific k-mers in order to predict the heterogametic sex. Using publicly-available datasets, CBS-tools correctly identified the known sex-system of the 31 species tested. Additionally, we used these k-mers to verify and correct phasing of sex chromosomes between haplotypes in species representing different sex-systems. Finally, we used these k-mers to delimit the SDR boundary using an interactive web platform. CBS-tools was developed with previously unexplored sex chromosome systems in mind, but is also suitable for well-examined sex chromosome pairs.