G3: Genes|Genomes|Genetics

Overexpression of -synuclein (-syn), an inherently disordered protein, triggers chronic activation of the mitochondrial unfolded protein response (UPRmt) pathway in Caenorhabditis elegans with enhanced dopaminergic (DAergic) neurodegeneration. Introduction of a loss-of-function(lf) mutation in atfs-1, the main transcriptional regulator of the UPRmt, into -syn nematodes results in significant neuroprotection from -syn-induced DA neuron loss. Using this sensitized neuroprotective background, we performed a F3 forward genetic screen in C. elegans atfs-1(lf) mutants to identify molecular components associated with the modulation of neurodegeneration in -syn-expressing DA neurons. Homozygous mutant animals were examined for enhanced neurodegeneration; multiple independent alleles were uncovered. Among these, we identified new nonsense alleles encoding the histone lysine demethylases (H3K27me3), jmjd-1.2 (orthologous to human KDM7A, PHF2, and PHF8) and jmjd-3.1 (homologous to yeast CYC8). Another line carried a nonsense allele of twk-14. This gene encodes a conserved protein termed KCNK12 in mammals that facilitates passive background K+ leak currents to set and stabilize resting membrane potential. To further examine the association of these gene products with DA neurodegeneration, we used neuron-targeted RNA interference, mutants, or both. DA neurodegeneration was observed in the -syn + atfs-1(lf) background when jmjd-1.2, jmjd-3.1, or twk-14 were individually depleted. These results provide evidence that jmjd-1.2 and jmjd-3.1, which encode previously characterized H3K27me3 demethylases, and the uncharacterized twk-14 gene product, orthologous to human KCNK12, naturally confer protection from -syn-induced neurotoxicity.

Decades of research has uncovered a wealth of mechanistic information about the development of sensory bristles in Drosophila melanogaster. By studying large-effect, often loss-of-function mutations, many genes have been associated with bristle development, morphology, patterning, and number. Equally, the number of bristles present in certain areas of the fly cuticle is a classic quantitative trait, the genetic basis of which has been studied using a range of tools, from artificial selection to QTL (Quantitative Trait Locus) mapping. Such studies have often implicated well-understood bristle development genes as contributing to natural variation in bristle number. Here we contribute to the study of bristle number genetic variation in flies by executing a GWAS (genomewide association study). We generated whole genome sequences for 897 phenotyped male D. melanogaster individuals derived from a wild-derived, but lab-adapted outbred population, revealing - following quality control and filtering - over 780,000 variants with frequencies greater than 5%. Using these data we estimated the SNP (Single Nucleotide Polymorphism) heritability for ABN (abdominal bristle number) and SBN (sternopleural bristle number) as 0.28 and 0.35, respectively. These values indicate that our set of genotyped variants collectively explain a substantial fraction of the variance in phenotype in the mapping panel. Subsequently, genome scans revealed 1085 (ABN) and 211 (SBN) genomewide significant sites, and - due to extensive LD (Linkage Disequilibrium) in our panel - nearly all these sites are clustered into three locations; We find a GWAS hit for ABN in the middle of chromosome 3L, and hits for SBN at the tip of the X chromosome (where several prior mapping studies have resolved QTL for bristle number), and on 2L. Surveying existing studies that identified genes that control bristle number/development, we highlight several candidates that may segregate for causative, functional variants.

Understanding the genetic diversity and population structure of breeding materials is essential for developing stress-resilient cultivars. In tropical maize, where drought and low soil nitrogen (low N) severely limit productivity, continuous development of tolerant varieties remains a priority. This study assessed the genetic diversity and population structure of 250 doubled haploid lines (DHLs) derived from five drought- and low N-tolerant tropical populations. Genotyping was performed using mid-density DArTseq markers, yielding 3,305 high-quality SNPs for analysis. Results revealed a moderate level of diversity among the DHLs, with an average genetic distance of 0.39, a polymorphism information content (PIC) of 0.33, and a minor allele frequency (MAF) of 0.29. These values reflect substantial allelic variation, important for identifying complementary parental combinations in hybrid development. Discriminant analysis of principal components (DAPC) grouped the DHLs into five distinct clusters, largely corresponding to their source populations, although some admixture was observed. This indicates that while the genetic backgrounds of the source populations were mostly retained, recombination introduced useful variation. Overall, the clear population structure and high diversity observed among these DHLs provide a strong genetic foundation for future maize improvement. These lines represent valuable resources for heterotic group formation, hybrid development, and recurrent selection schemes aimed at enhancing drought and low nitrogen tolerance in tropical maize.

Spontaneous mutations are a rare but important source of novel genetic variation, yet their detection and characterization within active breeding programs are seldom documented at gene-level resolution. Grain size and shape are key determinants of rice quality, yield, and market classification. Here, we report the discovery and genetic characterization of a spontaneous short-grain (SG) mutation arising in the long-grain wild-type (WT) advanced breeding line RU2002174 from the LSU AgCenter Rice Breeding Program. The SG phenotype was first observed in 2019 and segregated in subsequent generations as a single recessive gene across both indica and japonica genetic backgrounds. Genetic mapping localized the mutation to a 41.6 kb interval on chromosome 5. Whole-genome sequencing identified a single candidate causal variant: a G[->]T transversion in exon 4 of SRS3 (Os05g06280), introducing a premature stop codon and resulting in a truncated protein. This allele was absent from representative U.S. breeding germplasm and the IRRI 3K SNP database, demonstrating that it represents a novel spontaneous loss-of-function allele of a previously characterized grain-size gene. These findings document the real-time emergence of functional genetic variation in elite rice germplasm and highlight the importance of monitoring off-types during seed increase and purification in breeding programs. They also provide additional insight into the role of kinesin-mediated cell elongation in determining rice grain architecture.

Withdrawal StatementThe authors have withdrawn their manuscript because it was submitted and made public without full consent of all authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

Common scab disease on potato is caused by members of more than 10 pathogenic Streptomyces species. Genome-enabled methods are being increasingly deployed to characterize Streptomyces that cause common scab disease of potato and other tuber and root crops. However, the study of phytopathogenic Streptomyces is constrained by the limited availability of high-quality genome sequences. Here we report improvements to the quality and completeness of genome assemblies for 12 pathogenic type strains of Streptomyces and six closely related non-pathogenic type strains. These assemblies have an average N50 of 7.4 Mbp and with BUSCO scores all greater than 98.5%. Analyses showed that the genomes of phytopathogenic Streptomyces are consistently among the largest Streptomyces genomes sequenced and, relative to those of non-pathogenic strains, are more enriched in genes involved in carbohydrate and amino acid metabolism. Plasmids were not consistently detected across assemblies, suggesting that they are not conserved across species and are not necessary for pathogenicity. Furthermore, comparisons of genome assemblies among both closely and distantly related strains revealed multiple rearrangements within linear chromosomes and reduced synteny near telomeric regions. These improved genome assemblies, many of which correspond to type strains, provide valuable resources for advancing our understanding of the pathogenicity in the genus.

Copy number variants (CNVs) are a major source of genetic diversity and could contain some of the missing heritability for mouse models of human disease. However, mouse CNVs have not been comprehensively characterized because they are difficult to resolve in repeat-rich, segmentally duplicated or reference sequence-absent regions of the genome. Here we analyzed long range sequence (LRS) data for 40 inbred mouse strains and characterized CNVs using pangenome graph-based (and other) methods and a C57BL/6J telomere to telomere (T2T) genome reference sequence. We resolved 1,594 high-confidence CNVs that often overlap tandem repeats (60.3%), segmental duplications (44.8%) or pericentromeric regions (11.5%); and 131 CNVs were T2T sequence-specific. CNVs affected 384 protein-coding genes, which spanned a range of important functional classes. The 40-strain pangenome map expanded the genome sequence from 2.29 to 3.32 Gb, with the wild-derived strains accounting for the largest sequence increments. Two different AIs were sequentially used to analyze this database and identify a 29-kb deletion CNV within the Nlrp1b locus of KK mice that contributed to the metabolic syndrome they develop. Human NLRP1 alleles also were associated with metabolic syndrome features in human populations. Hence, AI analyses of this comprehensive T2T pangenome-based resource could uncover some of the missing heritability for mouse models of human diseases and biomedical traits.

Anthropogenic copper (Cu) contamination from agriculture, mining, and industrial runoff creates environmental gradients affecting physiology and behavior in wild populations. While Cu toxicity in Drosophila melanogaster is well characterized, it remains unclear whether Cu resistance is one integrated trait or several independently evolving components. Using a subset of recombinant inbred lines (RILs) from the Drosophila Synthetic Population Resource (DSPR), we measured three components of Cu response: feeding avoidance, oviposition avoidance, and physiological tolerance (median lethal time, LT50) under sustained Cu exposure. All three traits showed substantial phenotypic variation among RILs. Feeding and oviposition avoidance were both highly heritable (H 2 ~ 0.88), and RIL identity accounted for 49.5% of the variance in LT50. However, the three traits showed no significant correlation across RILs, indicating distinct genetic architecture. We identified a single male specific quantitative trait locus (QTL) on chromosome 2R that explained 17.7% of the variation in feeding preference; the interval included candidate detoxification genes Jheh1, Jheh2, Jheh3 and sano, the latter of which is associated with olfactory behavior. No significant QTL were detected for oviposition preference, suggesting a highly polygenic structure that may difficult to detect with our limited panel size. Together, these results indicate that Cu resistance in D. melanogaster is genetically modular. Behavioral avoidance during feeding, oviposition, and physiological tolerance are heritable but architecturally distinct components, each with potential to respond to selection independently.

The black bean aphid, Aphis fabae is a crop pest and vector of insect-transmitted pathogens, comprising closely related sub-species with overlapping host ranges. In other Aphis species, over-expression of specific detoxification genes has been linked to insecticide tolerance. We present two chromosome-scale assemblies for a clonal A. fabae line, representing two phased haplotypes, generated using HiFi and Hi-C sequencing technologies. A comprehensive genome annotation, built with PacBio Iso-Seq data, was used to investigate genes underlying insecticide tolerance. Both genomes are comprised of four chromosomal blocks (haplotype 1: 427 Mb; haplotype 2: 396 Mb) with high BUSCO completeness (98.7%). Comparative genomics revealed an expansion of UDP-glycosyltransferases, whose expression is linked to insecticide detoxification in other Aphis species. These high-quality references provide a foundation for studying A. fabae sub-species and a genomic resource for investigating insecticide tolerance across the Aphis genus. Author summaryHere we have provided a comprehensive assembly and annotation for further study into the Black bean aphid, Aphis fabae, using up to date long-range sequencing technologies. The final assemblies for both haplotypes are chromosome length and consist of 4 main chromosome blocks, consistent with the literature. The A. fabae genome was found to contain an increase in copy number of UDP-glycosyltransferases, which have previously been linked to insecticide resistance. The work here will be a resource to those studying insecticide tolerance in crop pests, as well as the differences between A. fabae sub-species.

Genotype-environment association (GEA) analyses are widely used to identify loci underlying local adaptation by examining correlations between allele frequencies and environmental variables across a species' range. A major challenge for this approach is distinguishing true adaptive signals from spurious associations arising from population structure. Several methods have been developed to account for population structure, but these methods can suffer from reduced statistical power or increased false positives under some conditions. To address this, we introduce a new GEA method, termed SimGEA. In essence, SimGEA infers a neutral evolutionary model that reproduces the population structure observed in empirical data and uses this model to simulate neutral alleles. By applying the same GEA statistic to both the empirical and simulated data, SimGEA evaluates the significance of observed associations against neutral expectations that account for population structure. We compared the performance of SimGEA with that of existing GEA methods, including LFMM2 and BayPass, using simulations of local adaptation in two-dimensional space. We found that SimGEA consistently controlled the false discovery rate without substantially sacrificing statistical power across the scenarios examined. These results suggest that calibrating statistics using neutral simulations provides a robust and flexible approach for accounting for population structure in GEA analyses.

Exogenous and endogenous mutagens generate a wide variety of DNA lesions, including bulky adducts, chemical modifications, and single- or double-stranded breaks. A phenomenon called "lesion segregation," in which lesions evade repair and persist for multiple cell divisions, has recently been documented in tumors and healthy somatic tissues from mice and humans, respectively. Persistent lesions can generate multi-allelic variants (MAVs) by serving as templates for multiple rounds of error-prone replication. By reanalyzing data from a large C. elegans mutagenesis experiment, we observed robust evidence for MAVs at a small fraction (~0.2%) of mutated sites in the offspring of strains treated with alkylating agents. Because these sequencing data were derived from the progeny of a single F1 animal -- itself the offspring of a mutagenized P0 -- all mutations should be biallelic. The presence of multi-allelic variation implies that some DNA lesions are transmitted to the F1 zygote, evade repair, and are repeatedly bypassed by error-prone polymerases during embryogenesis. We suspect that many more lesions are inherited than is suggested by MAV prevalence, and that a large fraction of biallelic mutations are also caused by inherited lesions. Our results demonstrate that DNA lesions serve as durable, transgenerational templates for mutagenesis in C. elegans . We speculate that lesion segregation in the early embryo may be a source of mosaicism and genetic diversity in humans, as well.

During C. elegans embryonic development, cells undergoing programmed cell death are engulfed by neighboring cells and degraded inside phagosomes. Here we characterize a DNase responsible for the degradation of the chromatin DNA of apoptotic cells. In the past, NUC-1, a homolog of mammalian DNase II, which is only active at acidic pH, was claimed to act in apoptotic cell nuclei for chromatin DNA degradation by some researchers, yet proposed to act in engulfing cells by others. We found that NUC-1 acts exclusively in engulfing cells to degrade apoptotic cell DNA. In nuc-1 mutant embryos, apoptotic cell chromatin DNA remains undegraded. We observed that being engulfed is necessary for the apoptotic chromatin DNA to be degraded. In addition, specific expression of nuc-1 in the engulfing but not dying cells rescues the nuc-1 mutant phenotype. Furthermore, blocking the fusion between lysosomes and a phagosome in engulfing cells blocks apoptotic chromatin DNA degradation. NUC-1 was reported to be a lysosome-located enzyme. We not only confirmed this localization pattern, but also further determined that NUC-1 does not reside in the nuclei of either apoptotic or live cells. This, together with our finding that the nucleus of an apoptotic cell is not acidic, indicates that NUC-1 does not act in the apoptotic cell nucleus; rather, it acts in the engulfing cell phagosomal lumen to degrade apoptotic chromatin DNA. Our work clarified a long-standing controversy regarding the action of NUC-1 and advanced our knowledge of the mechanisms that drive the degradation of specific components of dying cells.

Oxygen is essential for all terrestrial animals, but there is dramatic variability in how well different animals and even different cell types can adapt to reduced oxygen availability. We used a meta-analysis of the literature, with a focus on mouse studies, to identify pathways that might act to protect animals in low oxygen environments. We identified 108 genes whose mRNA levels change under hypoxia, and 55 genes critical for mounting a response to hypoxia. With this data, we developed a list of conserved genes, and we tested three C.elegans genes previously uncharacterized in hypoxia, mxl-3, yap-1, and ador-1, and found that loss of function altered egg-laying during and after hypoxia. Our method provides a more targeted approach of how to screen for hypoxic phenotypes and study in more genetically tractable organisms to show mechanisms.

Genomic mapping has yielded extensive catalogs of quantitative trait loci underlying agronomic traits, yet translating these discoveries into breeding gains remains inefficient. Here, we introduce Flywheel Genomics, a framework that integrates trait discovery directly within rapid cycling breeding populations. Using empirical data from a smallholder-oriented sorghum breeding program, we demonstrate that recurrent intermating and selection maintain genetic diversity, effective population size, and recombination while reducing confounding from plant height and maturity. Within this population, we resolve loci underlying simple adaptive and complex environmentally responsive traits and generate large segregating populations for mapping and near-isogenic lines for locus validation. We further demonstrate applicability in a public wheat breeding program, where known agronomic loci were readily detected. Simulations show that rapid cycling better preserves the population genetic properties required for Flywheel Genomics than conventional pure line development. By integrating discovery with improvement, Flywheel Genomics reframes breeding programs as engines of both crop improvement and genetic insight.

Common bean (Phaseolus vulgaris L.) is exposed to a broad spectrum of abiotic and biotic stresses that impose severe constraints on productivity, yet the molecular basis of stress tolerance remains poorly resolved, with independent studies yielding inconsistent and incomplete conclusions. To establish a comprehensive picture of the common bean stress transcriptome, we conducted a systematic meta-analysis of publicly available RNA-sequencing datasets spanning abiotic and biotic stress conditions across leaf and root tissues. Integrating statistical meta-analysis with machine-learning approaches, we identified stress-responsive gene sets whose robustness was verified through rigorous statistical approaches including independent dataset validation. Beyond confirming established stress-responsive genes, the machine-learning framework uncovered candidates overlooked by standard significance thresholds in individual studies yet carrying consistent transcriptional signals across studies. Co-expression and protein-protein network analyses further resolved these candidates into functionally coherent modules linked to specific stress-response programs. Notably, ethylene-responsive transcription factors were identified as hub genes in three of four stress-tissue groups, with NAC domain transcription factors emerging as additional hub genes in biotic stress contexts. Importantly, the biological significance of the identified gene sets was validated genomically: marker panels targeting consensus meta-analysis-derived and machine-learning-discovered gene regions improved genomic prediction accuracy for disease resistance traits in common bean and abiotic stress tolerance traits in cowpea relative to a baseline model with equivalent-sized random marker sets. Overall, these findings revealed conserved stress transcriptome signatures in common bean and provided a cross-species, evidence-based framework for prioritizing candidate genes and constructing biologically informed genomic selection tools to advance stress-resilient legume breeding.

Gene model for the ortholog of Insulin-like peptide 3 (Ilp3) in the D. pseudoobscura Apr. 2013 (BCM-HGSC Dpse_3.0/DpseGB3) Genome Assembly (GenBank Accession: GCA_000001765.2) of Drosophila pseudoobscura. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

Bluebunch wheatgrass (Pseudoroegneria spicata) exhibits substantial variation in its response to salt stress, making it a valuable model for studying salinity-tolerance mechanisms for use in crop improvement. In this study, we identified two P. spicata genotypes with contrasting responses to salt stress: the tolerant W6 56551, which maintained growth with green foliage under saline conditions, and the susceptible PI693916, which exhibited severe leaf chlorosis and stunted growth. To better understand the molecular basis of salt tolerance in blue-bunch wheatgrass, we conducted RNA-sequencing at 0, 1, and 4 days (D0, D1, and D4) after salt treatment at 160 mM level to examine changes in gene expression of salt-tolerant and salt-susceptible genotypes. Comparative analysis across time points identified 6,154 and 1,086 differentially expressed genes (DEGs) at D4 and D1 in PI693916, and 4,638 and 3,302 DEGs at D4 and D1 in W6 56551, respectively, relative to control (D0). Functional analysis of these DEGs showed that the salt-tolerant geno-type displayed an early and broad transcriptional reprogramming, including induction of photosynthesis, carbon metabolism, and flavonoid biosynthesis pathways, whereas the salt-susceptible genotype exhibited delayed and less coordinated responses, with enrichment of cyanoamino acid metabolism and repression of antioxidant-associated pathways. Notably, calcium signaling, ion transporter regulation, and osmolyte biosynthesis genes showed contrasting expression between genotypes, highlighting distinct strategies for ionic and osmotic homeostasis. Collectively, these results demonstrate that salt tolerance in P. spicata is associated with rapid metabolic adjustment, enhanced photosynthetic stability, and differential regulation of ion transport and osmoprotectant pathways.

Nesidiocoris tenuis is an important zoophytophagous mirid bug used as a biological control agent in agriculture, and breeding efforts based on genomic information aim to increase its utility. Visible eye-color mutants are useful genetic markers because they are easily distinguishable and are therefore widely used in insect genetics and genome editing studies. Here, we investigated the genetic basis of a spontaneous red-eye mutant identified in a laboratory strain of N. tenuis. Classical crossing experiments suggested that the red-eye phenotype is controlled by a single recessive locus. RNA-seq and RNA interference (RNAi) analyses identified scarlet and cinnabar as the primary candidate genes associated with the phenotype. Further genomic analysis revealed a large deletion and insertion within exon 5 of the mutant scarlet allele, potentially causing exon skipping and disrupting transporter structure. The insertion pattern is consistent with a microhomology-mediated break-induced replication (MMBIR)/fork stalling and template switching (FoSTeS)-like event that may have been generated through polymerase{theta} -mediated repair. Together, these findings identify the causative mutation underlying the red-eye phenotype and provide a useful visible marker for future functional genetic studies and genome-assisted breeding in N. tenuis.

Many biological characteristics arise by interactions between more than one biological organism or unit. Fertilization success in sexually reproducing species represents such an extended phenotype where both mates are required to be fertile for a successful outcome. Consequently, predictive models should account for the joint nature of reproductive performance while offering interpretable estimates for individual mate contributions. Recent advances in genomics and machine learning (ML) provide standardized, high-dimensional genetic information on one hand and computational tools capable of modeling complex biological systems on the other. Here, we construct and evaluate two-tower (TT) machine learning architectures for genomic prediction of binary reproductive outcomes and recovery of sex-specific fertility liabilities. Simulated datasets, generated under a range of genetic architectures, were utilized to compare multilayer perceptron (TT-MLP), convolutional neural network (TT-CNN), and L1-regularized linear (TT-LASSO) two-tower models. Simulation scenarios varied sex-specific heritabilities, genetic correlations, infertility prevalence, mating structure, and sex-specific infertility rates. Models were evaluated with regard to their ability to predict reproductive success at pair level and also recover true underlying genetic values for male and female fertility. Prediction accuracy increased with the underlying heritable component as expected, while sex-specific tower-scores successfully recovered latent fertility liabilities despite models being trained only on observed joint outcomes. TT-LASSO achieved the highest overall classification performance, whereas TT-MLP provided more balanced and consistent recovery of sex-specific genetic values across scenarios. An additional simulation, incorporating genotype-dependent mate compatibility demonstrated advantages of fully-connected neural networks for capturing non-additive interactions. These results indicate that two-tower frameworks provide a powerful approach for modeling reproductive traits, enabling simultaneous prediction of aggregate reproductive outcomes and sex-specific fertility liabilities from genotypic information.

Kinase fusion proteins (KFPs) have emerged as an important group of immune receptors encoded by plant resistance genes. Here, we report a new type of gene pair that controls resistance of wheat to the blast fungus, Pyricularia oryzae. We cloned a fungal gene involved in avirulence of P. oryzae pathotype Eleusine on wheat and designated it PWT8. We also identified its corresponding resistance gene in wheat, and tentatively named it Rwt8. This resistance gene was located at the same locus as previously identified resistance genes Rwt3 and Rwt6. Molecular cloning revealed that Rwt3, Rwt6, and Rwt8 were the same gene consisting of an identical gene pair, one encoding an NLR and the other encoding a mixed lineage kinase-like (MLKL) protein. These two genes were closely linked in a head-to-head orientation and behaved as a single gene. This gene pair recognized three AVR genes, PWT3, PWT6, and PWT8, and was designated Rwt3.6.8. The distribution of Rwt3.6.8 in common wheat landraces suggested that the gene pair may have been a factor which the D genome provided to the genus Triticum to broaden its adaptability to various environments in the world, especially in Asia and Africa.