G3 Genes|Genomes|Genetics

Reporters are widely used in Drosophila genetics to visualize gene expression and cell lineages. However, uncharacterized limitations in specific reporter lines can lead to data misinterpretation. Here, we identify a consistent, driver-independent tdTomato signal in the adult proventriculus from the widely used lexAop-tdTomato.nls reporter line. This signal was observed across multiple lexA driver combinations and was directly detectable in lexAop-tdTomato.nls responder-alone adult proventriculi lacking any lexA driver and without antibody staining. In contrast, no comparable native red fluorescence was detected in larval proventriculi under the same no-antibody imaging condition. Mouse and rabbit anti-RFP immunostaining further supported the presence of proventriculus-associated tdTomato/RFP antigen in adult responder-alone animals. In larval responder-alone proventriculi, antibody-amplified staining was antibody-source-dependent: a detectable signal was observed only with rabbit anti-RFP, whereas mouse and rat anti-RFP produced no reliable detectable signal under the same staining condition. A driver-matched comparison using lexAop-RFP.nls did not reproduce the proventricular signal, arguing against detectable ectopic activity of the tested lexA driver in this tissue. However, because lexAop-tdTomato.nls and lexAop-RFP.nls differ in reporter/transgene architecture and possibly genomic insertion context, the underlying cause cannot be assigned specifically to the lexAop sequence. Our findings highlight the necessity of including driver-negative and no-antibody controls when using this reporter line in adult Drosophila proventriculus and gut studies.

Gene model for the ortholog of tango (tgo) in the Sep. 2015 (UC Berkeley ASM127793v1/DbusGB1) Genome Assembly (GenBank Accession: GCA_001277935.1) of Drosophila busckii. 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.

BackgroundThe fission yeast stress-activated protein kinase (SAPK) pathway includes a conserved mitogen-activated protein (MAP) kinase cascade that regulates multiple cellular processes and is activated by several types of external stress. Understanding how Sty1, the MAP kinase in the SAPK pathway, controls these processes is complicated by the fact that different stressors can have stressor-specific effects that may be difficult to separate from the effects of Sty1 activation itself. Moreover, upon stress, Sty1 activation is usually short-lived. Previously, we developed a fission yeast strain, SISA, in which Sty1 kinase activity can be switched on in a sustained manner in the absence of external stress. This required combining multiple mutations in the SAPK pathway, including an analog-sensitive version of Sty1. When SISA cells are grown in the presence of analog-sensitive kinase inhibitors, Sty1 is inhibited, but when inhibitor is removed, Sty1 becomes hyperactive. While this strain was useful, it had several limitations. ResultsHere we describe and validate a more rationally-designed strain, SISA4, that retains the features of the original SISA strain while overcoming its limitations. SISA4 is more stable genetically than SISA, easier to use in genetic crosses, and easy to identify by phenotype or genotyping. We show that analog-sensitive kinase inhibitors 4-Amino-1-tert-butyl-3-(1-naphthylmethyl)pyrazolo[3,4-d]pyrimidine (1-NM-PP1) and 4-Amino-1-tert-butyl-3-(3-bromobenzyl)pyrazolo[3,4-d]pyrimidine (3-BrB-PP1) are equally potent for inhibiting analog-sensitive Sty1 in vivo, and we determine optimal inhibitor concentrations for converting SISA4 cells from a Sty1-inhibited state to a Sty1-hyperactive state. We also find that both 1-NM-PP1 and 3-BrB-PP1 have measurable off-target effects in wild-type cells, although these are modest and generally do not affect interpretation of experiments. Finally, using SISA4, we show that the Sty1-activated transcription factor Atf1 plays an unexpected role in maintaining cell-polarity disruption after Sty1 hyperactivation. ConclusionsSISA4 will be useful for investigating how SAPK pathway activation regulates diverse cellular processes.

Gene model for the ortholog of raptor in the D. grimshawi May 2011 (Agencourt dgri_caf1/DgriCAF1) Genome Assembly (GenBank Accession: GCA_000005155.1) of Drosophila grimshawi. 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.

Interest in quantifying linkage disequilibrium (LD, non-random associations of alleles at different loci) has skyrocketed in recent years as researchers have focused on use of LD in genome-wide association studies (GWAS), for studying historical demography, and for estimating effective population size (Ne). The most widely used LD metric is r2 = the squared correlation of alleles at a pair of loci. Despite a half century of efforts, developing an unbiased expectation of r2 as a function of the many factors that can affect it (physical linkage, genetic drift, selection, migration, mutation, mating systems) remains elusive. Furthermore, even when all of these other factors are absent, empirical estimates of r2 are upwardly biased by sampling a finite number (S) of individuals, and that must be accounted for if one wants to focus on the desired signal of LD. Previous approaches to estimate [Formula] have been shown to be biased to greater or lesser degrees. The purpose of this short paper is to demonstrate that a simple and apparently exact expression for [Formula] does exist for the special case where sampling error is the only factor contributing to r2, in which case [Formula] = 1/(S - 1). When other factors contribute heavily to LD, [Formula] shrinks toward 0 as empirical r2 [->] 1. However, for estimating contemporary Ne with unlinked markers, empirical r2 will generally be small and 1/(S - 1) will provide a robust estimate of [Formula].

Gene model for the ortholog of raptor in the May 2011 (Agencourt Dere_CAF1/DereCAF1) Genome Assembly (GenBank Accession: GCA_000005135.1) of Drosophila erecta. 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.

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

Caenorhabditis nematodes are a powerful model clade for evolutionary genetics. Isogenic lines and panels of recombinant inbred lines (RILs) are among the most essential tools for genetic studies in these species. While most Caenorhabditis species are gonochoristic, large RIL panels have only been developed for self-fertilizing species. This gap biases our understanding and limits our ability to address questions related to the genetic architecture of traits in outbred populations, which have radically higher genetic diversity, heterozygosity, and effective recombination than selfers. Having previously identified Caenorhabditis becei as a tractable gonochoristic species due to its moderate inbreeding depression, we generated two panels of advanced-intercross RILs derived from three individual outbred C. becei worms collected from a single locality on Barro Colorado Island, Panama. One panel derives from a pair of worms sampled from a single rotting fig; the other derives from a cross between worms from two different figs. The panels share one founder in common, yielding two half-sib RIL panels. We sequenced and haplotyped the lines, identifying millions of variants and thousands of recombination breakpoints. Using simulations, we demonstrate the suitability of these lines for quantitative genetics studies and QTL mapping. In our single-fig panel, we observe abundant heritable variation in population growth rate, individual body size, and sexual dimorphism for body size. We detected four QTLs associated with population growth rate and show that estimated allelic effects are good predictors of selection that occurred during panel derivation.

Gene model for the ortholog of Lst8 (Lst8) in the May 2011 (WUGSC dyak_caf1/DyakCAF1) Genome Assembly (GenBank Accession: GCA_000005975.1) of Drosophila yakuba. 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.

Many taxa have evolved heteromorphic sex chromosomes like the XY system found in mammals. In additional to the sex determination gene which directs development of the gonad into an ovary or testis, sex chromosomes can have drastically different gene content, leading to substantial genetic differences between genetic males and females beyond their gonad identity. Studying the effects of these genetic differences is challenging, as the sex chromosomes and sex determination gene are inherited together, so the effects of genetic differences between the X and Y cannot be easily isolated from the hormonal differences produced by the ovary and testis. The threespine stickleback fish has a heteromorphic XY sex chromosome system and a wide range of well documented sex differences in morphology and behaviors, including complex mating behaviors and male-only parental care. Through genetic manipulation of amhy, the newly identified sex determination gene in threespine stickleback, we are able to generate gonadal males and females with either the XX or XY sex chromosome complement and analyze the separate effects of gonadal sex and sex chromosome complement on sexually dimorphic gene expression. We find that sex chromosomes have a larger effect on gene expression than gonadal sex in somatic tissues, while gonadal sex has a larger effect on expression in the gonads. We also find that the X and Y chromosomes are enriched for genes which show differential expression between females and males. Our findings demonstrate the significant biological impact of sex chromosomes outside of primary sex determination and showcase the utility of the threespine stickleback for studying the genetic basis of sex differences.

Nuclear receptors, transcription factors essential for organism growth, development, and reproduction, are expressed in a variety of tissues, with some exhibiting differential expression between males and females. The Estrogen-related receptor (ERR) is a conserved metabolic nuclear receptor required for energy metabolism and lipid accumulation. While previous studies in Drosophila have identified potential ERR targets from mixed sex larval populations and adult males, it is unclear whether transcriptional targets and biological pathways downstream of ERR are altered in a sex-specific manner. Here, we took an RNA sequencing approach to identify candidate ERR targets specifically in adult females and compared differentially expressed genes to a published male-specific dataset. Whole body conditional knockout of ERR significantly downregulated transcription of enzymes associated with glycolysis and the pentose phosphate pathway. In contrast, components of the DNA replication machinery were selectively downregulated in adult females, whereas ribosome biogenesis transcription was increased. Our results have further defined the metabolic targets of ERR between males and females, as well as suggest that ERR regulates DNA replication and global translation in females. SUMMARYIn this manuscript, we used RNA sequencing to identify differential expression of transcripts dependent on the nuclear receptor ERR in Drosophila adult females. We find that ERR is required for activating transcription of glycolytic and pentose phosphate pathway enzymes, as observed in larvae and adult males. Furthermore, compared to males, loss of ERR in females specifically decreased DNA replication enzyme components while upregulating ribosomal components. Our results suggest that nuclear receptors have common and sex-specific targets, which will be of interest for those in the nuclear receptor and sexual dimorphism fields.

Ribosome biogenesis is a highly coordinated pathway that involves the assembly of ribosomal RNAs (rRNAs) with ribosomal proteins (r-proteins) to generate functional ribosomal subunits (r-subunits). The Saccharomyces cerevisiae (yeast) large 60S r-subunit consists of three rRNA molecules and 46 r-proteins. The contributions of nearly all r-proteins of the yeast large r-subunit have been characterized; however, a few non-essential proteins remain poorly understood. Although non-essential, human eL22 has been identified as a key player in p53 regulation during ribosomal stress and as a highly mutated target in cancers. Despite this function, the role of eL22 in ribosome maturation is still ill-defined. In this study, we characterized yeast eL22 r-protein. Our results show that eL22 assembles into intermediate nucleolar pre-60S ribosomal particles. Loss of eL22 impairs cell growth and reduces 60S r-subunit accumulation, phenotypes that are exacerbated at low temperatures. Analysis of pre-rRNA processing by pulse-chase labeling, northern blot hybridization, and primer extension reveals a defect in 27S pre-rRNA maturation, specifically at the level of 27SB pre-rRNA processing. Consequently, nuclear export of eL22-deficient pre-60S particles is mildly impaired. Furthermore, we identify genetic interactions between eL22 and neighboring r-proteins, eL38 and eL31. We conclude that eL22 assembly is required for optimal pre-60S maturation during middle nucleolar stages, particularly at low temperatures, a function likely supported by the cooperative action of other r-proteins associated with common elements of 25S rRNA. HighlightsO_LIWe have studied the role of r-protein eL22 in yeast ribosome assembly. C_LIO_LIeL22 is required for 60S ribosomal subunit production. C_LIO_LIThe absence of eL22 is critical at low temperatures. C_LIO_LIeL22 is important for 27SB pre-rRNA processing and nuclear export of pre-ribosomes. C_LIO_LIeL22 functionally interacts with r-proteins eL38 and eL31 in domain III of 25S rRNA. C_LI

Laboratory cultivation subjects model organisms to selective pressure and genetic drift that can result in the accumulation of many genomic and phenotypic differences over time. The nematode Caenorhabditis elegans has been used for research since the 1970s, and studies comparing the N2 Bristol and CB4856 Hawaiian isolates provided foundational knowledge about metazoan genome evolution. Most comparative genomics studies have used these isolates because their long-term geographical isolation promoted a high degree of genomic divergence within the species. Further, there is growing evidence of phenotypic differences between laboratory lineages of each wild type isolate after repeated independent lab cultivation of these strains. To examine the genomic divergence between different laboratory lineages the Bristol and Hawaiian backgrounds, we first generated de novo genome assemblies of two Bristol and two Hawaiian lineages from Illumina and PacBio sequencing reads. Following genome assembly, we quantified Single Nucleotide Polymorphisms (SNPs), short insertion/deletions (indels), and genomic structural variants (SVs). Between laboratory lineages of the Bristol isolate, we identified 25,432 SNPs, 5,202 indels, and 441 SVs. When aligning laboratory lineages of the Hawaiian isolate, we identified 4,518 SNPs, 1,188 indels, and 387 SVs. For both sets of comparisons, we find that SNPs and indels are broadly enriched in introns and depleted from coding sequences. In contrast to SNPs and indels, we find that genomic SVs are enriched in intergenic sequences. Taken together, our analyses reveal the accumulation of genomic divergence between lineages of Bristol and Hawaiian C. elegans from independent lab cultivation, and how these variants may underpin emergent phenotypic differences observed in the two most popularly used C. elegans wild type isolates. Author SummaryLaboratory model organisms, like natural populations, are subject to evolutionary pressures and genomic changes during prolonged laboratory cultivation. In this study we comprehensively quantify SNPs, indels, and SVs between independent lab cultivations of the C. elegans lineages of the Bristol and Hawaiian isolates.

Developmental processes depend on carefully coordinated gene expression. Expression is modulated by the binding of transcription factors (TFs) to cis-regulatory elements (CREs), like enhancers and promoters. Many computational and experimental approaches have been developed to find CREs, particularly enhancers, in the genome, each with strengths and caveats. Given the increasing availability of ATAC-seq data and methods to find TF binding therein, we hypothesized that we could use TF footprinting tools to find clusters of TF binding events within accessible chromatin that may act as CREs. Using Drosophila anterior-posterior patterning network as a test bed, we used a digital genomic footprinting tool (DGT), TOBIAS, on previously published early embryo ATAC-seq data to characterize the TF footprint landscape of 16 TFs essential for embryonic patterning. Even in this system, with its extensive enhancer annotation, most footprinted TF binding sites lie outside of known enhancers, with intergenic and intronic regions hosting the highest TF footprint count, albeit at low density. To find potential novel enhancers, we identified high-density TF footprint clusters that are highly conserved and overlap with active enhancer histone mark signals. Five high confidence candidates were selected for reporter assay validation and all five were found to drive spatially patterned expression in the embryo. This study shows that even in a highly characterized system, the analysis of footprinted TF binding sites in ATAC-seq data can uncover new regulatory regions and suggests this approach may be helpful in using existing ATAC-seq data to find novel CREs. ARTICLE SUMMARYGiven the increasing availability of ATAC-seq datasets, workflows to exploit the data to uncover new cis-regulatory elements (CREs), including enhancers, are valuable. Using early anterior-posterior patterning in the Drosophila embryo as a test case, we find that previously published transcription factor footprinting tools and ATAC-seq data can be analyzed to yield new candidate CREs. Experimental validation confirms the activity of selected candidate CREs, suggesting that existing data can be analyzed to find novel regulatory elements.

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

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.

Gene model for the ortholog of Density regulated protein (DENR) in the Apr. 2013 (BCM-HGSC/Deug_2.0) (DeugGB2) Genome Assembly (GenBank Accession: GCA_000236325.2) of D. eugracilis. 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.

Local adaptation of a species involves the selection of adaptive alleles that confer a fitness advantage in their local environment. Inversions prevent recombination between the standard and inverted heterozygous hybrids. Inversions can play a crucial role in local adaptation by locking together a set of co-adapted alleles, acting as supergenes. Inv4m is a 13 Mb inversion in maize prevalent in highland maize and highland wild relatives from Mexico. Maize from the highlands of the Trans-Mexican volcanic belt has been shown to be well-adapted to volcanic, acidic soils with low phosphorus availability. Inv4m carries several genes involved in P acquisition and utilization. We therefore tested the hypothesis that Inv4m contributes to maize adaptation to these environments through enhanced phosphorus acquisition or utilization. Alternatively, Inv4m possible adaptive value may operate through constitutive developmental effects independent of nutrient stress responses. To test this hypothesis, we introgressed a highland maize variety from the highlands of Michoacan, Mexico, carrying Inv4m into the temperate line B73 and developed Near-Introgression Lines (NILs) carrying Inv4m. We then grew NILs carrying the inversion and controls without it in soils with different phosphorus levels and evaluated the fitness effects of the inversion, as well as changes in gene expression using RNA-Seq. Our results show that P starvation elicits highly conserved transcriptomic, lipidomic, and ionomic responses, independently of the Inv4m inversion genotype. Therefore, phosphorus deficiency does not seem to be driving the adaptive value of Inv4m. Additionally, we observed a phosphorus modulated transcriptional gradient from the collar leaf downward, characterized by a decrease in the expression of photosynthesis genes and an increase in the expression of senescence-associated genes, corresponding to the positional onset and initial stages of sequential leaf senescence. Although the magnitude of the phosphorus response increased with leaf age, we did not observe significant interactions with Inv4m. Our multi-omics analysis of the maize phosphorus starvation response identified and characterized two coordinately regulated molecular programs, light harvesting shutdown and accelerated senescence, whose deployment depends on leaf developmental stage, with older leaves below the collar integrating nutrient limitation into the natural progression toward senescence.

Animals sleep more when they are sick. In C. elegans, stress-induced sleep (SIS) follows cellular injury such as exposure to ultraviolet (UV) light. The genetic regulators of SIS remain incompletely defined. Using a worm-picking robot, multi-well WorMotel imaging, and association analysis we performed a semi-automated screen of 941 whole-genome-sequenced Million Mutation Project (MMP) strains. We quantified behavioral activity and quiescence before and after ultraviolet (UV) radiation. We applied the Sequence Kernel Association Test (SKAT) to this behavioral data to prioritize 6,663 genes and observed significant enrichment of known SIS genetic regulators. Based on these results, we conducted a candidate validation screen for additional genes regulating SIS. We identified three genes (strd-1, egl-8, cla-1), mutations in which reproducibly influence SIS. Further exploration of these genes holds potential for enhancing our understanding of the molecular basis of SIS. These findings establish a pipeline for automated behavioral phenotyping coupled with gene-based association to accelerate studies of C. elegans neurogenetics.

The kynurenine pathway metabolizes tryptophan into 3-hydroxykynurenine (3-HK), a precursor for ommochrome eye pigments synthesized via the cardinal (cd) gene in mosquitoes. While cd disruption was presumed neutral, we observed fitness costs in Anopheles stephensi knock-in but not knock-out cd mutants. Here we investigated this anomaly further by assessing survival, fecundity, and midgut integrity across multiple cd mutant lines. Heterozygous knock-in lines, expressing a fluorescent marker and guide RNA for CRISPR/Cas9, exhibited reduced survival post-blood feeding, larva-to-adult survival deficits, and midgut barrier dysfunction, whereas knock-outs showed no such costs. Oral supplementation with xanthurenic acid partially rescued knock-in mortality, implicating oxidative stress linked to 3-HK metabolism. Expression analyses suggest transgene insertion effects, rather than cd disruption, underlie these fitness costs. These findings highlight the importance of evaluating insertional effects in gene drive target selection and support cd as a viable target for genetic control strategies in An. stephensi.