GENETICS

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.

Epigenetic information is required for the maintenance of gene expression states through cell division. Some epigenetic information can also persist through generations, raising the possibility that epigenetic differences may arise in populations and contribute to evolutionary processes such as drift and natural selection. Evaluating this requires characterising the properties of such epimutations, so that their rate, stability and genome-wide distribution can be assessed. Recent experiments in many organisms have demonstrated that epimutations occur, but have limited stability relative to DNA sequence mutations. However, the extent to which epimutations contribute to evolution is still unclear, in part because it is not clear whether epimutations respond dynamically to environmental conditions. Here, we use the fission yeast S. pombe, in which evolutionarily relevant epimutations have been observed, but not yet systematically characterised, to test whether a physiologically relevant stress, ethanol exposure, leads to changes in the properties of epimutations. Using laboratory evolution experiments with repeated population bottlenecks to minimise selection, we show that epimutations associated with changes in small interfering (si)RNAs occur at a greater rate in ethanol. Ethanol-induced epimutations are enriched at transposable element loci and correlate with changes in transposon expression. Ethanol exposure also increases gene expression noise genome-wide and variability in growth rate; importantly, both these increases are suppressed in mutants lacking siRNAs. Together, these results demonstrate that stress can alter the generation of heritable epigenetic information, and suggest that siRNAs may have a role in promoting phenotypic variability in response to environmental stress.

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 genetic basis of phenotypic differences between species is fundamental to our view of evolution. In contrast to variation within species, phenotypic differences between species can result from a long-term sequential process whereby prior steps and multiple changes at a single locus can play important roles. However, investigating the genetic basis of phenotypes that have evolved over long time periods is limited by reproductive barriers between species. In this study, we use hybrid genetic analysis to examine reproductively isolated Saccharomyces species that have diverged in their thermal growth limits over the last 15 million years. By selectively eliminating S. cerevisiae chromosomes in hybrids with S. uvarum or S. kudriavzevii, we show that most chromosomes cause a substantial loss of thermotolerance. Reciprocal loss of chromosome 5 (Chr 5) confirms that the hybrid's thermotolerance depends on the S. cerevisiae chromosome and shows that it is partially inhibited by the S. uvarum chromosome. Using CRISPR-Cas9 to induce targeted loss of heterozygosity, we find that loss of either the left or right arm of Chr 5 results in loss of thermotolerance. Fine-mapping, complementation and reciprocal hemizygosity analysis identify MMS21, which encodes an essential subunit of the Smc5-Smc6 complex, as responsible for loss of thermotolerance associated with the left arm of Chr 5. Our findings suggest that divergence in thermotolerance over long time-periods is caused by multiple loci across the genome, with each playing a critical role in enabling growth at high temperatures.

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.

Evolution in fluctuating environments depends critically on epistatic interactions between mutations and the pleiotropic effects these mutations have on fitness across multiple conditions. However, while these effects of epistasis and pleiotropy have been extensively studied individually, the interactions between them are less well understood. In this study, we analyze how genetic background shapes the effects of mutations across multiple environmental conditions in generic models of complex traits. We show that when epistasis is widespread and random, systematic patterns of cross-environment pleiotropy can emerge naturally. Specifically we outline two regimes, widespread random epistasis (WRE) and structured pleiotropy (SP), in which patterns of global epistasis in one environment can be predicted from those in other conditions. We outline these predictions in several classes of generic null models, and test these predictions in laboratory budding yeast by measuring the fitness effects of a large set of mutations across many genetic backgrounds in several growth environments. We find that only a subset of mutations fall within the WRE and SP regimes, but that in these cases two of our models provide accurate fits to the data. Finally, we use this framework to show how modular, pleiotropic architectures shape long-term evolutionary steady states in fluctuating environments, revealing how tradeoffs between environments can develop from the geometry of shared latent interaction structure.

Biofilm formation by the fungal pathogen Candida albicans is a major source of infection. The biofilm regulator Ume6 forms complexes with partner transcription factors Efg1, Ndt80, and Upc2 to drive expression of biofilm-related genes. Here we present chromatin immunoprecipitation with sequencing (ChIP-seq) data for Ume6-chromatin association in both wild-type and efg1{Delta}/{Delta} ndt80{Delta}/{Delta} upc2{Delta}/{Delta} backgrounds. Ume6 associates with two promoter region classes. For one class, Ume6 association is significantly decreased in the efg1{Delta}/{Delta} ndt80{Delta}/{Delta} upc2{Delta}/{Delta} background. This class includes 577 genes, many with well-established roles in biofilm formation or the related process of filamentation. For the second class, Ume6 association is unperturbed in the triple mutant background. This class includes 534 genes, some with roles in iron homeostasis (e.g., SFU1) and ergosterol synthesis (e.g., ERG11), which may contribute to the impact of Ume6 on ndt80{Delta}/{Delta} mutant azole drug sensitivity. It also includes FLO9, a putative adhesin gene that is required for the emergent biofilm state produced by efg1{Delta}/{Delta} ndt80{Delta}/{Delta} double mutants. The data show that Ume6 binding to ~half of its targets requires known partners, and Ume6 binding to ~half of its targets does not. Ume6 may bind to the latter set of promoter regions independently of any partner, or perhaps with additional partners that have yet to be discovered.

Evolutionary rescue occurs when genetic adaptation prevents extinction of a declining population. Mutation and recombination generate adaptive variation, but when their rates at adaptive loci are too low, rescue may require evolution toward higher rates of genetic change. Here, we derive and compare analytical approximations for the probability of rescue through two alternative routes: mutation-rate and recombination-rate evolution. Our model comprises two resident genotypes from which the same adaptive haplotype can arise along either route, with rescue requiring the appearance of an unlinked modifier allele that increases mutation at, or recombination between, two fitness-determining loci. We show that resident genotype composition determines the relative success of the two routes. Mutation-rate evolution yields a higher rescue probability when one resident genotype is sufficiently more common because mutation can act on either genotype whereas recombination requires both. Otherwise, the two routes yield similar rescue probabilities. Even when either route makes rescue appreciably likely, however, the modifier alleles facilitating rescue are often lost before rescue is complete. This loss is driven by multiple factors: segregation can separate the modifier from the adaptive haplotype; the fitness cost of modifier expression raises extinction risk for modifier-bearing lineages; and continued modifier-induced mutation disrupts the adaptive haplotype after it forms. The latter effect can make recombination-rate modifiers more likely to persist even when mutation-rate evolution yields a higher rescue probability. Overall, these results show that both mutation- and recombination-rate evolution can induce rescue, but successful rescue need not entail persistence of the modifier allele that facilitated it.

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.

The Yampolsky-Stoltzfus (YS) model provided the first formal demonstration that a bias in the introduction of new mutations can shape the direction of adaptive evolution, even when mutation rates are small relative to selection coefficients. Despite its foundational role, the model has been characterized almost entirely by simulation and closed-form solutions for its central quantity, the probability PA that a mutationally favored but less-fit genotype fixes ahead of a rarer, fitter alternative, have been available only in the limiting regimes of vanishing mutation supply and infinite population size. Here we derive closed-form approximations for PA across the intermediate regime of finite population size and appreciable mutation supply that lies between these two limits. Under strong selection between the competing mutants, we combine an establishment-probability argument with clonal interference theory to obtain an explicit expression for PA that accounts for both the ongoing input of the mutationally favored mutation and the frequency-dependent establishment probability of its competitor. Under weak selection between competing mutants, we derive a complementary expression based on the fixation of a mixed population under Kimura's classical formula. Both expressions agree closely with direct simulation of the underlying Wright-Fisher process, recover the known limiting cases, and remain consistent with one another over a substantial intermediate range of parameters. These results are expected to provide a basis for assessing how the strength of mutation bias affects adaptation in empirical data.

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.

Evolution can be thought of as taking place in a fitness landscape which maps each genotype to a fitness value. This abstraction has motivated significant efforts to quantify the statistical properties of random fitness landscapes with different amounts and types of interactions among loci---broadly referred to as epistasis. New high-throughput experimental techniques measuring the phenotypes of thousands of genotypes promise to bridge this theory with data. Yet, while impressive, thousands is still small relative to the size of genotype space. Moreover, experiments often assay a highly non-random subset of the fitness landscape. For example, a common experimental approach is to generate all possible 2M sequence intermediates between ancestral and evolved sequences differing by M much less than L mutations. Here, we ask to what extent the statistics of an empirical landscape constructed under distinct ascertainment protocols recapitulate the statistics of a random subset of the global landscape in a few well-studied random landscape models. We show that, in most landscapes, selecting mutations which occurred along an adaptive trajectory inflates the variance explained by lower order epistasis, reduces the number of local maxima, and increases the number of accessible paths relative to a random fitness landscape. Selecting the most beneficial or deleterious mutations, on the other hand, results in distortions to these statistics which depend more critically on the amount of epistasis in the global landscape. We then take advantage of several large-scale mutagenesis datasets to simulate the effects of ascertainment in more realistic settings.

Mitochondrial homeostasis is essential for cellular health. To maintain mitochondrial homeostasis in proliferating cells, mitochondrial inheritance to daughter cells must be tightly coordinated with growth and cell division. In budding yeast, mitochondrial inheritance is ensured by active transport into the growing bud. Although inheritance defects are well known to affect cell physiology, the regulatory mechanisms linking mitochondrial inheritance to cell cycle control remain unclear. Here, we use the inheritance defect of cells depleted of the mitochondrial inheritance adaptor Mmr1 to investigate this coordination. Time-resolved analysis of more than 8,000 budding events revealed that budding duration is directly linked to the time of mitochondrial inheritance. To understand the underlying mechanism, we performed a genetic interaction screen using the auxin-inducible degron library. Strains depleted of cell cycle regulators, particularly those involved in mitotic progression, were highly enriched in clones with synthetic growth defects. Among these, Swe1, the bud morphogenesis checkpoint kinase, emerged as a key candidate affecting budding duration in response to impaired mitochondrial inheritance. Co-depletion of Mmr1 and Swe1 strongly reduces the mitochondrial inheritance-dependent lengthening of budding duration, leading to a large fraction of daughter cells with insufficient mitochondrial content. Thus, Swe1-mediated mitotic delay contributes to slowing cell cycle progression in response to defective mitochondrial inheritance. We suggest calling this regulatory loop MIBA: mitochondrial inheritance-dependent budding adaptation. Together, our findings reveal a mechanism by which cells couple mitochondrial inheritance to cell cycle progression and highlight the importance of this coupling for mitochondrial homeostasis across the population.

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.

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.

Drosophila glutathione S-transferase S1 (GstS1) is a unique member of the glutathione S-transferase family and is considered the ortholog of vertebrate hematopoietic prostaglandin D synthase based on amino acid sequence similarity. A previous forward genetic screen revealed that a null mutation in GstS1 dominantly suppresses genetically induced behavioral hyperexcitability in several seizure-prone Drosophila mutants, including paraShu, a gain-of-function mutant of the voltage-gated sodium channel gene paralytic (para), and eas2, a loss-of-function mutant of the ethanolamine kinase gene easily shocked (eas). Here, using the GAL4/UAS system combined with GstS1 RNAi, we show that hemocyte-specific GstS1 knockdown suppresses hyperexcitable phenotypes in both paraShu and eas2. Notably, suppression of adult paraShu phenotypes required GstS1 knockdown before adult eclosion, suggesting that GstS1 modulates adult neuronal excitability by influencing neural development through neuroimmune interactions. Consistent with this model, hemocyte-specific GstS1 knockdown rescued abnormal dendritic morphology in developing class IV dendritic arborization (C4da) neurons of paraShu larvae. Moreover, paraShu and eas2 larvae exhibited increased numbers of sessile hemocytes surrounding C4da neuron somata, a phenotype reversed by either GstS1 knockdown or dietary supplementation with the {omega}-3 polyunsaturated fatty acid -linolenic acid. Together, these findings reveal a previously unrecognized developmental role for GstS1 in promoting nervous system hyperexcitability through hemocyte-mediated neuroimmune interactions, potentially involving bioactive lipid signaling. Our results highlight neuroimmune crosstalk as an important mechanism linking genetic perturbations to altered neural development and seizure-associated hyperexcitability.

Complex traits are often deemed highly polygenic when a mapping study fails to localize the loci underlying them, but a result that fails to identify major genes can also reflect a lack of power. Cuticle color in Drosophila offers a natural test of this distinction, since genes of large effect segregate in natural populations. We selected for dark and light thoracic trident color for 16 generations in two populations of D. melanogaster and two of D. simulans, then used pooled sequencing to scan each genome for allele-frequency differentiation between selected and control lines. Selection produced a strong, genome-wide shift in allele frequencies in every population, exceeding the expectation under drift. Simulations demonstrate that our design has low power to detect major-effect genes, which may explain why we do not observe peaks localizing to known color genes. We further show that a highly significant peak in each genome, on chromosome 3L, is an artifact of chorion-gene amplification in the pooled adult females. A source of false signal in pool-seq studies that has not been reported before. Cosmopolitan inversions shifted in frequency under selection in the one population that carried them, but direct testing showed they did not inflate genome-wide noise, contradicting a common assumption in the field. Together, these results demonstrate that a diffuse, polygenic-type response can arise from a trait with known large-effect genes, and provide a quantitative account of why an evolve-and-resequence design can fail to localize even a well-characterized genetic architecture.

Deleterious mutations are abundant in nature. Consequently, when an adaptive mutation arises, it will likely land on a haplotype with several deleterious mutations. While deleterious mutations may hitchhike with the adaptive variant, deleterious mutations are less likely to be found on the same haplotype with each other due to repulsion (i.e. Hill Robertson interference). Both hitchhiking and repulsion shape patterns of linkage disequilibrium (LD), but their simultaneous impact on LD have not been fully understood, leaving a gap in accurate inference of selection from genomic data. Here, we investigate patterns of LD during a sweep using simulations across a wide range of evolutionary parameters. On average, LD is elevated between pairs of intermediate frequency nonsynonymous variants relative to synonymous variants. This occurs because nonsynonymous variants, which are presumably deleterious, are more likely to rise to high frequency via hitchhiking rather than drift and thus will be predominantly found on the sweeping haplotype. However, we find that this elevation does not occur across all distances: when nonsynonymous variants are either too close to each other or too far from the adaptive locus, repulsion between deleterious variants results in lower LD among nonsynonymous variants. This results in a characteristic "criss-crossing" of LD. We find that criss-crossing is a feature of empirical data from Clostridioides difficile, a pathogen that has undergone several selective sweeps. However, some sweeps show elevation of nonsynonymous LD over synonymous LD across all distances. These sweeps have been previously identified to bear complex adaptations, and moreover, harbor elevated nucleotide diversity. Consistent with this, we demonstrate that lack of criss-crossing can arise when adaptation proceeds via epistatic, multi-locus architecture or introgression.

Meiotic chromosome segregation requires the earlier coordination of chromosome morphogenesis with cell-cycle progression. In C. elegans, the remodeling of chromosomes in preparation for the meiotic divisions and oocyte maturation is regulated by the master cell-cycle regulator cyclin-dependent kinase 1 (CDK-1). Here, we identify CYB-4 as a meiosis-specific B-type cyclin that is required for CDK-1-dependent functions in meiotic prophase. In a genetic suppressor analysis of a mutant defective in chromosome axis assembly, we isolated a null allele that revealed a function for CYB-4 in regulating chromosome structure at two key prophase transitions. Loss of CYB-4 first delays meiotic entry and the onset of chromosome axis formation, and at pachytene exit delays chromatin condensation, bivalent remodeling, and oocyte maturation. The defects in timely CO formation and bivalent packaging that accompany these delays are ultimately resolved before prophase exit, indicating that CYB-4 is required for the scheduling of events rather than if they occur. Together, our findings provide evidence that CDK-1 activity during meiotic prophase is defined by CYB-4 and support a model in which CYB-4/CDK-1 are essential for the sharp transitions at prophase entry and pachytene exit that coordinate chromosome morphogenesis with meiotic progression.

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.