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At least 19 recordsLinked to original sources

Pervasive context-dependent effects in the genetic architecture of complex and quantitative traits revealed by a powerful multiparent mapping population in yeast.

The genetic dissection of complex traits remains a major challenge in basic and biomedical research, but is essential for understanding the molecular pathways that shape phenotypic variation and for developing predictive models of trait and disease susceptibility. Here, we leverage a novel multiparent mapping population of budding yeast, CYClones, comprising 9,344 haploid strains derived from eight genetically diverse founders (~270,000 SNVs, ~ 1 per 44 bp, capturing 56% of common variants and 32% of all variants with a minor allele frequency greater than 0.005 in the global population), to identify quantitative trait loci (QTL) and systematically investigate the genetic architecture of growth rates across ten environmental conditions. In total, we identified 349 QTL (ranging from 18 to 49 QTL per growth condition) that explained between 60% and 100% of narrow sense heritability across traits. The high power and resolution of CYClones revealed that growth traits exhibited distinct, condition-specific genetic architectures with extensive allelic heterogeneity, where a QTL was the result of multiple tightly linked causal variants. We also observed pleiotropy among QTL with complex, trait-dependent allele effects that are also consistent with allelic heterogeneity. Genetic complexity varied widely, with some traits showing nearly Mendelian architectures, while others were highly polygenic. Introgressed loci played a prominent role in the landscape of growth rate QTL, including a QTL localized to a 2.4 kb interval in the PCA1 cadmium transporter that explains 72% of variation in cadmium resistance and is largely driven by an introgression, and a non-additive interaction between the GAL3 regulator and introgressed GAL1/7/10 alleles, extending a previously described three-locus GAL-pathway incompatibility to a four-locus interaction. In both cadmium and galactose conditions, we show that allelic variation at a small number of loci stratifies the population into regulatory or physiological subgroups, each with distinct genetic architectures, a specific manifestation of epistasis we term allele-dependent stratification. Collectively, our results provide novel insights into the genetics of growth rates in budding yeast, the architectural features of genetic complexity, and demonstrate that CYClones is a powerful platform for revealing the molecular basis of complex trait variation.

Quantitative Trait Loci

CYClones: a highly powered, fully genotyped, eight-parent yeast mapping population.

The budding yeast Saccharomyces cerevisiae is a remarkably adaptable organism that thrives in diverse environments. Global sequencing of natural isolates has revealed extensive genetic diversity within the species. Here, we describe the construction and characterization of CYClones (Collaborative Yeast Cross clones), a library of 11,392 segregants generated from a multiparent funnel cross of eight genetically diverse parental strains. To enable the genetic dissection of complex traits, we imputed whole-genome sequences for all segregants and show that CYClones captures a substantial fraction of the global genetic diversity of S. cerevisiae. Haplotype representation is well maintained, with each parental haplotype present at >5% frequency across >95% of the genome. Simulations demonstrate that CYClones has ≥95% power to detect variants with heritability as low as 0.36%, with mapping resolution often finer than the length of a single gene. In summary, CYClones is a powerful community resource for dissecting the genetic architecture of complex and quantitative traits, uncovering context-dependent mutational effects, and identifying causal variants underlying phenotypic diversity.

Saccharomyces cerevisiae

Sugar kelp (Saccharina latissima) population genetics map onto geographic distance and oceanographic features across coastal Maine.

Sugar kelp (Saccharina latissima; order Laminariales) plays a vital role in kelp forest ecosystems, as well as an expanding kelp aquaculture industry, in the Gulf of Maine, United States. However, ocean warming is eroding the resilience of Maine's kelp forests and may be compromising their local genetic diversity, with impacts on population structure and gene flow. Here, we used genome-wide single nucleotide polymorphism (SNP) data to assess the genetic diversity, structure, and connectivity of S. latissima populations at 11 outer coastal sites spanning the historical range of kelp forests in Maine. Our analyses identified moderate genetic diversity and limited inbreeding within sites (average heterozygosity: 0.27). Further, they revealed that three clusters comprising four genetically distinct populations exist across the study region. Population structure was strongly associated with geographic distance and oceanographic features, as supported by principal coordinate analysis, FST calculations, Bayesian clustering, and spore dispersal modeling. Lastly, our outlier analysis identified genes potentially under selection. Thus, our findings highlight distinct, genetically unique kelp populations along Maine's coast and emphasize the need for regional management strategies that support both ecosystem resilience and sustainable aquaculture under climate change.

Gulf of Maine

A transposable element insertion in AUX/IAA16 disrupts splicing and causes auxin resistance in Bassia scoparia.

A dicamba-resistant population of kochia (Bassia scoparia) identified in Colorado, USA in 2012 was used to generate a synthetic mapping population that segregated for dicamba resistance. Linkage mapping associating dicamba injury with genotype derived from restriction-site-associated DNA sequencing identified a single locus in the kochia genome associated with resistance on chromosome 4. A mutant version of Auxin/Indole-3-Acetic Acid 16 (AUX/IAA16; a gene previously implicated in dicamba resistance in kochia) was found near the middle of this locus in resistant plants. Long-read sequencing of dicamba-resistant plants identified a recently inserted long-terminal repeat (LTR) retrotransposon TRIM element near the beginning of the second exon of AUX/IAA16, leading to disruption of normal splicing and a mutated degron domain. Stable transgenic lines of Arabidopsis thaliana ectopically expressing the mutant and wild-type alleles of AUX/IAA16 were developed. Arabidopsis thaliana plants expressing the mutant AUX/IAA16 allele grew shorter roots on control media. However, transgenic root growth was less inhibited on media containing either dicamba (5 μM) or IAA (0.5 μM) when compared with non-transgenic plants or those expressing the wild-type allele of AUX/IAA16. In vitro assays indicate reduced binding affinity and more rapid dissociation of the mutant AUX/IAA16 with TIR1 in the presence of several auxins, and protein modeling suggests the substitution of the glycine residue in the degron domain of AUX/IAA16 is especially important for resistance. A fitness cost associated with the mutant allele of AUX/IAA16 has implications for resistance evolution and management of kochia populations with this resistance mechanism.

Indoleacetic Acids

Haplotype-specific expression of a terpene synthase underlies linalool variation in the grapevine cultivar Riesling.

Grapevine cultivars vary widely in monoterpenoid content, yet the genetic and regulatory mechanisms underlying this variation remain poorly characterized beyond highly aromatic Muscat types. We profiled free volatiles and monoterpenoid glycosides in a Riesling × Cabernet Sauvignon F1 mapping population, revealing extensive variation and transgressive segregation consistent with multigenic control. QTL mapping identified 70 significant loci associated with 48 volatile compounds and monoterpene glycosides, including two major QTLs explaining 33.6% and 33.4% of phenotypic variance in (3S)-linalool accumulation. Integration of haplotype-resolved transcriptomics with metabolite data, enabled by a chromosome-scale diploid Riesling genome assembly, resolved a (3S)-linalool/nerolidol synthase cluster on chromosome 10 and identified VviTPS54 as the strongest candidate underlying linalool variation. VviTPS54 exhibited haplotype-specific expression strongly correlated with (3S)-linalool accumulation across genotypes, while no QTL was detected at the 1-deoxy-D-xylulose-5-phosphate synthase 1 (VviDXS1) locus previously identified in Muscat cultivars. In addition, VviDXS1 expression was not correlated with terpene levels, indicating that regulatory variation within terpene synthase clusters, rather than methylerythritol phosphate (MEP) pathway flux, drives monoterpenoid composition in this population. These results establish regulatory variation of terpene synthases as a key mechanism underlying monoterpenoid diversity in grapevine and demonstrate that resolving such variation requires haplotype-phased genome assemblies coupled with haplotype-resolved transcriptomics to detect allele-specific expression differences at complex, heterozygous loci.

Grapevine

Quantitative trait loci for Globodera pallida resistance derived from wild potato species Solanum gourlayi.

Globodera pallida is a major pest that is responsible for huge losses in potato yields worldwide. Expanding the gene pool of cultivated potatoes with clones resistant to this pest is made possible by searching for resistance genes in wild Solanum species. The aim of this study was to identify quantitative trait loci (QTLs) for potato resistance to Globodera pallida derived from Solanum gourlayi. A resistant diploid potato clone, Sg 2/7 (Solanum gourlayi, accession CGN17592), was crossed with a susceptible potato hybrid clone, DW 94-4235, to generate an F1 mapping population. All clones were tested for nematode resistance using G. pallida, pathotypes Pa2 and Pa3, in 2 or 3 years (2017-2019), respectively. Diversity Array Technology (DArTseq) was used for genotyping and genetic map construction. QTLs for nematode resistance were identified on potato chromosomes II, IV, V, VI, VII, X, XI, and XII, explaining from 10.1 to 21.5% of phenotypic variance. The most significant QTL for resistance to G. pallida pathotype Pa2 was identified on chromosome XII, explaining 20.9% of the phenotypic variance in the dataset from 2017. The most significant QTL for resistance to the G. pallida Pa3 pathotype was identified on chromosome VI, with a CAPS marker Exp928 in its peak, explaining 21.5% of the phenotypic variance in the dataset from 2017. The novel QTLs for resistance to S. gourlayi may be useful for breeding resistant potato cultivars, further studies of candidate genes, and host responses of potato to G. pallida infection.

Quantitative Trait Loci

Meta-QTL Analysis Reveals Consensus Genomic Regions and Candidate Genes for Resistance to Sudden Death Syndrome in Soybean.

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is one of the most economically important diseases limiting soybean production worldwide. Although numerous quantitative trait loci (QTL) associated with SDS resistance have been reported, inconsistencies among mapping populations, marker systems, and experimental conditions have hindered the identification of robust resistance loci for soybean improvement. In this study, a comprehensive meta-analysis was conducted to integrate published QTL and identify stable consensus genomic regions associated with SDS resistance. After a systematic literature survey and data curation, 153 QTL derived from 14 linkage-mapping studies were analyzed using a custom R-based workflow, resulting in the identification of 23 consensus meta-QTL (MQTL) distributed across 17 chromosomes. Several MQTL, particularly those located on chromosomes 6, 8, 18, and 20, were supported by multiple independent studies and represented major genomic hotspots for SDS resistance. Physical localization and functional annotation of these MQTL identified 217 candidate genes, including genes predicted to be involved in plant defense, signal transduction, transcriptional regulation, and secondary metabolism. Gene Ontology enrichment analysis identified response to salicylic acid as the only biological process that remained significant after FDR correction, whereas Kyoto Encyclopedia of Genes and Genomes pathway analysis did not identify significantly enriched pathways. Independent support using five published genome-wide association studies further supported several MQTL, especially those on chromosomes 6, 18, and 20, thereby increasing confidence in these genomic regions. The identified MQTL and prioritized candidate genes provide potential genomic resources for future marker development, improvement applications, and functional validation aimed at improving soybean resistance to SDS.

Fusarium virguliforme

High-resolution, genotype-free mapping of genetic variation with CRI-SPA-Map.

Genetic variation within species shapes phenotypes, but identifying the specific genes and variants that cause phenotypic differences is costly and challenging. Here, we introduce CRI-SPA-Map, a genetic mapping strategy combining CRISPR-Cas9 genome engineering, selective ploidy ablation (SPA), and high-throughput phenotyping for precise genetic mapping with or without genotyping in the yeast Saccharomyces cerevisiae. In CRI-SPA-Map, a donor strain carrying SPA machinery is mated to a genetically different recipient strain harboring a genome-integrated selectable cassette. In the resulting diploid, CRISPR-Cas9 cuts the cassette for replacement with DNA from the homologous donor chromosome. Donor chromosomes are then removed using SPA to yield haploid recombinant strains. To establish CRI-SPA-Map, we mated a W303 SPA strain to 92 strains from the BY4742 yeast knockout collection that carry gene deletion cassettes on the left arm of chromosome XIV and created 1,451 recombinant isolates. Whole-genome sequencing verified that deletion cassette replacement introduced short donor DNA tracts of variable length, resulting in a finely recombined mapping population. Using only the known location of the gene deletions, which marks where donor DNA is introduced, we identified a 6.5 kb-region shaping yeast growth. Further dissection of this region pinpointed two causal variants in two genes, MKT1 and SAL1. Engineering these variants alone and in combination revealed gene-by-environment interactions at both genes, as well as epistatic interactions between them that were in turn dependent on the environment. CRI-SPA-Map is a cost-effective strategy for creating high-resolution recombinant panels of yeast strains for identifying the genetic basis of phenotypic variation.

Journal Article

The genetic basis of chloride exclusion in grapevines.

Mediterranean regions are among the most important areas for global grape production, characterized by dry climates and frequent challenges associated with soil salinity. In these environments, chloride toxicity is a major factor limiting vine growth and fruit quality. Despite the critical role of chloride exclusion in salinity tolerance, the genetic mechanisms underlying this trait remain poorly understood. In this study, we analyzed natural variation in chloride exclusion using a diverse panel of 335 accessions representing 18 wild and cultivated Vitis species. This panel, comprising accessions from the southwestern United States and Mexico, captures a broad range of evolutionary adaptations to abiotic stress and provides a valuable genetic resource for breeding efforts aimed at introducing novel traits. Using genome-wide association and quantitative trait loci (QTL) mapping, we identified a major QTL on chromosome 8, now designated qClEx8.1, containing candidate genes encoding cation/H⁺ exchangers (CHXs), which are involved in ion transport and homeostasis. To validate these findings, we analyzed a mapping population derived from Vitis acerifolia longii 9018 and the commercial rootstock GRN3, confirming the chromosome 8 locus as a major determinant of chloride exclusion. Structural variant analysis revealed nonsynonymous substitutions within CHX genes that may influence protein function and salinity tolerance. Additionally, we discovered a novel QTL on chromosome 19 enriched with G-type lectin S-receptor-like serine/threonine-protein kinases, known regulators of stress signaling. By integrating phenotypic and genomic data across a diverse Vitis collection, this study advances our understanding of the genetic architecture underlying chloride exclusion and highlights candidate genes for breeding salt-tolerant rootstocks.

Vitis

Genetic basis for broad interspecific compatibility in Solanum verrucosum.

Solanum verrucosum Schlechtendal (2x = 2n = 24) is unique among the clade 4 Solanum Sect Petota species. In addition to being one of the only fully self-compatible diploid potato species, S. verrucosum is the only clade 4 species that lacks prezygotic interspecific reproductive barriers. This allows S. verrucosum to accept pollen from a broad range of Solanum species and thereby serving as a genetic "bridge" between the cultivated or primary potato gene pool and distantly related wild relatives in the tertiary gene pool. The genetic mechanisms underlying self-compatibility in Solanum often underpin interspecific compatibility interactions, which in S. verrucosum, has been attributed to the lack of S-RNase expression. Using an interspecific F2 mapping population (n = 150), we investigated the genetic mechanisms responsible for the lack of interspecific reproductive barriers in S. verrucosum. This F2 population was evaluated for the ability to accept pollen from two clade 1, 1 EBN species (S. pinnatisectum and S. tarnii); from which two QTL for interspecific compatibility were identified on chromosomes 1 and 11, explaining 56.6% of the phenotypic variation observed. To identify the genetic basis of interspecific compatibility, we generated a chromosome-scale genome assembly of S. verrucosum MSII1813-2 and performed gene expression profiling of reproductive organs. Differential gene expression of S-RNase, located within the chromosome 1 QTL, confirmed the central role of the S-locus and specifically, S-RNase, in interspecific compatibility. Discovery of a non-S-locus QTL is consistent with previous findings that other non-S-locus factors are necessary for interspecific compatibility in S. verrucosum.

Solanum

Consistent and idiosyncratic pleiotropy in shaping genetic correlations.

Pleiotropy, the phenomenon where a single mutation influences multiple phenotypic traits, creates genetic correlations that can constrain evolutionary trajectories. Yet genetic correlations differ in their persistence: some remain stable over long evolutionary timescales, whereas others change rapidly across generations or environments. One explanation is that similar values of genetic correlation, rG, can arise from different pleiotropic architectures: broadly aligned effects across many loci, or disproportionate covariance contributions from a few large effect loci. Motivated by the distinction between vertical and horizontal pleiotropy, here, we develop a bivariate marker effect framework for recombinant mapping populations that separates candidate large covariance contributors from the polygenic background correlation, rD. We define rD as the correlation among marker effects after trimming markers with unusually large covariance contributions. rD is a trait-pair summary of how consistently small and moderate effect markers align across the genome; high rD is expected when many perturbations propagate through shared developmental, physiological, causal, or geometric structure. Applying this framework to high-dimensional yeast single-cell morphology, we show that trait pairs with similar rG can differ substantially in rD, and that a small number of candidate outlier regions can strongly influence some marker effect correlations. We then test whether rD predicts the environmental stability of genetic correlations under geldanamycin-mediated Hsp90 perturbation. Trait pairs with stronger rD show smaller absolute changes in rG. These results suggest that genetic correlations supported by a strong polygenic marker effect background are more environmentally stable than correlations shaped primarily by a few large covariance contributors.

Genetic Pleiotropy

Twisted Sister1: an agravitropic mutant of bread wheat (Triticum aestivum) with altered root and shoot architectures.

We identified a mutant of hexaploid wheat (Triticum aestivum) with impaired responses to gravity. The mutant, named Twisted Sister1 (TS1), had agravitropic roots that were often twisted along with altered shoot phenotypes. Roots of TS1 were insensitive to externally applied auxin, with the genetics and physiology suggestive of a mutated AUX/IAA transcription factor gene. Hexaploid wheat possesses over 80 AUX/IAA genes, and sequence information did not identify an obvious candidate. Bulked segregant analysis of an F2 population mapped the mutation to chromosome 5A, and subsequent mapping located the mutation to a 41 Mbp region. RNA-seq identified the TraesCS5A03G0149800 gene encoding a TaAUX/IAA protein to be mutated in the highly conserved domain II motif. We confirmed TraesCS5A03G0149800 as underlying the mutant phenotype by generating transgenic Arabidopsis thaliana. Analysis of RNA-seq data suggested broad similarities between Arabidopsis and wheat for the role of AUX/IAA genes in gravity responses, although there were marked differences. Here we show that the sequenced wheat genome, along with previous knowledge of the physiology of gravity responses from other plant species, gene mapping, RNA-seq, and expression in Arabidopsis have enabled the cloning of a key wheat gene that defines plant architecture.

Triticum

QTLs associated with phenolic acid accumulation and antioxidant activity in tropical maize.

Maize represents a significant source of phytochemicals, with phenolic acids standing out as one of the most extensively studied functional compound families. These bioactive molecules have gained attention for their potent antioxidant properties and potential contributions to human health improvement. To evaluate the segregation of phenolic compounds in maize and its genetic basis, this study was conducted to identify quantitative trait loci (QTLs) associated with major phenolic compounds and their antioxidant capacity. The mapping population comprised 100 recombinant inbred lines (RILs) derived from the cross between P84 and Kilima. Twelve traits were analyzed: free and cell wall-bound antioxidant capacity, total phenolic content, and contents of p-coumaric acid, ferulic acid, three isomers of di-ferulic acid, and three isomers of tri-ferulic acid. The RILs exhibited substantial diversity in phenolic compound profiles. In total, 19 QTLs were identified for nine traits, with the number of associated regions ranging from 1 to 5 and explaining between 2.95% and 37.48% of the phenotypic variation. This research provides substantial evidence for the co-localization of major QTLs for principal phenolic acids in maize with genomic regions harboring genes putatively related to their biosynthesis and biotic resistance. This is the first study to report QTLs associated with triferulic acids in maize. The identified regions co-localizing with biotic stress resistance genes represent targets for marker-assisted selection toward the improvement of phenolic acid accumulation in maize breeding programs.

QTLs

Association mapping in structured populations.

The use, in association studies, of the forthcoming dense genomewide collection of single-nucleotide polymorphisms (SNPs) has been heralded as a potential breakthrough in the study of the genetic basis of common complex disorders. A serious problem with association mapping is that population structure can lead to spurious associations between a candidate marker and a phenotype. One common solution has been to abandon case-control studies in favor of family-based tests of association, such as the transmission/disequilibrium test (TDT), but this comes at a considerable cost in the need to collect DNA from close relatives of affected individuals. In this article we describe a novel, statistically valid, method for case-control association studies in structured populations. Our method uses a set of unlinked genetic markers to infer details of population structure, and to estimate the ancestry of sampled individuals, before using this information to test for associations within subpopulations. It provides power comparable with the TDT in many settings and may substantially outperform it if there are conflicting associations in different subpopulations.

Alleles

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum

Genomic Divergence Shaped the Genetic Regulation of Meiotic Homologous Recombination in Brassica Allopolyploids.

The tight regulation of meiotic recombination between homologs is disrupted in Brassica AAC allotriploids, a genomic configuration that may have facilitated the formation of rapeseed (Brassica napus L.) ∼7,500 years ago. Indeed, the presence of the haploid C genome induces supernumerary crossovers between homologous A chromosomes with dramatically reshaped distribution. However, the genetic mechanisms driving this phenomenon and their divergence between nascent and established lineages remain unclear. To address these concerns, we generated hybrids carrying additional C chromosomes derived either from an established lineage of the allotetraploid B. napus or from its diploid progenitor B. oleracea. We then assessed recombination variation across twelve populations by mapping male meiotic crossovers using single nucleotide polymorphism markers evenly distributed across the sequenced A genome. Our findings reveal that the C09 chromosome of B. oleracea is responsible for the formation of additional crossovers near pericentromeric regions. Interestingly, its counterpart from an established lineage of B. napus shows no significant effect on its own, despite having a similar content of meiotic genes. However, we showed that the B. napus C09 chromosome influences crossover formation through inter-chromosomal epistatic interactions with other specific C chromosomes. These results provide new insights into the genetic regulation of homologous recombination in Brassica and emphasize the role of genomic divergence since the formation of the allopolyploid B. napus.

Meiosis

QTL mapping for seed vigor-related traits under artificial aging in common wheat in two introgression line (IL) populations.

BACKGROUND: Seed vigor recognized as a quantitative trait is of particular importance for agricultural production. However, limited knowledge is available for understanding genetic basis of wheat seed vigor. METHODS: The aim of this study was to identify quantitative trait loci (QTL) responsible for 10 seed vigor-related traits representing multiple aspects of seed-vigor dynamics during artificial aging with 6 different treatment times (0, 24, 36, 48, 60, and 72 h) under controlled conditions (48 °C, 95% humidity, and dark). The mapping populations were two wheat introgression lines (IL-1 and IL-2) derived from recipient parent (Lumai 14) and donor parent (Shaanhan 8675 or Jing 411). RESULTS: A total of 26 additive QTLs and 72 pairs of epistatic QTLs were detected for wheat seed-vigor traits. Importantly, chromosomes 1B and 7B contained several co-located QTLs, and chromosome 2A had a QTL-rich region near the marker Xwmc667, indicating that these QTLs may affect wheat seed vigor with pleiotropic effects. Furthermore, several possible consistent QTLs (hot-spot regions) were examined by comparison analysis of QTLs detected in this study and reported previously. Finally, a set of candidate genes for wheat seed vigor were predicted to be involved in transcription regulation, carbohydrate and lipid metabolism. CONCLUSION: The present findings lay new insights into the mechanism underlying wheat seed vigor, providing valuable information for wheat genetic improvement especially marker-assisted breeding to increase seed vigor and consequently achieve high grain yield despite of further investigation required.

Triticum

EPIC: Event Prototyping via Information Constrained graph learning for personalized cancer driver gene prediction.

MOTIVATION: Precision oncology relies on accurately distinguishing patient-specific driver mutations from the vast background of passenger alterations. While graph-based computational methods have emerged as powerful tools for this task, they often struggle to preserve the distinct genomic context of individual mutations within complex biological networks. Consequently, subtle patient-specific driver signals are frequently obscured by dominant topological patterns, critically impeding the identification of individualized oncogenic events essential for personalized cancer therapy. RESULTS: To address this, we propose EPIC, a novel framework for Event Prototyping via Information Constrained Graph Learning. Unlike traditional node-centric approaches, EPIC redefines driver prediction as a metric learning task in an event embedding space. We introduce an information-constrained learning strategy that imposes explicit geometric constraints on feature variance, effectively preventing feature collapse and ensuring that low-frequency driver signals are distinctively preserved. Experiments on large-scale cancer cohorts demonstrate that EPIC significantly outperforms established baselines. Notably, the model prioritizes low-frequency driver variants typically overlooked by population-based methods, mapping them to critical oncogenic mechanisms associated with drug resistance and metastasis. Furthermore, clinical actionability analysis confirms that EPIC substantially expands the patient population eligible for targeted therapies. EPIC provides a robust and context-aware solution for personalized cancer driver discovery, bridging the gap between genomic data and actionable therapeutic insights. AVAILABILITY AND IMPLEMENTATION: The source code and datasets are available at https://github.com/spcho-dev/EPIC.

Humans