Sun H, Zhang J, Liao S
… +23 more, Guo S, Zhou Z, Zhao X, Wu S, Zhao J, Gong G, Wang J, Li M, Yu Y, Ren Y, Tian S, Li S, Zhang H, Hammar SA, McGregor C, Jarret R, Wechter P, Branham SE, Kousik C, Levi A, Grumet R, Fei Z, Xu Y
Pangenomes are increasingly important for harnessing crop genetic diversity, yet their resolution and utility are often limited by insufficient sampling of high-quality genome assemblies. Here we present a population-lev...Pangenomes are increasingly important for harnessing crop genetic diversity, yet their resolution and utility are often limited by insufficient sampling of high-quality genome assemblies. Here we present a population-level watermelon super-pangenome constructed from 138 reference-grade assemblies, including 135 newly generated genomes representing all seven species. This super-pangenome captures approximately 1 million structural variants (SVs), enabling accurate variant genotyping across 914 accessions. Broader sampling within the pangenome provides insights into watermelon genome evolution and the origin of cultivated watermelon. Incorporating SVs into genome-wide association studies improves mapping resolution and reveals a copy number variant upstream of ClFCI1 that regulates flesh color intensity in a dosage-dependent manner. Leveraging this comprehensive variation map, we developed high-accuracy genomic prediction models for 18 agronomic traits. Together, these findings and genomic resources establish a foundation for dissecting complex traits and accelerating precision breeding in watermelon, while offering a valuable model for SV-resolved pangenomics in crops.
Cancer-causing mutations have been identified primarily from positive selection signals in cancer genomes. However, positive selection is also a ubiquitous feature of normal tissue aging. Here we develop a statistical fr...Cancer-causing mutations have been identified primarily from positive selection signals in cancer genomes. However, positive selection is also a ubiquitous feature of normal tissue aging. Here we develop a statistical framework to disentangle selection in normal tissue and causation of carcinogenesis. By comparing cancer and normal tissue genomes, we estimate the effects of mutations on cancer risk in the blood, esophagus and colon. We determine that stronger cancer-causing mutations are enriched at younger patient ages. This enables cancer-causing mutations to be identified from patient age distributions, even without normal tissue data. Moreover, we show for acute myeloid leukemia that the age-dependence of purported causal mutations can be explained largely by normal blood evolution, challenging the long-standing notion that childhood cancers require distinct mutations. Broadly, our framework delineates carcinogenesis from normal tissue aging, improving the assessment of cancer risk conferred by mutations.
Grillo G, Nadorp B, Qamra A
… +15 more, Drylie B, Mitchell A, Arlidge C, Nand A, Takayama N, Murison A, Madani Tonekaboni SA, Kang KK, Arruda A, Wang JCY, Minden MD, Deniz Ö, Boutzen H, Dick JE, Lupien M
Despite most acute myeloid leukemia (AML) patients achieving complete remission after induction chemotherapy, two-thirds relapse within 5 years. AML follows a cellular hierarchy sustained by leukemia stem cells (LSCs), w...Despite most acute myeloid leukemia (AML) patients achieving complete remission after induction chemotherapy, two-thirds relapse within 5 years. AML follows a cellular hierarchy sustained by leukemia stem cells (LSCs), which drive tumor progression and relapse. Little is known about the genetic determinants driving LSCs stemness properties. By identifying chromatin variants from accessibility measurements across LSCs, hematopoietic stem cells and downstream progeny, we identified transposable elements (TEs) as genetic determinants of primitive versus mature populations. Accessibility at 121 TE subfamilies distinguished LSCs from mature leukemic cells and stratified AML patients by stemness and survival. Functional assays revealed that these TE subfamilies serve as docking sites for genome topology regulators or lineage-specific transcription factors, including LYL1 in LSCs. Chromatin editing established the necessity of accessibility at LTR12C elements to maintain LSC stemness. Thus, TEs regulate primitive versus mature cell states, with distinct subfamilies underlying stemness in normal versus leukemic stem cells.
Aplastic anemia (AA) results from T-cell-mediated destruction of hematopoietic stem and progenitor cells (HSPCs), driving clonal hematopoiesis via loss of human leukocyte antigen (HLA) risk alleles (HLA loss-of-function...Aplastic anemia (AA) results from T-cell-mediated destruction of hematopoietic stem and progenitor cells (HSPCs), driving clonal hematopoiesis via loss of human leukocyte antigen (HLA) risk alleles (HLA loss-of-function mutations or uniparental disomy 6p, UPD6p), paroxysmal nocturnal hemoglobinuria and clonal hematopoiesis of indeterminate potential (CHIP) mutations. Here genomic profiling of 619 patients with AA revealed clonal hematopoiesis in 69% of cases, with ASXL1, BCOR and BCORL1 identified as the most frequent CHIP mutations in pediatric cases. Single-cell multi-omics analysis of 304,902 cells from 48 samples uncovered complex branching clonal architecture, with a median of three HLA loss events per patient, converging to inactivate HLA risk alleles. Single-cell whole-genome sequencing (WGS) resolved up to 15 HLA loss clones per patient and phylogenetic reconstruction indicated that these clones originated years before diagnosis. Long-read WGS precisely mapped UPD6p breakpoints and HLA methylation. HLA loss conferred a protective effect against CHIP, evidenced by their near-absent co-occurrence. Longitudinal single-cell analysis demonstrated that long-lived clones were enriched in the CD34 HSPC compartment. These findings reveal parallel evolutionary pathways used by hematopoietic cells to evade immune attack.
Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can enhance biological and therapeutic discovery and improve risk prediction. Here we performed genome-wide genetic association and...Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can enhance biological and therapeutic discovery and improve risk prediction. Here we performed genome-wide genetic association and fine-mapping analyses in 20,355 T1D and 797,363 nondiabetic individuals of European ancestry and in 10,107 T1D and 19,639 nondiabetic individuals at the MHC locus, which identified 160 risk signals. We trained a machine learning model, T1GRS, to predict T1D using genetic risk, which improved classification in Europeans and performed similarly in African Americans, compared to previous scores. T1GRS particularly improved prediction in T1D, with fewer high-risk HLA haplotypes and more complex risk profiles, and revealed 154 nonlinear interactions between MHC and non-MHC loci. Finally, we identified four genetic subclusters based on T1GRS features with significant differences in age of onset and diabetic complications. Overall, improved genetic discovery and prediction will have wide clinical, therapeutic and research applications for T1D.
Koller D, He J, Løkhammer S
… +14 more, Aranda S, Qiu D, Davtian D, Chen Q, Xu Z, Mao Z, Friligkou E, Karaca S, Cormand B, Flores I, Altmäe S, Mitjans M, Cabrera-Mendoza B, Polimanti R
Endometriosis is a chronic systemic disease affecting ~10% of women, yet its genetic basis and molecular mechanisms remain poorly understood. Hence, here we conducted a genome-wide association study of endometriosis and...Endometriosis is a chronic systemic disease affecting ~10% of women, yet its genetic basis and molecular mechanisms remain poorly understood. Hence, here we conducted a genome-wide association study of endometriosis and adenomyosis in ~1.4 million women, including 105,869 cases, aiming to expand loci discovery across ancestries, dissect symptom-specific effects and integrate multi-omic data. We identified 80 genomic regions associated with endometriosis risk, including 37 new loci, of which 5 are also associated with adenomyosis. We identified putative causal variants underlying over 50 of these associations. Transcriptomic, epigenetic and proteomic analyses across tissues linked endometriosis risk to pathways involved in cell differentiation, immune and hormonal regulation, tissue remodeling and inflammation. Drug-repurposing analyses highlighted potential treatments currently used for breast cancer, contraception and preterm birth prevention. Endometriosis polygenic risk interacted with abdominal pain, anxiety, migraine and nausea. This study advances understanding of genetic risk factors for endometriosis and provides molecular support for several hypotheses on its pathogenesis.
Fejzo M, Wang X, Tan Q
… +31 more, Zöllner J, Pujol-Gualdo N, Laisk T, Estonian Biobank Research Team, Finer S, van Heel DA, Genes & Health Research Team, Brumpton B, Bhatta L, Hveem K, Jasper EA, Velez Edwards DR, Hellwege JN, Edwards T, Jarvik GP, Luo Y, Khan A, MacGibbon K, Gao Y, Ge G, Averbukh I, Soon E, Angelo M, Magnus P, Johansson S, Njølstad PR, Kim A, Gazal S, Vaudel M, Shu CA, Mancuso N
Ancient DNA (aDNA) has revolutionized our ability to study human evolution by enabling the direct observation of genetic changes through time. This has reshaped our understanding of human adaptation and its relevance for...Ancient DNA (aDNA) has revolutionized our ability to study human evolution by enabling the direct observation of genetic changes through time. This has reshaped our understanding of human adaptation and its relevance for modern health and disease. In recent years, high-quality ancient genomes and large datasets have made it possible to track allele frequency dynamics and identify episodes of natural selection with unprecedented resolution. Here, we synthesize insights from recent studies that have systematically investigated how humans adapted to shifts in diet, mobility, pathogen exposure and environment. We summarize the approaches used to detect selection in aDNA, examine the role of major migration and admixture events and connect results across time periods and archaeological contexts. Finally, we outline future challenges and opportunities that need to be addressed for aDNA studies to provide new insights into human adaptation that could not be inferred from present-day genomes alone.
Recent advances in spatial transcriptomics (ST) have generated an expanding collection of heterogeneous datasets, offering unprecedented opportunities to investigate tissue organizations and functions. However, effective...Recent advances in spatial transcriptomics (ST) have generated an expanding collection of heterogeneous datasets, offering unprecedented opportunities to investigate tissue organizations and functions. However, effective interpretation and integration of data originating from diverse sources and conditions remain a major challenge. We present INSPIRE, a deep-learning method for interpretable, integrative analysis of multiple ST datasets. INSPIRE adopts an adversarial learning strategy with graph neural networks to achieve spatially informed and adaptive data integration. By incorporating non-negative matrix factorization, INSPIRE identifies interpretable spatial factors and associated gene programs that characterize tissue architecture, cell-type organization and biological processes. Across a broad range of applications, INSPIRE demonstrates superior performance in resolving fine-grained biological signals, integrating complementary strengths across technologies, capturing condition-specific variation, uncovering tumor microenvironment heterogeneity, elucidating developmental dynamics and facilitating three-dimensional tissue reconstruction. INSPIRE also scales to extremely large datasets, as demonstrated by applications to Xenium-profiled human breast cancer and Stereo-seq mouse organogenesis datasets.
Calabrò L, Caruso FP, Covre A
… +28 more, Noviello TMR, Lofiego MF, Tufano R, Ferraro L, Grisolia P, De Falco A, Lagano V, Sgambelluri F, Sabella G, Rossi G, Gibilisco G, Marzani F, Bello E, Simonetti E, D'Alonzo V, Caraglia M, Coral S, De Angelis A, Cerbone L, Delfanti S, Giannarelli D, Grosso F, Di Giacomo AM, Milione M, Mortarini R, Anichini A, Ceccarelli M, Maio M
Pleural mesothelioma (PM) has a poor prognosis and standard therapy with immune checkpoint inhibitors (ICIs) CTLA-4 and PD-1 is still clinically unsatisfying. No predictive biomarkers of ICI efficacy in PM are available...Pleural mesothelioma (PM) has a poor prognosis and standard therapy with immune checkpoint inhibitors (ICIs) CTLA-4 and PD-1 is still clinically unsatisfying. No predictive biomarkers of ICI efficacy in PM are available yet. In the retrospective multicenter NIBIT-EPI-MESO study, multi-omics analysis of pre-ICI therapy tumor lesions from 91 patients with PM treated in earlier clinical trials or in daily practice identified four PM subsets with progressively increasing global DNA methylation profiles-demethylated, LOW, intermediate and CpG island methylator phenotype (CIMP). These methylation subsets predicted response and survival to ICI therapy. The LOW subset was enriched in responder patients, who had the longest median overall survival and the highest 3-year overall survival rate, and showed a T cell- and B cell-rich immune microenvironment. Conversely, the CIMP subtype was enriched in nonresponder patients with the shortest median overall survival and overall survival, along with a depleted immune microenvironment. A methylation-based probabilistic decision-making classification tool to predict the outcome of ICI treatment in patients with PM was developed.
Bian J, Zhang Y, Ding S
… +20 more, Guo H, Li K, Guan Y, Zhou G, Li J, Garg V, Cui Y, Lv Y, Chitikineni A, Meng Q, Li T, He L, Zhao C, Wang X, Tang R, Zhang L, Deng XW, Varshney RK, He H, Liu X
Peanut (Arachis hypogaea L.) is a globally significant leguminous oil crop. Here we present telomere-to-telomere genome assemblies for two diploid and four tetraploid peanut varieties, resulting in high-quality reference...Peanut (Arachis hypogaea L.) is a globally significant leguminous oil crop. Here we present telomere-to-telomere genome assemblies for two diploid and four tetraploid peanut varieties, resulting in high-quality reference genomes, showing that the complex activities of transposable elements, chromosomal rearrangements and centromere expansions within subgenomes collectively contribute to the asymmetrical evolution of the tetraploid genome, and unique structural variants in the four tetraploid peanut varieties provide clear evidence of domestication. Population analyses of 521 peanut accessions revealed asymmetric selection events between subgenomes during breeding, and genome-wide association studies identified candidate genes linked to oil content, seed size and weight, kernel dehydration rate, and arachidic acid content. In addition, transcriptomic and metabolomic analyses revealed enhanced activity in lipidomic and anthocyanin biosynthetic pathways during seed development. These comprehensive findings provide insights into genome organization, evolutionary dynamics and phenotypic differentiation across peanut varieties that could inform future peanut breeding and improvement strategies.
With the advent of spatial multi-omics, mosaic integration of diverse datasets with partially overlapping modalities enables the construction of comprehensive multimodal spatial atlases from heterogeneous sources. Here w...With the advent of spatial multi-omics, mosaic integration of diverse datasets with partially overlapping modalities enables the construction of comprehensive multimodal spatial atlases from heterogeneous sources. Here we present SpaMosaic, a tool that uses contrastive learning and graph neural networks to build a modality-agnostic, batch-corrected latent space for spatial domain identification and missing-modality imputation. We systematically benchmarked SpaMosaic against existing integration methods using simulated data and experimentally acquired datasets spanning RNA and protein abundance, chromatin accessibility and histone modifications from brain, embryo, tonsil and lymph node tissues. SpaMosaic consistently outperformed other methods in identifying coherent spatial domains by reducing noise and mitigating batch effects. We further challenged SpaMosaic with heterogeneous real-world datasets spanning different technologies, developmental stages, resolutions and modality compositions, where it consistently resolved fine anatomical structures and enabled comprehensive mouse embryo atlasing. Beyond integration, SpaMosaic enables accurate imputation of missing modalities. In a mosaic mouse brain dataset, the imputed histone modifications not only recapitulated expected transcriptome-epigenome correlations but also uncovered more region-specific regulatory links compared to the measured chromatin accessibility data, demonstrating the ability to infer relationships across modalities without coprofiling. Computationally, SpaMosaic is highly scalable, capable of integrating over 100 sections and processing a single section with more than 800,000 spots. In summary, SpaMosaic provides a versatile framework for unifying the rapidly accumulating heterogeneous spatial omics data into comprehensive biological atlases.
Polycystic ovary syndrome (PCOS) and its underlying features remain poorly understood. In this genetic study (n = 544,513), we expand the number of genetic loci from 16 to 29, and additionally identify 31 associated plas...Polycystic ovary syndrome (PCOS) and its underlying features remain poorly understood. In this genetic study (n = 544,513), we expand the number of genetic loci from 16 to 29, and additionally identify 31 associated plasma proteins. Many risk-increasing loci were associated with later age at menopause, underscoring the reproductive longevity related to an increased oocyte number and/or availability across the lifespan. Hormonal regulation in the etiology of this condition, through metabolic and reproductive features, was emphasized. The proteomic analysis highlighted metabolic biology known to be related to PCOS. A polygenic risk score (PRS) was associated with adverse cardiometabolic outcomes, with differing relevance of testosterone and body mass index in women and men. Finally, while oligo-anovulation and anovulatory infertility are features of PCOS, we observed no impact of PCOS susceptibility on childlessness. We suggest that PCOS susceptibility confers balanced pleiotropic influences on fertility in women, and life-long adverse metabolic consequences in both sexes.
Intratumor heterogeneity fundamentally challenges cancer treatment, as coexisting, molecularly distinct cell states with non-overlapping drug sensitivities can drive therapeutic resistance. We establish and validate a ge...Intratumor heterogeneity fundamentally challenges cancer treatment, as coexisting, molecularly distinct cell states with non-overlapping drug sensitivities can drive therapeutic resistance. We establish and validate a generalizable, network-based framework to systematically identify combination therapies targeting complementary tumor cell states. Applied to diffuse midline glioma (DMG)-a universally fatal pediatric malignancy-this approach identified master regulator protein dependencies in seven coexisting cell states, confirmed by pooled CRISPR-Cas9 assays. Perturbational transcriptional profiles for 372 clinically relevant drugs prioritized candidates predicted to invert state-specific master regulator activity. State-selective drug sensitivity was validated for eight out of nine (89%) drugs in vivo, including avapritinib, ruxolitinib and larotrectinib. Compared with monotherapy, co-administering drugs targeting complementary states significantly prolonged survival across virtually all combinations, with avapritinib plus ruxolitinib extending median survival nearly threefold versus vehicle and 1.5-fold versus avapritinib alone. These findings establish clinically actionable DMG combinations and a tumor-agnostic and mutation-agnostic framework for rational combination therapy design.
Genebanks have a vital role in safeguarding plant genetic resources and providing access to valuable genetic diversity that is absent from modern breeding gene pools. Yet, a major challenge for using genebank materials i...Genebanks have a vital role in safeguarding plant genetic resources and providing access to valuable genetic diversity that is absent from modern breeding gene pools. Yet, a major challenge for using genebank materials in crop improvement programs lies in selecting manageable subsets of accessions that maximize genetic diversity for traits of interest. The integration of genomic information is creating new opportunities to address this challenge. Recent studies have shown that k-mer-based bioinformatic approaches capture and reveal previously hidden functional diversity that is missing in elite cultivars. Here we present a perspective on how such approaches enable a precise identification of allele and haplotype diversity across large genebank collections that can guide the strategic selection of accessions for crop improvement. Incorporating this untapped genetic diversity from genebanks into crop improvement pipelines is increasingly recognized as a crucial strategy for developing climate-resilient cultivars.
Cheng FF, Liu X, Mi H
… +26 more, Wang L, Ma R, Guo Y, Sidorenko J, Jiang C, Islam T, Meguro A, Hikino K, Ishikawa Y, Tang S, Li T, Chen R, Wang L, Mägi R, Metspalu A, Estonian Biobank Research Team, 23andMe Research Team, Takeuchi M, Mizuki N, Choquet H, Jin ZB, Chen G, Zhou K, Terao C, Zeng J, Yang J
Refractive errors (REs) affect over half of the global population, with consequences ranging from blurred vision to blindness. Here we conducted ancestry-stratified and cross-ancestry meta-analyses of genome-wide associa...Refractive errors (REs) affect over half of the global population, with consequences ranging from blurred vision to blindness. Here we conducted ancestry-stratified and cross-ancestry meta-analyses of genome-wide association studies for RE in people of European (n = 1,495,159), East Asian (n = 121,172) and African (n = 144,737) ancestries. The cross-ancestry meta-analysis identified 932 RE-associated variants, including 241 previously unknown associations, four East Asian-specific associations and one African-specific association. Statistical fine-mapping pinpointed 16 high-confidence putative causal variants, and gene prioritization analyses highlighted 23 genes involved in eye development. We constructed an enhanced polygenic predictor incorporating functional annotations that explained 21.4% of RE variation, effectively stratified the onset, progression and severity of myopia, and achieved an area under the receiver operating characteristic curve of 0.806 for predicting high myopia. Our multi-ancestry genome-wide association study expands substantially the catalog of genetic variants for RE and demonstrates the potential clinical utility of polygenic prediction in identifying high-risk people across diverse populations.