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Transient histone deacetylase inhibition induces cellular memory of gene expression and 3D genome folding.

Paldi F, Szalay MF, Dufau S … +5 more , Di Stefano M, Reboul H, Jost D, Bantignies F, Cavalli G

Nat Genet · 2026 Feb · PMID 41639407 · Full text

Epigenetic memory enables the propagation of gene expression patterns following transient stimuli. Although three-dimensional chromatin organization is emerging as a key regulator of genome function, it is unknown whethe... Epigenetic memory enables the propagation of gene expression patterns following transient stimuli. Although three-dimensional chromatin organization is emerging as a key regulator of genome function, it is unknown whether it contributes to cellular memory. Here we establish that acute perturbation of the epigenome can induce cellular memory of gene expression in mouse embryonic stem cells. We uncover how a pulse of histone deacetylase inhibition translates to changes in transcription, histone modifications and genome folding. While most epigenomic and transcriptional changes are initially reversed once the perturbation is removed, some loci remain transcriptionally deregulated and genome architecture partially maintains its perturbed conformation. Consequently, a second pulse of transient hyperacetylation induces stronger memory of transcriptional deregulation. Using ultradeep Micro-C, we associate memory of gene expression with repressive Polycomb-mediated chromatin topology. These results demonstrate how cells can record transient stresses in their genome architecture, thereby enabling an enhanced response to subsequent perturbations.

Childhood brain tumors instruct cranial hematopoiesis and immunotolerance.

Cooper E, Posner DA, Lee CYC … +24 more , Hu L, Bonner S, Taylor JT, Baldwin O, Jimenez-Guerrero R, Masih KE, Rahrmann KW, Eigenbrood J, Ngo G, Franklin VNR, D'Santos CS, Mair R, Santarius T, Craven C, Jalloh I, Moreno Vicente J, Halim TYF, Wang L, Kreigstien AR, Wainwright B, Swartling FJ, Khan J, Clatworthy MR, Gilbertson RJ

Nat Genet · 2026 Feb · PMID 41634415 · Full text

Recent research has challenged a long-held view of the brain as an immune-privileged organ, revealing active immunosurveillance with therapeutic relevance. Using a new genetically engineered mouse model of ZFTA-RELA epen... Recent research has challenged a long-held view of the brain as an immune-privileged organ, revealing active immunosurveillance with therapeutic relevance. Using a new genetically engineered mouse model of ZFTA-RELA ependymoma, a childhood brain tumor, we characterized an immune circuit between the tumor and antigen-presenting hematopoietic stem and progenitor cells (HSPCs) in the skull bone marrow. The presentation of antigens by HSPCs to CD4 T cells biased HSPC lineages toward myelopoiesis and polarized CD4 T cells to regulatory T cells, culminating in tumor immunotolerance. Remarkably, normalizing hematopoiesis with a single infusion of antibodies directed against cytokines enriched in the cerebrospinal fluid of mice bearing ZFTA-RELA ependymomas, choroid plexus carcinomas or group 3 medulloblastoma-all aggressive childhood brain tumors-disrupted this process and caused profound tumor regression. These findings demonstrate the existence of a skull bone marrow-tumor immunological interface and suggest that modulating the local supply of myeloid cells could represent a less toxic therapeutic strategy for aggressive childhood brain tumors.

Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling.

Strom NI, Verhulst B, Bacanu SA … +134 more , Cheesman R, Purves KL, Gedik H, Mitchell BL, Kwong AS, Faucon AB, Singh K, Medland S, Colodro-Conde L, Krebs K, Hoffmann P, Herms S, Gehlen J, Ripke S, Awasthi S, Palviainen T, Tasanko EM, Peterson RE, Adkins DE, Shabalin AA, Adams MJ, Iveson MH, Campbell A, Thomas LF, Winsvold BS, Drange OK, Børte S, Ter Kuile AR, Naamanka J, Nguyen TH, Meier SM, Corfield EC, Hannigan L, Levey DF, Czamara D, Weber H, Choi KW, Pistis G, Couvy-Duchesne B, Van der Auwera S, Teumer A, Karlsson R, Garcia-Argibay M, Lee D, Wang R, Bjerkeset O, Stordal E, Bäckman J, Salum GA, Zai CC, Kennedy JL, Zai G, Tiwari AK, Heilmann-Heimbach S, Schmidt B, Kaprio J, Kennedy MM, Boden J, Havdahl A, Middeldorp CM, Lopes FL, Akula N, McMahon FJ, Binder EB, Fehm L, Ströhle A, Castelao E, Tiemeier H, Stein DJ, Whiteman D, Olsen C, Fuller Z, Wang X, Wray NR, Byrne EM, Lewis G, Timpson NJ, Davis LK, Hickie IB, Gillespie NA, Milani L, Schumacher J, Woldbye DP, Forstner AJ, Nöthen MM, Hovatta I, Horwood J, Copeland WE, Maes HH, McIntosh AM, Andreassen OA, Zwart JA, Mors O, Børglum AD, Mortensen PB, Ask H, Reichborn-Kjennerud T, Najman JM, Stein MB, Gelernter J, Milaneschi Y, Penninx BW, Boomsma DI, Maron E, Erhardt-Lehmann A, Rück C, Kircher TT, Melzig CA, Alpers GW, Arolt V, Domschke K, Smoller JW, Preisig M, Martin NG, Lupton MK, Luik AI, Reif A, Grabe HJ, Larsson H, Magnusson PK, Oldehinkel AJ, Hartman CA, Breen G, Docherty AR, Coon H, Conrad R, Lehto K, Veterans Affairs Million Veteran Program, FinnGen, 23andMe Research Team, Deckert J, Eley TC, Mattheisen M, Hettema JM

Nat Genet · 2026 Feb · PMID 41634414 · Full text

The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder and phobias) are highly prevalent, often onset early and cause substantial global disability. Although distinct in their clinical p... The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder and phobias) are highly prevalent, often onset early and cause substantial global disability. Although distinct in their clinical presentations, they probably represent differential expressions of a dysregulated threat-response system. Here, we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 out of the 58 associations replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism implicated in ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.

Fast and flexible joint fine-mapping of multiple traits via the Sum of Single Effects model.

Zou Y, Carbonetto P, Xie D … +2 more , Wang G, Stephens M

Nat Genet · 2026 Feb · PMID 41634413 · Full text

We introduce mvSuSiE, a multitrait fine-mapping method, to identify putative causal variants from genetic association data (individual-level or summary). mvSuSiE learns patterns of shared genetic effects from data, and e... We introduce mvSuSiE, a multitrait fine-mapping method, to identify putative causal variants from genetic association data (individual-level or summary). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal single nucleotide polymorphisms (SNPs). Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multitrait methods, and uniformly improves over single-trait fine-mapping (Sum of Single Effects) performed separately for each trait. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing traits and modeling heterogeneous effect-sharing patterns, we identified a substantially larger number of causal SNPs (>3,000) than single-trait fine-mapping and achieved narrower credible sets. mvSuSiE also more comprehensively characterized how genetic variants affect blood cell traits; 68% of causal SNPs showed significant effects across more than one blood cell type.

Single-nucleus DNA sequencing delves into the varied genomic evolution of pancreatic cancer.

Nat Genet · 2026 Feb · PMID 41629674 · Publisher ↗

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Improved polygenic risk prediction models for breast cancer subtypes in women of African ancestry.

Li JL, Zhang H, Wang X … +52 more , Jia G, McClellan JC, Guo W, Sun Y, Fiorica PN, Ambs S, Barnard ME, Chen Y, Garcia-Closas M, Gu J, Hu JJ, John EM, Nathanson KL, Nemesure B, Pal T, Shu XO, Press MF, Sanderson M, Sandler DP, Troester MA, Yao S, Long J, Ahearn TU, Brewster AM, Falusi A, Kraft P, Hennis AJM, Makumbi T, Mapoko BSE, O'Brien KM, Ojengbede O, Olshan AF, Reid S, Zirpoli G, Cai Q, Butler EN, Huang M, Obafunwa J, Weinberg CR, Ambrosone C, Ping J, Tao R, Li B, Guo X, Gao G, Conti DV, Chatterjee N, Palmer JR, Olopade OI, Zheng W, Haiman CA, Huo D

Nat Genet · 2026 Mar · PMID 41629673 · Full text

Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models... Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models for overall BC, estrogen receptor (ER)-positive, ER-negative and triple-negative BC (TNBC) in African-ancestry women using data from the African Ancestry Breast Cancer Genetics consortium (17,391 cases and 18,800 controls). We applied several PRS methods and integrated information across ancestries and BC subtypes. The best models for overall, ER-positive, ER-negative and TNBC showed an area under the receiving operating curve of 0.612, 0.621, 0.611 and 0.639, respectively, and maintained predictive accuracy in external validation studies with area under the receiving operating curves of 0.612, 0.640, 0.605 and 0.652. We further introduce a parsimonious 162-variant PRS for TNBC with comparable accuracy (0.626). These findings demonstrate markedly improved PRS accuracy for BC risk prediction in African-ancestry women. Using these PRS models for screening will help promote more equitable cancer prevention efforts.

Mutational scanning reveals oncogenic CTNNB1 mutations have diverse effects on signaling.

Krishna A, Meynert A, Dolt KS … +24 more , Kelder M, Mesropian A, Ewing A, Brouwers C, Claassens JW, Linssen MM, Sheraz S, Taylor GC, Gautier P, Ferrer-Vaquer A, Grimes G, Becher H, Silk R, Gris-Oliver A, Pinyol R, Semple CA, Kendall TJ, Bird TG, Hadjantonakis AK, Marsh JA, Llovet JM, Hohenstein P, Wood AJ, Ozdemir DD

Nat Genet · 2026 Feb · PMID 41629672 · Full text

CTNNB1, the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signaling pathway, typically through missense mutations within a degron hotspot motif in exon 3. Here, we com... CTNNB1, the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signaling pathway, typically through missense mutations within a degron hotspot motif in exon 3. Here, we combine saturation genome editing with a fluorescent reporter assay to quantify signaling phenotypes for all 342 possible missense mutations in the mutation hotspot. Our data define the genetic requirements for β-catenin degron function, refine the consensus motif for substrate recognition by β-TRCP and reveal diverse levels of signal activation among known driver mutations. Tumorigenesis in different human tissues involves selection for CTNNB1 mutations spanning distinct ranges of predicted activity. In hepatocellular carcinoma, mutation effect scores distinguish two tumor subclasses with different levels of β-catenin signaling, and weaker mutations predict greater immune cell infiltration in the tumor microenvironment. Our work provides a resource to understand mutational diversity within a pan-cancer mutation hotspot, with potential implications for targeted therapy.

Written in our genes, epigenetically edited by infection.

Barreiro LB, Mhlanga MM

Nat Genet · 2026 Feb · PMID 41593235 · Publisher ↗

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Genetics and environment distinctively shape the human immune cell epigenome.

Wang W, Hariharan M, Ding W … +42 more , Bartlett A, Barragan C, Castanon R, Wang R, Rothenberg V, Song H, Nery JR, Aldridge A, Altshul J, Kenworthy M, Liu H, Tian W, Zhou J, Zeng Q, Chen H, Wei B, Gündüz IB, Norell T, Broderick TJ, McClain MT, Satterwhite LL, Burke TW, Petzold EA, Shen X, Woods CW, Fowler VG, Ruffin F, Panuwet P, Barr DB, Beare JL, Smith AK, Spurbeck RR, Vangeti S, Ramos I, Nudelman G, Sealfon SC, Castellino F, Walley AM, Evans T, Müller F, Greenleaf WJ, Ecker JR

Nat Genet · 2026 Feb · PMID 41593234 · Full text

The epigenome of human immune cells is shaped by both genetics and environmental factors, yet the relative contributions of these influences remain incompletely characterized. Here we use single-nucleus methylation seque... The epigenome of human immune cells is shaped by both genetics and environmental factors, yet the relative contributions of these influences remain incompletely characterized. Here we use single-nucleus methylation sequencing and assay for transposase-accessible chromatin using sequencing (ATAC-seq) to systematically explore how pathogen and chemical exposures, along with genetic variation, are associated with changes in the immune cell epigenome. Distinct exposure-associated differentially methylated regions (eDMRs) and differentially accessible regions were identified, and a significant correlation between these two modalities was observed. Additionally, genotype-associated DMRs (gDMRs) were detected, indicating that eDMRs are enriched in regulatory regions, whereas gDMRs are preferentially located within gene body marks. Disease-associated single-nucleotide polymorphisms were frequently colocalized with methylation quantitative trait loci, providing cell-type-specific insights into the genetic basis of diseases. These findings highlight the complex interplay between genetic and environmental factors in shaping the immune cell epigenome and advance understanding of immune cell regulation in health and disease.

Reply to: a quantitative trait locus for reduced microglial APOE expression associates with reduced cerebral amyloid angiopathy.

Shade LMP, Qiao Q, Katsumata Y … +6 more , Mukherjee S, Broome JG, Johnson LA, Ebbert MTW, Nelson PT, Fardo DW

Nat Genet · 2026 Feb · PMID 41588233 · Full text

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A quantitative trait locus for reduced microglial APOE expression associates with reduced cerebral amyloid angiopathy.

Belloy ME, Graff-Radford J, Greicius MD

Nat Genet · 2026 Feb · PMID 41588232 · Publisher ↗

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Single-cell atlas of the transcriptome and chromatin accessibility in the human retina.

Li J, Wang J, Ibarra IL … +23 more , Cheng X, Luecken MD, Lu J, Monavarfeshani A, Yan W, Zheng Y, Zuo Z, Colborn SLZ, Cortez BS, Owen LA, Wick B, Bao X, Choi J, Haeussler M, Tran NM, Shekhar K, Sanes JR, Stout JT, Chen S, Li Y, DeAngelis MM, Theis FJ, Chen R

Nat Genet · 2026 Feb · PMID 41578023 · Full text

Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here we present an integrated dual-modal reference atlas of the most accessible portion of the mammalian ce... Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here we present an integrated dual-modal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 3.9 million cells from 125 donors of diverse ancestral backgrounds, including 8 published studies and 2.7 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) with more than 130 cell types identified. We annotated each cluster, identified marker genes and characterized cis-regulatory elements and gene regulatory networks. Our analysis uncovered differences in transcriptome, chromatin and gene regulatory networks across cell types. We modeled changes in gene expression and chromatin accessibility across age, ancestry and tissue region. This integrated atlas enhanced the fine-mapping of genome-wide association study and expression quantitative trait loci variants. Accessible through interactive browsers, this multimodal multidonor and multilab HRCA can facilitate a better understanding of retinal function and pathology.

Aberrant cellular communities underlying disease heterogeneity in chronic obstructive pulmonary disease.

Zhang Y, Wei H, Nouws J … +29 more , Jiang W, Brewster RM, Nguyen JP, Liang S, Pass SM, Wang W, Collin F, Oill AT, Kim SH, Siller SS, Liu J, Zhao AY, Hansbro P, Dela Cruz C, Britto C, Gomez J, Cloonan SM, Herzog EL, Lam TT, Banovich NE, Raredon MSB, Zhang X, Mangiola S, Homer RJ, Kaminski N, McDonough J, Polverino F, Yan X, Sauler M

Nat Genet · 2026 Feb · PMID 41578022 · Full text

Chronic obstructive pulmonary disease (COPD) is clinically and molecularly heterogeneous. To investigate COPD heterogeneity, we profiled lung tissue by single-nucleus RNA sequencing from 141 study participants (1,516,727... Chronic obstructive pulmonary disease (COPD) is clinically and molecularly heterogeneous. To investigate COPD heterogeneity, we profiled lung tissue by single-nucleus RNA sequencing from 141 study participants (1,516,727 nuclei) and identified shifts in cell composition and emergent cell states that correlated with lung function, emphysema and composite symptom scores. Epithelial regenerative states peaked in early COPD and declined thereafter, whereas inflamed nonimmune cells and profibrotic/remodeling states, together with select immune populations, expanded with disease progression. Clustering study participants by the proportion of pathologic cells coupled with spatial transcriptomics identified distinct patterns of cellular co-occurrence within spatially localized niches. Proteomic analyses identified plasma biomarkers of cell states and their impact on the extracellular matrix. Mediation and cell communication analyses revealed cell-autonomous and intercellular communication networks associated with disease. These data define the cellular landscape of COPD heterogeneity, revealing molecular drivers and biomarkers that could inform therapeutic strategies.

Genomic evolution of pancreatic cancer at single-cell resolution.

Zhang H, Sashittal P, Karnoub ER … +16 more , Jakatdar A, Umeda S, Hong J, Noronha AM, Cardenas A, Erakky A, McIntyre CA, Hayashi A, Lecomte N, Hilmi M, Park W, Pang N, O'Reilly EM, Wei AC, Raphael BJ, Iacobuzio-Donahue CA

Nat Genet · 2026 Feb · PMID 41571832 · Full text

Most evolutionary studies on pancreatic cancer rely on bulk sequencing, yet clonal evolution happens at the single-cell level. We used single-nucleus DNA sequencing to study 137,491 single nuclei from 24 pancreatic neopl... Most evolutionary studies on pancreatic cancer rely on bulk sequencing, yet clonal evolution happens at the single-cell level. We used single-nucleus DNA sequencing to study 137,491 single nuclei from 24 pancreatic neoplasms reflecting various clinical scenarios. We found higher frequencies of somatic alterations to driver genes that bulk studies indicate; many manifest as copy number alterations and account for the majority of spatial heterogeneity. In pancreatic cancers with canonical KRAS oncogenic mutations, we found likely varied dependence on the genotype that may signify differential response to KRAS inhibition. In pancreatic cancers with germline heterozygous BRCA2 mutations, we discovered varied mechanisms and timing of inactivation of the wild-type allele that sculpted differential evolutionary trajectories. Inactivation of tumor-intrinsic response to transforming growth factor-β happens through various mechanisms, takes place after oncogenesis and coincides with invasion and metastasis, reflecting increasing selective pressure for the phenotype later in pancreatic ductal adenocarcinoma development.

Central role of glycosylation processes in human genetic susceptibility to SARS-CoV-2 infections with Omicron variants.

Geller F, Wu X, Lammi V … +42 more , Abner E, Valliere JT, Nastou K, Burns A, Rasmussen M, Andersson NW, Quinn L, DBDS Genomic Consortium, Aagaard B, Banasik K, Bliddal S, Boding L, Brunak S, Brøns N, Bybjerg-Grauholm J, Christoffersen LAN, Didriksen M, Dinh KM, Erikstrup C, Feldt-Rasmussen U, Grønbæk K, Kaspersen KA, Mikkelsen C, Nielsen CH, Nielsen HS, Nielsen SD, Nissen J, Sequeros CB, Tommerup N, Ullum H, Estonian Biobank Research Team, FinnGen, Spiliopoulos L, Bager P, Hviid A, Sørensen E, Pedersen OB, Lane JM, Lassaunière R, Ollila HM, Ostrowski SR, Feenstra B

Nat Genet · 2026 Feb · PMID 41571831 · Full text

The host genetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have previously been studied based on cases from the earlier waves of the pandemic in 2020 and 2021, identifying 51 genomic loci associate... The host genetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have previously been studied based on cases from the earlier waves of the pandemic in 2020 and 2021, identifying 51 genomic loci associated with infection and/or severity. SARS-CoV-2 has shown rapid sequence evolution, increasing transmissibility, particularly for Omicron variants, which raises the question of whether this affected the host genetic factors. We performed a genome-wide association study of SARS-CoV-2 infection with Omicron variants, including more than 150,000 cases from four cohorts. We identified 13 genome-wide significant loci, of which only five were previously described as associated with SARS-CoV-2 infection. The strongest signal was a single nucleotide polymorphism in an intron of ST6GAL1, a gene affecting immune development and function, connected to three other associated loci (harboring MUC1, MUC5AC and MUC16) through O-glycan biosynthesis. Our study provides robust evidence for individual genetic variation related to glycosylation, translating into susceptibility to SARS-CoV-2 infections with Omicron variants.

Multi-trait and multi-ancestry genetic analysis of comorbid lung diseases and traits improves genetic discovery and polygenic risk prediction.

He Y, Lu W, Jee YH … +15 more , Shih MY, Wang Y, Tsuo K, Qian DC, Diao JA, Huang H, Patel CJ, Byun J, Pasaniuc B, Atkinson EG, Amos CI, Feng YA, Moll M, Cho MH, Martin AR

Nat Genet · 2026 Feb · PMID 41565855 · Full text

While respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma share many risk factors, most studies investigate them in isolation and in predominantly European-ancestry populations. Here, we... While respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma share many risk factors, most studies investigate them in isolation and in predominantly European-ancestry populations. Here, we conducted the most powerful multi-trait and multi-ancestry genetic analysis of respiratory diseases and auxiliary traits to date, identifying 25 new loci associated with lung function in individuals of East Asian ancestry. Using these results, we developed PRSxtra (cross-trait and cross-ancestry), a multi-trait and multi-ancestry polygenic risk score (PRS) approach that leverages shared components of heritable risk via pleiotropic effects. PRSxtra significantly improved the prediction of asthma, COPD and lung cancer compared to trait- and ancestry-matched PRSs in a multi-ancestry cohort from the All of Us Research Program, especially in diverse populations. Our results present a new framework for multi-trait and multi-ancestry studies of respiratory diseases to improve genetic discovery and polygenic prediction.

Impact and correction of segmentation errors in spatial transcriptomics.

Mitchel J, Gao T, Petukhov V … +2 more , Cole E, Kharchenko PV

Nat Genet · 2026 Feb · PMID 41559218 · Publisher ↗

Spatial transcriptomics aims to elucidate how cells coordinate within tissues by connecting cellular states to their native microenvironments. Imaging-based assays are especially promising, capturing molecular and cellul... Spatial transcriptomics aims to elucidate how cells coordinate within tissues by connecting cellular states to their native microenvironments. Imaging-based assays are especially promising, capturing molecular and cellular features at subcellular resolution in three dimensions. Interpretation of such data, however, hinges on accurate cell segmentation. Assigning individual molecules to the correct cells remains challenging. Here we re-analyze data from multiple tissues and platforms to find that segmentation errors currently confound most downstream analysis of cellular state, including differential expression, neighbor influence and ligand-receptor interactions. The extent to which misassigned molecules impact the results can be striking, frequently dominating the results. Thus, we show that matrix factorization of local molecular neighborhoods can effectively identify and isolate such molecular admixtures, thereby reducing their impact on downstream analyses, in a manner analogous to doublet filtering in single-cell RNA sequencing. As the applications of spatial transcriptomics assays become more widespread, accounting for segmentation errors will be important for resolving molecular mechanisms of tissue biology.

Engineering AI co-scientists for statistical genetics applications.

Zhao B

Nat Genet · 2026 Feb · PMID 41559217 · Publisher ↗

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The polygenic, omnigenic and stratagenic models of complex disease risk.

García-González J, O'Reilly PF

Nat Genet · 2026 Feb · PMID 41559216 · Publisher ↗

A key goal of human genetics research is to understand how the effects of genetic variants combine to produce the risk of complex disease. Here we discuss and contrast three conceptual models developed to explain how mul... A key goal of human genetics research is to understand how the effects of genetic variants combine to produce the risk of complex disease. Here we discuss and contrast three conceptual models developed to explain how multigenic risk is generated. The polygenic model, derived from the century-old infinitesimal model, has been the dominant framework for understanding the genetic inheritance of complex traits. More recently, two mechanistic models have been proposed: the omnigenic model, which hypothesizes core genes with direct effects on disease and peripheral genes with regulatory, indirect effects, and what we call the 'stratagenic' model, in which the genetic risk of disease is stratified across genomic pathways of functional relevance. There are key differences in the implications of these models for research, drug development and precision medicine. Therefore, it is essential to determine which model is most accurate for each disease or whether a single model is broadly optimal across complex diseases.

Exploring and visualizing stratified GWAS results with PheWeb2.

Bellavance J, Xiao H, Chang L … +7 more , Kazemi M, Wickramasinghe S, Mayhew AJ, Raina P, VandeHaar P, Taliun D, Gagliano Taliun SA

Nat Genet · 2026 Feb · PMID 41555088 · Publisher ↗

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