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This study found higher RSV antibody levels were associated with lower RSV risk in children outside the hospital. An earlier rise in incidence and higher incidence rates were observed among children <5 years compared to older children and adults.

Lineage tracing in mice identifies a subpopulation of basal cells that express Tmprss2 and Nkx3 as the origin of ERG-driven prostate cancer. Upon expansion, these cells show an enrichment for STAT3 chromatin binding and elevated expression of KMT2A and DOT1L as dependencies for ERG oncogenicity.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

The authors introduce the Neurolipid Atlas, a dynamic resource for the community to gain insight into lipid alterations in neurodegenerative disease, and they leverage the platform to show how cholesterol alterations in astrocytes can dysregulate neuroinflammatory pathways in Alzheimer disease.

NIPBL perturbation activates long terminal repeat (LTR)-derived alternative promoters due to reorganization of chromatin’s hierarchical structure, leading to LTR co-option and oncogene activation in melanoma cell lines.

In an updated report on 70 laboratory-confirmed highly pathogenic avian influenza A H5N1 cases in the USA between March 2024 and May 2025, the absence of human-to-human transmission to date was confirmed, with no known mutations of resistance to neuroaminidase inhibitors.

A cross-ancestry meta-analysis of genome-wide association studies identifies association signals for stroke and its subtypes at 89 (61 new) independent loci, reveals putative causal genes, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as potential drug targets, and provides cross-ancestry integrative risk prediction.

In this Comment, the authors overview the latest deep learning models for predicting regulatory function from genomic sequence and highlight key topics going forward, including the trade-off between specialized and general models, multitasking across cell types, and training on genetic variation and diverse species.

Hematopoietic stem cells (HSCs) differentiate into multiple lineages, with such capacity impacted by aging. Here the authors identify Kit^lo HSCs as a functionally distinct population that exhibits distinct lymphoid-primed chromatin landscapes, which drive enhanced lymphoid reconstitution capacity, and is altered in aged hosts.

Whether multimorbidity accelerates brain Aβ deposition in humans remains largely unknown. Here, the authors demonstrate that higher self-reported multimorbidity burden predicts increased brain Aβ accumulation rates in the ADNI cohort.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Christina Leslie and colleagues report an integrative analysis of the enhancer landscape and gene expression dynamics during hematopoietic differentiation. They also develop a quantitative model to predict gene expression changes from DNA sequence content and the lineage history of active enhancers and suggest a new mechanistic role for PU.1 at transition peaks during B cell specification.

This flagship study from the European Solve-Rare Diseases Consortium presents a diagnostic framework including bioinformatic analysis of clinical, pedigree and genomic data coupled with expert panel review, leading to 500 new diagnoses in a cohort of 6,000 families with suspected rare diseases.

In this Viewpoint article, we asked four experts to share their thoughts on the implementation of artificial intelligence and machine learning techniques into cancer research and care, and how to separate the hope from the hype to overcome the challenges ahead.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

Analyses of genome and exome sequencing data identify rare coding and structural variants associated with atrial fibrillation and highlight genetic links between atrial fibrillation and cardiomyopathies.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

The authors show that terminally differentiated colonic T_reg cells are required for maintaining colonic health and, although these cells are major producers of this cytokine, IL-10 is dispensable for their suppressive function.

Multiancestry genome-wide association analyses identify new risk loci for stroke and stroke subtypes. Fine mapping and bioinformatics analyses of these risk loci point to mechanisms not previously implicated in stroke pathophysiology.

A retrospective analysis using PCR testing, viral enrichment-based sequencing and agnostic metagenomic sequencing finds an association between adeno-associated virus type 2 and paediatric hepatitis of unknown cause.

The slow maturation of human neurons is regulated by epigenetic modification in nascent neurons, mediated by EZH2, EHMT1, EHMT2 and DOT1L.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Obtaining a high-resolution contact map using current 3D genomics technologies can be challenging with small input cell numbers. Here, the authors develop ChromaFold, a deep learning model that predicts cell-type-specific 3D contact maps from single-cell chromatin accessibility data alone.

The RNA binding protein MUSASHI-2 (MSI2) is a potential therapeutic target for acute myeloid leukemia. Here the authors identify a small molecule inhibitor of MSI2 and characterize its effects in a murine leukemia model.

By learning to embed DNA k-mers and cells into a joint space, CellSpace improves single-cell ATAC-seq analysis in multiple tasks such as latent structure discovery, transcription factor activity inference and batch effect mitigation.

The efficiency of preclinical drug testing and characterization of cellular function can be improved through the use of optogenetic tools. Here Klimas et al. present and validate OptoDyCE, a fully automated system for all-optical high-throughput cardiac electrophysiology.

An international consortium reports the genomic sequence for ten Drosophila species, and compares them to two other previously published Drosophila species. These data are invaluable for drawing evolutionary conclusions across an entire phylogeny of species at once.

Trans-ancestry meta-analysis of estimated glomerular filtration rate (eGFR) from 1,046,070 individuals identifies 264 associated loci, providing a resource of molecular targets for translational research of chronic kidney disease.