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Multi-ancestry GWAS meta-analysis identifies risk loci for severe nausea and vomiting of pregnancy. Downstream analyses explore maternal and fetal contributions of these loci and their temporal effects.

When 100 social and behavioural science claims were examined, 34% of reanalyses closely matched the original results, with 74% reaching the same conclusion, revealing limited robustness of single-path analyses and the need to address analytical uncertainty.

Ongoing chikungunya virus replication leads to the accumulation of inflammatory macrophages and CD4⁺ T cells in joint-associated tissues. Inhibition of chikungunya virus replication during chronic disease reduced viral RNA and joint inflammation in mice.

Adaptive optical vision Fourier transformer (AOViFT) is a machine learning-based framework for accurately inferring aberrations and restoring diffraction-limited performance in diverse biological specimens.

cellSTAAR advances noncoding rare variant association analysis by integrating single-cell genomics data.

Using well-calibrated statistical methods the authors jointly analyze Undiagnosed Diseases Network genomes, identifying known and novel disease genes. Software is publicly available to support future cross-cohort rare disease discovery efforts.

Analysis of soundscape data from 139 globally distributed sites reveals that sounds of biological origin exhibit predictable rhythms depending on location and season, whereas sounds of anthropogenic origin are less predictable. Comparisons between paired urban–rural sites show that urban green spaces are noisier and dominated by sounds of technological origin.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

Whole-genome and transcriptome analysis of 1,364 cases of breast cancer from South Korea broadens our understanding of breast cancer biology and reveals genomic features that connect tumour biology with treatment responses and clinical outcomes.

MultiSTAAR provides a general and flexible statistical framework for functionally informed multi-trait rare variant analysis of biobank-scale sequencing studies by jointly analyzing multiple traits and incorporating annotation information.

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.

An integrated analysis of de novo and inherited coding variants in 42,607 individuals with autism spectrum disorder identifies 60 risk genes of which five have not previously been associated with neurodevelopmental disorders.

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.

Here, the authors perform large trans-ancestry fine-mapping analyses identifying large numbers of association signals and putative target genes for colorectal cancer risk, advancing our understanding of the genetic and biological basis of this cancer.

Wastewater surveillance can help in pandemic or outbreak response. Here, the authors report an unsupervised learning approach to detect emerging SARS-CoV-2 variants from rural and urban wastewater showing it achieves earlier detection than existing methods and detects new variants without clinical testing data.

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.

Complex structural variations and rearrangements in cancer are identified using long-read sequencing.

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.

Authors perform an analysis of the patient data and risk factors to evaluate unfavorable outcomes and adverse events in adults with pulmonary tuberculosis treated with a 4-month rifapentine based regimen. Low rifapentine exposure was the most clinically significant risk factor for treatment failure and tuberculosis relapse.

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

GIANT, a genetically informed brain atlas, integrates genetic heritability with neuroanatomy. It shows strong neuroanatomical validity and surpasses traditional atlases in discovery power for brain imaging genomics.

Royal jelly is the queen-maker for the honey bee that also has effects on longevity, fertility, and regeneration in mammals. Here the authors provide evidence that its major protein component Royalactin, and the mammalian structural analog Regina, maintain pluripotency in mouse ESCs by activating a ground-state pluripotency-like gene network.

Here, the authors develop the Gut Microbiome Wellness Index 2 (GMWI2), an enhanced version of the original GMWI prototype, designed as a disease-agnostic health status indicator based on gut microbiome taxonomic profiles.

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.

In this Stage 2 Registered Report, Buchanan et al. show evidence confirming the phenomenon of semantic priming across speakers of 19 diverse languages.

Genome-wide analyses identify common variants associated with 11 distinct neuropathology endophenotypes, providing insights into the mechanisms underlying the genetic risk of Alzheimer’s disease and related dementias.

Polygenic risk scores can help identify individuals at higher risk of type 2 diabetes. Here, the authors characterise a multi-ancestry score across nearly 900,000 people, showing that its predictive value depends on demographic and clinical context and extends to related traits and complications.

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.

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.

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.

Together with a companion paper, the generation of a transcriptomic atlas for the mouse lemur and analyses of example cell types establish this animal as a molecularly tractable primate model organism.

Together with an accompanying paper presenting a transcriptomic atlas of the mouse lemur, interrogation of the atlas provides a rich body of data to support the use of the organism as a model for primate biology and health.

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.

Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.

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.

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.

Here, the authors leverage whole-genome sequencing from >88,000 diverse individuals to uncover 18 BMI-related genetic signals, including novel variants in participants of African genetic ancestry, highlighting the value of diversity in genetic discovery.

Targeted delivery to the lower regions of the lung is necessary for the treatment of parenchymal lung injury and disease but is challenging. Here, the authors develop an mRNA delivery platform to treat acute lung injury in mice and demonstrate that it can reach the lower regions of the lung.

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.

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.

Most genetic studies have been done on European cohorts, which affects the efficacy of polygenic risk scores in non-European populations. Here, the authors demonstrate that a colorectal cancer PRS including Asian and European ancestries has improved performance over the European-centric PRS across racial and ethnic groups.

The process of protein crystallization is poorly understood and difficult to program through the primary sequence. Here the authors develop a computational approach to designing three-dimensional protein crystals with prespecified lattice architectures with high accuracy.

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.

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.

Using data from a single time point, passenger-approximated clonal expansion rate (PACER) estimates the fitness of common driver mutations that lead to clonal haematopoiesis and identifies TCL1A activation as a mediator of clonal expansion.

Pooling participant-level genetic data into a single analysis can result in variance stratification, reducing statistical performance. Here, the authors develop variant-specific inflation factors to assess variance stratification and apply this to pooled individual-level data from whole genome sequencing.

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.