Search

Indonesian cattle are unique due to their history of admixture involving both zebu and banteng. Here, Wang et al. identify ~3.5 million novel introgressed SNP variants and provide a genomic map of banteng introgression within and across many cattle breeds, each with unique introgression histories.

Researchers use a chimeric approach to reveal the first near-atomic resolution structures the yellow fever virion, showing key differences between vaccine and virulent strains that affect how antibodies recognise and neutralise the virus.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

Transcription factors (TFs) represent an emerging class of therapeutic targets in oncology. Here, the authors develop Epiregulon, a computational method that constructs gene regulatory networks from ChIP-seq, ATAC-seq and RNA-seq data for accurate prediction of TF activity at the single-cell level, thereby facilitating the discovery of therapeutics targeting TFs.

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.

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.

Here, the authors sample air and surfaces in hospital rooms of COVID-19 patients, detect SARS-CoV-2 RNA in air samples of two of three tested airborne infection isolation rooms, and find surface contamination in 66.7% of tested rooms during the first week of illness and 20% beyond the first week of illness.

The largest harmonized proteomic dataset of plasma, serum and cerebrospinal fluid samples across major neurodegenerative diseases reveals both disease-specific and transdiagnostic proteomic signatures, including a robust plasma profile associated with the APOEε4 genotype.

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.

The advantage of living in cities compared with rural areas with respect to height and BMI in children and adolescents has generally become smaller globally from 1990 to 2020, except in sub-Saharan Africa.

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.

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.

Multi-ancestry fine-mapping of breast cancer susceptibility regions identifies candidate causal variants and prioritizes likely effector genes supported by functional genomic evidence.

The cell nucleus coordinates diverse functions. Here, the authors utilise multiplexed super-resolution imaging to study how nuclear proteins are distributed relative to each other from the micro to the nanoscale, providing an approach to understand the organisation of different nuclear environments.

A multi-ancestry genome-wide association study meta-analysis, combined with transcriptome- and methylome-wide association analyses, identifies risk loci associated with colorectal cancer. Credible effector genes and their target tissues are also highlighted, showing that over a third probably act outside the colonic mucosa.

Despite being an important driver of a subset of medulloblastomas, efforts to therapeutically target Sonic Hedgehog (SHH) signaling, such as with the use of Smoothened (SMO) inhibitors, have had limited success. Here, the authors find that SHH medulloblastomas are sensitive to netrin-1 inhibition and investigate netrin-1 as a mechanism of resistance to SMO inhibition.

Genome-wide association analysis of gout and urate identifies 148 new loci, implicating biological pathways and prioritizing candidate genes involved in inflammatory processes.

The electronic structure of benzene has been a test bed for competing theories along the years. Here the authors show via quantum chemistry calculations that the wavefunction of benzene can be partitioned into tiles which show that the two electron spins exhibit staggered Kekulé structures.

Despite being essential to organic chemistry, the curly arrow notation of reaction mechanisms has been treated with suspicion due to its unclear connection with quantum mechanics. Here, the authors show that analysis of wavefunction 'tiles' along a reaction coordinate reveals the electron motion depicted by curly arrows.

Here, Chen et. al. characterize the relationship between the gut microbiota and plasma metabolite changes in the context of ST-elevation myocardial infarction (STEMI), unveiling a role of butyrate-producing bacteria and their ketogenesis in post-STEMI cardiac repair, a finding validated in nonhuman primate and mouse models. They show that butyrate supplementation reduces myocardial infarction severity in mice, underscoring the significance of butyrate-producing bacteria and beta-hydroxybutyrate in improving post-MI outcomes.

The decades-old limit on how long human embryos can be grown in culture is under debate. A new road map outlines how to extend the length of culture responsibly.

Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.

Flexible electronics require that all parts can be printed on plastic substrates, but finding materials that can act as high-capacitance dielectrics is a priority. An emerging class of polymer electrolytes, ion gels, can do the job—with high capacitance and at low voltage.

Binary stars with orbital periods of less than a day show magnetic activity beyond the saturation limit of single stars. This enhanced activity is probably driven by a large-scale α–ω dynamo during common-envelope evolution.

Lattice mismatches are a difficult obstacle in the formation of core-shell heterostructures. Here, the authors develop a strategy to overcome the lattice mismatch and grow α-phase lead halide perovskites onto β-phase lanthanide-doped nanoparticles.