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The APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer’s disease, but it is not deterministic. Here, the authors show that common genetic variation changes how APOE-ε4 influences cognition.

Plasma p-tau217 tests used to develop clocks that predict when cognitively unimpaired individuals would develop symptoms of Alzheimerʼs disease.

Hepatic glycogenolysis is essential for protein glycosylation and rhythmic secretion by the liver. Disruptions to hepatic glycogenolysis, caused by congenital diseases or physiological factors such as obesity, caloric restriction and changes to meal timing, alter hepatic protein secretion.

The lowest-frequency gravitational wave background may be shaped by supermassive black hole binaries that scatter nearby stars or dark matter. In this case, the NANOGrav 15-year dataset favours dense galactic centres with 10⁶ solar masses per cubic parsec.

Humanity’s Last Exam, a multi-modal benchmark at the frontier of human knowledge, is designed to be an expert-level closed-ended academic benchmark with broad subject coverage.

AvrPm4 is a chimeric powdery mildew effector that is recognized by the wheat kinase fusion resistance protein Pm4. The pathogen can evade Pm4 recognition by expressing the suppressor SvrPm4, an RNase-like effector with multiple roles.

Stepp and colleagues present hybrid-EDA, an event-driven acquisition (EDA) that enables gentle investigation of rare mitochondrial events. This approach combines continuous, low-phototoxicity phase-contrast surveillance with event-triggered fluorescence imaging, powered by dynamics-aware machine-learning event detection.

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.

A group of microbiome researchers discuss some of the challenges in developing a new generation of microbiome therapies.

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.

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.

Here the authors map the dynamics of human NK cell residency and recirculation, showing that CD56^bright NK cells transiently occupy tissues and recirculate via lymphatics, whereas CD56^dim NK cells remain vascular except during inflammation.

cfDNA fragmentomics is a potential clinically applicable method for identifying cancer. Here, the authors assess fragmentomics analysis methods and their application to commercial targeted sequencing panels.

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.

WGS data were used from 347,630 individuals with European ancestry in the UK Biobank to obtain high-precision estimates of coding and non-coding rare variant heritability for 34 complex traits and diseases.

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.

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

Inventory data from more than 1 million trees across African, Amazonian and Southeast Asian tropical forests suggests that, despite their high diversity, just 1,053 species, representing a consistent ~2.2% of tropical tree species in each region, constitute half of Earth’s 800 billion tropical trees.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Food pantries are part of the emergency food network in the United States, but they are an understudied component of food access. The Pantry Accessibility Index and Individual Accessibility Index developed here allow measurement of the spatiotemporal availability of these services to the food insecure of south-central Indiana.

The affected cellular populations during Alzheimer’s disease progression remain understudied. Here the authors use a cohort of 84 donors, quantitative neuropathology and multimodal datasets from the BRAIN Initiative. Their pseudoprogression analysis revealed two disease phases.

Higgins et al. present an AI tool that uses patient data to personalise treatment for Helicobacter pylori, the leading agent of gastric cancer, demonstrating improved eradication rates over prescribed therapies in retrospective clinical analysis.

Data from a variety of sources—including satellite, climate and soil data, as well as field-collected information on plant traits—are pooled and analysed to map the functional diversity of tropical forest canopies globally.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

An investigation using various methods reports an association between adeno-associated virus 2 and paediatric hepatitis of unknown aetiology.

The nature of the microbial reactions occurring during cap rock formation is poorly understood. Here the authors find that sulfur and carbon isotope signatures indicate sulfate-dependent anaerobic oxidation of methane (AOM) as a primary driver of cap rock carbonate formation.

How changes in brain blood vessels lead to a chronic reduction in blood flow and, consequently, to vascular dementia is poorly understood. Here, the authors show that venous endothelial dysfunction driven by EPAS1 promotes abnormal vascular remodeling and contributes to cognitive decline.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Wood density is a key control on tree biomass, and understanding its spatial variation improves estimates of forest carbon stock. Sullivan et al. measure >900 forest plots to quantify wood density and produce high resolution maps of its variation across South American tropical forests.

The authors present BARASA, an approach to assign backbone triple resonance spectra of proteins that augments traditional approaches with a Bayesian statistical analysis of the observed chemical shifts. The algorithm employs a simulated annealing engine to establish a consensus set of resonance assignments and is tested against systems ranging in size to over 450 amino acids including examples of intrinsically disordered proteins.

Here, the authors describe the global distribution of crAssphage, its presence in Old-World and New-World primates, and its association with gut bacterial communities and dietary factors, providing insights into the origin, evolution and epidemiology of human gut crAssphage.

Early drivers of T2D include ectopic fat accumulation that impairs insulin sensitivity. Here, the authors show that GLP1/GCGR dual agonism provides multimodal benefits in obese male mice by reducing liver fat and improving insulin sensitivity resulting in endogenous β-cell recovery.