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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.

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

The study combines bulk, single-cell, and spatial transcriptomics of human carotid plaques. It identifies immune– stromal cell diversity, spatial macrophage gradients, smooth muscle cell heterogeneity, and morphology-defined plaque subtypes.

A genome-wide association study meta-analysis combined with multiomics data of osteoarthritis identifies 700 effector genes as well as biological processes with a convergent involvement of multiple effector genes; 10% of these genes express the target of approved drugs.

Glycine sensing in the dorsal vagal complex (DVC) regulates hepatic glucose production in rodents. Here the authors show that pharmacological and molecular inhibition of glycine reuptake in the DVC potentiates NMDA receptors, and improves metabolic homeostasis in animal models of obesity and diabetes.

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.

Lee et al. use an aggregation-prone CLN4 mutant that causes lysosomal damage in neurons and show that in non-neurons, the ubiquitin ligase CHIP prevents CLN4-dependent lysotoxicity via microautophagy.

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.

Yin et al. harmonized 1,091 fMRI scans across five imaging cohorts to map developmental trajectories of brain functional connectivity in early childhood, revealing early brain development and its links to cognitive abilities.

The brain has a central role in the regulation of organismal energy homeostasis. Here the authors show that neurons in the mediobasal hypothalamus respond to fatty acids by generating neuronal signals, relayed to the liver viavagal nerves that mediate secretion of very-low-density lipoproteins.

Detecting dilute airborne biomarkers is important in healthcare but is limited by the low sensitivity of current gas sensors. A portable, low-cost device is introduced that uses water condensation to enrich airborne biomarkers into a concentrated liquid, enabling existing liquid sensors to detect biomarkers with high sensitivity and broad accessibility.

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

Somatic mutations accumulate with age; however, the role they have in cardiac aging is unclear. Here Choudhury et al. describe the somatic mutation landscape of human heart muscle cells by single-cell whole-genome sequencing and report mutational signatures indicative of increased oxidative DNA damage and failed repair.

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.

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.

Nanosized chemical heterogeneities modulate andesitic magma viscosity at early stages of nano-crystallization, according to viscosity models that account for variations in transition metal content

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.

It is critical to understand different drivers of regional hydroclimate change and to reduce uncertainty in future projections. This study disentangles the effects of CO₂ physiology and deforestation on projected precipitation, surface relative humidity and air temperature in Amazonia using multiple Coupled Model Intercomparison Project Phase 6 experiments.

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.

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.

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.

The authors summarize the data produced by phase III of the Encyclopedia of DNA Elements (ENCODE) project, a resource for better understanding of the human and mouse genomes.

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.

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.

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.

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.

Machine learning can be used to identify subtypes of psychiatric disease. Here the authors identified two neurostructural subgroups in schizophrenia, each showing reproducibility and generalizability across different collection locations and illness stages, using the SuStain algorithm.

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.

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.

Ferumoxytol (Fer) is an FDA-approved iron oxide formulation that disrupts caries-causing biofilms with high specificity but cannot interfere with enamel acid demineralization. Here, Fer is combined with stannous fluoride (SnF2), resulting in enhanced stability of SnF2 and inhibition of both biofilm accumulation and enamel damage more effectively than either alone.

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.

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.

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.

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.

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.

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.

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.

Imaging in the second near-infrared window has attracted attention due to superior penetration depth and low signal interference. Here, the authors describe a new organic nano fluorophore with high quantum yield and demonstrate its use for in vivo imaging.

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.

An adversarial domain translation framework is presented for scalable integration of single-cell atlases across samples, technical platforms, data modalities and species.

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.

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.

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 goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

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.

Human disease mutations affect protein–protein interfaces in a three-dimensional structurally resolved interaction network. Predicted oncoPPIs in cancer correlate with survival and drug sensitivity, and affect growth in vitro, supporting their relevance to disease pathogenesis.

The Human Muscle Ageing Cell Atlas provides a series of integrated cellular and molecular explanations for sarcopenia and frailty development in advanced ages.

Jones et al. examine the generalizability of the valence–dominance model of social judgements of faces in 41 countries across 11 world regions. They find evidence of both generalizability and variation, depending on the analytical method.

AI reduces building energy and emissions in design/construction, equipment, occupancy, and control/operation. By accelerating high-efficiency and net-zero buildings, AI could cut energy and emissions by 40-90% by 2050 combined with adequate policies.