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Analysis combining multiple global tree databases reveals that whether a location is invaded by non-native tree species depends on anthropogenic factors, but the severity of the invasion depends on the native species diversity.

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

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.

Climate change can alter when and how animals grow, breed, and migrate, but it is unclear whether this allows populations to persist. This global study shows that shifts in seasonal timing are key to helping vertebrate species maintain population growth under global warming.

Global Burden of Disease estimates show that between 1990 and 2023, the prevalence and burden of drug use disorders, inclusive of amphetamine, cannabis, cocaine and opioid use, have been increasing in high-income countries, particularly in the USA.

Chronic care manages long-term, progressive conditions, while acute care handles short-term ones. Here, authors show chronic conditions account for most of the global health burden, with 68% of DALYs and 93% of YLDs attributed to chronic care needs.

The 4D Nucleome Project demonstrates the use of genomic assays and computational methods to measure genome folding and then predict genomic structure from DNA sequence, facilitating the discovery of potential effects of genetic variants, including variants associated with disease, on genome structure and function.

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.

Through next-generation spectral analysis, scientists have uncovered an evolutionary path for Wolf–Rayet stars in metal-poor environments. Characterized by hard ionizing radiation, these stars challenge current assumptions about massive star evolution.

An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

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 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.

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 extreme flare has been seen from a supermassive black hole at redshift z = 2.6. First detected in 2018, it is 30 times brighter than similar events. The most likely cause is the shredding of a star of 30 solar masses or more.

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.

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.

Species’ traits and environmental conditions determine the abundance of tree species across the globe. Here, the authors find that dominant tree species are taller and have softer wood compared to rare species and that these trait differences are more strongly associated with temperature than water availability.

Analysing >1,700 inventory plots from the Amazon Tree Diversity Network, the authors show that the majority of Amazon tree species can occupy floodplains and that patterns of species turnover are closely linked to regional flood patterns.

Fresh basaltic glass preserved in a sample of volcanic breccia record a single eruptive event at the Alpha Ridge around 90 Ma, suggesting that parts of the ridge were emergent during the final stages of magmatism in the High Arctic Large Igneous Province, according to geochemical and geochronological analysis of the sample.

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.

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.

Genome-wide analysis in individuals of African ancestry identifies a nonsense variant in CD36 associated with increased risk of dilated cardiomyopathy (DCM), partly accounting for the higher incidence of DCM in African-ancestry populations.

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.

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.

A type Ia supernova shows the presence of helium-rich circumstellar material, as demonstrated by its spectral features, infrared emission and a radio counterpart, that probably originates from a single-degenerate system in which a white dwarf accretes material from a helium donor star.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

EchoNext, a deep learning model for electrocardiograms trained and validated in diverse health systems, successfully detects many forms of structural heart disease, supporting the potential of artificial intelligence to expand access to heart disease screening at scale.

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.

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.