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

Baked sediment, heat-shattered artefacts and introduced pyrite in a 400,000-year-old Palaeolithic occupation site in Suffolk, UK provide evidence of intentional fire-making, marking a pivotal moment in human development.

A comparison of alpha diversity (number of plant species) and dark diversity (species that are currently absent from a site despite being ecologically suitable) demonstrates the negative effects of regional-scale anthropogenic activity on plant diversity.

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.

Analysis of whole-genome sequences of 25,465 individuals of European ancestry shows that rare variants contribute substantially to the heritability of height and body mass index.

In the Tumor Profiler proof-of-concept observational study, a multiomics approach for profiling tumors from patients with melanoma was feasible, returning data within 4 weeks and informing treatment recommendations in 75% of cases.

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.

Head and neck squamous cell carcinoma (HNSCC) frequency and risk factors vary considerably across regions and ancestries. Here, the authors conduct a multi-ancestry genome-wide association study and fine mapping study of HNSCC subsites in cohorts from multiple continents, finding susceptibility and protective loci, gene-environment interactions, and gene variants related to immune response.

The molecular mechanisms underlying drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML) remain to be explored. Here, the use of bulk and single cell multi-omics and ex vivo drug profiling for 21 rrAML patients reveals mechanisms of resistance to the Bcl-2 inhibitor venetoclax and treatment vulnerabilities.

Reduced glomerular filtration rate (eGFR) is a hallmark of chronic kidney disease. Here, Pattaro et al. conduct a meta-analysis to discover several new loci associated with variation in eGFR and find that genes associated with eGFR loci often encode proteins potentially related to kidney development.

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.

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.

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.

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.

HistoPlexer, a deep learning model, generates multiplexed protein expression maps from H&E images, capturing tumour–immune cell interactions. It outperforms baselines, enhances immune subtyping and survival prediction and offers a cost-effective tool for precision oncology.

Sheehan et al. have characterized the circadian translatomes of astrocytes and microglia in the mouse cortex in the context of amyloid pathology or aging, revealing cell- and disease-specific reprogramming of neurodegeneration-related pathways.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Data independent acquisition (DIA) has been gaining momentum in clinical proteomics. Here, the authors create a benchmark dataset comprising inter-patient heterogeneity to compare popular DIA data analysis workflows for identifying differentially abundant proteins.

A study shows that clonal haematopoiesis of indeterminate potential is associated with an increased risk of chronic liver disease specifically through the promotion of liver inflammation and injury.

Most studies of the genetics of the metabolome have been done in individuals of European descent. Here, the authors integrate genomics and metabolomics in Black individuals, highlighting the value of whole genome sequencing in diverse populations and linking circulating metabolites to human disease.

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data.

STAARpipeline is a comprehensive framework for flexible and scalable rare-variant association analysis using whole-genome sequencing data and annotation information.

Whole genome sequences enable discovery of rare variants which may help to explain the heritability of common diseases. Here the authors find that ultra-rare variants explain ~50% of coronary artery disease (CAD) heritability and highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Platelet aggregation is associated with myocardial infarction and stroke. Here, the authors have conducted a whole genome sequencing association study on platelet aggregation, discovering a locus in RGS18, where enhancer assays suggest an effect on activity of haematopoeitic lineage transcription factors.

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.

Rational design has endowed self-assembling peptides with structural similarities to natural materials, but recreating the dynamic functional properties inherent to natural systems remains challenging. Here the authors report the discovery of a short peptide based on the tryptophan zipper motif, that shows multiscale hierarchical ordering into hydrogels that display emergent dynamic properties.

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 the proportions of individuals who have completed key levels of schooling across all low- and middle-income countries from 2000 to 2017 reveal inequalities across countries as well as within populations.