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Sharma and colleagues show that, in Caenorhabditis elegans, age-associated decline in peroxisomal function causally impairs lipid mobilization, resulting in lipid droplet accumulation, metabolic inflexibility and secondary mitochondrial dysfunction. Restoring peroxisomal activity reinstates metabolic resilience during aging.

In this individual participant data meta-analysis, and across 321,345 smartphone-ratings of affective well-being and nearly 1 million hours of physical activity measurement, Rehder et al. clarify the nature and extent of activity–well-being relations and document their relevance in humans’ everyday life.

Multi-ancestry GWAS meta-analysis identifies risk loci for severe nausea and vomiting of pregnancy. Downstream analyses explore maternal and fetal contributions of these loci and their temporal effects.

RNA velocity is a widely used method to predict the fate of single cells. Here the authors show that the concept can be adapted to predict the fate of individual human subjects, using RNA velocity of whole blood at a single point in time to predict future clinical outcomes and treatment responses.

DNA-sequencing data from primary tumours and paired metastases from participants in the TRACERx lung study and PEACE autopsy programme are used to analyse the metastatic diversity of advanced non-small cell lung cancer and the seeding patterns that underpin it.

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 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.

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.

Multisystem inflammatory syndrome in children (MIS-C) onsets in COVID-19 patients with manifestations similar to Kawasaki disease (KD). Here the author probe the peripheral blood transcriptome of MIS-C patients to find signatures related to natural killer (NK) cell activation and CD8+ T cell exhaustion that are shared with KD patients.

A meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

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.

Transcriptomic and clinical data analyses from multiple cohorts of patients with cancer receiving immunotherapy find that PD-1 blockade potentiates tumor-specific IgG1 plasma cell responses that complement cellular immunity and contribute to clinical benefit.

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.

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).

De novo assemblies of 43 Y chromosomes spanning 182,900 years of human evolution reveal considerable diversity in the size and structure of the human Y chromosome.

De novo and inherited dominant variants in genes encoding U4 and U6 small nuclear RNAs are identified in individuals with retinitis pigmentosa. The variants cluster at nucleotide positions distinct from those implicated in neurodevelopmental disorders.

Here, the authors implement a genetic approach grouping fasting insulin-associated genetic variants based on their genetic and phenotypic similarities and highlight specific processes that decouple increased fasting insulin levels from T2D and cardiovascular risk, offering potential avenues for investigating process-specific pathways of disease risk.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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

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.

Response to anti-PD-1 in patients with hepatocellular carcinoma is associated with clonal expansion of intratumoral CXCL13⁺ CD4⁺ helper T cells and effector-like CD8⁺ T cells, and local dendritic cells enriched in expression of maturation and regulatory molecules help facilitate CD8⁺ T cell differentiation.

Exome-sequencing analyses of a large cohort of patients with type 2 diabetes and control individuals without diabetes from five ancestries are used to identify gene-level associations of rare variants that are associated with type 2 diabetes.

Transcriptomic analyses of acute phase whole blood from a large cohort of patients with COVID-19 identify molecular determinants of post-infection long-term sequelae.

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.

An understanding of the molecular mechanisms promoting the generation of immunoregulatory and tumour-promoting monocytes and macrophages is key to breaking the cycle of tumour myelopoiesis and developing more effective myeloid-targeting therapies.

Here, the authors used electronic healthcare records to analyse the genetic basis of variation in 42 routinely-acquired quantitative blood tests among up to 40,000 British South Asian volunteers from the Genes and Health study. By combining their results with genetic findings from UK Biobank, they explore similarities and differences between ancestries in the genetic basis of these traits.

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.

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.

A consensus cell type atlas for the fly brain provides both an intellectual framework and open-source toolchains for brain-scale comparative connectomics.

Gene expression profiles can classify breast cancer into five clinically relevant subtypes. Here, the authors perform an in-depth quantitative profiling of the proteome of 45 breast tumors, and show they can recapitulate the transcriptome-based classifications and identify many potentially antigenic tumour-specific peptides.

Single-cell transcriptomics studies on human and mouse non-small cell lung cancer and conditional knockout mouse models show that IL-4 from bone marrow basophils drives the development of granulocyte-monocyte progenitors to myeloid cells that suppress antitumour immunity.

Polygenic scores and partitioned polygenic scores related to insulin resistance derived in multiancestry populations show distinct association with neurological outcomes

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.