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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.

Standard of care in patients with unresectable stage III non-small cell lung cancer (NSCLC) is concurrent chemo-radiotherapy followed by immunotherapy. Here, the authors report a phase II trial investigating induction chemo-immunotherapy (atezolizumab, carboplatin and paclitaxel) followed by concurrent chemoradiotherapy and immunotherapy maintenance in patients with stage III NSCLC.

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.

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).

Genome-wide analyses identify 30 independent loci associated with obsessive–compulsive disorder, highlighting genetic overlap with other psychiatric disorders and implicating putative effector genes and cell types contributing to its etiology.

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

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.

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.

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.

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.

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.

Nanoparticle-based ‘microgauges’ are developed for in vivo force sensing and deployed in C. elegans to investigate how mechanical force correlates with electrical signalling in neuromuscular organs.

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.

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.

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.

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.

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.

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 authors perform meta-analysis of GWAS studies for asthma from multiancestral cohorts. They identify five new loci and find that the asthma-associated loci are enriched near enhancer marks in immune cells.

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.

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.

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.

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.

Fine-mapping of causal variants and integration of epigenetic and chromatin conformation data identify likely target genes for 150 breast cancer risk regions.

GIANT, a genetically informed brain atlas, integrates genetic heritability with neuroanatomy. It shows strong neuroanatomical validity and surpasses traditional atlases in discovery power for brain imaging genomics.

Understanding the dynamics of the gut microbiota over the course of cancer treatment regimens and their associated adverse events can help identify microbial features that associate with response to immune checkpoint blockade.

The flux of methane—a greenhouse gas—from submarine hydrocarbon seeps to the atmosphere is not well quantified. Direct measurements of methane concentrations and isotopic depth profiles in deepwater hydrocarbon plumes indicate that a significant amount of methane from deep-ocean sources could reach the surface ocean.

Jayavelu, Samaha et al., apply machine learning models on hospital admission data, including antibody titers and viral load, to identify patients at high risk for Long COVID. Low antibody levels, high viral loads, chronic diseases, and female sex are key predictors, supporting early, targeted interventions.

Wastewater treatment plants are important reservoirs of antibiotic resistance genes (ARGs). Here, the authors analyze ARGs in a global collection of samples from wastewater treatment plants across six continents, providing insights into biotic and abiotic mechanisms that appear to control ARG diversity and distribution.

Cecilia Lindgren and colleagues report results of a large-scale genome-wide association study for waist-to-hip ratio, a measure of body fat distribution. They identify 13 new loci associated with this trait, several of which show stronger effects in women than in men.

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.

A transcriptome-wide association study identifies associations of genetically predicted gene expression with breast cancer risk. This analysis finds 48 candidate genes implicated in breast cancer susceptibility, including 14 at novel loci.

Population-based genome sequencing provides an increasingly rich resource for the identification of low-frequency, large effect variants associated with clinically important phenotypes. Timpson et al. use UK10K data to identify a variant of the APOC3gene strongly associated with plasma triglyceride levels.

Nociceptin is an opioid peptide regulating important brain functions, including motivation and 2stress responses. Here, the authors develop and validate a genetically encoded sensor as a tool for high-resolution detection of endogenous nociceptin in living animals.

Here, the authors leveraged genetic and proteomic information from the UK Biobank and two randomized controlled trials to characterize how polygenic disease risk for T2D and related comorbidities perturbs the plasma proteome and glean therapeutic insights.