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This study applies generalized linear mixed models (GLMM) and advanced transcriptome wide association study (TWAS) methods to improve the discovery of colorectal cancer risk transcription factors and genes, including potential druggable targets.

Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic.

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).

The early genetic evolution of uveal melanoma (UM) remains poorly understood. Here, the authors perform genetic profiling of 1140 primary UMs, including 131 small early-stage tumours, finding that most genetic driver aberrations have occurred by the time small tumours are biopsied; in addition, the15-gene expression profile discriminant score can predict the transition from low- to high-risk tumours.

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.

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.

Wastewater-based surveillance tends to focus on specific pathogens. Here, the authors mapped the wastewater virome from 62 cities worldwide to identify over 2,500 viruses, revealing city-specific virome fingerprints and showing that wastewater metagenomics enables early detection of emerging viruses.

Living plant collections hold an immense wealth of plant diversity and have critical educational, scientific and conservation roles. This Perspective examines current data management practices of living collections and advocates for higher data standards and a robust and inclusive global data ecosystem.

Antimicrobial resistance genes that have been mobilized between bacterial species represent a subset of the naturally occurring resistome. Here, the authors compare the abundance, diversity and geographical patterns of acquired resistance genes with latent resistance genes in global sewage metagenomes.

A multi-ancestry genome-wide association study meta-analysis, combined with transcriptome- and methylome-wide association analyses, identifies risk loci associated with colorectal cancer. Credible effector genes and their target tissues are also highlighted, showing that over a third probably act outside the colonic mucosa.

Proteins are often modified by complex carbohydrates (N-glycans). Here, authors identified gene regulators of this process and uncovered links between plasma protein Nglycosylation, metabolic and liver diseases, and anti-inflammatory proteins.

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.

Majzner and colleagues show that engineering T cells with a membrane-tethered version of the signaling adaptor molecule SLP-76 alongside a chimeric antigen receptor (CAR) enhances CAR T cell activity against low-antigen-density tumors.

An investigation using various methods reports an association between adeno-associated virus 2 and paediatric hepatitis of unknown aetiology.

Here, the authors perform large trans-ancestry fine-mapping analyses identifying large numbers of association signals and putative target genes for colorectal cancer risk, advancing our understanding of the genetic and biological basis of this cancer.

A case–control study investigating the causes of recent cases of acute hepatitis of unknown aetiology in 32 children identifies an association between adeno-associated virus infection and host genetics in disease susceptibility.

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.

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.

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.

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.

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 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.

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.

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 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.

CRISPR arrays form the physical memory of prokaryotic adaptive immune systems by incorporating viral DNA sequences as spacers. Here, Blombach et al. show that transcription factor Cbp1 recruits chromatin protein Cren7 at CRISPR arrays, forming ‘chimeric’ chromatin-like structures that regulate expression of long CRISPR arrays in Sulfolobales archaea.

Reconstructing short-term plate-motion changes through time provides important geodynamical information, but data noise is a problem at fine temporal resolution. This study presents a trans-dimensional hierarchical Bayesian framework that eliminates noise without loss of temporal resolution.

A genome-wide association study of critically ill patients with COVID-19 identifies genetic signals that relate to important host antiviral defence mechanisms and mediators of inflammatory organ damage that may be targeted by repurposing drug treatments.