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Cellular niches are highly heterogenous in triple negative breast cancer. Here, the authors utilise imaging mass cytometry and spatial transcriptomics to characterise the microenvironment in Black American and White American patients.

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).

Here, the authors leverage whole-genome sequencing from >88,000 diverse individuals to uncover 18 BMI-related genetic signals, including novel variants in participants of African genetic ancestry, highlighting the value of diversity in genetic discovery.

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.

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.

A multi-ancestry genome-wide gene–smoking interaction study identifies 13 new loci associated with serum lipids.

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.

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

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

GWAS have identified more than 500 genetic loci associated with blood lipid levels. Here, the authors report a genome-wide analysis of interactions between genetic markers and physical activity, and find that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol.

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

Numerous methylated residues exist on histone tails, the functional significance of which remains unknown. New studies in budding yeast now identify monomethylation of histone H4 lysine residues 5, 8 and 12 as functionally important marks that regulate cell growth and stress responses and are catalyzed by the first known H4 methyltransferase in budding yeast, Set5.

Jones et al. examine the generalizability of the valence–dominance model of social judgements of faces in 41 countries across 11 world regions. They find evidence of both generalizability and variation, depending on the analytical method.

Phenotypic robustness to environmental variation is seemingly at odds with evolvability. Here, the authors analyze carotenoid use and accommodation in feather development across a recent avian range expansion and show that cooption of a stress-buffering mechanism can reconcile robustness and evolvability.

The mechanisms that accommodate variable external dependencies in evolution are not clear. Here, the authors show that switches between external and internal metabolic controls of carotenoid-producing networks in birds are linked to shifts in evolutionary rates, with internalization of control resulting in bursts of evolutionary diversification.

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.

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.

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

The Cancer Genome Atlas Research Network reports an integrative analysis of more than 400 samples of clear cell renal cell carcinoma based on genomic, DNA methylation, RNA and proteomic characterisation; frequent mutations were identified in the PI(3)K/AKT pathway, suggesting this pathway might be a potential therapeutic target, among the findings is also a demonstration of metabolic remodelling which correlates with tumour stage and severity.

Data from more than 200 million observations of plants, animals and fungi provide support for the concept that terrestrial biodiversity patterns reflect distinct ecoregions.

Heart failure is a complex syndrome that is associated with many different underlying risk factors. Here, to increase power, the authors jointly analyse cases of heart failure of different aetiologies in a genome-wide association study and identify 11 loci of which ten had not been previously reported.

This study finds that sST2 is a disease-causing factor for Alzheimer’s disease. Higher sST2 levels impair microglial Aβ clearance in APOE4⁺ female individuals. A genetic variant, rs1921622, is associated with a reduction in sST2 level and protects against AD in APOE4⁺ female individuals.

Whether Alzheimer’s disease originates in basal forebrain or entorhinal cortex remains highly debated. Here the authors use structural magnetic resonance data from a longitudinal sample of participants stratified by cerebrospinal biomarker and clinical diagnosis to show that tissue volume changes appear earlier in the basal forebrain than in the entorhinal cortex.

Late-onset Alzheimer's disease (LOAD) is a complex multi-factorial disorder. Here, the authors perform a data-driven analysis of LOAD progression, including multimodal brain imaging, plasma and CSF biomarkers, and find vascular dysfunction is among the earliest and strongest altered events.

Brain-iron elevation is implicated in Alzheimer’s disease (AD), but the impact of the metal on disease outcomes has not been analysed in a longitudinal study. Here, the authors examine the association between the levels of ferritin, an iron storage protein, in the cerebrospinal fluid (CSF) of AD patients and show that CSF ferritin levels predict AD outcomes.

Comprehensive analyses of 178 lung squamous cell carcinomas by The Cancer Genome Atlas project show that the tumour type is characterized by complex genomic alterations, with statistically recurrent mutations in 11 genes, including TP53 in nearly all samples; a potential therapeutic target is identified in most of the samples studied.