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Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders.

A connectome of the right optic lobe from a male fruitfly is presented together with an extensive collection of genetic drivers matched to a comprehensive neuron-type catalogue.

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.

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).

Comparative analysis of genetic variations of bread wheat accessions created in the last 150 years and 45 related species revealed a major contribution of introgressions and chromosomal rearrangements to cultivated wheat diversity.

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

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.

Chronic infection with SARS-CoV-2 leads to the emergence of viral variants that show reduced susceptibility to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma.

Sera from vaccinated individuals and some monoclonal antibodies show a modest reduction in neutralizing activity against the B.1.1.7 variant of SARS-CoV-2; but the E484K substitution leads to a considerable loss of neutralizing activity.

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 study of the evolution of the SARS-CoV-2 virus in England between September 2020 and June 2021 finds that interventions capable of containing previous variants were insufficient to stop the more transmissible Alpha and Delta variants.

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.

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.

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.

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.

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.

Systematic characterization of longitudinal tau variability in human Alzheimer’s disease using an unbiased subtyping algorithm reveals four trajectories of tau deposition with distinct clinical features.

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.

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.

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.

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.

Coral reef health is declining globally and is projected to lead to net loss of reef structure. This study shows that ecological change across the Caribbean has reduced reef growth rates to levels lower than those measured over the last ~8,000 years, threatening the ability of reefs to keep pace with future sea-level rise.

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.

A machine learning algorithm can predict the future risk of idiopathic pulmonary fibrosis, a disease that is difficult to diagnose at its early stages, based on comorbidity signatures in electronic health records.

Analyses of multiregional tumour samples from 421 patients with non-small cell lung cancer prospectively enrolled to the TRACERx study reveal determinants of tumour evolution and relationships between intratumour heterogeneity and clinical outcome.

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.

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.

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 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.

Patient-derived xenografts are important tools for cancer drug development. Here, the authors develop models from 22 non-small cell lung cancer patients. They show genomic differences between models created from different spatial regions of tumours and a bottleneck on model establishment.

A longitudinal evolutionary analysis of 126 lung cancer patients with metastatic disease reveals the timing of metastatic divergence, modes of dissemination and the genomic events subject to selection during the metastatic transition.

Computational and machine-learning approaches that integrate genomic and transcriptomic variation from paired primary and metastatic non-small cell lung cancer samples from the TRACERx cohort reveal the role of transcriptional events in tumour evolution.

Whole-genome sequencing analysis of individuals with primary immunodeficiency identifies new candidate disease-associated genes and shows how the interplay between genetic variants can explain the variable penetrance and complexity of the disease.

Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population.