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Characterizing how genetic variation impacts cell morphology can provide an important links between disease association and cellular function. Here the authors identified the morphological impacts of genomic variants by generating high-throughput morphological profiling and whole genome sequencing data on iPSCs from 297 donors.

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).

Methods to study how natural selection shapes genetic architecture of complex traits rely on individual level genome-wide association study (GWAS) data. Here, the authors present a Bayesian method using GWAS summary statistics to study genetic architecture and apply this to 155 complex traits.

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.

Fourier Mixture Regression (FMR) is a method for estimating common-variant effect-size distributions. Applying FMR to summary statistics for complex traits from the UK Biobank shows that heritability is spread across a wide range of effect sizes.

Transcriptome-wide analysis of differential expression (TRADE) is a broadly applicable tool for characterizing patterns of differential expression across the genome.

A high-bandwidth neuromotor interface offers performant out-of-the-box generalization across people.

Here authors visualize dynamics GAGA pioneer factor (GAF) association with chromatin in vivo in Drosophila hemocytes. The characterization of GAF kinetics provides a temporal mechanism for maintenance of open chromatin for transcriptional responses to homeostatic, environmental and developmental signals.

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

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.

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.

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.

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.

An integrated analysis of de novo and inherited coding variants in 42,607 individuals with autism spectrum disorder identifies 60 risk genes of which five have not previously been associated with neurodevelopmental disorders.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Linkage disequilibrium graphical models (LDGMs) derived from genome-wide genealogies provide an efficient representation of LD, yielding large improvements in runtime for LD matrix computations. LDGMs will enable methods that scale to millions of variants and individuals.

The engagement of immunological memory is a key component to the protective anti-SARS-CoV-2 B and T cell responses. Here the authors assess the B and T cells of a cohort of UK healthcare workers in response to infection and longitudinally track the compartment showing distinct trajectories following early priming.

Common polygenic variation at chromosome 16p and rare recurrent deletions of 16p11.2 influencing autism risk are associated with reduced expression of genes throughout the 16p region, suggesting functional convergence of rare and common variant effects.

A trans-ancestry genome-wide association study of serum urate levels identifies 183 loci influencing this trait. Enrichment analyses, fine-mapping and colocalization with gene expression in 47 tissues implicate the kidney and liver as key target organs and prioritize potential causal genes.

Dimethyl fumarate (DMF) is an anti-inflammatory drug proposed as a treatment for COVID19. Here the results are reported from a randomised trial testing DMF treatment in 713 patients hospitalised with COVID-19. DMF was not associated with any improvement in day 5 outcomes.

Climate change can exert a significant effect on the ozone recovery. Here, the authors show that the Arctic polar vortex shift associated with Arctic sea-ice loss could slow down ozone recovery over the Eurasian continent.

A heritability-based framework for evaluation of SNP-to-gene linking methods is used to construct an optimal, combined approach and applied to 49 traits. Analysis of trait omnigenicity suggests gene-level architecture varies depending on variant frequency.

 An analysis of rare coding variants across 22 common traits and diseases indicates that these variants will contribute substantially to biological insights but modestly to population risk stratification.

Obtaining data on antimicrobial resistance (AMR) from healthy human populations is difficult. Here, Hendriksen et al. use metagenomic analysis to obtain AMR data from untreated sewage from 79 sites in 60 countries, finding correlations with socio-economic, health and environmental factors.

Mediated expression score regression (MESC) is a new method that estimates disease heritability mediated by the cis genetic component of gene expression levels by using summary statistics from GWAS and eQTL studies.

Negative selection removes deleterious genetic variation, and can influence genetic architectures and evolution of complex traits. Here, the authors analyze data from 25 UK Biobank diseases and complex traits, and quantify frequency-dependent genetic architectures which suggests actions of negative selection.

PolyFun is a computationally scalable framework for functionally informed fine-mapping that makes full use of genome-wide data. It prioritizes more variants than previous methods when applied to 49 complex traits from UK Biobank.