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There is an increasing interest in studying antibiotic resistance genes in microbial communities, however, there is no unified way to identify them in metagenomics datasets or to interpret the risks associated with them. In this Comment, the authors discuss current technical challenges and how to mitigate them.

Small intestine neuroendocrine tumors (SI-NETs) are frequently multifocal and metastatic, but their tumourigenesis is still poorly understood. Here, the authors analyse multifocal SI-NET tumours with whole-genome sequencing, revealing the landscape of genomic alterations and frequent polyclonal origins.

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.

Multi-ancestry genome-wide and transcriptome-wide association studies of aortic stenosis identify more than 200 independent risk loci and provide insights into its genetic architecture.

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.

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.

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.

Evolutionary principles could help distinguish driver from passenger mutations in cancer. Here, the authors develop SEISMIC, a method to identify cancer driver genes based on their deviation from expected mutation status patterns across a cohort under neutral evolution, and find potential drivers in melanoma and other cancer types.

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.

Terrestrial organic matter boosts methyl-mercury bioaccumulation in coastal planktons by promoting heterotrophy, but increased dissolved organic matter thiols reduces its bioavailability, making net mercury uptake depend on changing organic-matter inputs, based on Baltic Sea mesocosm experiments.

Imbalanced nucleotide metabolism leads to age- and mtDNA-dependent inflammatory responses and senescence-associated secretory phenotype in senescence.

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.

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.

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.

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.

Erik Larsson and colleagues present an analysis pipeline for identifying likely transcription-altering noncoding somatic mutations in cancer using publicly available data from 505 tumor genomes across 14 cancer types. They find that TERT promoter mutations show strong associations to altered transcriptional levels and identify recurrent promoter mutations in DPH3 and PLEKHS1.

Patrick Chinnery, Nils-Goran Larsson and colleagues show that mitochondrial heteroplasmy levels are principally determined prenatally within the developing female germline in mice transmitting a heteroplasmic single base-pair deletion in the mitochondrial tRNA^Met gene.

Mutations at two key positions in the TERT promoter are frequent drivers of cancer, but the role of rare, atypical mutations in this region remains unclear. Here, the authors demonstrate that atypical TERT promoter mutations develop after canonical ones due to locally elevated UV-induced DNA damage.

Genome-wide association meta-analyses of attention-deficit/hyperactivity disorder symptom measures and clinical diagnoses identify new risk loci, highlight putative effector genes and yield improved polygenic risk scores.

The authors use spatial and single-cell transcriptomics to examine spatial dynamics during early human cardiogenesis, yielding insights into the development of the cardiac pacemaker-conduction system, autonomic innervation, heart valves and atrial septum, and heterogeneity of cardiac mesenchymal cells.

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

The dynamics of antimicrobial resistance gene transfer remain unclear. Here, by integrating bacterial genome and metagenome data with machine learning the authors show that genetic incompatibility is a main limiting factor, while co-occurrence of bacteria in the human microbiome and wastewater contributes to gene transfer.

Muscle mass is lost in patients with diabetes, which is associated with mitochondrial disfunction. Here they show that SLIRP maintains muscle mitochondria and that exercise training can compensate for SLIRP loss, improving mitochondrial function and quality control in muscle.

Proteins binding to DNA can locally alter DNA damage formation by UV light. Here, Elliott et al. generate high-resolution quantitative UV damage profiles for genomic regions of interest, revealing distinctive damage signatures for specific proteins and elevated UV damage at melanoma mutation hotspots.

The FET family proteins FUS, EWSR1 and TAF15 are RNA-binding proteins with diverse nuclear functions. PAR-CLIP analyses now reveal the genome-wide RNA targets of all three human FET proteins and of two FUS mutants that cause amyotrophic lateral sclerosis. Although the RNA-binding properties of the mutants remain unchanged, the spectrum of RNA targets is altered because of the changed subcellular localization of the mutants.

The genetics of uveal melanoma has mainly been studied in primary tumours. In this study, the authors perform whole genome sequencing as well as immune cell profiling of biopsy samples obtained from metastatic uveal melanoma patients, providing an updated genomic landscape of these advanced lesions.

Long non-coding RNAs are implicated in multiple aspects of tumourigenesis. Here, the authors generate a landscape of these macromolecules in a wide array of cancer types and examine which RNAs are transcriptionally altered in relation to somatic driver mutations in established coding cancer genes.

Large-scale deletions of mitochondrial DNA (mtDNA) are associated with different human mitochondrial diseases and normal human ageing. Here the authors present a model for mtDNA formation based on generation sequencing analysis of patients samples and in vitro reconstituted mtDNA deletion using purified proteins.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Viruses contribute to the pathogenesis of certain cancers. Using massively parallel sequencing data from The Cancer Genome Atlas to analyse viral expression in 19 tumour types, Tang et al. both confirm and reject previously described viral associations and present new information on viral integration and host interaction.

A large integrated genome and transcriptome analysis of colorectal cancer identifies prognostic mutations and expression subtypes.