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Michelle Francl wonders if there is a risk to making yourself at home in the lab.

cellSTAAR advances noncoding rare variant association analysis by integrating single-cell genomics data.

Measuring the rate of aging holds potential for capturing heterogeneity in aging. Here, the authors use longitudinal trajectories of aging phenotypes in the Baltimore Longitudinal Study of Aging and create a longitudinal phenotypic score that is associated with accelerated decline in health and physical and cognitive function.

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.

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.

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.

A high-resolution, global atlas of mortality of children under five years of age between 2000 and 2017 highlights subnational geographical inequalities in the distribution, rates and absolute counts of child deaths by age.

Cytoskeletal remodeling is known to facilitate mitophagy, but the mechanism is not fully understood. Here, the authors show that damaged mitochondria recruit a RhoA GTPase activating protein that promotes their capture and encasement by autophagosomes.

Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1.

Michelle Francl wants a chemistry book that could conjure up Linus Pauling.

Mercey et al. demonstrate that without deuterosomes, multiciliated cells still develop the proper number of centrioles with normal step-wise kinetics, independent of the growing platform.

Multi-ancestry genome-wide association analyses identify new risk loci for Parkinson’s disease, and fine-mapping and co-localization analyses implicate candidate genes whose expression is associated with disease susceptibility.

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.

An integrative genomic analysis of several hundred endometrial carcinomas shows that a minority of tumour samples carry copy number alterations or TP53 mutations and many contain key cancer-related gene mutations, such as those involved in canonical pathways and chromatin remodelling; a reclassification of endometrial tumours into four distinct types is proposed, which may have an effect on patient treatment regimes.

The tumour immune microenvironment remains poorly characterised in paediatric brain tumours. Here, the authors develop a clinical immune-oncology gene expression assay to profile 1382 paediatric brain tumour samples, and reveal immune profiles and biomarkers that can contribute to diagnosis, prognosis, and treatment response.

A study shows that clonal haematopoiesis of indeterminate potential is associated with an increased risk of chronic liver disease specifically through the promotion of liver inflammation and injury.

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

A mathematical framework to estimate the fitness of cancer driver mutations by integrating mutational bias, oncogenicity and immunogenicity finds fundamental trade-offs in cancer evolution.

In this Case Study, Hladunewich and colleagues describe the case of a woman with a twin pregnancy with a single fetal demise who presented earlier than 20 weeks' gestation with severe nephrotic syndrome, hypertension and renal insufficiency. The authors describe how aberrant levels of anti-angiogenic and angiogenic factors helped confirm the diagnosis of pre-eclampsia in this complex renal presentation, allowing for the rapid discontinuation of unnecessary immunosuppressive agents and the avoidance of the potential risks inherent with diagnostic renal biopsy.

Centrioles organize chromosome segregation, migration, and the immune synapse. Here, Schapfl et al. show that B cell progenitors tolerate centriole overamplification, but not loss, while mature B cells can mount a humoral immune response in their absence.

Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.

Analyses of genome and exome sequencing data identify rare coding and structural variants associated with atrial fibrillation and highlight genetic links between atrial fibrillation and cardiomyopathies.

A new tool to visualize high-dimensional single-cell data, when integrated with mass cytometry, reveals phenotypic heterogeneity of human leukemia.