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

The electronic structure of superconducting magnesium diboride is predicted theoretically to have a distribution of energy gap values. Chenet al. observe this distribution of values experimentally, by means of high-resolution electron tunnelling spectroscopy.

Choi et al. introduce a machine learning model that integrates diverse multi-view data to predict disease phenotypes. The model includes an interpretable explainer that identifies interacting biological features, such as synergistic genes in astrocytes and microglia associated with Alzheimer’s disease.

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.

The cytochrome bc₁ oxidase of Mycobacterium tuberculosis is a potential target in the fight against tuberculosis. Here, the authors evaluate the potential of cytochrome bc₁ inhibitors as partner drugs in tuberculosis treatment regimens.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

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 meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

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.

Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.

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

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 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

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 genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

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.

Analysis of samples from the asteroid Ryugu provide evidence of late fluid flow in a carbonaceous asteroid, indicating that such bodies may have retained two to three times more water than previously thought.

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.

Different functional variants in ADH1B (and elsewhere) in Europeans and Africans strongly affect risk for alcohol dependence. Dependence only partly genetically correlates with consumption, with strong correlations to other psychiatric disorders.

Herpes simplex virus establishes lifelong latency in ganglionic neurons, which are the source for recurrent infection. Here Aubert et al. report a promising antiviral therapy based on gene editing with adeno-associated virus-delivered meganucleases, which leads to a significant reduction in ganglionic HSV loads and HSV reactivation.

Using data from a single time point, passenger-approximated clonal expansion rate (PACER) estimates the fitness of common driver mutations that lead to clonal haematopoiesis and identifies TCL1A activation as a mediator of clonal expansion.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

This paper shows that tropical cyclones contribute between 40% and 100% of the extreme wave events approaching coastlines in basins prone to tropical cyclone activity, while they can also impact remote areas via swell propagation across the ocean.

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.

Petrels are wide-ranging, highly threatened seabirds that often ingest plastic. This study used tracking data for 7,137 petrels of 77 species to map global exposure risk and compare regions, species, and populations. The results show higher exposure risk for threatened species and stress the need for international cooperation to tackle marine litter.

Wartewig et al. show that PDCD1 in T cell lymphoma restricts glycolytic energy and acetyl-CoA production. Inhibition of PD-1 signaling enforces ACLY activity and generates extramitochondrial acetyl-CoA for histone acetylation to enable AP-1 hyperactivation.

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.

A cross-ancestry meta-analysis of genome-wide association studies identifies association signals for stroke and its subtypes at 89 (61 new) independent loci, reveals putative causal genes, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as potential drug targets, and provides cross-ancestry integrative risk prediction.

Genome-wide association meta-analyses identify more than 350 loci associated with atrial fibrillation. A polygenic score derived from these results improves atrial fibrillation risk prediction compared to published clinical and polygenic scores.

Large genome-wide meta-analysis of clinically diagnosed late-onset Alzheimer’s disease (LOAD) from 94,437 individuals identifies new LOAD risk loci and implicates Aβ formation, tau protein binding, immune response and lipid metabolism.

Using mouse lines in which subsets of neurons are genetically labelled, the authors provide generalized anatomical rules for connections within and between the cortex and thalamus.