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Across many North American forests, recent years with exceptional area burned are not unprecedented when considering the multi-century perspective offered by fire-scarred trees. Nevertheless, abundant evidence suggests that the severity of contemporary wildfire is unprecedented in its adverse impacts on forests and humans.

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.

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.

Chronic care manages long-term, progressive conditions, while acute care handles short-term ones. Here, authors show chronic conditions account for most of the global health burden, with 68% of DALYs and 93% of YLDs attributed to chronic care needs.

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

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.

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.

Zhang et al. identify and characterize supermeres as extracellular nanoparticles that exhibit unique biological and functional properties with potential prognostic and therapeutic value across distinct diseases.

Louveau et al. demonstrate that meningeal lymphatics drain CSF-derived macromolecules and immune cells and play a key role in regulating neuroinflammation. Meningeal lymphatics may represent a new therapeutic target for multiple sclerosis.

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 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.

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.

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.

Although progress in the coverage of routine measles vaccination in children in low- and middle-income countries was made during 2000–2019, many countries remain far from the goal of 80% coverage in all districts by 2019.

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.

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.

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.

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.

Sun et al. report human lifespan changes in the brain’s functional connectome in 33,250 individuals, which highlights critical growth milestones and distinct maturation patterns and offers a normative reference for development, aging and diseases.

Exome sequencing and copy number analysis are used to define genomic aberrations in early sporadic pancreatic ductal adenocarcinoma; among the findings are mutations in genes involved in chromatin modification and DNA damage repair, and frequent and diverse somatic aberrations in genes known as embryonic regulators of axon guidance.

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.

The development of asthma following eczema is known as the atopic march. Here the authors conduct a GWAS on affected children and identify two novel loci associated with the disease phenotype.

Elevated extrinsic tissue-scale forces can drive pathological foreign-body responses to implants, mediated by the Rac2-mediated activation of a subpopulation of mechanoresponsive myeloid cells.

GDF15 has potent anti-obesity effects, but its receptor was unknown. GFRAL has now been identified as the receptor and mediates GDF15's effects through central actions in the hindbrain.

Instead of using capacitively coupled charge sensors, which imply additional complexity in the device architecture, radiofrequency reflectometry on the gate defining the quantum dot can read out the spin state of a double quantum dot in a single shot.

The interplay between amyloid and tau pathology in Alzheimer’s disease is still not well understood. Here, the authors show that amyloid-related increased in soluble p-tau is related to subsequent accumulation of tau aggregates and cognitive decline in early stage of the disease.

In one-dimensional systems, the combination of a strong spin-orbit interaction and an applied magnetic field can give rise to a spin-gap, however experimental identification is difficult. Here, the authors present new signatures for the spin-gap, and verify these experimentally in hole QPCs.

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.

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

Several studies show that APOE-ε4 coding variants are associated with Alzheimer’s disease (AD) risk. Here, Zhou et al. perform fine-mapping of the APOE region and find AD risk haplotypes with non-coding variants in the PVRL2 and APOC1 regions that are associated with relevant endophenotypes.

The largest whole-exome sequencing study of sporadic congenital hydrocephalus identities mutations associated with disrupted fetal neuro-gliogenesis as the primary pathophysiological event in a significant number of cases.

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.

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.

Late-onset Alzheimer's disease (LOAD) is a complex multi-factorial disorder. Here, the authors perform a data-driven analysis of LOAD progression, including multimodal brain imaging, plasma and CSF biomarkers, and find vascular dysfunction is among the earliest and strongest altered events.

This study finds that sST2 is a disease-causing factor for Alzheimer’s disease. Higher sST2 levels impair microglial Aβ clearance in APOE4⁺ female individuals. A genetic variant, rs1921622, is associated with a reduction in sST2 level and protects against AD in APOE4⁺ female individuals.

In Alzheimer’s disease (AD) tau and neurodegeneration have complex regional relationships. Here, the authors show neuronal hypometabolism discordant with tau burden defines functional resilience or susceptibility to Alzheimer’s pathology via limbic/cortical axes. Susceptible groups have faster cognitive decline and evidence of non-Alzheimer’s pathologies.

Alzheimer’s disease has been associated with increased structural brain aging. Here the authors describe a model that predicts brain aging from resting state functional connectivity data, and demonstrate this is accelerated in individuals with pre-clinical familial Alzheimer’s disease.

Alzheimer’s disease is heterogeneous in its neuroimaging and clinical phenotypes. Here the authors present a semi-supervised deep learning method, Smile-GAN, to show four neurodegenerative patterns and two progression pathways providing prognostic and clinical information.

Progressive diseases tend to be heterogeneous in their underlying aetiology mechanism, disease manifestation, and disease time course. Here, Young and colleagues devise a computational method to account for both phenotypic heterogeneity and temporal heterogeneity, and demonstrate it using two neurodegenerative disease cohorts.