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In two independent studies, Song et al. and Jiang, Dalgarno et al. present computational frameworks, perturbation-response score and Mixscale, respectively, to determine individual cellular variation in response to perturbation.

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 APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer’s disease, but it is not deterministic. Here, the authors show that common genetic variation changes how APOE-ε4 influences cognition.

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.

Meta-analysis of genome-wide association studies on Alzheimer’s disease and related dementias identifies new loci and enables generation of a new genetic risk score associated with the risk of future Alzheimer’s disease and dementia.

This Review describes how an approach that starts from genetic changes under selection during human evolution and integrates comparative and functional studies can reveal adaptive phenotypes across different evolutionary timescales.

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

Amyloid fibrils can accumulate in tissues outside the brain, yet the impact is incompletely understood. Here the researchers show that, with age, mouse bone marrow fat cells become senescent and secrete SAP/PTX2, driving amyloid buildup and bone loss. Clearing senescent fat cells or depleting SAP/PTX2 reduces marrow amyloid deposits and restores bone health.

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.

A region on chromosome 19p13 is associated with the risk of developing ovarian and breast cancer. Here, the authors genotyped SNPs in this region in thousands of breast and ovarian cancer patients and identified SNPs associated with three genes, which were analysed with functional studies.

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.

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.

BRCA1 and BRCA2 are well known breast cancer predisposition genes, however, many variants have not yet been classified for their pathogenicity. Here, the authors analyse a large combined cohort to provide evidence of variant pathogenicity.

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.

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.

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 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.

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.

This study quantifies mid-21st century hourly building energy use in 277 urban areas in the USA, revealing spatially and temporally heterogeneous changes influenced by future climate, population dynamics, and electric power sector decarbonization.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A draft sequence of the staple crop kabuli chickpea, together with resequencing and analysis of 90 additional lines from 10 countries, provides a resource for breeders.

A whole-genome sequencing analysis of 100 pancreatic ductal adenocarcinomas has discovered known and newly identified genetic drivers of pancreatic cancer; these genetic alterations can be classified into four subtypes, which raises the possibility of improved targeting of clinical treatments.

Reducing friction and wear in mechanical systems can lower energy consumption and material loss. Here, a green lubricant additive is introduced, free of harmful elements, that effectively minimizes friction and wear, offering a sustainable solution.

Narcolepsy has genetic and environmental risk factors, but the specific genetic risk loci and interaction with environmental triggers are not well understood. Here, the authors identify genetic loci for narcolepsy, suggesting infection as a trigger and dendritic and helper T cell involvement.

Stig Bojesen, Georgia Chenevix-Trench, Alison Dunning and colleagues report common variants at the TERT-CLPTM1L locus associated with mean telomere length measured in whole blood. They also identify associations at this locus to breast or ovarian cancer susceptibility and report functional studies in breast and ovarian cancer tissue and cell lines.

Oestrogen negative breast cancer is associated with a poor prognosis. In this study, the authors perform a meta-analysis of 11 breast cancer genome-wide association studies and identify four new loci associated with oestrogen negative breast cancer risk. These findings may aid in stratifying patients in the clinic.

Senolytics have the potential to extend healthspan by selectively killing senescent cells (SCs), but senolytics that target Bcl-xl may cause platelet toxicity. Here, the authors generated a Bcl-xl proteolysis-targeting chimera (PROTAC) senolytic, which effectively clears SCs and rejuvenates tissue stem and progenitor cells in naturally aged mice without causing severe thrombocytopenia.

Paul Pharoah, Joellen Schildkraut, Thomas Sellers and colleagues report a meta-analysis of genome-wide association studies for epithelial ovarian cancer and genotyping using the iCOGS array in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. They identify three new ovarian cancer susceptibility loci, including one specific to the serous subtype, and their integrated molecular analysis of genes and regulatory regions at these loci suggests disease mechanisms.

As phase 1 of the Earth Microbiome Project, analysis of 16S ribosomal RNA sequences from more than 27,000 environmental samples delivers a global picture of the basic structure and drivers of microbial distribution.

Cristen Willer and colleagues report genome-wide association analyses for blood lipid levels in 188,578 individuals. They identify 62 loci newly associated with blood lipid levels, refine the association signals at 12 loci and examine associations with cardiovascular and metabolic traits.

Genome-wide association studies have identified regions which confer risk of high-grade serous epithelial ovarian cancer. Here the authors use expression quantitative train locus analysis to identify candidate genes and functionally characterise them, identifying a role for HOXD9 in ovarian cancer.

Most confirmed susceptibility variants for epithelial ovarian cancer lie in non-protein-coding sequences. Here Permuth-Wey and colleagues investigate variants in 3′ untranslated regions (UTRs) and uncover a new susceptibility locus.

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.