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Insects are crucial for ecosystem functioning but face multiple threats, including invasive alien species. Here the authors quantify impacts of invasive alien species on four insect orders, with effects varying by insect group and type of invader.

Humanity’s Last Exam, a multi-modal benchmark at the frontier of human knowledge, is designed to be an expert-level closed-ended academic benchmark with broad subject coverage.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

Pollinator loss is a concern but data on their status is lacking. Here Powney et al. use occupancy modelling to estimate the degree of loss in wild bee and hoverfly species across Great Britain, and report a 55% decline in upland species and a 12% increase in dominant crop pollinators.

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

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.

An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Deep learning methods have been used to design proteins that can neutralize the effects of three-finger toxins found in snake venom, which could lead to the development of safer and more accessible antivenom treatments.

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.

A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent risk loci. Comparisons with other psychiatric disorders and candidate gene analyses provide new insights into major depressive disorder.

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.

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.

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.

The association between certain mitochondrial DNA variants and increased risk of late-onset diseases in humans could be explained by a direct role of mitochondrial DNA in the regulation of cellular proteostasis.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Climate change and land use change may have independent or interactive effects on species’ distributions. Here, the authors show that changes in bird, lepidopteran and plant ranges across Great Britain are often explained by individual or additive effects of land conversion and temperature change.

A smartphone-based system, designed to induce a steady gaze in children using cartoon-like video stimuli, can identify visually impaired children across a wide range of ophthalmic disorders, based on analysis of gazing behaviors and facial features.

In this largest whole-exome sequencing study of epilepsies to date, the Epi25 Collaborative identified extremely rare variants that confer risk for diverse epilepsy subtypes, highlighting roles in synaptic transmission and neuronal excitability.

Red List information is used to generate global maps of the likelihood of impacts on terrestrial vertebrates exerted by agriculture, hunting and trapping, logging, pollution, invasive species and climate change.

Habitat loss and climate change are widely acknowledged as drivers of wildlife population change, but socioeconomic impacts are relatively unexplored. This study explores drivers of population change in large carnivores and reveals that socioeconomic growth is more associated with population declines than habitat loss and climate change.

In a new study including 200 families who experienced perinatal death, adding genomic analyses to standard autopsies improved the identification of underlying pathogenic causes and informed genetic counseling.

Global change may affect the resilience of ecosystem functions by altering community composition. Here, Oliver et al.show that in Great Britain since the 1970s there have been significant net declines among animal species that provide key ecosystem functions such as pollination and pest control.

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.

By analysing changes in occupancy among >5,000 species of invertebrates, bryophytes and lichens in the United Kingdom over the past 45 years, the authors find substantial turnover in community composition among all groups, although average declines are evident only among terrestrial non-insect invertebrates.

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

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.

Environmental influences during prenatal development may have implications for health and disease later in life. Here, Czamara et al. assess DNA methylation in cord blood from new-born under various models including environmental and genetic effects individually and their additive or interaction effects.

A genome-wide-association meta-analysis of 18,381 austim spectrum disorder (ASD) cases and 27,969 controls identifies five risk loci. The authors find quantitative and qualitative polygenic heterogeneity across ASD subtypes.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

A consortium reports the tripling of the number of genetic markers in Phase II of the International HapMap Project. This map of human genetic variation will continue to revolutionize discovery of susceptibility loci in common genetic diseases, and study of genes under selection in humans.