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The authors simulate phytoplankton macromolecular composition—proteins, carbohydrates and lipids—under present and future scenarios. They show increased protein allocation in subtropical phytoplankton but declines in high-latitude populations under warming, with implications for marine food webs.

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

The authors model the emergence of climate-driven changes in Antarctic sea ice, phytoplankton, krill, fish and penguins. They show earlier emergence for higher trophic levels, as well as highly seasonal and regional responses.

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.

Here, the authors perform large trans-ancestry fine-mapping analyses identifying large numbers of association signals and putative target genes for colorectal cancer risk, advancing our understanding of the genetic and biological basis of this cancer.

In this study, long-read RNA sequencing achieves accurate single-nucleotide polymorphism calling, haplotype phasing and allele-specific expression analysis.

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

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.

Large-effect variants in autism remain elusive. Here, the authors use long-read sequencing to assemble phased genomes for 189 individuals, identifying pathogenic variants in TBL1XR1, MECP2, and SYNGAP1, plus nine candidate structural variants missed by short-read methods.

Zonal positioning in the liver determines whether the CTNNB1 oncogene can induce liver cancer.

A combination of high-resolution spatial imaging, spatial proteomics and transcriptional data reveals sparse and heterogeneous bacterial signals in gliomas and brain metastases.

A multi-ancestry genome-wide association study meta-analysis, combined with transcriptome- and methylome-wide association analyses, identifies risk loci associated with colorectal cancer. Credible effector genes and their target tissues are also highlighted, showing that over a third probably act outside the colonic mucosa.

How extracellular calcium can trigger Nlrp3 inflammasome activation has been somewhat controversial and unclear. Here the authors show calciprotein particles are taken up by myeloid cells via calcium-sensing receptor-dependent macropinocytosis in response to high levels of extracellular Ca2+ and this pathway might be critical to inflammatory conditions.

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.

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.

In cancer many gene variants may contribute to disease etiology, but the impact of a given gene variant may have varied effect size. Here, the authors analyse summary statistics of genome-wide association studies from fourteen cancers, and show the utility of polygenic risk scores may vary depending on cancer type.

Pooling participant-level genetic data into a single analysis can result in variance stratification, reducing statistical performance. Here, the authors develop variant-specific inflation factors to assess variance stratification and apply this to pooled individual-level data from whole genome sequencing.

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.

Previous studies have shown that both rare pathogenic mutations and common genetic variants contribute to the familial risk of developing colorectal cancer. Here, the authors carry out a two-stage genome-wide association study and identify six new loci associated with colorectal cancer.

Climate change is a major human rights challenge. This research shows how climate change is impeding the human rights of Ni-Vanuatu, outlines what can be done in response, and discusses how the future loss and damage fund should consider human rights restoration and compensation packages.

Most genetic studies have been done on European cohorts, which affects the efficacy of polygenic risk scores in non-European populations. Here, the authors demonstrate that a colorectal cancer PRS including Asian and European ancestries has improved performance over the European-centric PRS across racial and ethnic groups.

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

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 analyses based on whole-genome sequencing and imputation identify 40 new risk variants for colorectal cancer, including a strongly protective low-frequency variant at CHD1 and loci implicating signaling and immune function in disease etiology.

Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient ‘biotypes’ characterized by partially distinct disease mechanisms.

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.

Zeng et al. show that TDP-43, known for repressing cryptic exon usage in frontotemporal dementia/amyotrophic lateral sclerosis, also controls alternative polyadenylation, impacting expression of disease-linked genes (SFPQ, NEFL and TMEM106B).

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.

An integrated analysis of de novo and inherited coding variants in 42,607 individuals with autism spectrum disorder identifies 60 risk genes of which five have not previously been associated with neurodevelopmental disorders.

Using well-calibrated statistical methods the authors jointly analyze Undiagnosed Diseases Network genomes, identifying known and novel disease genes. Software is publicly available to support future cross-cohort rare disease discovery efforts.

The authors report a computational framework for determining the meiotic/mitotic origin of nondisjunction (NDJ) in trisomies without parental data. Applying this to Down syndrome, they uncover links between NDJ error stage and leukemia genomics.

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 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.

The authors collate literature on the responses of bird assemblages to forest loss and show that locations with a more variable natural environment and a longer history of agricultural land use have bird assemblages that are more tolerant to forest loss.

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.

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

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.

Lim et al. identify CD34 as a surface marker of the heart’s sinoatrial node pacemaker cells, enabling their isolation from stem cell differentiation cultures, advancing future disease modeling, drug discovery, and biological pacemaker applications.

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.

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.

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.

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 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.