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Single-cell RNA sequencing maps tissue-level gene expression heterogeneity but faces challenges in interpreting biological signals due to noise and technical confounders. Here, the authors present sciRED, a method that enhances the interpretation of scRNA-seq factorization by linking factors to known covariates and hidden biological phenomena.

Clonal hematopoiesis is driven by the selective advantage of mutant hematopoietic stem cells. Here, authors discover that elevated mitochondrial activity is a targetable mechanism by which mutant hematopoietic stem cells gain a selective advantage.

Dnmt3a mutations in mouse haematopoietic stem and progenitor cells equivalent to R882 mutations in human cause increased mitochondrial respiration, suggesting that this is a mechanism of clonal haematopoiesis and a potential therapeutic target.

Knowledge of the transcriptional programs of human kidney cell populations at homeostasis is limited. Here, the authors show sex-based differences in gene expression of kidney parenchymal cells and examine the complexity of kidney-resident immune cells using single cell RNA sequencing of healthy living kidney donors.

Endothelial cells from vascular-dependent central nervous system (CNS) diseases reveal reactivated fetal pathways, display common hallmarks of disease — including a partial loss of arteriovenous specification and CNS-specific properties as well as an upregulation of MHC class II receptors — and play a key role in the human brain neurovascular unit across development, adulthood and 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.

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.

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.

Cardiomyocytes of heart ventricles consist of subpopulations of trabecular and compact subtypes. Here the authors describe the generation of structurally, metabolically and functionally mature compact ventricular cardiomyocytes as well as mature atrial cardiomyocytes from human pluripotent stem cells.

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.

Genome-wide CRISPR screens in mouse cancer cell lines are used to identify a core, conserved set of genes and pathways that govern how cancer cells evade killing by cytotoxic T lymphocytes.

Multi-omics datasets are integrated to generate a unified and clinically informed molecular classification of meningiomas.

The development of single cell RNA sequencing technologies has been instrumental in advancing our understanding of tissue biology. Here, MacParland et al. performed single cell RNA sequencing of human liver samples, and identify distinct populations of intrahepatic macrophages that may play specific roles in liver disease.

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.

Pugh and colleagues use single-cell RNA sequencing, CRISPR screens and functional assays to define a gradient of developmental and wound-response cell states in glioblastoma stem cells, revealing insights into glioblastoma origins and potential therapeutic targets.

This machine learning method predicts whether single-nucleotide variants disrupt or create phosphorylation sites.

BIONIC uses a deep learning framework for accurate and scalable integration of biological networks.

Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours.

Thomas, Egan et al. report that hexokinase 2 localizes to the nucleus of leukaemic and normal haematopoietic cells to maintain stemness by interacting with nuclear proteins and modulating chromatin accessibility independently of its kinase activity.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A software tool, EPIC, is developed to determine protein complex membership using chromatographic fractionation–mass spectrometry data, and is applied to map the global Caenorhabditis elegans interactome.

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.

Malignant peripheral nerve sheath tumours are an aggressive form of sarcoma, with limited treatment options. Here, the authors utilise DNA methylation and transcriptomic data to identify two subtypes of tumours with potential therapeutic vulnerabilities.

Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population.

The Wnt molecular subgroup of medulloblastoma is associated with better prognosis than the other molecular subgroups. Here, the authors show that activating Wnt signaling impairs tumor development and improves survival in Group 3 and Group 4 medulloblastoma preclinical models.

Distinguishing the drivers of metastasis versus those of the primary tumour in breast cancer remains challenging. Here, the authors explore primary-only, metastatic-only, and shared drivers in breast cancer using mammary-specific transposon mutagenesis screens, which leads to potential therapeutic targets to prevent metastasis.

Molecular heterogeneity of acute myeloid leukaemia (AML) across patients is a major challenge for prognosis and therapy. Here, the authors show that NPM1 mutated AML is a heterogeneous class, consisting of two subtypes which exhibit distinct molecular characteristics, differentiation state, patient survival and drug response.

A human binary protein interactome map that includes around 53,000 protein–protein interactions involving more than 8,000 proteins provides a reference for the study of human cellular function in health and disease.

Wesley et al. describe the developmental trajectories of human foetal liver cell types at single-cell resolution and generate bipotential hepatoblast organoids, which can serve as a new platform to investigate human liver development.

Medulloblastoma is the most common malignant brain tumour in children; having assembled over 1,000 samples the authors report that somatic copy number aberrations are common in medulloblastoma, in particular a tandem duplication of SNCAIP, a gene associated with Parkinson’s disease, which is restricted to subgroup 4α, and translocations of PVT1, which are restricted to Group 3.