Search

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

Lape et al. use electronic health records and a discovery-replication cohort study design to investigate links between common pathogens and non-communicable diseases. Evidence is found for over 200 associations, such as a role for human cytomegalovirus in ulcerative colitis.

Bosonic qubits can be engineered to feature intrinsic protection against certain kinds of errors, which makes quantum error correction across many bosonic qubits possible with less overhead.

Across 13 longitudinal studies (3,737 adults), the authors show that brain atrophy parallels memory loss, with a stronger coupling in later life. APOE ε4 increases decline, yet genetic risk does not modify the brain–memory relationship.

Long-lived entanglement is a key resource for quantum metrology with optical clocks. Rydberg-based entangling gates within arrays of neutral atoms enable the generation of clock-transition Bell states with high fidelity and long coherence times.

Differentiating neutrophil functional states is difficult. Here the authors show, using single cell RNA-sequencing and trajectory analyses, that mouse neutrophils can be presented as a transcriptome continuum rather than discrete subsets, but are affected by inflammation to express distinct transcriptional states.

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 integrative genomic analysis of several hundred endometrial carcinomas shows that a minority of tumour samples carry copy number alterations or TP53 mutations and many contain key cancer-related gene mutations, such as those involved in canonical pathways and chromatin remodelling; a reclassification of endometrial tumours into four distinct types is proposed, which may have an effect on patient treatment regimes.

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.

Analysis of exomes and transcriptomes from 100 African American patients with acute myeloid leukemia identifies ancestry-related variation in mutation profiles and survival. Refined risk classification suggests clinical relevance of these ancestry-associated differences.

Seshadri, Davis and colleagues show that individuals who do not develop an infection with Mycobacterium tuberculosis (Mtb), despite exposure to the bacteria and expansion of CD4⁺ T cell clones specific to Mtb antigens, show enrichment of T_H17 cell and T regulatory functional programs.

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.

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.

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.

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 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.

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.

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 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.

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.

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.

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

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.

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.

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.

The response to infectious and inflammatory challenges differs among people but the reasons for this are poorly understood. Here the authors explore the impact of variables such as age, sex, and the capacity for controlling inflammation and maintaining immunocompetence, linking this capacity to favourable health outcomes and lifespan.

Reduced precipitation changes competitive outcomes among plant species, and species pairs that were functionally more similar were less likely to experience these changes.

There are dynamic interactions between immune cells and β cells that lead to β cell destruction in the context of autoimmune diabetes. Here the authors show that TET2, a methylcytosine dioxygenase, can regulate this interaction and deletion of TET2 can prevent the autoimmune destruction of β cells in mice.

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.

Mouse models of lung and colorectal cancer with sporadic DNA mismatch repair deficiency clarify that the intratumor heterogeneity and clonal architecture rather than tumor mutational burden are powerful determinants of immunotherapy response.

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.

Large-scale sequence-based analyses identify novel risk variants and susceptibility genes for Crohn’s disease, and implicate mesenchymal cell-mediated intestinal homeostasis in disease etiology.

A study shows that clonal haematopoiesis of indeterminate potential is associated with an increased risk of chronic liver disease specifically through the promotion of liver inflammation and injury.

Most studies of the genetics of the metabolome have been done in individuals of European descent. Here, the authors integrate genomics and metabolomics in Black individuals, highlighting the value of whole genome sequencing in diverse populations and linking circulating metabolites to human disease.

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

A spatially resolved transcriptional atlas of the mid-gestational developing human brain has been created using laser-capture microdissection and microarray technology, providing a comprehensive reference resource which also enables new hypotheses about the nature of human brain evolution and the origins of neurodevelopmental disorders.