Search

Rare cells are often biologically and clinically important, but their low abundance makes them challenging to study using single-cell transcriptomics. Here, the authors develop PURE-seq which integrates FACS and PIP-seq to directly sequence ultra-rare cells. It captures cells at 1 in 1,000,000 rarity, which the authors demonstrate by profiling circulating tumor cells and identifying Egr1 as a regulator of mouse hematopoietic stem cell aging.

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

The authors analyze 162 primary mismatch-repair-deficient gliomas and identify three subgroups underpinned by distinct somatic mutations in replicative DNA polymerases and IDH1.

Here, the authors examine the mechanisms behind cheatgrass’s successful invasion of North American ecosystems. Their genetic analyses and common garden experiments demonstrate that multiple introductions and migrations facilitated cheatgrass local adaptation.

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.

Radiation and steroid dosing can affect the immune composition of brain metastasis (BM). The authors have designed a pilot study of pre-operative stereotactic radiosurgery with low or high dose of peri-operative dexamethasone for resectable brain metastases, here reporting clinical outcomes and characterization of intratumor TCF1+ CD8+ stem-like T cell immune niches in the brain.

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.

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.

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.

Investigation of variation in three cohorts has identified multiple genetic signals associated with the pregnancy-specific liver disorder, intrahepatic cholestasis of pregnancy, giving insight into the disease which can cause preterm birth and stillbirth.

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.

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.

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.

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.

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.

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

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.

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.

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.

Multiomic analysis of blast-phase myeloproliferative neoplasms identifies a chromosome 21 amplicon harboring DYRK1A as a clonal and therapeutically targetable event in around a quarter of cases.

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.

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.

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.

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.

Here the authors evaluate single cell gene expression from mouse and human Huntington’s disease brains, finding incomplete oligodendrocyte maturation and pathways involved. Treating mice with thiamine/biotin ameliorates molecular pathology.

Digitisation of vast archives of histology slides provides opportunities to use machine learning to identify specific tissue substructures associated with disease. Here the authors use self-supervised learning on 1.7 million histology images from 23 human tissues. The model segments tissues, detects pathologies and predicts RNA expression, linking morphology and gene 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.

In a prospective study including 2,300 pediatric and adult patients with liquid and solid tumors, RNA sequencing provided actionable molecular information in 87% of cases, with applications in diagnostics and therapy matching.

Whole-genome sequencing and phenotype data sharing are introduced in a national health system to streamline diagnosis and to discover coding and non-coding variants that cause rare diseases.

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.

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.

High entanglement fidelity between neutral atoms is achieved using highly excited Rydberg states. The unique electron structure provided by alkaline-earth atoms makes it a promising platform for various quantum-technology-based applications.

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.

The human genome includes a large amount of repetitive sequence, such as human satellite II (HSATII), but their function remains largely unknown. Here, Nogalski et al. show that herpesvirus infection induces HSATII RNA expression, which in turn affects virus replication and cell motility.

The evolution of myeloid malignancies is investigated using combined single-cell sequencing and immunophenotypic analysis.

Glioblastoma is an immunologically cold tumour, with poor CD8 + T cell infiltration and enrichment in immunosuppressive tumour-associated myeloid cells. Here, the authors generate a bispecific lipid nanoparticle targeting CD47 and PD-L1, combined with a STING agonist, to promote anti-tumour immunity.

Autophagic activity decreases with age via unknown mechanisms. Here the authors show that expression of the negative autophagy regulator Rubicon increases with age, that its genetic ablation improves lifespan and ameliorates a number of age-associated phenotypes in invertebrates and in mouse models.

Ross Levine and colleagues report that the JAK2^V617F somatic mutation that drives the development of chronic myeloproliferative neoplasms is associated with the presence of a specific inherited SNP in JAK2.

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.

Inputs to functionally related synapses have been suggested to show cooperative summation, although the rules governing these interactions are unclear. Here, Weber et al. uncover non-linear interactions dependent on NMDAR signalling that vary across the proximal-distal axis of individual dendrites.

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.

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.

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

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.