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

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.

The ρ-type GABAA receptors are potential therapeutic targets in several neurological conditions. Here, authors elucidate interactions of it with three therapeutic drugs, offering mechanistic insights and a prospective basis for further pharmaceutical development.

Xenotransplantation of a genetically edited pig kidney with a thymic autograft into a brain-dead human for 61 days with immunosuppression resulted in stable kidney function without proteinuria, and xenograft rejection was treated and reversed by the end of the study.

Nine researchers, editors and science communicators share their views about the barriers that Asian scientists encounter in publishing their work and becoming more visible on the international level.

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

E. coli sequence type 131 is a significant cause of community-onset infection. Here, the authors perform a prospective household-based cohort study in Singapore including samples from humans, companion animals, the environment, and food, to characterise transmission and carriage dynamics.

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.

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.

MetaSTAAR enables functionally informed rare variant association analysis in biobank-scale cohorts using an efficient, sparse matrix approach for summary statistic storage.

T-cell acute lymphoblastic leukemia is a highly aggressive disease with varying recurrence rates. Here, the authors build a single cell transcriptomic atlas of childhood T-cell acute lymphoblastic leukaemia (T-ALL). They identified a distinctive cancer cell state that correlates with high risk, treatment refractory T-ALL.

Here, the authors perform a machine learning meta-analysis of Parkinson’s disease (PD) classification based on microbiome features, showing that the accuracy of models can be generalizable and improve disease specificity when trained on multiple datasets, identifying PD-associated microbial pathways, including those involved in solvent and pesticide biotransformation.

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.

Living plant collections hold an immense wealth of plant diversity and have critical educational, scientific and conservation roles. This Perspective examines current data management practices of living collections and advocates for higher data standards and a robust and inclusive global data ecosystem.

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.

Examination of a complete structural phase diagram of twisted trilayer graphene shows that several large-scale moiré domain lattices can be formed, the physical properties of which can be tuned by the twist angles between layers.

STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components. STAAR accounts for population structure and relatedness and is scalable for analyzing large whole-genome sequencing studies.

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.

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.

By affecting which form of a gene is expressed, alternative splicing is a major source of diversity in the nervous system. Here, the authors present an atlas of splice variants across neurons, and explore its impacts and mechanisms in the nematode nervous system.

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.

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.

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.

Data collected from more than 2,000 taxa provide an unparalleled opportunity to quantify how extreme wildfires affect biodiversity, revealing that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas.

The planum temporale is a key structure in the human language network. Here the authors show that planum temporale asymmetry at birth in baboons predicts the development of communicative right-hand use, which suggests some common features in the wiring of communicative properties between species.

Typical quantum error correcting codes assign fixed roles to the underlying physical qubits. Now the performance benefits of alternative, dynamic error correction schemes have been demonstrated on a superconducting quantum processor.

Together with an accompanying paper presenting a transcriptomic atlas of the mouse lemur, interrogation of the atlas provides a rich body of data to support the use of the organism as a model for primate biology and health.

Cell type labelling in single-cell datasets remains a major bottleneck. Here, the authors present AnnDictionary, an open-source toolkit that enables atlas-scale analysis and provides the first benchmark of LLMs for de novo cell type annotation from marker genes, showing high accuracy at low cost.

Together with a companion paper, the generation of a transcriptomic atlas for the mouse lemur and analyses of example cell types establish this animal as a molecularly tractable primate model organism.

The Human Endometrial Cell Atlas integrates single-cell transcriptomic datasets from women with and without endometriosis. Novel and known cell types are registered using spatial transcriptomics to provide a comprehensive map of the human endometrium in controls and endometriosis cases.

An implementation trial conducted across 60 schools in Rwanda found that CyberRwanda, a digital, school-based intervention, did not affect the primary outcomes of modern contraceptive use, childbearing and HIV testing among adolescents but was associated with higher contraceptive use among sexually active participants.

PENSIEVE-AI is a drawing-based, digital cognitive test that can be self-administered in <5 min. It matches traditional tests in detecting cognitive impairment and dementia, offering promise for early detection in literacy-diverse populations.

Controlling nanoscale colloidal crystallization is not straightforward. Such control is now achieved by leveraging a metastable liquid phase of charged nanocrystals.

A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

Parity induces an accumulation of CD8⁺ T cells, including cells with a tissue-resident-memory-like phenotype within human normal breast tissue, offering long-term protection against triple-negative breast cancer.

Ad-sig-hMUC1/ecdCD40L is a recombinant adenovirus vaccine comprising human MUC1 antigen fused to the extracellular domain of the CD40 ligand. Here the authors report the result of a phase I clinical trial of Ad-sig-hMUC1/ecdCD40L in patients with advanced adenocarcinoma.