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

Vassy, Dornisch and colleagues developed a genomics-based prostate cancer risk model to support a randomized clinical trial of precision screening in a national healthcare system.

Incorporating membrane-destabilizing zwitterionic lipids into commercially available LNPs boosts mRNA expression in antigen-presenting cells within lymph nodes, enhancing cytotoxic T cell activation, and dampens reactogenicity in mice.

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 vivo experiments and clinical cohort analyses show that hypoxia-inducible factor 2 (HIF2)-induced parathyroid hormone-related protein (PTHrP) expression contributes to cachexia in the context of renal cell carcinoma (RCC). The pathway can be targeted by HIF2 inhibitors, including belzutifan, which may reduce cachexia in patients with RCC.

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.

A high-bandwidth neuromotor interface offers performant out-of-the-box generalization across people.

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.

Resistance to rifamycin antibiotics, which target bacterial RNA polymerases, is a growing problem. Here, the authors identify gene clusters from soil metagenomes encoding production of rifamycin analogues that are active against rifampicin-resistant bacteria through a distinct mechanism.

African ancestry is a known risk factor for prostate cancer development, but the genetic determinants of this are incompletely understood. Here, the authors identify 172 potentially pathogenic variants which are enriched in an African population.

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.

Experimental measurements of high-order out-of-time-order correlators on a superconducting quantum processor show that these correlators remain highly sensitive to the quantum many-body dynamics in quantum computers at long timescales.

Functionally relevant phosphorylation sites are detected by integrating phosphoproteomic and phenotypic data.

This study explores the relationship between telomere length and clonal hematopoiesis. Splicing factor and PPM1D gene mutations are more frequent in people with genetically predicted shorter telomere lengths, suggesting that these mutations protect against the consequences of telomere attrition.

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.

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.

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

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 study of several longitudinal birth cohorts and cross-sectional cohorts finds only moderate overlap in genetic variants between autism that is diagnosed earlier and that diagnosed later, so they may represent aetiologically different conditions.

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.

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.

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.

Metformin may serve as a non-toxic intervention to inhibit mitochondrial metabolism and slow DNMT3A-R882 clonal haematopoiesis expansion, thus delaying or averting progression to acute myeloid leukaemia.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Polygenic risk scores predict the likelihood that an individual will develop a certain cancer, however these are often specific for a given population. Here, the authors show that a risk score developed to assess the risk of breast cancer in European women can also predict risk in Asian populations.

Wave propagation is often nonlinear in character, yet the interplay between disorder and nonlinearity remains elusive. Kim et al. use experiments and corroborating numerical simulations to investigate this phenomenon and demonstrate superdiffusive energy transport in disordered granular chains.

Genome-wide analyses identify variants associated with sinus node dysfunction, distal conduction disease and pacemaker implantation, implicating ion channel function, cardiac developmental programs and sarcomeric structure in bradyarrhythmia susceptibility.

Tumor-derived soluble PD-L1 drives immune checkpoint inhibitor (ICI) resistance and has recently been reported to be removed by therapeutic plasma exchange (TPE). Here, the authors report a phase I clinical trial investigating the combination of radiotherapy, TPE, and ICI rechallenge in patients with ICI-refractory metastatic melanoma with high PD-L1.

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.

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.

A multi-ancestry meta-regression study analyses diverse genome-wide association studies and genome loci associated with tobacco and alcohol use.

This study unveils a synergistic bioinspired design, seamlessly merging owl feather and cicada wing geometries into propeller configurations. Authors achieve reduction in noise by up to 5.5 dB while boosting aerodynamic efficiency by over 20% compared to current industry standards.

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

Ramabadran et al. identify a DNA methylation-independent role for DNMT3A in stem cell activation, mediated through recruitment of SF3B1 and splicing regulation.

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.

Differences in MCT1 function among melanoma cells confer differences in oxidative stress resistance and metastatic potential.

Nguyen et al. identify TDP-43 and METTL3 as key regulators of disrupted RNA splicing in Huntington’s disease, offering insight into how TDP-43 mislocalization and aberrant m6A RNA modification and localization relate to disease pathogenesis.