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To enable a sensed RNA to activate diverse RNA effectors, the authors engineer a programmable dual-site ribozyme that, upon RNA trigger binding, self-cleaves to release an embedded RNA. It enables trigger-dependent release of diverse ncRNAs and controls CRISPR-Cas9 editing in zebrafish and human cells.

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

Neurocognitive impairment and premature aging often occur in childhood survivors of cancer. Here, the authors investigate the link between biological markers of age and neurocognitive functioning in survivors of childhood cancer who received either central nervous system (CNS)-targeted or non-CNS-targeted therapy.

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.

TDP-43 dysfunction in ALS/FTD causes faulty splicing of the KCNQ2 ion channel, leading to toxic protein buildup, neuron hyperactivity and a potential new biomarker and treatment target using RNA-based therapies.

High-depth sequencing of non-cancerous tissue from patients with metastatic cancer reveals single-base mutational signatures of alcohol, smoking and cancer treatments, and reveals how exogenous factors, including cancer therapies, affect somatic cell evolution.

A meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

Apolipoprotein L1 genetic variants contribute to a subtype of proteinuric kidney disease referred to as APOL1-mediated kidney disease (AMKD). Here the authors report the discovery and characterization of potent and selective APOL1 ion channel inhibitors for the potential treatment of AMKD.

Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.

Predicting highly enantioselective ligands for a given asymmetric catalytic reaction is very challenging, but could greatly reduce the need for high-throughput, trial-and-error experimentation. Here, the authors report a freely available, automated tool to identify appropriate chiral ligands for given substrates in asymmetric catalysis.

Urinary albumin-to-creatinine ratio (UCAR) is associated with various clinical outcomes such as kidney disease and cardiovascular disease. Here, the authors report genome-wide meta-analysis in over 500,000 individuals and find 68 UACR loci, followed by statistical fine-mapping, gene prioritization and experimental validation in flies.

The authors present a multiomics study of type 2 diabetes and quantitative blood lipid and lipoprotein traits in Hispanic/Latino populations. They demonstrate how integrating GWAS with omics characterization can advance precision medicine.

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.

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.

Integrated multi-omic analyses using samples from the TRACERx study highlight cross-talk between DNA hypermethylation and genomic lesions in non-small cell lung cancer.

Spatial multi-omics methodologies are essential for capturing the molecular heterogeneity of complex biological systems. In this study, the authors introduce a multi-omics imaging workflow capable of mapping metabolite-protein interactions with spatial specificity, enabling pathway-level resolution across distinct placental tissue microenvironments.

Physical realizations of qubits are often vulnerable to leakage errors, where the system ends up outside the basis used to store quantum information. A leakage removal protocol can suppress the impact of leakage on quantum error-correcting codes.

In lung adenocarcinoma, antibodies against endogenous retroviruses promote anti-tumour activity, and expression of endogenous retroviruses can predict outcomes of immunotherapy.

Breast cancer risk for BRCA1/BRCA2 mutation carriers varies depending on other genetic factors. Here, the authors perform a case-only genome-wide association study and highlight novel loci associated with breast cancer risk for BRCA1/BRCA2 mutation carriers.

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.

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.

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.

Combination of epidemiology, preclinical models and ultradeep DNA profiling of clinical cohorts unpicks the inflammatory mechanism by which air pollution promotes lung cancer

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.

Major histocompatibility complex (MHC) loss of heterozygosity, allele-specific mutation and measurement of expression and repression (MHC Hammer) detects disruption to human leukocyte antigens due to mutations, loss of heterogeneity, altered gene expression or alternative splicing. Applied to lung and breast cancer datasets, the tool shows that these aberrations are common across cancer and can have clinical implications.

This overview of the ENCODE project outlines the data accumulated so far, revealing that 80% of the human genome now has at least one biochemical function assigned to it; the newly identified functional elements should aid the interpretation of results of genome-wide association studies, as many correspond to sites of association with human disease.

Children receiving chest radiotherapy for childhood cancer have a higher risk of developing breast cancer later in life. Here, using the data from the Childhood Cancer Survivor Study, the authors investigate the treatment and survival outcomes of breast cancer patients who previously survived childhood cancer finding them to receive altered treatment and having increased mortality.

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

Reductive aminases show strong potential for the sustainable synthesis of chiral amines, but their application in industrial scale processes is lacking. Now, such an enzyme is screened and engineered allowing its use in commercial manufacturing of abrocitinib JAK1 inhibitor in multi-metric tons.

Many SARS-CoV-2 infections may go undetected through conventional PCR or lateral flow tests. Here, the authors analyse the utility of analysing longitudinal nucleocapsid antibody trajectories to improve identification of prior SARS-CoV-2 infections using surveillance data from the UK.

Mutations that dysregulate Notch1 and Ras/PI3K signalling are common in T-cell acute lymphoblastic leukaemia; here, treatment with a PI3K inhibitor is shown to induce drug resistance that is associated with downregulation of activated Notch1 signalling, suggesting that inhibition of both Notch1 and PI3K could promote drug resistance.

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.

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.

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.

A genome-wide study by the Long COVID Host Genetics Initiative identifies an association between the FOXP4 locus and long COVID, implicating altered lung function in its pathophysiology.

Computational and machine-learning approaches that integrate genomic and transcriptomic variation from paired primary and metastatic non-small cell lung cancer samples from the TRACERx cohort reveal the role of transcriptional events in tumour evolution.

A longitudinal evolutionary analysis of 126 lung cancer patients with metastatic disease reveals the timing of metastatic divergence, modes of dissemination and the genomic events subject to selection during the metastatic transition.

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.

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.

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.