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Measurement-free quantum error correction allows to avoid costly mid-circuit measurements and feed-forward controls. Here, the authors present a toolbox of logical operations needed for measurement-free fault-tolerant universal quantum computing and demonstrate a measurement-free logical fault-tolerant logical algorithm using an error-detecting code on an ion-trap quantum processor.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

Intentional defect creation in graphene is key to engineering its electrical, chemical, magnetic and mechanical properties. Robertsonet al. create defects by electron beam irradiation with sub-knock-on damage threshold, and show control over the defect position at the nanoscale and over the defect complexity.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

Polyethylene glycol conjugation to chimeric antigen receptor T (CAR T) cells creates a physical block between CAR T cell interactions and other immune and tumour cells, controlling tumour lysis and immune response stimulation to mitigate cytokine release syndrome.

JMML is an aggressive hematologic malignancy with myeloproliferative characteristics affecting young children. Here the authors report that C-type lectin-like molecule-1 (CLL-1) is upregulated in JMML and they develop CLL-1 CAR T cells showing in vitro and in vivo anti-JMML activity.

Aarrestad et al. show that, in contrast to psychedelics, the nonhallucinogenic psychoplastogen tabernanthalog promotes neuroplasticity through 5-HT_2AR activation without immediately increasing extracellular glutamate levels or immediate early gene expression.

Singla et al. report the secondary analysis of the Scaling Up Maternal Mental healthcare by Increasing access to Treatment (SUMMIT) trial.

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.

Radiolabel-based bioassays, nanoSIMs, metagenomics and lipidomics conducted on samples collected along the East Pacific Rise show higher than expected chemosynthetic microbial activity on inactive vents.

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

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.

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 myeloid cells in gliomas, a type of brain tumour, used a factor-based computational framework to reveal four immunomodulatory gene-expression programs that are expressed across myeloid cell types, driven by microenvironmental cues and predictive of therapeutic response.

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.

Liu et al. developed a platform to identify transcription factors (TFs) that turn stem cells into desired cell types. They discovered six key TFs that produce microglia efficiently, enhancing cell differentiation methods.

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.

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.

Loss of let-7, a key microRNA, causes lung alveolar stem cells to grow abnormally and dieprematurely, leading to scarring and lung damage. Here the study links let-7 loss to cancer-like signals and epigenomic gene changes, revealing new treatment paths for lung fibrosis.

The Vertebrate Genome Project has used an optimized pipeline to generate high-quality genome assemblies for sixteen species (representing all major vertebrate classes), which have led to new biological insights.

AlphaFold is used to predict the structures of almost all of the proteins in the human proteome—the availability of high-confidence predicted structures could enable new avenues of investigation from a structural perspective.

Multisystem inflammatory syndrome in children (MIS-C) onsets in COVID-19 patients with manifestations similar to Kawasaki disease (KD). Here the author probe the peripheral blood transcriptome of MIS-C patients to find signatures related to natural killer (NK) cell activation and CD8+ T cell exhaustion that are shared with KD patients.

A recurrent, transformer-based neural network, called AlphaQubit, learns high-accuracy error decoding to suppress the errors that occur in quantum systems, opening the prospect of using neural-network decoders for real quantum hardware.

An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.

AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.

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.

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.

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.

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.

Genome-wide ancient DNA data from individuals from the Middle Bronze Age to Iron Age documents large-scale movement of people from the European continent between 1300 and 800 bc that was probably responsible for spreading early Celtic languages to Britain.

Aeneas, a generative neural network trained on ancient texts, helps historians contextualize inscriptions and perform epigraphic tasks, offering an improved starting point for historical research.

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.

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.

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.

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.

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.

Infection with SARS-CoV2 and the development of Coronavirus disease 2019 (COVID-19) has been linked to induction of autoimmunity and autoantibody production. Here the authors characterise the new-onset IgG autoantibody response in hospitalised patients with COVID-19 which they correlate to the magnitude of the SARS-CoV2 response.

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.

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.