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In Drosophila, the physical structure of the eye has a key role in the directional tuning of motion-sensitive neurons, showing how navigational behaviour is tightly associated with anatomy.

High-throughput volume electron microscopy and deep learning-driven automated segmentation have revolutionized the mapping of neural circuits at the level of individual neurons and synapses, revealing new cell types and unexpected network architectures in diverse species. Although prospects for continued progress in connectomics are excellent, substantial technical and conceptual hurdles remain.

Navigation relies on detecting left versus right body asymmetries for gaze and course stability. A central three-layer optic flow-sensitive network with competitive lateral disinhibition extracts asymmetries from complex motion patterns.

To date, various aspects of connectivity have been inferred from electron microscopy (EM) of synaptic contacts, light microscopy of axonal and dendritic arbors, and correlations in activity. However, until now it has not been possible to relate the complex structural wiring between neurons to the function of individual cells. Using a combination of functional imaging and three-dimensional serial EM reconstruction at unprecedented scale, two papers now describe the connectivity of single cells in the mouse visual system. This study investigates the connectivity of inhibitory interneurons in primary visual cortex.

A consensus cell type atlas for the fly brain provides both an intellectual framework and open-source toolchains for brain-scale comparative connectomics.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

FlyWire presents a neuronal wiring diagram of the whole fly brain with annotations for cell types, classes, nerves, hemilineages and predicted neurotransmitters, with data products and an open ecosystem to facilitate exploration and browsing.

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.

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.

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.

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.

Single motor neurons in Drosophila are stimulated to show that they direct head movements towards specific postures rather than generating fixed movement vectors, suggesting that the brain controls movements through a continuing proprioceptive–motor loop.

The relationships that control seed production in trees are key to understand evolutionary pressures that have shaped forests. A global synthesis of fecundity data reveals that while seed production is not constrained by a strict size-number trade-off, it is influenced by taxonomy and nutrient allocation.

Bacterial chemosensory systems are grouped into 17 flagellar classes (F1-17). Here the authors employ electron cryotomography and comparative genomics to characterise the chemosensory arrays in γ-proteobacteria and identify a structural distinct form of F7 that was repurposed to a different biological role over the course of its evolution.

High-frequency measurements at low temperatures typically require connecting external sources to the device using bulky, lossy, and expensive RF cables. To address this issue, the authors present on-chip Josephson junction arrays that generate GHz-range microwaves with a tuneable frequency controlled by a DC bias voltage. This offers a compact, efficient alternative for high-frequency applications.

Richter syndrome (RS) is the transformation of chronic lymphocytic leukaemia (CLL) into aggressive lymphoma, in most cases diffuse large B-cell lymphoma (DLBCL). Here, the authors characterize the DNA methylation and transcriptomic profiles of RS samples, find a clonally-related CLL epigenetic imprint, and develop classifiers for “RS-type” de novo DLBCLs.

An analysis of skyrmion dynamics at different temperatures and electric drive currents is used to develop a complete description of the skyrmion Hall angle in ferromagnetic multilayers from the creep to the flow regime and illustrates that skyrmion trajectories can be engineered for device applications.