The rapid pace of innovation in biological imaging and the diversity of its applications have prevented the establishment of a community-agreed standardized data format. We propose that complementing established open formats such as OME-TIFF and HDF5 with a next-generation file format such as Zarr will satisfy the majority of use cases in bioimaging. Critically, a common metadata format used in all these vessels can deliver truly findable, accessible, interoperable and reusable bioimaging data.

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Auditory experience drives neural circuit refinement during windows of heightened brain plasticity, but little is known about the genetic regulation of this developmental process. The primary auditory cortex (A1) of mice exhibits a critical period for thalamocortical connectivity between postnatal days P12 and P15, during which tone exposure alters the tonotopic topography of A1. We hypothesized that a coordinated, multicellular transcriptional program governs this window for patterning of the auditory cortex. To generate a robust multicellular map of gene expression, we performed droplet-based, single-nucleus RNA sequencing (snRNA-seq) of A1 across three developmental time points (P10, P15, and P20) spanning the tonotopic critical period. We also tone-reared mice (7 kHz pips) during the 3-d critical period and collected A1 at P15 and P20. We identified and profiled both neuronal (glutamatergic and GABAergic) and nonneuronal (oligodendrocytes, microglia, astrocytes, and endothelial) cell types. By comparing normal- and tone-reared mice, we found hundreds of genes across cell types showing altered expression as a result of sensory manipulation during the critical period. Functional voltage-sensitive dye imaging confirmed GABA circuit function determines critical period onset, while Nogo receptor signaling is required for its closure. We further uncovered previously unknown effects of developmental tone exposure on trajectories of gene expression in interneurons, as well as candidate genes that might execute tonotopic plasticity. Our single-nucleus transcriptomic resource of developing auditory cortex is thus a powerful discovery platform with which to identify mediators of tonotopic plasticity.

Biological imaging is one of the most innovative fields in the modern biological sciences. New imaging modalities, probes, and analysis tools appear every few months and often prove decisive for enabling new directions in scientific discovery. One feature of this dynamic field is the need to capture new types of data and data structures. While there is a strong drive to make scientific data Findable, Accessible, Interoperable and Reproducible (FAIR, 1), the rapid rate of innovation in imaging impedes the unification and adoption of standardized data formats. Despite this, the opportunities for sharing and integrating bioimaging data and, in particular, linking these data to other "omics" datasets have never been greater; therefore, to every extent possible, increasing "FAIRness" of bioimaging data is critical for maximizing scientific value, as well as for promoting openness and integrity. In the absence of a common, FAIR format, two approaches have emerged to provide access to bioimaging data: translation and conversion. On-the-fly translation produces a transient representation of bioimage metadata and binary data but must be repeated on each use. In contrast, conversion produces a permanent copy of the data, ideally in an open format that makes the data more accessible and improves performance and parallelization in reads and writes. Both approaches have been implemented successfully in the bioimaging community but both have limitations. At cloud-scale, those shortcomings limit scientific analysis and the sharing of results. We introduce here next-generation file formats (NGFF) as a solution to these challenges.

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.