Jason A. Hilton

The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center has developed the ENCODE Portal database and website as the source for the data and metadata generated by the ENCODE Consortium. Two principles have motivated the design. First, experimental protocols, analytical procedures and the data themselves should be made publicly accessible through a coherent, web-based search and download interface. Second, the same interface should serve carefully curated metadata that record the provenance of the data and justify its interpretation in biological terms. Since its initial release in 2013 and in response to recommendations from consortium members and the wider community of scientists who use the Portal to access ENCODE data, the Portal has been regularly updated to better reflect these design principles. Here we report on these updates, including results from new experiments, uniformly-processed data from other projects, new visualization tools and more comprehensive metadata to describe experiments and analyses. Additionally, the Portal is now home to meta(data) from related projects including Genomics of Gene Regulation, Roadmap Epigenome Project, Model organism ENCODE (modENCODE) and modERN. The Portal now makes available over 13000 datasets and their accompanying metadata and can be accessed at: https://www.encodeproject.org/.

The Encyclopedia of DNA Elements (ENCODE) is an ongoing collaborative research project aimed at identifying all the functional elements in the human and mouse genomes. Data generated by the ENCODE consortium are freely accessible at the ENCODE portal (https://www.encodeproject.org/), which is developed and maintained by the ENCODE Data Coordinating Center (DCC). Since the initial portal release in 2013, the ENCODE DCC has updated the portal to make ENCODE data more findable, accessible, interoperable and reusable. Here, we report on recent updates, including new ENCODE data and assays, ENCODE uniform data processing pipelines, new visualization tools, a dataset cart feature, unrestricted public access to ENCODE data on the cloud (Amazon Web Services open data registry, https://registry.opendata.aws/encode-project/) and more comprehensive tutorials and documentation.

Hundreds of millions of single cells have been analyzed using high-throughput transcriptomic methods. The cumulative knowledge within these datasets provides an exciting opportunity for unlocking insights into health and disease at the level of single cells. Meta-analyses that span diverse datasets building on recent advances in large language models and other machine-learning approaches pose exciting new directions to model and extract insight from single-cell data. Despite the promise of these and emerging analytical tools for analyzing large amounts of data, the sheer number of datasets, data models and accessibility remains a challenge. Here, we present CZ CELLxGENE Discover (cellxgene.cziscience.com), a data platform that provides curated and interoperable single-cell data. Available via a free-to-use online data portal, CZ CELLxGENE hosts a growing corpus of community-contributed data of over 93 million unique cells. Curated, standardized and associated with consistent cell-level metadata, this collection of single-cell transcriptomic data is the largest of its kind and growing rapidly via community contributions. A suite of tools and features enables accessibility and reusability of the data via both computational and visual interfaces to allow researchers to explore individual datasets, perform cross-corpus analysis, and run meta-analyses of tens of millions of cells across studies and tissues at the resolution of single cells.

Among eukaryotes, four major phytoplankton lineages are responsible for marine photosynthesis; prymnesiophytes, alveolates, stramenopiles, and prasinophytes. Contributions by individual taxa, however, are not well known, and genomes have been analyzed from only the latter two lineages. Tiny "picoplanktonic" members of the prymnesiophyte lineage have long been inferred to be ecologically important but remain poorly characterized. Here, we examine pico-prymnesiophyte evolutionary history and ecology using cultivation-independent methods. 18S rRNA gene analysis showed pico-prymnesiophytes belonged to broadly distributed uncultivated taxa. Therefore, we used targeted metagenomics to analyze uncultured pico-prymnesiophytes sorted by flow cytometry from subtropical North Atlantic waters. The data reveal a composite nuclear-encoded gene repertoire with strong green-lineage affiliations, which contrasts with the evolutionary history indicated by the plastid genome. Measured pico-prymnesiophyte growth rates were rapid in this region, resulting in primary production contributions similar to the cyanobacterium Prochlorococcus. On average, pico-prymnesiophytes formed 25% of global picophytoplankton biomass, with differing contributions in five biogeographical provinces spanning tropical to subpolar systems. Elements likely contributing to success include high gene density and genes potentially involved in defense and nutrient uptake. Our findings have implications reaching beyond pico-prymnesiophytes, to the prasinophytes and stramenopiles. For example, prevalence of putative Ni-containing superoxide dismutases (SODs), instead of Fe-containing SODs, seems to be a common adaptation among eukaryotic phytoplankton for reducing Fe quotas in low-Fe modern oceans. Moreover, highly mosaic gene repertoires, although compositionally distinct for each major eukaryotic lineage, now seem to be an underlying facet of successful marine phytoplankton.