A spatiotemporal atlas of cholestatic injury and repair in mice.

Cholestatic liver injuries, characterized by regional damage around the bile ductular region, lack curative therapies and cause considerable mortality. Here we generated a high-definition spatiotemporal atlas of gene expression during cholestatic injury and repair in mice by integrating spatial enhanced resolution omics sequencing and single-cell transcriptomics. Spatiotemporal analyses revealed a key role of cholangiocyte-driven signaling correlating with the periportal damage-repair response. Cholangiocytes express genes related to recruitment and differentiation of lipid-associated macrophages, which generate feedback signals enhancing ductular reaction. Moreover, cholangiocytes express high TGFß in association with the conversion of liver progenitor-like cells into cholangiocytes during injury and the dampened proliferation of periportal hepatocytes during recovery. Notably, Atoh8 restricts hepatocyte proliferation during 3,5-diethoxycarbonyl-1,4-dihydro-collidin damage and is quickly downregulated after injury withdrawal, allowing hepatocytes to respond to growth signals. Our findings lay a keystone for in-depth studies of cellular dynamics and molecular mechanisms of cholestatic injuries, which may further develop into therapies for cholangiopathies.

A spatiotemporal atlas of mouse liver homeostasis and regeneration.

The mechanism by which mammalian liver cell responses are coordinated during tissue homeostasis and perturbation is poorly understood, representing a major obstacle in our understanding of many diseases. This knowledge gap is caused by the difficulty involved with studying multiple cell types in different states and locations, particularly when these are transient. We have combined Stereo-seq (spatiotemporal enhanced resolution omics-sequencing) with single-cell transcriptomic profiling of 473,290 cells to generate a high-definition spatiotemporal atlas of mouse liver homeostasis and regeneration at the whole-lobe scale. Our integrative study dissects in detail the molecular gradients controlling liver cell function, systematically defining how gene networks are dynamically modulated through intercellular communication to promote regeneration. Among other important regulators, we identified the transcriptional cofactor TBL1XR1 as a rheostat linking inflammation to Wnt/ß-catenin signaling for facilitating hepatocyte proliferation. Our data and analytical pipelines lay the foundation for future high-definition tissue-scale atlases of organ physiology and malfunction.

LettuceDB: an integrated multi-omics database for cultivated lettuce.

Crop genomics has advanced rapidly during the past decade, which generated a great abundance of omics data from multi-omics studies. How to utilize the accumulating data becomes a critical and urgent demand in crop science. As an attempt to integrate multi-omics data, we developed a database, LettuceDB (https://db.cngb.org/lettuce/), aiming to assemble multidimensional data for cultivated and wild lettuce germplasm. The database includes genome, variome, phenome, microbiome and spatial transcriptome. By integrating user-friendly bioinformatics tools, LettuceDB will serve as a one-stop platform for lettuce research and breeding in the future. Database URL: https://db.cngb.org/lettuce/.

STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization.

Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualization and analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.

High-resolution 3D spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae.

Drosophila has long been a successful model organism in multiple biomedical fields. Spatial gene expression patterns are critical for the understanding of complex pathways and interactions, whereas temporal gene expression changes are vital for studying highly dynamic physiological activities. Systematic studies in Drosophila are still impeded by the lack of spatiotemporal transcriptomic information. Here, utilizing spatial enhanced resolution omics-sequencing (Stereo-seq), we dissected the spatiotemporal transcriptomic changes of developing Drosophila with high resolution and sensitivity. We demonstrated that Stereo-seq data can be used for the 3D reconstruction of the spatial transcriptomes of Drosophila embryos and larvae. With these 3D models, we identified functional subregions in embryonic and larval midguts, uncovered spatial cell state dynamics of larval testis, and revealed known and potential regulons of transcription factors within their topographic background. Our data provide the Drosophila research community with useful resources of organism-wide spatiotemporally resolved transcriptomic information across developmental stages.

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.

PIRD: Pan Immune Repertoire Database.

MOTIVATION: T and B cell receptors (TCRs and BCRs) play a pivotal role in the adaptive immune system by recognizing an enormous variety of external and internal antigens. Understanding these receptors is critical for exploring the process of immunoreaction and exploiting potential applications in immunotherapy and antibody drug design. Although a large number of samples have had their TCR and BCR repertoires sequenced using high-throughput sequencing in recent years, very few databases have been constructed to store these kinds of data. To resolve this issue, we developed a database. RESULTS: We developed a database, the Pan Immune Repertoire Database (PIRD), located in China National GeneBank (CNGBdb), to collect and store annotated TCR and BCR sequencing data, including from Homo sapiens and other species. In addition to data storage, PIRD also provides functions of data visualization and interactive online analysis. Additionally, a manually curated database of TCRs and BCRs targeting known antigens (TBAdb) was also deposited in PIRD. AVAILABILITY AND IMPLEMENTATION: PIRD can be freely accessed at https://db.cngb.org/pird.

Access to RNA-sequencing data from 1,173 plant species: The 1000 Plant transcriptomes initiative (1KP).

BACKGROUND: The 1000 Plant transcriptomes initiative (1KP) explored genetic diversity by sequencing RNA from 1,342 samples representing 1,173 species of green plants (Viridiplantae). FINDINGS: This data release accompanies the initiative's final/capstone publication on a set of 3 analyses inferring species trees, whole genome duplications, and gene family expansions. These and previous analyses are based on de novo transcriptome assemblies and related gene predictions. Here, we assess their data and assembly qualities and explain how we detected potential contaminations. CONCLUSIONS: These data will be useful to plant and/or evolutionary scientists with interests in particular gene families, either across the green plant tree of life or in more focused lineages.