Ze Zhang

Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray–Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.

Sex differences in mammalian complex traits are prevalent and are intimately associated with androgens1-7. However, a molecular and cellular profile of sex differences and their modulation by androgens is still lacking. Here we constructed a high-dimensional single-cell transcriptomic atlas comprising over 2.3 million cells from 17 tissues in Mus musculus and explored the effects of sex and androgens on the molecular programs and cellular populations. In particular, we found that sex-biased immune gene expression and immune cell populations, such as group 2 innate lymphoid cells, were modulated by androgens. Integration with the UK Biobank dataset revealed potential cellular targets and risk gene enrichment in antigen presentation for sex-biased diseases. This study lays the groundwork for understanding the sex differences orchestrated by androgens and provides important evidence for targeting the androgen pathway as a broad therapeutic strategy for sex-biased diseases.

Alerting for imminent earthquakes is particularly challenging due to the high nonlinearity and nonstationarity of geodynamical phenomena. In this study, based on spatiotemporal information (STI) transformation for high-dimensional real-time data, we developed a model-free framework, i.e., real-time spatiotemporal information transformation learning (RSIT), for extending the nonlinear and nonstationary time series. Specifically, by transforming high-dimensional information of the global navigation satellite system into one-dimensional dynamics via the STI strategy, RSIT efficiently utilizes two criteria of the transformed one-dimensional dynamics, i.e., unpredictability and instability. Such two criteria contemporaneously signal a potential critical transition of the geodynamical system, thereby providing early-warning signals of possible upcoming earthquakes. RSIT explores both the spatial and temporal dynamics of real-world data on the basis of a solid theoretical background in nonlinear dynamics and delay-embedding theory. The effectiveness of RSIT was demonstrated on geodynamical data of recent earthquakes from a number of regions across at least 4 y and through further comparison with existing methods.

Background  Extrachromosomal circular DNA (eccDNA) is a kind of DNA that widely exists in eukaryotic cells. Studies in recent years have shown that eccDNA is often enriched during tumors and aging, and participates in the development of cell physiological activities in a special way, so people have paid more and more attention to the eccDNA, and it has also become a critical new topic in modern biological research. Description  We built a database to collect eccDNA, including animals, plants and fungi, and provide researchers with an eccDNA retrieval platform. The collected eccDNAs were processed in a uniform format and classified according to the species to which it belongs and the chromosome of the source. Each eccDNA record contained sequence length, start and end sites on the corresponding chromosome, order of the bases, genomic elements such as genes and transposons, and other information in the respective sequencing experiment. All the data were stored into the TeCD (The eccDNA Collection Database) and the BLAST (Basic Local Alignment Search Tool) sequence alignment function was also added into the database for analyzing the potential eccDNA sequences. Conclusion  We built TeCD, a platform for users to search and obtain eccDNA data, and analyzed the possible potential functions of eccDNA. These findings may provide a basis and direction for researchers to further explore the biological significance of eccDNA in the future.