Chinese researchers provide information on a curated collection of data from epigenome-wide association studies (EWAS) spanning a range of traits, conditions, and cell types. The EWAS Atlas currently contains nearly 329,200 high-quality, manually curated associations involving epigenetic associations, particularly those involving DNA methylation, the team reports. These associations — representing 305 traits — were documented in more than 100 tissues or cell lines, the authors say, and were gleaned from more than 1,800 cohorts analyzed for hundreds of studies. "Considering the great potential of epigenetic modifications in precision medicine," they write, "EWAS Atlas would be of great utility in dissecting complex molecular mechanisms associated with various disease and promoting the development of novel diagnostics and therapeutics."
A Chinese Academy of Science-led team introduces iDog, an integrated collection of genome sequence variations, genome assemblies, RNA sequence data, functional annotation clues, and other omics data for domestic dogs or wild canids. The collection is complemented by sequence alignment and data visualization, the researchers explain, along with documented dog phenotypes, disease traits, and shared dog-human disease features. "In the future, we will keep updating the existing dataset as new data of high quality is made available," they write, adding "we will continue developing and integrating more tools for genomes, population, evolution, and network analysis, as well as more interactive visualization methods for various omics data."
Finally, researchers from the University of Copenhagen and elsewhere describe an updated database known as BloodSpot for documenting, visualizing, and analyzing gene expression profiles in hematopoietic cell types, based on array-based expression, RNA sequence, and single-cell messenger RNA data for fluorescence-activated cell sorted blood cell types. "The visualizations have been updated to accommodate new datatypes and the database has been largely expanded with RNA sequencing datasets, both purified in bulk and at single cell resolution," the team notes, explaining that the database aims to "assist researchers and clinicians within the fields of leukemia, stem cells, and development, to test and generate hypotheses."