EmAtlas: a comprehensive atlas for exploring spatiotemporal activation in mammalian embryogenesis

Abstract

The emerging importance of embryonic development research rapidly increases the volume for a professional resource related to multi-omics data. However, the lack of global embryogenesis repository and systematic analysis tools limits the preceding in stem cell research, human congenital diseases and assisted reproduction. Here, we developed the EmAtlas, which collects the most comprehensive multi-omics data and provides multi-scale tools to explore spatiotemporal activation during mammalian embryogenesis. EmAtlas contains data on multiple types of gene expression, chromatin accessibility, DNA methylation, nucleosome occupancy, histone modifications, and transcription factors, which displays the complete spatiotemporal landscape in mouse and human across several time points, involving gametogenesis, preimplantation, even fetus and neonate, and each tissue involves various cell types. To characterize signatures involved in the tissue, cell, genome, gene and protein levels during mammalian embryogenesis, analysis tools on these five scales were developed. Additionally, we proposed EmRanger to deliver extensive development-related biological background annotations. Users can utilize these tools to analyze, browse, visualize, and download data owing to the user-friendly interface. EmAtlas is freely accessible at http://bioinfor.imu.edu.cn/ematlas.

RevGel-seq: instrument-free single-cell RNA sequencing using a reversible hydrogel for cell-specific barcoding

“…( B ) Cell classification and 2D embedding from a PBMC sample of 10,000 input cells prepared with RevGel-seq were downsampled by raw read subsampling at a depth of 20,000 raw reads per cell on average. Post-processing was performed using Seurat 21 and automated cell classification was performed using the SingleR 22 algorithm based on the reference dataset MonacoImmuneData 23 . Unassigned cells had classification uncertainties that were considered too high according to the pruneScores method with default parameters.…”

“…Other investigations have focused on specific organs, often in relation to pathologies 16 , especially cancer, immunotherapy, and cardiovascular diseases 17 – 19 . Research has focused as well on development 20 , 21 , various forms of multiomics 22 , and spatial transcriptomics 23 . In addition, applications to plants are emerging 24 , highlighting single-nucleus (snRNA-seq) approaches 25 .…”

Deciphering the decisive factors driving fate bifurcations in somatic cell reprogramming

“…For scRNA-seq data preprocessing, all raw data were controlled by FastQC software ( http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ) and were trimmed based on Trimmomatic (version 0.38) 35 to remove low-quality reads. 36 , 37 Next, filtered reads were mapped to the UCSC mm10 genome using genome-aligner STAR (version 2.5.1b) with default parameters. Then, UMI counts were performed with cellranger from the 10X Genomics pipeline (version 1.1.0, with default parameters).…”

GametesOmics: A Comprehensive Multi-Omics Database for Exploring the Gametogenesis in Humans and Mice

“…dbEmbryo and DevOmics integrate multi-omics sequencing data across different developmental stages in human and mouse early embryos [13,14]. EmAtlas exhibits the spatiotemporal landscape of human and mouse embryos from the perspective of cell, tissue, genome, gene and protein levels [15]. These current databases greatly promote the understanding of the genetic and epigenetic mechanisms in the development of human and mouse.…”