Systematic identification of cell-fate regulatory programs using a single-cell atlas of mouse development

Abstract

Waddington's epigenetic landscape is an abstract metaphor frequently used to explain cell fate decisions. Recent advances in single-cell genomics are altering our understanding of the Waddington landscape. Yet, the molecular regulations behind remain poorly understood. We construct a dynamic cell landscape of mouse lineage differentiation at the single-cell level and thereby reveal both lineage-common and lineage-specific regulatory programs during cell type maturation. We verify lineage-common regulatory programs that are universal during the development of invertebrates and vertebrates. In particular, we identify Xbp1 as an evolutionarily conserved regulator of cell fate determinations across different species. We demonstrate that Xbp1 transcriptional regulation is important for the stabilization of the genetic network for a wide range of cell types. Our results offer genetic and molecular insights into the gene regulatory programs systematically and provide resources to advance the understanding of the cell fate decisions.

Secuer: Ultrafast, scalable and accurate clustering of single-cell RNA-seq data

“…Fifteen publicly available scRNA-seq datasets, including six gold-standard datasets, six-silver standard datasets and three ultra-large datasets, are used to evaluate the clustering accuracy of our method (see S1 Table for details) [1,5,[26][27][28][29][30][31][32][33][34][35][36][37][38][39][40]. In six gold-standard datasets, cells are highly confident to be labeled as a specific cell type/stage according to their surface markers.…”

TEDD: a database of temporal gene expression patterns during multiple developmental periods in human and model organisms

“…To exemplify how TEDD can help researchers understand the temporal patterns of expression and chromatin accessibility of the gene(s) of interest, we used the AFP (Alpha Fetoprotein) gene as an example. Alpha fetoprotein is a well-established marker for the diagnosis and prognosis of hepatocellular carcinoma ( 3 ), and its role primarily is to transport heavy metal ions and various insoluble molecules in fetal blood circulation ( 32 ). As a paralog of AFP , the ALB gene is found to have a similar expression pattern in embryonic stem cell-derived hepatocytes ( 6 ).The AFP gene is involved in the Hippo signaling pathway (hsa04390), which regulates organ size, cell fate, and carcinogenesis in the liver ( 5 ) through the activation of YAP (gene YAP1 ) and TAZ (gene WWTR1 ) ( 33 ).…”

“…The emergence of transformative technologies such as single-cell omics sequencing unlocked the capability to understand the underlying mechanisms of cell fate decisions and cellular processes and how they are controlled and determined during organ development. Thus, we can gain insight into diseases in both human and model organisms ( 3–5 ).…”

Single-cell transcriptomics to understand the cellular heterogeneity in toxicology

“…The first is automatic cell-type identification (Table 1), in which clusters are annotated to specific cell types based on public resources of scRNA-seq data. This approach uses pre-annotated marker genes (or known marker genes) and a reference single-cell map for tissues; MSigDB (Liberzon et al 2015), DRscDB (Hu et al 2021), ScType (Ianevski et al 2022), CellMeSH (Mao et al 2021), (Fei et al 2022). The advantages of automatic cell-type identification are that it can be used by those without sufficient knowledge of cell markers or biology, applied to individual cells and to cell clusters, and can quickly identify major cell types.…”