Using single-cell genomics to understand developmental processes and cell fate decisions.

High-throughput -omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision-making is inherently a unicellular process to which "bulk" -omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single-cell methods bridge this gap, allowing high-throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single-cell gene expression data and highlight areas of developmental biology where single-cell techniques have made important contributions. These include understanding of cell-to-cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.

Griffiths JA ，Scialdone A ，Marioni JC 《Molecular Systems Biology》

Next-Generation Lineage Tracing and Fate Mapping to Interrogate Development.

Lineage tracing and fate mapping, overlapping yet distinct disciplines to follow cells and their progeny, have evolved rapidly over the last century. Lineage tracing aims to identify all progeny arising from an individual cell, placing them within a lineage hierarchy. The recent emergence of genomic technologies, such as single-cell and spatial transcriptomics, has fostered sophisticated new methods to reconstruct lineage relationships at high resolution. In contrast, fate maps, schematics showing which parts of the embryo will develop into which tissue, have remained relatively static since the 1970s. However, fate maps provide spatial information, often lost in lineage reconstruction, that can offer fundamental mechanistic insight into development. Here, we broadly review the origins of fate mapping and lineage tracing approaches. We focus on the most recent developments in lineage tracing, permitted by advances in single-cell genomics. Finally, we explore the current potential to leverage these new technologies to synthesize high-resolution fate maps and discuss their potential for interrogating development at new depths.

VanHorn S ，Morris SA 《-》

Single-cell multi-omics and lineage tracing to dissect cell fate decision-making.

The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate.

Haghverdi L ，Ludwig LS 《Stem Cell Reports》

Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq.

Treutlein B ，Brownfield DG ，Wu AR ，Neff NF ，Mantalas GL ，Espinoza FH ，Desai TJ ，Krasnow MA ，Quake SR ... -  《-》

Single-cell Transcriptome Profiling reveals Dermal and Epithelial cell fate decisions during Embryonic Hair Follicle Development.

It is estimated that 50% of men and 25% of women worldwide suffer from hair loss, and therefore it is of great significance to investigate the molecular pathways driving hair follicle de novo morphogenesis. However, due to high cellular heterogeneity and the asynchronous development of hair follicles, our current understanding of the molecular mechanisms involved in follicle development remains limited. Methods: Single-cell suspensions from the dorsal skin of E13.5 (induction stage), E16.5 (organogenesis) fetal mice, and newborn mice (cytodifferentiation stage, postnatal day 0, P0) were prepared for unbiased single-cell RNA sequencing. To delineate the single-cell transcriptional landscape during hair follicle de novo morphogenesis, we performed t-distributed Stochastic Neighbor Embedding (tSNE), pseudotime cell trajectory inference, and regulon enrichment analysis to dissect cellular heterogeneity and reveal the molecular pathways underlying major cell type cell fate decisions. To validate our analysis, we further performed immunohistochemistry analysis of the key molecules involved during hair follicle morphogenesis. Meanwhile, intercellular communication between different cell populations was inferred based on a priori knowledge of ligand-receptor pairs. Results: Based on tSNE analysis, we identified 14 cell clusters from skin tissue and delineated their cellular identity from specific gene expression profiles. By using pseudotime ordering analysis, we successfully constructed the epithelium/dermal cell lineage differentiation trajectory. For dermal cell lineage, our analysis here recapitulated the dynamic gene expression profiles during dermal condensate (DC) cell fate commitment and delineated the heterogeneity of the different dermal papilla (DP) cell populations during in utero hair follicle development. For the epithelium cell lineage, our analysis revealed the dynamic gene expression profiles of the underappreciated matrix, interfollicular epidermis (IFE), hair shaft and inner root sheath (IRS) cell populations. Furthermore, single-cell regulatory network inference and clustering analysis revealed key regulons during cell fate decisions. Finally, intercellular communication analysis demonstrated that strong intercellular communication was involved during early hair follicle development. Conclusions: Our findings here provide a molecular landscape during hair follicle epithelium/dermal cell lineage fate decisions, and recapitulate the sequential activation of core regulatory transcriptional factors (TFs) in different cell populations during hair follicle morphogenesis. More importantly, our study here represents a valuable resource for understanding the molecular pathways involved during hair follicle de novo morphogenesis, which will have implications for future hair loss treatments.

Ge W ，Tan SJ ，Wang SH ，Li L ，Sun XF ，Shen W ，Wang X ... -  《Theranostics》