Single-cell transcriptomics reveals evolutionary reconfiguration of embryonic cell fate specification in the sea urchin Heliocidaris erythrogramma.

Altered regulatory interactions during development likely underlie a large fraction of phenotypic diversity within and between species, yet identifying specific evolutionary changes remains challenging. Analysis of single-cell developmental transcriptomes from multiple species provides a powerful framework for unbiased identification of evolutionary changes in developmental mechanisms. Here, we leverage a "natural experiment" in developmental evolution in sea urchins, where a major life history switch recently evolved in the lineage leading to Heliocidaris erythrogramma, precipitating extensive changes in early development. Comparative analyses of scRNA-seq developmental time courses from H. erythrogramma and Lytechinus variegatus (representing the derived and ancestral states respectively) reveals numerous evolutionary changes in embryonic patterning. The earliest cell fate specification events, and the primary signaling center are co-localized in the ancestral dGRN but remarkably, in H. erythrogramma they are spatially and temporally separate. Fate specification and differentiation are delayed in most embryonic cell lineages, although in some cases, these processes are conserved or even accelerated. Comparative analysis of regulator-target gene co-expression is consistent with many specific interactions being preserved but delayed in H. erythrogramma, while some otherwise widely conserved interactions have likely been lost. Finally, specific patterning events are directly correlated with evolutionary changes in larval morphology, suggesting that they are directly tied to the life history shift. Together, these findings demonstrate that comparative scRNA-seq developmental time courses can reveal a diverse set of evolutionary changes in embryonic patterning and provide an efficient way to identify likely candidate regulatory interactions for subsequent experimental validation.

DNA-GPS: A theoretical framework for optics-free spatial genomics and synthesis of current methods.

While single-cell sequencing technologies provide unprecedented insights into genomic profiles at the cellular level, they lose the spatial context of cells. Over the past decade, diverse spatial transcriptomics and multi-omics technologies have been developed to analyze molecular profiles of tissues. In this article, we categorize current spatial genomics technologies into three classes: optical imaging, positional indexing, and mathematical cartography. We discuss trade-offs in resolution and scale, identify limitations, and highlight synergies between existing single-cell and spatial genomics methods. Further, we propose DNA-GPS (global positioning system), a theoretical framework for large-scale optics-free spatial genomics that combines ideas from mathematical cartography and positional indexing. DNA-GPS has the potential to achieve scalable spatial genomics for multiple measurement modalities, and by eliminating the need for optical measurement, it has the potential to position cells in three-dimensions (3D).

Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root.

Brassinosteroids are plant steroid hormones that regulate diverse processes, such as cell division and cell elongation, through gene regulatory networks that vary in space and time. By using time series single-cell RNA sequencing to profile brassinosteroid-responsive gene expression specific to different cell types and developmental stages of the Arabidopsis root, we identified the elongating cortex as a site where brassinosteroids trigger a shift from proliferation to elongation associated with increased expression of cell wall-related genes. Our analysis revealed HOMEOBOX FROM ARABIDOPSIS THALIANA 7 (HAT7) and GT-2-LIKE 1 (GTL1) as brassinosteroid-responsive transcription factors that regulate cortex cell elongation. These results establish the cortex as a site of brassinosteroid-mediated growth and unveil a brassinosteroid signaling network regulating the transition from proliferation to elongation, which illuminates aspects of spatiotemporal hormone responses.

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.

In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model for investigating the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single-cell resolution. In addition to estimating developmental progressions in pseudotime, we employed the mathematical concept of optimal transport to infer developmental trajectories and identify their underlying regulators. To demonstrate the utility of the atlas to interpret new datasets, we profiled mutants for two key transcriptional regulators at single-cell resolution, shortroot and scarecrow. We report transcriptomic and in vivo evidence for tissue trans-differentiation underlying a mixed cell identity phenotype in scarecrow. Our results support the atlas as a rich community resource for unraveling the transcriptional programs that specify and maintain cell identity to regulate spatiotemporal organ development.

Optimal transport analysis reveals trajectories in steady-state systems.

Understanding how cells change their identity and behaviour in living systems is an important question in many fields of biology. The problem of inferring cell trajectories from single-cell measurements has been a major topic in the single-cell analysis community, with different methods developed for equilibrium and non-equilibrium systems (e.g. haematopoeisis vs. embryonic development). We show that optimal transport analysis, a technique originally designed for analysing time-courses, may also be applied to infer cellular trajectories from a single snapshot of a population in equilibrium. Therefore, optimal transport provides a unified approach to inferring trajectories that is applicable to both stationary and non-stationary systems. Our method, StationaryOT, is mathematically motivated in a natural way from the hypothesis of a Waddington's epigenetic landscape. We implement StationaryOT as a software package and demonstrate its efficacy in applications to simulated data as well as single-cell data from Arabidopsis thaliana root development.

Developmental single-cell transcriptomics in the Lytechinus variegatus sea urchin embryo.

Using scRNA-seq coupled with computational approaches, we studied transcriptional changes in cell states of sea urchin embryos during development to the larval stage. Eighteen closely spaced time points were taken during the first 24 h of development of Lytechinus variegatus (Lv). Developmental trajectories were constructed using Waddington-OT, a computational approach to 'stitch' together developmental time points. Skeletogenic and primordial germ cell trajectories diverged early in cleavage. Ectodermal progenitors were distinct from other lineages by the 6th cleavage, although a small percentage of ectoderm cells briefly co-expressed endoderm markers that indicated an early ecto-endoderm cell state, likely in cells originating from the equatorial region of the egg. Endomesoderm cells also originated at the 6th cleavage and this state persisted for more than two cleavages, then diverged into distinct endoderm and mesoderm fates asynchronously, with some cells retaining an intermediate specification status until gastrulation. Seventy-nine out of 80 genes (99%) examined, and included in published developmental gene regulatory networks (dGRNs), are present in the Lv-scRNA-seq dataset and are expressed in the correct lineages in which the dGRN circuits operate.