The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution

TLDR

Mapping the vertebrate developmental landscape, researchers have used single‑cell RNA sequencing to chart transcriptional changes that generate diverse cell types from pluripotent cells during embryogenesis. The study aims to analyze transcriptional changes accompanying vertebrate embryonic development using single‑cell RNA sequencing. The authors sequenced over 90,000 zebrafish cells and tens of thousands of embryonic cells, constructed branching transcriptional trees, and examined whole frog embryos to map cell states across lineages over time. The branching trees revealed progressive gene‑expression changes leading to cell specialization, demonstrating that these datasets enable comprehensive reconstruction of developmental transcriptional trajectories. Data and analyses are published in Science (pp.

Abstract

Mapping the vertebrate developmental landscape As embryos develop, numerous cell types with distinct functions and morphologies arise from pluripotent cells. Three research groups have used single-cell RNA sequencing to analyze the transcriptional changes accompanying development of vertebrate embryos (see the Perspective by Harland). Wagner et al. sequenced the transcriptomes of more than 90,000 cells throughout zebrafish development to reveal how cells differentiate during axis patterning, germ layer formation, and early organogenesis. Farrell et al. profiled the transcriptomes of tens of thousands of embryonic cells and applied a computational approach to construct a branching tree describing the transcriptional trajectories that lead to 25 distinct zebrafish cell types. The branching tree revealed how cells change their gene expression as they become more and more specialized. Briggs et al. examined whole frog embryos, spanning zygotic genome activation through early organogenesis, to map cell states and differentiation across all cell lineages over time. These data and approaches pave the way for the comprehensive reconstruction of transcriptional trajectories during development. Science , this issue p. 981 , p. eaar3131 , p. eaar5780 ; see also p. 967