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

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.
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DOI:
10.1016/j.devcel.2022.01.008
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发表时间:
2022-02-28
期刊:
影响因子:
11.8
通讯作者:
Ohler, Uwe
Ohler, Uwe
中科院分区:
生物学1区
文献类型:
--
作者:
Shahan, Rachel;Hsu, Che-Wei;Nolan, Trevor M.;Cole, Benjamin J.;Taylor, Isaiah W.;Greenstreet, Laura;Zhang, Stephen;Afanassiev, Anton;Vlot, Anna Hendrika Cornelia;Schiebinger, Geoffrey;Benfey, Philip N.;Ohler, Uwe

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In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model to investigate 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. How do transcriptional networks regulate organ development? Using scRNA-seq, Shahan and Hsu et al. produced an Arabidopsis root atlas, revealing gradual gene expression changes underlying differentiation of cell types and candidate regulators of cell fate. The atlas enabled interpretation of smaller scRNA-seq datasets and revealed new phenotypes in developmental mutants.
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