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      High-Throughput Single-Cell Transcriptome Profiling of Plant Cell Types

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          SUMMARY

          Single-cell transcriptome profiling of heterogeneous tissues can provide high-resolution windows into developmental dynamics and environmental responses, but its application to plants has been limited. Here, we used the high-throughput Drop-seq approach to profile >12,000 cells from Arabidopsis roots. This identified numerous distinct cell types, covering all major root tissues and developmental stages, and illuminated specific marker genes for these populations. In addition, we demonstrate the utility of this approach to study the impact of environmental conditions on developmental processes. Analysis of roots grown with or without sucrose supplementation uncovers changes in the relative frequencies of cell types in response to sucrose. Finally, we characterize the transcriptome changes that occur across endodermis development and identify nearly 800 genes with dynamic expression as this tissue differentiates. Collectively, we demonstrate that single-cell RNA-seq can be used to profile developmental processes in plants and show how they can be altered by external stimuli.

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          In Brief

          The application of single-cell transcriptome profiling to plants has been limited. Shulse et al. performed Drop-seq on Arabidopsis roots, generating a transcriptional resource for >12,000 cells across major populations. This revealed marker genes for distinct cell types, cell frequency changes resulting from sucrose addition, and genes dynamically regulated during development.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            A high-resolution root spatiotemporal map reveals dominant expression patterns.

            Transcriptional programs that regulate development are exquisitely controlled in space and time. Elucidating these programs that underlie development is essential to understanding the acquisition of cell and tissue identity. We present microarray expression profiles of a high-resolution set of developmental time points within a single Arabidopsis root and a comprehensive map of nearly all root cell types. These cell type-specific transcriptional signatures often predict previously unknown cellular functions. A computational pipeline identified dominant expression patterns that demonstrate transcriptional similarity between disparate cell types. Dominant expression patterns along the root's longitudinal axis do not strictly correlate with previously defined developmental zones, and in many cases, we observed expression fluctuation along this axis. Both robust co-regulation of gene expression and potential phasing of gene expression were identified between individual roots. Methods that combine these profiles demonstrate transcriptionally rich and complex programs that define Arabidopsis root development in both space and time.
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              A gene expression map of the Arabidopsis root.

              A global map of gene expression within an organ can identify genes with coordinated expression in localized domains, thereby relating gene activity to cell fate and tissue specialization. Here, we present localization of expression of more than 22,000 genes in the Arabidopsis root. Gene expression was mapped to 15 different zones of the root that correspond to cell types and tissues at progressive developmental stages. Patterns of gene expression traverse traditional anatomical boundaries and show cassettes of hormonal response. Chromosomal clustering defined some coregulated genes. This expression map correlates groups of genes to specific cell fates and should serve to guide reverse genetics.
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                Author and article information

                Journal
                101573691
                39703
                Cell Rep
                Cell Rep
                Cell reports
                2211-1247
                11 September 2019
                14 May 2019
                24 September 2019
                : 27
                : 7
                : 2241-2247.e4
                Affiliations
                [1 ]Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
                [2 ]Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
                [3 ]Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
                [4 ]Lead Contact
                Author notes

                AUTHOR CONTRIBUTIONS

                Investigation, C.N.S., D.C., J.L., Y.Y., M.G., and Y.Z.; Formal Analysis, C.N.S. and B.J.C.; Resources, G.M.T. and S.M.B.; Conceptualization & Supervision, D.E.D., R.C.O., and S.M.B.; Writing-Original Draft, C.N.S., B.J.C., and D.E.D.; Writing – Review & Editing, C.N.S., B.J.C., D.C., J.L., Y.Y., M.G., G.M.T., Y.Z., R.C.O., S.M.B., and D.E.D.

                [* ]Correspondence: dedickel@ 123456lbl.gov
                Article
                NIHMS1539475
                10.1016/j.celrep.2019.04.054
                6758921
                31091459
                962b7c49-8108-402f-a4c6-ab43ba0e9271

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

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                Cell biology
                Cell biology

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