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Published November 26, 2021 | Supplemental Material + Submitted + Published
Journal Article Open

Whole-animal multiplexed single-cell RNA-seq reveals transcriptional shifts across Clytia medusa cell types


We present an organism-wide, transcriptomic cell atlas of the hydrozoan medusa Clytia hemisphaerica and describe how its component cell types respond to perturbation. Using multiplexed single-cell RNA sequencing, in which individual animals were indexed and pooled from control and perturbation conditions into a single sequencing run, we avoid artifacts from batch effects and are able to discern shifts in cell state in response to organismal perturbations. This work serves as a foundation for future studies of development, function, and regeneration in a genetically tractable jellyfish species. Moreover, we introduce a powerful workflow for high-resolution, whole-animal, multiplexed single-cell genomics that is readily adaptable to other traditional or nontraditional model organisms.

Additional Information

© 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). Received: 20 February 2021. Accepted: 6 October 2021. We thank X. Da and X. Wang for technical assistance, T. Momose for assistance with the single-cell experimentation, the Caltech Single-Cell Profiling and Engineering Center for the use of their single-cell and sequencing tools, and the Caltech Bioinformatics Resource Center for transcriptome assembly and annotation analysis. We additionally thank the Caltech Center for Evolutionary Science for the bioinformatics resources to create a local UCSC Genome Browser. We thank A. S. Booeshaghi for help with kallisto, bustools, and the kITE demultiplexing of the ClickTag reads and for rescuing the stimulation experiment sequencing data. We thank J. Malamy for helping to establish Clytia work at Caltech. We thank S. Peron for initial characterization of some of the cell type marker genes, P. Lapébie for identification of novel neuropeptide sequences, M. Jager for valuable advice on the in situ protocol, and J. R. Mateu for providing pp11 probe. J.G., M.H., and L.P. were supported in part by a seed grant from the Chen Institute at the California Institute of Technology. T.C., J.G., and L.P. were supported in part by NIH U19MH114830 and NIH RF1AG062324A. We thank the Marine Resources Centre (CRBM and PIV imaging platform) of Institut de la Mer de Villefranche (IMEV), supported by EMBRC-France. The French state funds of EMBRC-France are managed by the ANR within the investments of the Future program. L.L. was supported by the Agence Nationale de la Recherche (ANR-19-CE13-0003). A.F., R.R.C., and E.H. were supported by the H2020/Marie Skłodowska-Curie ITN "EvoCell" Grant agreement no. 766053. B.W. was supported in part by a Howard Hughes Medical Institute Fellowship of the Life Sciences Research Foundation and by NIH K99NS119749. This work was in part supported by the Whitman Center of the Marine Biological Laboratory in Woods Hole, MA and a visiting grant from EMBRC-France. D.J.A. is an Investigator of the Howard Hughes Medical Institute. Author contributions: Conceived of the experiments: T.C., B.W., J.G., R.R.C., E.H., D.J.A., and L.P. Developed cell dissociation, fixation, and labeling procedures compatible with the 10X Genomics platform: J.G. and M.H. Performed the single-cell experiments: T.C., B.W., and J.G. Performed the in situ hybridization and other microscopy experiments: B.W., A.F., L.L., and S.C. Performed whole-organism qPCR: T.C. Performed bioinformatics analysis including assembly and annotation of the transcriptome: F.G. and R.R.C. Wrote scripts for processing the data and code for the analysis: T.C. and J.G. Developed the Google Colab notebooks: T.C. Analyzed and interpreted the data: T.C., B.W., J.G., A.F., L.L., R.R.C., E.H., D.J.A., and L.P. Writing and editing the manuscript: T.C., B.W., J.G., A.F., L.L., R.R.C., E.H., D.J.A., and L.P. The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. All raw sequencing and processed data files used for analysis are available from CaltechData, (https://data.caltech.edu/search?page=1&size=25&ln=en&q=clytia), with links additionally provided via the notebooks in the code repository. The sequencing read alignments are available at http://evolution.caltech.edu/genomebrowser/cgi-bin/hgTracks?db=hub_135_clyHem1&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=scaffold_1%3A1%2D30003&hgsid=3413_LS7OcP5N7VA2rApGOfk8iaX2kVFR, and an interactive browser for gene expression visualization (, is publicly hosted on a UCSC Genome Browser by the Caltech Bioinformatics Resource Center. The softwares used are as follows: Cell Ranger 3.0.1, Trinity-v2.8.4, Cufflinks v2.2.1, kallisto v0.46.2, bustools v0.40.0, anndata 0.7.5, louvain 0.7.0, rpy2 3.4.2, scanpy 1.6.0, biopython 1.78, pysam, fuzzywuzzy 0.18.0, numpy 0.19.5, pandas 1.1.5, matplotlib 3.2.2, sklearn 0.0, scipy 1.4.1, seaborn 0.11.1, requests 2.23.0, tqdm 4.41.1, multiprocess, DESeq2 1.3.0, topGO 2.42.0, and UpSet 1.4.0. Code availability: All the codes used to perform the analyses and generate the results and figures are available in Google Colab notebooks archived with Zenodo at https://zenodo.org/record/5519756#.YUonytNKgUE and directly available at https://github.com/pachterlab/CWGFLHGCCHAP_2021. The notebooks, which include the complete preprocessing of the raw data and a walkthrough of the code, provide a transparent implementation of the methods and can be run for free in the Google cloud.

Attached Files

Published - sciadv.abh1683.pdf

Submitted - 2021.01.22.427844v2.full.pdf

Supplemental Material - sciadv.abh1683_sm.pdf

Supplemental Material - sciadv.abh1683_tables_s3_and_s5.zip


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August 20, 2023
December 22, 2023