Defining endogenous barcoding sites for CRISPR/Cas9-based cell lineage tracing in zebrafish
-
Abstract: There is a growing interest in developing experimental methods for tracking the developmental cell lineages of a complex organism. The recently developed CRISPR/Cas9-based barcoding method is, although highly promising, difficult to scale up because it relies on exogenous barcoding sequences that are engineered into the genome. In this study, we characterized 78 high-quality endogenous sites in the zebrafish genome that can be used as CRISPR/Cas9-based barcoding sites. The 78 sites are all highly expressed in most of the cell types according to single-cell RNA sequencing (scRNA-seq) data. Hence, the barcoding information of the 78 endogenous sites is recovered by the available scRNA-seq platforms, enabling simultaneous characterization of cell type and cell lineage information.
-
Key words:
- Zebrafish /
- CRISPR/Cas9 /
- Cell lineage /
- Development /
- Single-cell RNA sequencing
-
Fig. 1. Cell types of juvenile zebrafish and genome editing by selected sgRNAs. A: The tSNE plot of 3545 cells of a single juvenile zebrafish (25–30 dpf) clustered into 24 groups. Inferred cell types of the clusters are indicated. B: Representative Sanger sequencing results of eight successful editings by the selected sgRNAs. The sequences on the top of each chromatogram are the references (purple shadings indicate PAM sequences) and red arrows represent the putative cleavage sites. Note that after the cutting sites, the signals become noisy since Cas9 introduces indels into the DNA template.
Fig. 2. Recovery performance of the 78 barcoding sites. A: tSNE representation of cells colored by the number of barcoding sites detected. B: The distribution of UMI counts of barcoding sites per cell. C: Relationship between the number of sites detected and the percentage of cells at different cutoffs (UMI number equal to or greater than 1, 2 and 5).
Fig. 3. Barcoding with multiple endogenous sites. A: Schematic overview of the barcoding system using endogenous sites. Cas9 and sgRNAs were injected into one-cell stage embryos. Scars accumulate over time and were readout by next-generation sequencing of target-specific multiplex PCR products. B: Comparison of mutation rates between the low and high dose of sgRNAs injected. Dots represent the median percentage of reads with scars of each target site (low dose, 4 × 78 = 312 pg, n = 2; high dose, 20 × 78 = 1560 pg, n = 3). C: The number of unique scars created by different sgRNAs.
Fig. 4. Performance of barcoding in single larvae. A: Variation in the frequencies of scars in an individual and only the top 30 scars are listed. Each scar can be identified by the site it occurred and its frequency ranking in that site. Scars are sorted in order of decreasing frequencies.B: The timeline of editing events estimated by frequencies of the scars, which are colored by the sites they occurred. The frequency rankings of the scar in its barcoding site are indicated by different shapes. C: Distribution of the number of newly created scars in each division cycle of different samples (the estimated division cycle number are rounded).
-
[1] Alemany, A., Florescu, M., Baron, C.S., Peterson-Maduro, J., Van Oudenaarden, A., 2018. Whole-organism clone tracing using single-cell sequencing. Nature 556, 108-112. [2] Amsterdam, A., Nissen, R.M., Sun, Z., Swindell, E.C., Farrington, S., Hopkins, N., 2004. Identification of 315 genes essential for early zebrafish development. Proc. Natl. Acad. Sci. U. S. A. 101, 12792-12797. [3] Butler, A., Hoffman, P., Smibert, P., Papalexi, E., Satija, R., 2018. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411-420. [4] Chan, M.M., Smith, Z.D., Grosswendt, S., Kretzmer, H., Norman, T.M., Adamson, B., Jost, M., Quinn, J.J., Yang, D., Jones, M.G., Khodaverdian, A., Yosef, N., Meissner, A., Weissman, J.S., 2019. Molecular recording of mammalian embryogenesis. Nature 570, 77-82. [5] Chen, S., Zhou, Y., Chen, Y., Gu, J., 2018. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884-i890. [6] Deppe, U., Schierenberg, E., Cole, T., Krieg, C., Schmitt, D., Yoder, B., von Ehrenstein, G., 1978. Cell lineages of the embryo of the nematode Caenorhabditis elegans. Proc. Natl. Acad. Sci. U. S. A. 75, 376-380. [7] Di Tommaso, P., Moretti, S., Xenarios, I., Orobitg, M., Montanyola, A., Chang, J. M., Taly, J. F., Notredame, C., 2011. T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension. Nucleic Acids Res. 39, W13-W17. [8] Doench, J.G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E.W., Donovan, K.F., Smith, I., Tothova, Z., Wilen, C., Orchard, R., Virgin, H.W., Listgarten, J., Root, D.E., 2016. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34, 184-191. [9] Howe, D.G., Bradford, Y.M., Conlin, T., Eagle, A.E., Fashena, D., Frazer, K., Knight, J., Mani, P., Martin, R., Moxon, S.A.T., Paddock, H., Pich, C., Ramachandran, S., Ruef, B.J., Ruzicka, L., Schaper, K., Shao, X., Singer, A., Sprunger, B., Van Slyke, C.E., Westerfield, M., 2013. ZFIN, the Zebrafish Model Organism Database: increased support for mutants and transgenics. Nucleic Acids Res. 41, D854-D860. [10] Jao, L. E., Wente, S.R., Chen, W., 2013. Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proc. Natl. Acad. Sci. 110, 13904-13909. [11] Kalhor, R., Kalhor, K., Mejia, L., Leeper, K., Graveline, A., Mali, P., Church, G.M., 2018. Developmental barcoding of whole mouse via homing CRISPR. Science. 361, eaat9804. [12] Keller, P.J., Schmidt, A.D., Wittbrodt, J., Stelzer, E.H.K., 2008. Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy. Science. 322, 1065-1069. [13] Kimmel, C.B., Ballard, W.W., Kimmel, S.R., Ullmann, B., Schilling, T.F., 1995. Stages of embryonic development of the zebrafish. Dev. Dyn. 203, 253-310. [14] Kobitski, A.Y., Otte, J.C., Takamiya, M., Schafer, B., Mertes, J., Stegmaier, J., Rastegar, S., Rindone, F., Hartmann, V., Stotzka, R., Garcia, A., Van Wezel, J., Mikut, R., Strahle, U., Nienhaus, G.U., 2015. An ensemble-averaged, cell density-based digital model of zebrafish embryo development derived from light-sheet microscopy data with single-cell resolution. Sci. Rep. 5, 1-10. [15] Li, H., Durbin, R., 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754-1760. [16] Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., 2009. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078-2079. [17] Magoc, T., Salzberg, S.L., 2011. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957-2963. [18] Mali, P., Yang, L., Esvelt, K.M., Aach, J., Guell, M., DiCarlo, J.E., Norville, J.E., Church, G.M., 2013. RNA-guided human genome engineering via Cas9. Science 339, 823-826. [19] McKenna, A., Findlay, G.M., Gagnon, J.A., Horwitz, M.S., Schier, A.F., Shendure, J., 2016. Whole-organism lineage tracing by combinatorial and cumulative genome editing. Science 353, aaf7907. [20] Montague, T.G., Cruz, J.M., Gagnon, J.A., Church, G.M., Valen, E., 2014. CHOPCHOP: a CRISPR/Cas9 and TALEN web tool for genome editing. Nucleic Acids Res. 42, W401-W407. [21] Perli, S.D., Cui, C.H., Lu, T.K., 2016. Continuous genetic recording with self-targeting CRISPR-Cas in human cells. Science. 353, aag0511. [22] Raj, B., Wagner, D.E., McKenna, A., Pandey, S., Klein, A.M., Shendure, J., Gagnon, J.A., Schier, A.F., 2018. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat. Biotechnol. 36, 442-450. [23] Salvador-Martinez, I., Grillo, M., Averof, M., Telford, M.J., 2019. Is it possible to reconstruct an accurate cell lineage using CRISPR recorders? eLife 8, e40292. [24] Spanjaard, B., Hu, B., Mitic, N., Olivares-Chauvet, P., Janjuha, S., Ninov, N., Junker, J.P., 2018. Simultaneous lineage tracing and cell-type identification using CrIsPr-Cas9-induced genetic scars. Nat. Biotechnol. 36, 469-473. [25] Sulston, J.E., Horvitz, H.R., 1977. Post-embryonic cell lineages of the nematode, Caenorhabditis elegans. Dev. Biol. 56, 110-156. [26] Sulston, J.E., Schierenberg, E., White, J.G., Thomson, J.N., 1983. The embryonic cell lineage of the nematode Caenorhabditis elegans. Dev. Biol. 100, 64-119. [27] Wagner, D.E., Weinreb, C., Collins, Z.M., Briggs, J.A., Megason, S.G., Klein, A.M., 2018. Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo. Science. 360, 981-987. [28] Wingo, T.S., Kotlar, A., Cutler, D.J., 2017. MPD: multiplex primer design for next-generation targeted sequencing. BMC Bioinformatics 18, 14. [29] Zheng, G.X.Y., Terry, J.M., Belgrader, P., Ryvkin, P., Bent, Z.W., Wilson, R., Ziraldo, S.B., Wheeler, T.D., McDermott, G.P., Zhu, J., Gregory, M.T., Shuga, J., Montesclaros, L., Underwood, J.G., Masquelier, D.A., Nishimura, S.Y., Schnall-Levin, M., Wyatt, P.W., Hindson, C.M., Bharadwaj, R., Wong, A., Ness, K.D., Beppu, L.W., Deeg, H.J., McFarland, C., Loeb, K.R., Valente, W.J., Ericson, N.G., Stevens, E.A., Radich, J.P., Mikkelsen, T.S., Hindson, B.J., Bielas, J.H., 2017. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049. -