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Published in final edited form as: Differentiation. 2026 Jun 7;150:100973. doi: 10.1016/j.diff.2026.100973

Validated CRISPR/Cas9 guide RNAs targeting neurodevelopmental genes in the tunicate Ciona robusta

Sydney Popsuj a, Tenzin Kalsang b, Kwantae Kim b, Erica Drummond b, Pooja Manekar b, Pranavvarma Munagapati b, Manasi Oleti b, Hiroki Sato b, Izabella Vickery b, Eduardo D Gigante c, Alberto Stolfi b,*
PMCID: PMC13480310  NIHMSID: NIHMS2203367  PMID: 42269486

Abstract

The tunicate Ciona robusta provides a powerful and simplified model for dissecting the genetic control of developmental and cell biology. With a larval CNS composed of just over 200 neurons and sensory cells, it has also emerged as a model organism for neurobiology and the development of the nervous system. Although CRISPR/Cas9-mediated mutagenesis is now routinely used in Ciona as an important technique used to interrogate gene function in diverse biological processes, validated single-guide RNAs (sgRNAs) have yet to be validated for several key neural genes. Here, we report the design and experimental validation of 25 novel sgRNAs targeting eight conserved genes encoding conserved proteins involved in neurodevelopment and neural function, including six transcription factors (Cdx, Foxb, Sox1/2/3, Dmbx, Engrailed, and Mnx) and two neural effector genes (Tyrosinase and Slc18a3/VAChT). Candidate sgRNAs were selected and tested for mutagenesis efficiency using Illumina-based target site amplicon sequencing. All sgRNAs induced insertions or deletions at their target loci, with most genes yielding at least one sgRNA with mutagenesis efficacy exceeding 30%, with the exception of Dmbx, for which maximal efficacy reached 25%. We further compared measured mutagenesis rates to scores generated by different predictive algorithms, observing a modest but potentially improved correlation with predictions based on a newer algorithm. Based on these results, we recommend considering both scoring algorithms in combination, for improved predictive value for Ciona.

1. Introduction

The development of the central nervous system (CNS) in any organism relies on the precise spatial and temporal transcriptional regulation of genes that control the differentiation of neural progenitors into distinct, fully functional neuronal subtypes (Hobert and Kratsios, 2019). Ciona robusta, a tunicate, represents a simplified model system for investigating nervous system development, with a much reduced CNS comprised of little over 200 neurons and sensory cells (Nishino, 2018; Ryan and Meinertzhagen, 2019).

Like many tunicates, Ciona follow a biphasic lifecycle, meta-morphosing from a swimming larva into a sessile adult (Karaiskou et al., 2015). Swimming behaviors in Ciona are directly controlled by a handful of CNS cells that comprise the motor ganglion (MG) and tail nerve cord, parts of which might be homologous to vertebrate hindbrain and spinal cord (Kourakis et al., 2025; Piekarz and Stolfi, 2024). Various swimming behaviors enable the larvae to identify suitable, hard substrates on which to settle and initiate metamorphosis. (Bostwick et al., 2019; Hoyer et al., 2024; Kourakis et al., 2019; Salas et al., 2018; Tolstenkov et al., 2025; Yang et al., 2026). Upon adherence to an appropriate substrate, metamorphosis can be triggered through mechanosensory cues (Hozumi et al., 2025; Totsuka and Hotta, 2025; Wakai et al., 2021).

Although tunicates have been studied as model organisms for cell, developmental, and organismal biology for over 100 years (Conklin, 1905; Lemaire, 2009), various molecular techniques have been more recently adapted to studying the Ciona CNS (Olivo et al., 2021). Of note, CRISPR/Cas9 is now routinely used to study gene function in Ciona and other tunicates (Pennati et al., 2024). Recent improvements to the experimental pipeline for the design and validation of single-chain guide RNAs (sgRNAs) for tissue-specific CRISPR/Cas9-mediated mutagenesis have been described in Ciona (Pennati et al., 2024; Popsuj et al., 2024; Sasakura and Horie, 2023). Here we report the use of such improved methods to design and validate new sgRNAs targeting genes of interest expressed in the larval CNS of Ciona robusta. Their targets comprise a variety of conserved transcriptional regulators of neurodevelopment, in addition to two conserved effectors of sensory/neural cell function. Most of these genes have not been previously knocked out in Ciona using CRISPR/Cas9. These reagents are being made freely available to the Ciona community, in the hopes that they can be readily used to further study the larval nervous system.

2. Methods and results

We sought to design and validate sgRNAs targeting several C. robusta genes involved in neural development and function. To start, we selected 6 transcription factor genes with well-documented expression patterns in Ciona development (Imai et al., 2004, 2006, 2009), encoding a mix of early-expressed regulators (Cdx, Foxb, Sox1/2/3) and later-onset ones (Dmbx, Engrailed, Mnx). Additionally, we designed sgRNAs targeting the Tyrosinase (Tyr) gene, which encodes the rate-limiting enzyme for melanin biosynthesis in pigmented cells associated with photo- and geo-sensory organs of the larva. Tyr-targeting sgRNAs have already been designed (Pickett and Zeller, 2018; Song et al., 2022; Vitrinel et al., 2023), though these have not been formally validated by target amplicon next-generation sequencing, to our knowledge. Finally, we also designed sgRNAs targeting Slc18a3 (commonly referred to as Vesicular acetylcholine transporter, or VAChT). This gene part of a highly conserved “cholinergic locus” that also encodes for Choline acetyltransferase (ChAT), with both VAChT and ChAT transcripts sharing a first exon (Kratsios et al., 2012). In Ciona, VAChT/ChAT is expressed in motor neurons and other cholinergic neurons of the CNS (Horie et al., 2010; Imai et al., 2009; Jokura et al., 2020; Nishino et al., 2011; Takamura et al., 2010; Yoshida et al., 2004).

Candidate sgRNAs were identified using the online webtool CRISPOR (Concordet and Haeussler, 2018), according to our recent guidelines (Popsuj et al., 2024). Where possible, sgRNAs with predicted Doench ’16 efficacy scores >50 were selected. For Dmbx, suitable sgRNAs were limited due to its very small exons and a paucity of highly scored sgRNA candidates. The sgRNA expression plasmids (containing the small U6 RNA promoter) were constructed using either older oligonucleotide- or PCR-based subcloning protocols (Stolfi et al., 2014) or a newer approach based on de novo gene synthesis and custom cloning services (Twist Bioscience)(Johnson et al., 2023). In all, 25 sgRNAs targeting the 8 genes were tested by a standard, commercially available Illumina-based, next-generation target site amplicon sequencing service (Amplicon-EZ by Genewiz) as previously described (Popsuj et al., 2024). This commercial service returns automated indel frequencies for each sgRNA, with no additional bioinformatic knowledge or analysis needed. The protocol for sgRNA validations can be found at: https://doi.org/10.17504/protocols.io.14egnr97yl5d/v1.

Amplicon sequencing revealed indels at the target site for all sgRNAs tested, with varying indel frequency, or mutation efficacy, as automatically calculated by the Amplicon-EZ service. Those sgRNAs with the best, or acceptable measured indel rates are shown according to their target location in each locus, along with their corresponding amplicon sequencing indel plots (Figs. 1–3). These are the sgRNAs we would recommend using to disrupt these genes. All genes had at least one sgRNA with efficacy >30%, again with the exception of Dmbx. Although we designed and tested 5 sgRNAs against this gene, the highest efficacy achieved was 25% with one particular sgRNA (Fig. 2). All sgRNA sequences, PCR primer sequences, and the predicted and measured efficacies of each sgRNA are presented here (Fig. 4, Supplemental Table 1, Supplemental Sequences File). Some of the measured efficacies were approximated by measuring the peak of the resulting indel plot, as naturally occurring indels and SNPs prevented the automated return of a precise efficacy value.

Fig. 1. Cdx, Foxb, and Sox1/2/3 loci and sgRNA validation results.

Fig. 1.

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Selected sgRNA target sites are indicated, along with Amplicon-EZ (Genewiz) indel plots and estimated mutagenesis rates. Red arrows indicate CRISPR-generated indel peaks. Grey asterisks indicate naturally-occurring indels. Mutagenesis rates are automatically calculated by the Amplicon-EZ service where only one major indel peak is present. Rates are approximated for plots in which naturally occurring indels confounded automatic rate estimation. In such cases, the mutagenesis rate is at least higher than the height of the CRISPR indel peak.

Fig. 3. Tyrosinase and VAChT loci and sgRNA validation results.

Fig. 3.

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A) Selected Tyrosinase sgRNA target sites are indicated, along with Amplicon-EZ (Genewiz) indel plots and automated mutagenesis rate estimations. Mutagenesis rates are approximated for plots in which naturally occurring indels confounded automatic rate estimation as described before. B) Left: diagram of simple pigmentation assay (see text for details). Right: results of pigmentation assay of Tyr CRISPR larvae using sgRNAs 1.185 and 5.16 together (40 μg each) in combination with 50 μg Sox1/2/3>Cas9::GemininNterminus. (Pennati et al., 2024; Stolfi et al., 2014). CRISPR larvae (n = 45) were compared to negative control larvae (n = 29) electroporated with 80 μg of the “control” sgRNA plasmid instead (Stolfi et al., 2014). Plasmid DNA amounts indicated per 700 μl of total electroporation volume. Statistical significance determined using Fisher’s exact test. C) Selected VAChT sgRNA target sites indicated, along with indel plots. Dashed red line indicates alternative splicing of first exon with remaining exons encoding choline acetyltransferase (ChAT) out of view, as part of a conserved cholinergic locus. Red arrows indicate CRISPR-generated indel peaks. Grey asterisks indicate naturally-occurring indels.

Fig. 2. Dmbx, Engrailed, and Mnx loci and sgRNA validation results.

Fig. 2.

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Selected sgRNA target sites are indicated, along with Amplicon-EZ (Genewiz) indel plots and automated mutagenesis rate calculations. Red arrows indicate CRISPR-generated indel peaks. Grey asterisks indicate naturally-occurring indels. Mutagenesis rates are approximated for plots in which naturally occurring indels confounded automatic rate estimation as described before.

Fig. 4. Table of all sgRNAs designed and tested in this study.

Fig. 4.

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All sgRNA target sequences tested in this study, along with predicted efficacy scores from CRISPOR, namely Doench ’16 and Doench Ruleset 3 (RS3). Norm. ’16 and Norm. RS3 represents normalized Doench ’16 and Doench RS3 scores, in which the represented ranges (not absolute theoretical score ranges) are converted to a scale from 0 to 1. Norm + Ave = normalized Doench ’16 and RS3 scores averaged. Mut. % = mutagenesis efficacy as measured by Amplicon-EZ sequencing. Mut. % scores in blue represent efficacies estimated from size of indel peak, and not the automated efficacies as given by automated Amplicon-EZ analysis (black Mut. % scores).

To further validate the efficacy of Tyr sgRNAs, we performed a simple cell pigmentation assay (Fig. 3B). We combined sgRNA expression vectors 1.185 and 5.16, which target separate exons, and coelectroporated them with Sox1/2/3>Cas9::GemininNterminus to knock out Tyr in the ectoderm from which the pigment cells are derived. While wild-type larvae typically have two pigment cells (1 ocellus pigment cell and 1 otolith), loss of Tyrosinase function results in loss of pigmentation (Jiang et al., 2005; Pickett and Zeller, 2018). Indeed, we found a statistically significant increase in the frequency of larvae with zero or only one pigment cell. The latter is expected in cases of left/right mosaic knockouts. The ~50% reduction in pigment cell frequency was around that expected given the sgRNA efficacies we measured by amplicon sequencing (Fig. 3A). However, even though it is known that combining sgRNAs can result in large deletions spanning the sgRNA target sites (Abdul-Wajid et al., 2015), the Amplicon-EZ sequencing parameters prevent our measuring the efficacy of such large deletions with this service. We are also unaware of any other commercially available sequencing technology that could accurately measure large deletion efficacies in F0.

CRISPOR recently introduced the use of an updated Doench ’16 algorithm, named “Doench Ruleset 3” (RS3)(DeWeirdt et al., 2022). Whereas we typically avoid Doench ’16 scores <50, RS3 scores span a larger range of values. However, our initial sgRNA designs did not take Doench RS3 into account. We therefore sought to re-evaluate the correlation between these predictive algorithms and the actual mutagenesis efficacies, as the newer algorithm was not offered during previous Ciona CRISPR optimization studies. In our small dataset, there was moderate correlation between predicted scores and measured mutagenesis efficacies, with slightly higher Pearson correlation coefficients specifically for the RS3 algorithm (Fig. 5). The correlation was slightly higher when comparing measured efficacies to the average of both Doench scores after normalization (“Doench Norm + Ave”). We therefore recommend that both Doench scores (’16 and RS3) be taken into consideration when selecting candidate sgRNAs for CRISPR in C. robusta, though RS3 might be the more reliable predictive algorithm going forward. Future studies using an unbiased set of predicted sgRNAs will be needed to more thoroughly compare these algorithms, bearing in mind that the sgRNAs analyzed here were already selected for high Doench ’16 scores.

Fig. 5. Plotting predicted and measured mutagenesis efficacies.

Fig. 5.

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Plots comparing predicted efficacy scores (Doench ’16, Doench Ruleset 3/RS3, or normalized/averaged Doench scores) to actual mutagenesis efficacies as measured/estimated by Amplicon-EZ sequencing. All data according to the table in Fig. 4. Pearson’s correlations calculated and shown for each set of predictions.

3. Conclusion

We have designed and tested novel sgRNA expression plasmids targeting 8 different neurodevelopmental genes in the model tunicate Ciona robusta. We are publishing and sharing these immediately, in the hopes that they will be of use for the larger Ciona research community. These and other published plasmids (e.g. Cas9 expression plasmids) are available upon request. We are also happy to share access to our onboarded sgRNA and Cas9 expression at Twist Bioscience, for easy custom synthesis and cloning of new sgRNAs and Cas9 vectors. Finally, comparing predicted and measured indel efficacy rates suggests that the new “Doench Ruleset 3” score in the online prediction tool CRISPOR might be the preferred algorithm to consider when picking new sgRNAs for CRISPR in Ciona, though for now we recommend selecting sgRNAs that score highly with both algorithms.

Supplementary Material

Supplemental Table 1
Supplemental Sequences

Acknowledgments

This work was funded by NIH grants R35GM158421 and R01HD104825 to A.S. We thank Dexter Dean and past and current members of the lab for helpful feedback and technical assistance.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.diff.2026.100973.

Footnotes

CRediT authorship contribution statement

Sydney Popsuj: Conceptualization, Investigation, Project administration, Supervision, Writing – review & editing. Tenzin Kalsang: Conceptualization, Investigation. Kwantae Kim: Conceptualization, Investigation. Erica Drummond: Conceptualization, Investigation, Writing – review & editing. Pooja Manekar: Conceptualization, Data curation, Investigation, Writing – review & editing. Pranavvarma Munagapati: Conceptualization, Investigation. Manasi Oleti: Conceptualization, Investigation. Hiroki Sato: Conceptualization, Investigation. Izabella Vickery: Conceptualization, Investigation. Eduardo D. Gigante: Conceptualization, Investigation, Resources. Alberto Stolfi: Conceptualization, Data curation, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft.

References

  1. Abdul-Wajid S, Morales-Diaz H, Khairallah SM, Smith WC, 2015. T-type calcium channel regulation of neural tube closure and EphrinA/EPHA expression. Cell Rep. 13, 829–839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bostwick M, Smith E, Borba C, Newman-Smith E, Guleria I, Kourakis M, Smith W, 2019. Antagonistic inhibitory circuits integrate visual and gravitactic behaviors. Curr. Biol. 600–609.e602. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Concordet J-P, Haeussler M, 2018. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res. 46, W242–W245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Conklin EG, 1905. Organ-forming substances in the eggs of ascidians. Biol. Bull. 8, 205. [Google Scholar]
  5. DeWeirdt PC, McGee AV, Zheng F, Nwolah I, Hegde M, Doench JG, 2022. Accounting for small variations in the tracrRNA sequence improves sgRNA activity predictions for CRISPR screening. Nat. Commun. 13, 5255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Hobert O, Kratsios P, 2019. Neuronal identity control by terminal selectors in worms, flies, and chordates. Curr. Opin. Neurobiol. 56, 97–105. [DOI] [PubMed] [Google Scholar]
  7. Horie T, Nakagawa M, Sasakura Y, Kusakabe TG, Tsuda M, 2010. Simple motor system of the ascidian larva: neuronal complex comprising putative cholinergic and GABAergic/glycinergic neurons. Zool. Sci. 27, 181–190. [DOI] [PubMed] [Google Scholar]
  8. Hoyer J, Kolar K, Athira A, van den Burgh M, Dondorp D, Liang Z, Chatzigeorgiou M, 2024. Polymodal sensory perception drives robust attachment and metamorphosis of a prevertebrate zooplanktonic larva. Curr. Biol. [DOI] [PubMed] [Google Scholar]
  9. Hozumi A, Totsuka NM, Onodera A, Wang Y, Hamada M, Shiraishi A, Satake H, Horie T, Hotta K, Sasakura Y, 2025. Stimulatory and inhibitory G-protein signaling relays drive cAMP accumulation for timely metamorphosis in the chordate Ciona. eLife 13. RP99825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Imai KS, Hino K, Yagi K, Satoh N, Satou Y, 2004. Gene expression profiles of transcription factors and signaling molecules in the ascidian embryo: towards a comprehensive understanding of gene networks. Development 131, 4047–4058. [DOI] [PubMed] [Google Scholar]
  11. Imai KS, Levine M, Satoh N, Satou Y, 2006. Regulatory blueprint for a chordate embryo. Science 312, 1183. [DOI] [PubMed] [Google Scholar]
  12. Imai KS, Stolfi A, Levine M, Satou Y, 2009. Gene regulatory networks underlying the compartmentalization of the Ciona central nervous system. Development 136, 285–293. [DOI] [PubMed] [Google Scholar]
  13. Jiang D, Tresser JW, Horie T, Tsuda M, Smith WC, 2005. Pigmentation in the sensory organs of the ascidian larva is essential for normal behavior. J. Exp. Biol. 208, 433–438. [DOI] [PubMed] [Google Scholar]
  14. Johnson CJ, Kulkarni A, Buxton WJ, Hui TY, Kayastha A, Khoja AA, Leandre J, Mehta VV, Ostrowski L, Pareizs EG, Scotto RL, Vargas V, Vellingiri RM, Verzino G, Vohra R, Wakade SC, Winkeljohn VM, Winkeljohn VM, Rotterman TM, Stolfi A, 2023. Using CRISPR/Cas9 to identify genes required for mechanosensory neuron development and function. Biol. Open 12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Jokura K, Nishino JM, Ogasawara M, Nishino A, 2020. An α7-related nicotinic acetylcholine receptor mediates the ciliary arrest response in pharyngeal gill slits of Ciona. J. Exp. Biol. 223 jeb209320. [DOI] [PubMed] [Google Scholar]
  16. Karaiskou A, Swalla BJ, Sasakura Y, Chambon JP, 2015. Metamorphosis in solitary ascidians. Genesis 53, 34–47. [DOI] [PubMed] [Google Scholar]
  17. Kourakis MJ, Borba C, Zhang A, Newman-Smith E, Salas P, Manjunath B, Smith WC, 2019. Parallel visual circuitry in a basal chordate. eLife 8, e44753. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kourakis MJ, Ryan K, Newman-Smith ED, Meinertzhagen IA, Smith WC, 2025. Motor neurons in the tunicate caudal central nervous system reveal homology to the vertebrate spinal cord. Development 152. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kratsios P, Stolfi A, Levine M, Hobert O, 2012. Coordinated regulation of cholinergic motor neuron traits through a conserved terminal selector gene. Nat. Neurosci. 15, 205. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Lemaire P, 2009. Unfolding a chordate developmental program, one cell at a time: invariant cell lineages, short-range inductions and evolutionary plasticity in ascidians. Dev. Biol. 332, 48–60. [DOI] [PubMed] [Google Scholar]
  21. Nishino A, 2018. Morphology and Physiology of the Ascidian Nervous Systems and the Effectors, Transgenic Ascidians. Springer, pp. 179–196. [DOI] [PubMed] [Google Scholar]
  22. Nishino A, Baba SA, Okamura Y, 2011. A mechanism for graded motor control encoded in the channel properties of the muscle ACh receptor. Proc. Natl. Acad. Sci. 108, 2599–2604. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Olivo P, Palladino A, Ristoratore F, Spagnuolo A, 2021. Brain sensory organs of the Ascidian Ciona robusta: structure, function and developmental mechanisms. Front. Cell Dev. Biol. 2435. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Pennati A, Jakobi M, Zeng F, Ciampa L, Rothbächer U, 2024. Optimizing CRISPR/Cas9 approaches in the polymorphic tunicate Ciona intestinalis. Dev. Biol. 510, 31–39. [DOI] [PubMed] [Google Scholar]
  25. Pickett C, Zeller RW, 2018. Efficient genome editing using CRISPR-Cas-mediated homology directed repair in the ascidian Ciona robusta. Genesis 56, e23260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Piekarz KM, Stolfi A, 2024. Development and circuitry of the tunicate larval Motor Ganglion, a putative hindbrain/spinal cord homolog. J. Exp. Zool. B Mol. Dev. Evol. 342, 200–211. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Popsuj S, Cohen L, Ward S, Lewis A, Yoshida S, Herrera RA, Cota CD, Stolfi A, 2024. CRISPR/Cas9 protocols for disrupting gene function in the non-vertebrate chordate Ciona. Integr. Comp. Biol. icae108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Ryan K, Meinertzhagen IA, 2019. Neuronal identity: the neuron types of a simple chordate sibling, the tadpole larva of Ciona intestinalis. Curr. Opin. Neurobiol. 56, 47–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Salas P, Vinaithirthan V, Newman-Smith E, Kourakis MJ, Smith WC, 2018. Photoreceptor specialization and the visuomotor repertoire of the primitive chordate Ciona. J. Exp. Biol. jeb. 177972. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Sasakura Y, Horie T, 2023. Improved Genome Editing in the Ascidian Ciona with CRISPR/Cas9 and TALEN, Genome Editing in Animals: Methods and Protocols. Springer, pp. 375–388. [DOI] [PubMed] [Google Scholar]
  31. Song M, Yuan X, Racioppi C, Leslie M, Stutt N, Aleksandrova A, Christiaen L, Wilson MD, Scott IC, 2022. GATA4/5/6 family transcription factors are conserved determinants of cardiac versus pharyngeal mesoderm fate. Sci. Adv. 8 eabg0834. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Stolfi A, Gandhi S, Salek F, Christiaen L, 2014. Tissue-specific genome editing in Ciona embryos by CRISPR/Cas9. Development 141, 4115–4120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Takamura K, Minamida N, Okabe S, 2010. Neural map of the larval central nervous system in the ascidian Ciona intestinalis. Zool. Sci. 27, 191–203. [DOI] [PubMed] [Google Scholar]
  34. Tolstenkov O, Ozawa A, Allombert-Blaise C, Høyer J, Hiraiwa T, Chatzigeorgiou M, 2025. The cellular and behavioral blueprints of chordate rheotaxis. bioRxiv 2025, 2003.2022.644710. [Google Scholar]
  35. Totsuka NM, Hotta K, 2025. Optogenetic activation of primary sensory neurons induces metamorphosis in Ciona. Dev. Biol. [DOI] [PubMed] [Google Scholar]
  36. Vitrinel B, Vogel C, Christiaen L, 2023. Ring finger 149-Related is an FGF/MAPK-Independent regulator of pharyngeal muscle fate specification. Int. J. Mol. Sci. 24, 8865. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Wakai MK, Nakamura MJ, Sawai S, Hotta K, Oka K, 2021. Two-round Ca2+ transient in papillae by mechanical stimulation induces metamorphosis in the ascidian Ciona intestinalis type A. Proc. Roy. Soc. B 288, 20203207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Yang L-K, Qin Q, Zhang J, Zhang Z, Yu H, Zhao C, Dong B, 2026. Taurine-driven chemotaxis and metamorphosis in ascidian tadpole larvae. Sci. Adv. 12 eaeb9574. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Yoshida R, Sakurai D, Horie T, Kawakami I, Tsuda M, Kusakabe T, 2004. Identification of neuron-specific promoters in Ciona intestinalis. Genesis 39, 130–140. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Table 1
NIHMS2203367-supplement-Supplemental_Table_1.xlsx (14.5KB, xlsx)
Supplemental Sequences
NIHMS2203367-supplement-Supplemental_Sequences.docx (18.3KB, docx)

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