1 Molecular profiles, sources and lineage

2 restrictions of stem cells in an annelid

3 regeneration model

4 Alexander W. Stockinger¹,²,³,⁴,⁵*, Leonie Adelmann¹,²,³,⁴,⁵*, Martin Fahrenberger¹,³,⁴,⁶,⁷,

5 Christine Ruta⁸, B. Duygu Özpolat⁹,#, Nadja Milivojev¹,²,³,⁴,⁵, Guillaume Balavoine⁹,@, Florian

6 Raible¹,²,³,@

7

8 1, Max Perutz Labs, Vienna Biocenter Campus (VBC), Vienna, Austria

9 2, University of Vienna, Center for Molecular Biology, Department of Genetics and Microbiology, Vienna, Austria

10 3, Research Platform Single-Cell Regulation of Stem Cells (SinCeReSt), University of Vienna, Vienna, Austria

11 4, Vienna Biocenter PhD Program, a Doctoral School of the University of Vienna and the Medical University of Vienna, Vienna, Austria

15 5, PhD Programme Stem Cells, Tissues, Organoids – Dissecting Regulators of Potency and Pattern Formation (SCORPION), University of Vienna, Vienna, Austria

17 6, Center for Integrative Bioinformatics Vienna (CIBIV), University of Vienna and Medical University of Vienna, Austria

19 7, Medical University of Vienna, Max Perutz Labs, Vienna, Austria.

20 8, Institute of Biology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

21 9, Université de Paris Cité, CNRS, Institut Jacques Monod, Paris, France

22

23 * these authors contributed equally to this work

24 # present address: Department of Biology, Washington University in Saint Louis, MO, USA

25

26 @ correspondence for transgenic work: guillaume.balavoine@ijm.fr

27 @ correspondence for single-cell analyses: florian.raible@univie.ac.at
28

Abstract

29

30

31

32

33

34

35

36

37

38

39

40

41

42

Regeneration of missing body parts can be observed in diverse animal phyla, but it remains unclear to which extent these capacities rely on shared or divergent principles. Research into this question requires detailed knowledge about the involved molecular and cellular principles in suitable reference models. By combining single-cell RNA sequencing and mosaic transgenesis in the marine annelid *Platynereis dumerilii*, we map cellular profiles and lineage restrictions during posterior regeneration. Our data reveal cell-type specific injury responses, re-expression of positional identity factors, and the re-emergence of stem cell signatures in multiple cell populations. Epidermis and mesodermal coelomic tissue produce distinct putative posterior stem cells (PSCs) in the emerging blastema. A novel mosaic transgenesis strategy reveals both developmental compartments and lineage restrictions during regenerative growth. Our work supports the notion that posterior regeneration involves dedifferentiation, and reveals molecular and mechanistic parallels between annelid and vertebrate regeneration.
43 Introduction

44 The ability of some animals to regenerate missing body parts is a fascinating phenomenon.
45 Whereas the regenerative ability of mammals is generally limited to individual cell types or
46 a few specific organs, other animals are capable of rebuilding their entire body from mere
47 fragments of tissue. Complex tissue regeneration can be observed in almost all clades of
48 bilaterian life and might therefore reflect an ancient capacity ¹,². This regenerative process
49 usually involves the formation of an epimorphic, proliferative cell mass called blastema ³.
50 The cellular sources and molecular properties of blastema cells, however, differ between
51 available model systems. For example, whereas some invertebrates like the planarian
52 *Schmidtea mediterranea* form their blastemas from totipotent stem cells⁴, other regenerative
53 models employ less potent stem cells, such as uni- or oligopotent progenitors, and make use
54 of dedifferentiation, transdifferentiation or a combination of these processes ³,⁵⁻⁷. While
55 molecular similarities between these regenerative strategies can be observed across phyla,
56 we still lack comprehensive data on representative species to uncover whether or not these
57 similarities indicate true homologies ³. Defining molecular signatures of blastema formation
58 in accessible model systems and regeneration paradigms will be a key requirement for such
59 comparisons.
60

60
61 Annelids show particular promise as models to inform mechanisms and pathways of
62 blastema-based regeneration. Many species within this clade exhibit the ability to regenerate
63 large parts of their primary body axis. Annelids are phyletically well-positioned for long-
64 range comparisons with other lophotrochozoan clades, such as planarians, as well as
65 deuterostomes (which include vertebrates). Likewise, comparisons between different
66 annelids provides an avenue to assess modulation of regenerative capacities within the clade
67 8-12. This makes annelids ideal models to assess both commonalities and differences in
68 regeneration processes.
69

70 The nereidid worm *Platynereis dumerilii* has a long history as a model system for
71 regeneration and regenerative growth 8,9. This bristleworm can be continuously bred in the
72 laboratory, and offers a variety of molecular and genetic tools for analysis, including
73 transcriptomic profiling, multiplexed detection of RNAs in fixed specimens, and transgenic
74 manipulation 9,13-17.

75
76 During normal development, *Platynereis* grows by continuous segment addition, which
77 involves a dedicated ring-shaped “segment addition zone” (SAZ) located between the
78 posterior-most segment and the post-segmental pygidium 18. Molecularly, the SAZ harbors
79 putative posterior stem cells (PSCs) that express members of the germline multipotency
80 program (GMP) 19, such as *piwi*, *vasa* and *nanos*.
81

81
Upon amputation across the primary body axis, *Platynereis* re-establishes a functional SAZ which then produces the missing posterior segments. Morphologically, this process has been well characterized (reviewed in ⁸,¹⁰,²⁰): in a first, rapid response to injury, the gut seals the wound. In a second step, epidermal cells cover the injury under a wound epithelium, followed by the formation of a largely undifferentiated blastemal cell mass, from which the new SAZ emerges. After this point, new segments are added and the animals grow faster than during regular development ¹⁰,²¹.

The source of stem cells during regeneration has been of long-standing interest. Tissue-residual stem cells, as well as the de- and trans-differentiation of somatic cells have been observed as sources of animal blastemas (reviewed in ⁵,⁶,²²). While adult stem cells as a source have been described in some invertebrates, such as planarians (see above), most data within annelids point towards de-differentiation as a likely source of stem cells during regeneration (reviewed in ⁸,²⁰), with few exceptions found among the class *Clitellata* (reviewed in¹⁰).

In *Platynereis*, early cytological evidence already suggested the amputation-induced emergence of new stem cells in differentiated tissues such as the wound-adjacent epidermis. This process has classically been referred to as “re-embryonalisation” ²³. Re-amputation, along different planes of posterior regenerates that had been labeled using EdU (5'-ethynyl-2'-deoxyuridine) incorporation, suggests that resident proliferating cells do not contribute disproportionately to the regenerating SAZ. It has therefore been suggested that the *Platynereis* SAZ regenerates from wound-adjacent, presumably differentiated cells, which activate GMP gene expression and re-enter the cell cycle after injury ²¹.

24 hours post amputation (hpa), the wound is covered with an epithelium. This stage can be reached even when proliferation is inhibited ²¹. At 24 hpa, several genes usually found in the SAZ of uninjured animals, such as the ectodermal PSC marker *hox3* and the GMP members *piwi* and *myc*, are expressed *de novo* in and near the wound.

After 48 hpa, injured worms have formed a blastema, at which point proliferation increases markedly ²¹. Bulk transcriptomic profiling and an analysis of epigenetic factor expression during regeneration support the idea that these steps are accompanied by chromatin remodeling ²⁴,²⁵. While other cell sources, such as quiescent and currently undiscovered residual stem cells can not be fully excluded, these findings support the notion of differentiated cells providing the source for a regenerating SAZ through dedifferentiation.

Currently available data lack the cellular resolution to identify tissue- and cell type specific properties of regeneration in *Platynereis*, including the transcriptional profile of cells responding to injury with chromatin remodeling and GMP gene expression as outlined above.
Additionally, no information regarding the differentiation potential / lineage restriction of *Platynereis* PSCs is currently available, further complicating comparative analyses. To gain deeper and unbiased insight into this process and enable cross-species comparisons of blastema based regeneration, molecular profiling at cellular resolution and clonal information of lineage restriction are required.

Here, we follow a dual approach of single-cell RNA sequencing and transgenesis experiments throughout posterior regeneration to address these challenges. By sampling single-cell transcriptomes at multiple regenerative stages and comparing them to wound-adjacent tissue right after injury, we are able to derive a comprehensive, time-resolved map of cellular profiles over the regenerative process. We detect cell-type specific injury responses and re-expression of positional identity factors. We also uncover that multiple wound-adjacent cell populations start expressing stem cell related genes and enter the cell cycle upon injury, consistent with the notion that these cells undergo dedifferentiation.

Investigating signature genes for two of these populations, we identify the epidermis and mesodermal coelomic tissue as two likely source tissues that produce distinct PSCs in the segment addition zone. Capitalizing on a novel mosaic transgenesis strategy, we are able to identify both developmental compartments and restrictions in cell lineages throughout posterior growth and regeneration. We demonstrate that the SAZ of *Platynereis dumerilii* harbors separate pools of lineage-restricted PSCs and that these pools are regenerated from cells originating from distinct embryonic germ layers. Our combined datasets provide a detailed view of the sources, molecular signatures and differentiation potential of major cell types in the blastema, and reveal molecular and mechanistic similarities between annelid and vertebrate regeneration.

## 147 Results

### A temporally resolved single cell atlas reveals the dynamic transcriptional landscape of posterior regeneration

To establish a first unbiased, in-depth analysis of the transcriptomic landscape of individual cell populations during posterior regeneration in annelids, we devised a suitable sampling scheme. For this, we induced posterior regeneration by removing approximately ⅓ of the animals' posterior tissue, including the SAZ and its rapidly proliferating progeny, amputating between segments 30 and 31. For sampling, we then isolated the posteriormost segment along with any newly regenerated tissue at distinct time points after amputation (Supplementary Fig. 1a).
We reasoned that inclusion of the last non-amputated segment in these analyses would not only provide us with data on differentiated cell types, but also allow us to detect any molecular signatures associated with the response of this segment to the adjacent wound. To assess whether this sampling scheme captured relevant molecular events in the early phases of blastema formation, we first performed a bulk RNA sequencing experiment, in which the total mRNA of each sampling time point was sequenced from biological triplicates. By using an unbiased gene-clustering approach, we determined seven major categories of gene expression dynamics over the first three days of regeneration, including four categories in which gene expression increased after amputation, with differences in the point of onset and kinetics (Supplementary Fig. 1b). Genes in these categories include known markers for stem cells and the SAZ, as well as proliferation-related transcripts (Supplementary Fig. 1b). These findings are consistent with previous observations<sup>21,24,25</sup> and confirmed that our sampling strategy could be used to capture relevant molecular processes.

Based on these results, we devised a similar sampling scheme to build a comprehensive single cell atlas of posterior regeneration (Fig. 1a). We obtained single cells from multiple dissociated samples, representing five distinct stages of regeneration. These spanned from freshly amputated individuals (0 hpa, equivalent to uninjured trunk segments, but not the posterior-most tissues such as the SAZ and its immediate progeny) to 72 hpa, corresponding to the onset of rapid proliferation in the regenerated SAZ<sup>21</sup>, increasing the temporal resolution in early regenerative stages by adding a 12 hpa timepoint (Fig. 1a). After removing outlier and low-quality cells, we obtained a total of 80,298 transcriptomes of individual cells, sampled in two independent biological replicates of 4 and 5 timepoints, respectively (Supplementary Data 1). Even though the sampling timepoints of this single cell experiment slightly differed from those sampled in bulk (see above), we compared the two datasets using a correlation analysis. Despite the use of different sampling, sequencing and processing techniques, all replicates correspond most strongly with those in the respective other dataset sampled at the closest time point (Supplementary Fig. 1c).
<figure><img src="image_1.png" /><figcaption>**C** merged timepoint contribution</figcaption></figure>

<figure><img src="image_2.png" /><figcaption>**f** *hox3*</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>**h** *myc*</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>**j**</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**b** merged single-cell regeneration atlas</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**d** *cdx*</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**e** *foxa*</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**g** *piwi*</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>**i**</figcaption></figure>

<figure><img src="image_10.png" /></figure>
Figure 1. A temporally resolved single cell atlas reveals the dynamic transcriptional landscape of cell populations during posterior regeneration. (a) Sampling scheme illustrating posterior amputation and sampling timepoints, ranging from 0 hours post amputation (0 hpa, equivalent to a regular trunk segment) to 72 hpa, matching morphologically defined stages (st. 0 to 3). (b) UMAP visualization of cells, annotated by tentative cell type / population identity. (c) UMAP visualization showing the regenerative timepoint at which cells were sampled. (d,e) UMAP visualizations showing the expression of posterior identity markers (cdx, foxa) on the merged dataset, contrasting the freshly amputated sample (left) with the post-amputation time points (right) (f-i) similar UMAP visualizations, highlighting the changes in expression of stem-cell related genes (hox3, piwi, myc) (f-h) as well as the emergence of hypertranscriptomic cells (UMIs/cell) (i),(j) UMAP visualization of CytoTRACE values (calculated per cluster; high level indicates high differentiation potential).

195

Single-cell data comprising multiple replicates or biological samples might suffer from batch effects, where technical differences between sampling rounds could overshadow biologically meaningful differences between samples or cell types ²⁶. To counter this effect and minimize technical variations, we took advantage of the recent establishment of a combined cell fixation and storage protocol (ACetic-MEthanol/ACME) that is compatible with single-cell sequencing ²⁷. The adaptation of this protocol for our *Platynereis* regenerate paradigm allowed us to sort, process and sequence cells from all sampled stages in parallel. We subsequently used standard single-cell RNA sequencing (scRNA-seq) analysis methods to process the joined data-set (see Methods).

205

Unbiased clustering of the cells resulted in 38 transcriptionally distinct clusters. The comparison between biological replicates and timepoints did not suggest any batch effect affecting cluster formation (Supplementary Data 1, Supplementary Fig. 2a-e). The resulting clusters, as illustrated on a uniform manifold approximation and projection (UMAP) visualization ²⁸ (Fig. 1b), correspond to cell populations of similar transcriptomic profiles. Algorithmic prediction ²⁹ identifies one cluster (cluster 26) as the possible product of doublet formation, so this cluster was not investigated further (Supplementary Data 1). We annotated these populations based on the identities of cluster-specific marker genes, and their expression levels of known annelid cell-type markers. In total, we annotated 35 of the clusters, either as known cell populations, or based on their most diagnostic marker gene (Fig. 1b, see details in Supplementary Data 2 and 3).

217

As each sampled tissue contains the segment adjacent to the injury site, we were able to identify a variety of cell types in our dataset. For example, an investigation of genes previously used for assigning different *Platynereis* muscle cell types ³⁰, allowed us to distinguish several populations of smooth (clusters 3, 6, 8, 12 and 14) and striated (clusters 2, 10, and 17) muscle. Even less abundant cell types, such as chaetal sac cells (cluster 24) which form the bristle worm's chitinous bristles ³¹,³² and extracellular globin-secreting cells (cluster 15) ³³, were identified as distinct populations. This shows that our approach yielded a high-quality cell atlas containing biologically meaningful clusters of cell populations and with sufficient sensitivity to resolve rare and poorly understood cell types.

218

219
227
228

Molecular repatterning and emerging stem cell-like properties
in distinct cell populations

229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264

As outlined above, deconvolving the dynamic injury response to individual cell populations in an annelid is expected to advance our understanding of regeneration in an evolutionary context. By capitalizing on the temporal information embedded in each transcriptome of our dataset (Fig. 1c), we were able to perform comparisons of gene expression within cell populations across time.

235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264

A common challenge in complex tissue regeneration is the re-establishment of appropriate positional information, such as the position along the antero-posterior axis. To test whether our dataset could be used to identify the individual cell types involved in repatterning, we analyzed the expression of several transcription factors involved in posterior identity. Bulk RNA sequencing of posterior regeneration and unbiased clustering of genes with similar expression dynamics using mfuzz (Supplementary Fig. 1b) revealed the presence of genes encoding posteriorly expressed transcription factors such as *caudal* (*cdx*), *distalless* (*dlx*) and *foxA*, in gene sets upregulated after injury. This is consistent with previous suggestions that early steps in annelid regeneration include a morphallactic adjustment of positional values<sup>34</sup>.

235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264

Using the single cell atlas, we were able to add cellular resolution to this process. For example, cells of midgut identity (cluster 16) are only found in the freshly amputated sample (0 hours post amputation, hpa), subsequently yielding to a population (cluster 4) demarcated by *foxA* and *cdx* as hindgut after injury (Fig. 1d,e). This morphallactic process of gut posteriorization indicated by *foxA* has previously been proposed in *Platynereis* <sup>35</sup>, demonstrating the validity of our *in silico* approach. In addition, a subset of neuronal populations (clusters 11, 20) expresses *cdx* and *foxA* shortly after injury (Fig. 1d, e), while two other populations (clusters 0, epithelium; cluster 9, *gcm+* neurons) started to express *dlx* (Supplementary Fig. 3a). Similarly, we observed a molecular shift in presumptive smooth muscle cells from cluster 14 (pre-injury) to clusters 8 (post-injury), involving genes like *thrombospondin*, *rho kinase* <sup>36</sup> and *octopamine receptor 2*, which play a role in muscle attachment, function and regeneration in other species <sup>37-40</sup> (Supplementary Data 3).

259
260
261
262
263
264

As these data supported our approach to reconstructing temporal dynamics, we next investigated the expression of stem cell related genes after posterior injury. We reasoned that if stem cells are, at least in part, regenerated by dedifferentiation or activation of wound-adjacent cells, we should detect cell populations that are already present at 0 hpa, but start to express stem cell and proliferation-related markers only after injury.
To assess this point, we first investigated the expression of the homeobox gene *hox3*, whose transcripts are rapidly upregulated in posterior regeneration of *Platynereis dumerilii*<sup>41</sup> and mostly restricted to a population of PSCs that are generally referred to as ectodermal PSCs in accordance with their presumed developmental origin<sup>18,21</sup>. Whereas homeostatic trunk cells (0 hpa) are almost entirely devoid of *hox3* expression, we could detect a strong and mostly cluster-specific upregulation of this gene in post-injury time points of cluster 0 (Fig. 1f). Likewise, we find that this cluster expresses *Platynereis piwi* (Fig. 1g), a key member of the GMP<sup>19</sup>, and *myc* (Fig. 1h), both of which are expressed in *Platynereis* PSCs<sup>18</sup>. These data suggest that cluster 0 is a source of ectodermal PSCs.

As outlined above, *hox3* is preferentially expressed in ectoderm-derived PSCs. However, additional populations of stem cells contributing to *Platynereis* growth and regeneration have previously been hypothesized, including mesoderm-derived PSCs<sup>21,42</sup>. We therefore systematically queried our single-cell atlas with a combined signature of stem cells (*piwi*, *vasa*, *nanos*), proliferation (*proliferating cell nuclear antigen/pcna*) and chromatin remodeling (*dnmt1*, *chd1*) These genes are expressed in cells of post-injury timepoints within several clusters, hinting at additional sources of PSCs (Fig. 1g-h, Supplementary Fig. 3b-f).

To identify the most stem-like cells in each cluster in an unbiased, systematic way, we used CytoTRACE, a computational method which assigns cells a score representative of their "developmental potential", a proxy for stemness<sup>43</sup>. Cells were ranked by their CytoTRACE score (within each cluster), and genes correlated with this score were calculated. This analysis provides an unbiased, systematic overview of transcriptional changes within each cell population as cells acquire a higher degree of developmental potential (Supplementary data 4). We further determined gene ontology (GO) terms associated with the transcriptional changes within each cluster, providing a more comprehensive resource for the involved biological processes (Fig. 1i; Supplementary Data 4 and below).

As an additional approach to identify potential stem cells, we took advantage of the observation that *Platynereis* PSCs exhibit larger nuclei and nucleoli<sup>18,23</sup>, a feature usually associated with increased transcriptional (and translational) activity<sup>44</sup>. Increased, broad transcription, referred to as "hypertranscription", is frequently observed in active stem cells and progenitors, closely associated with proliferation, and plays a role in stem cell activation and function during growth and regeneration. Recently, absolute scaling of single cell transcriptomes using Unique Molecular Identifier (UMI)-based sequencing data has been shown to identify hypertranscriptomic stem cells and progenitors<sup>45</sup>. We therefore investigated the dynamic changes in transcriptional activity upon injury in our dataset and found evidence for hypertranscription (increased numbers of total UMIs detected per cell) (Fig. 1j). Our analysis shows that there is a progressive increase in high-UMI cells during regeneration (Supplementary Fig. 3g). Hypertranscriptomic cells are located within hotspots
305 of GMP-related gene expression and high CytoTRACE values on the UMAP (Fig. 1i) and can
306 be found in several clusters. Our analysis also revealed a sub-population of smooth muscle
307 cells showing high CytoTRACE values and piwi expression even before injury (cluster 12,
308 Figure 1b,g,ii), which could imply the existence of a dedicated progenitor state within this
309 specific tissue.

310

311 Taken together, we found several features associated with stem cells and the SAZ in injury-
312 adjacent cells. These features are predominantly detected after injury, increasing as posterior
313 regeneration proceeds. We found cells that strongly display these features distributed
314 among multiple, but not all clusters in this dataset, indicating multiple different sources of
315 regenerating PSCs.

316 To understand these putative sub-populations of the regenerated SAZ, and their cellular
317 origins, we focused our analysis on two major cell populations (clusters 0 and 1), which show
318 a strong activation of stem-cell-related features as described above.

319

320 To characterize these populations, we identified strongly expressed marker genes and
321 performed *in situ* Hybridisation Chain Reactions (HCR, see Methods and Supplementary Data
322 5) to detect their expression in the tissue. ¹⁶,⁴⁶. Co-labeling of both genes in posterior parts
323 of uninjured, posteriorly growing animals revealed that they demarcate two spatially distinct
324 tissues, corresponding to the ectodermal epidermis (cluster 0) and a sub-epidermal
325 mesodermal cell type (cluster 1) (Fig. 2a-e). The latter population covers the sub-epidermal
326 region, but does not include muscle. We therefore refer to this population as coelomic
327 mesoderm.
<figure><img src="image_11.png" /><figcaption>Figure 2. Distinct wound-adjacent cell populations acquire stem cell properties upon amputation.</figcaption></figure>

(a,c) UMAP visualization of markers specific to cluster 0 (epig1) and 1 (ccdc134). (b,d,e) *in situ* HCR (uninjured animal, posterior end), showing mutually exclusive expression of *epig1* and *ccdc134* in the epidermis and coelomic mesoderm, respectively. Scale bar = 50µm. (f) Nuclear staining and *in situ* HCR of *col6a6* expression in wound-adjacent epidermal tissue at 3 timepoints after

328
329
330
331
332
333
334
335
336
337
338

posterior amputation. Amputation plane indicated with dotted line. Scale bar upper panels = 250µm, lower panels = 25µm. (g)
Quantification of nuclear and nucleolar size change in regenerating tissue at 0, 12 and 48 hpa; each timepoint represents 3
individuals with 50 nuclei or corresponding nucleoli per individual. Statistical significance was calculated using a one-way
ANOVA test with multiple comparisons. (h) *In situ* HCR of regenerating tissue at 0 and 72 hpa (stage 3), showing the expression
of putative stem cell markers for ectodermal (hox3) and mesodermal (prrx), combined with a ubiquitous stem cell marker (piwi)
and a proliferation label (EdU, 30min pulse before fixation); Scalebar = 50µm.

339
340

PSCs of ecto- and mesodermal origin exhibit shared and distinct
molecular signatures

341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357

Having found evidence for distinct sources of regenerated PSCs, we next aimed to
molecularly characterize them and profile them in situ. If indeed multiple populations of
wound-adjacent cells acquire stem cell properties and repopulate the regenerating SAZ, our
*in silico* data allows us to make certain testable predictions:

346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371

First, we examined whether cells of somatic origin change towards a teloblast-like
morphology. As described above, *Platynereis* PSCs display a unique morphology with
notably increased nuclear and nucleolar sizes. To test whether cells of this morphology
emerge in wound-adjacent tissue, we stained tissue of posteriorly amputated *Platynereis*
worms for the expression of *collagen alpha 6(VI) chain* (*col6a6*). Based on our CytoTRACE
calculation, *col6a6* is strongly expressed in epidermal cells (cluster 0) and progressively lost
as they acquire PSC-like properties (Supplementary data 4). Quantifying the surface area of
nuclei and nucleoli in this population during regeneration showed a strong increase in both
metrics after injury (Fig, 2f,g; Supplementary Fig. 4a-c), along with a gradual reduction of
*col6a6* levels. These data are consistent with the gradual acquisition of a teloblast-like
morphology.

358
359
360
361
362
363
364
365
366
367
368
369
370
371

Next, we reasoned that if these PSC-like sub-populations are distinct from each other, we
should be able to find genes specifically enriched in either of them and should find their
expression in distinct groups of cells *in situ*. As mentioned above, *hox3* has previously been
described as a marker predominantly expressed in ectoderm-derived PSCs, and accordingly
is mostly restricted to the PSCs we identified among epidermal cells (cluster 0). Based on
this observation, we sub-clustered cells of both the epidermal (cluster 0) and the coelomic
mesodermal (cluster 1) populations to define their respective PSC-like sub-populations. We
used CytoTRACE-scores, the total number of UMs and the expression of GMP, SAZ,
proliferation and epigenetic remodeling-related genes to identify the respective subclusters
(Supplementary Fig. 4) and discovered novel molecular markers unique to these cells
(Supplementary data 3; Supplementary Fig. 4d-f, 5a-s). These new markers include genes
encoding putative receptors, as well as proteins with DNA binding motifs such as
transcription factors, thus establishing a set of molecules with possible regulatory functions
(Supplementary Data 3).
372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

For ectoderm-derived PSCs, our analysis not only identifies the previously described genes *hox3* and *evenskipped* (*evx*) but adds markers such as a gene encoding a fibronectin leucine-rich transmembrane protein of unclear orthology (*flrtl*, Supplementary Fig. 6f-j) and a gene (*sp/btd*) encoding the *Platynereis* homolog of the transcription factor *Sp9*<sup>47</sup>. This population of cells further expresses early neuronal progenitor genes and patterning factors, such as the transcription factor gene *soxb1* (Supplementary Data 6) and the gene *four-jointed* that is involved in planar cell polarity, and was previously demonstrated to be expressed in developing medial neuroectoderm<sup>36</sup>. These data are consistent with the concept that these cells are the source of new neurons in post-regenerative growth.

For the mesoderm-derived population of PSCs, our analysis also predicts distinct marker genes. These include the gene *chd3/4/5b* that encodes a chromodomain helicase DNA-binding protein, and has previously been detected in regenerating mesoderm<sup>24</sup>, as well as a gene we identify as *Platynereis paired-related homeobox* gene (*prrx*) (Fig. 2j,k, Supplementary Data 6; Supplementary Fig. 6k-o). The putative purinoreceptor gene *p2x* (Fig. 2i) and the *Platynereis* orthologue of the mesoderm related homeobox factor *msx*<sup>48,49</sup> are also predicted to be expressed in mesoderm-derived PSCs, albeit less exclusively than *prrx* (Supplementary Fig. 6k-t; Supplementary Data 3).

If *prrx* and *flrtl* are novel markers of distinct populations of stem cells, they should be expressed in separate, injury-adjacent populations of cells and exhibit morphological and molecular properties of stem cells. To test this prediction, we designed specific *in situ* HCR probes (Supplementary Data 5) and used these to analyze the expression of both genes in posterior regenerates (Fig. 2j,k; Supplementary Fig. 4d,e; whole-mount *in situ* hybridisation in Supplementary Fig. 4e). In agreement with our digital data, *flrtl* transcripts were co-expressed with *hox3* in cells of the epidermal layer, both at stage 1 and 3 (Supplementary Fig. 4d). By contrast, the predicted mesodermal stem cell marker *prrx* labeled cells at a deeper layer (Fig. 2j; Supplementary Fig. 4d). Consistent with the time-resolved atlas (Supplementary Fig. 6k-o), *prrx* was not yet detectable at stage 1 (Fig. 2l), but from stage 2 on (Fig. 2p). In both cases, a subset of labeled cells shows enlarged nucleoli as described for PSCs (arrowheads in Fig. 2h-k).

These sub-populations, based on our *in silico* data and their putative identity as stem cells, are predicted to be proliferating and expressing GMP genes. We therefore co-stained markers for ectoderm (*hox3*) and mesoderm (*prrx*) derived putative stem cells with the proliferation marker EdU and the key GMP factor *piwi*. We found both markers expressed in proliferating, *piwi* positive cells with teloblast-like morphology (Fig. 2h-j).
Taken together, these results are consistent with the notion that, during regeneration, distinct populations of PSCs of mesodermal and ectodermal origin derive from existing cells not displaying any stem cell related properties prior to injury. Our single-cell atlas allows the identification of novel markers of these cells.

Clonal analysis by mosaic transgenesis reveals germ-layer based lineage restriction of posterior growth and regeneration

Whereas our data argued for PSCs of distinct ecto- and mesodermal origin in the blastema, it still remained unclear if these cells had identical potency, contributing to derivatives in all of the regenerate, or if they were more restricted in their developmental potential. We therefore turned towards a transgenic strategy that would allow us to address this question at least on the broad level of germ layers.

Several other lines of evidence from previous studies suggest the existence of lineage-restricted ectodermal and mesodermal stem cells during larval and juvenile posterior growth in *Platynereis* ¹⁸,⁵⁰⁻⁵². The early embryogenesis of *Platynereis* follows a stereotypical programme known as spiral cleavage ⁵³,⁵⁴. Highly asymmetric cell divisions (unequal cleavage) in the early embryo produce blastomeres of characteristic sizes and positions, whose fate are strictly determined ⁵⁰. Micro-injection of a fluorescent lineage-tracing dye in individual blastomeres at the earliest stages of the spiral cleavage process, shows that ectodermal, mesodermal, and endodermal trunk tissues of the 4-day, three segmented larva are produced, respectively, by micromere 2d, micromere 4d, and the macromeres 4A-4D of the early embryo ⁵⁰. In another study, individual cells were tracked via live imaging from early embryogenesis into early larval stages to identify the fates of the mesodermal 4d blastomere ⁵². This work revealed that the mesodermal bands and the primordial germ cells are produced by asymmetric divisions of the 4d lineage. In addition, the final divisions of the lineage during embryogenesis forms a group of undifferentiated cells at the posterior end of the hatched larvae, which will possibly become the mesodermal PSCs in later stages. Due to the transient nature of the signal (mRNA or dye injections), tracking the fate of putative PSCs into later juvenile stages was not feasible. However, molecular profiling ¹⁸ suggests but does not demonstrate the existence of at least two pools of PSCs with specific signatures, ectodermal and mesodermal, organized as two concentric rings anterior to the pygidium, the terminal piece of the *Platynereis* trunk (Supplementary Data 7, part A). So far, no transgenic lineage tracing technique has been used to clarify the origin of tissues in the posteriorly growing or regenerating juvenile.

To address this gap, we devised a mosaic transgenesis strategy using previously-established Tol2 transgenesis methods ¹⁵. We constructed a Tol2 transgenesis construct with a nuclear mCherry and a membrane EGFP ⁵², under the control of the ribosomal protein rps9 promoter
449 for ubiquitous expression ¹⁵ (Fig. 3a). We injected several batches of zygotes at the one-cell
450 stage with the donor plasmid containing rps9::H2A:mCherry:F2A:mGFP transgene and
451 transposase mRNA. These G0 worms typically show mosaic integration of the transgene.
452 We raised the G0 batches that showed high numbers of surviving juveniles (Supplementary
453 Data 7) (Fig. 3b-j). To screen these individuals for fluorescence patterns and identify which
454 clonal lineages had the transgene integration, we amputated juvenile worms when they
455 reached 6 weeks. These original tails (pygidium + a few growing segments) were imaged via
456 confocal microscopy from both the dorsal and ventral sides. The amputated worms were
457 further raised in individual containers and allowed to regenerate their posterior parts for
458 three weeks. They were then amputated again one segment anterior to the regenerated part
459 to collect the regenerated posterior parts for imaging. The whole cycle was repeated once.
460 For each transgenic individual, we thus collected pictures of the primary clones derived from
461 transgenic blastomeres as a result of normal development, as well as pictures of two
462 reiterative, independent regeneration events from the same primary clones originating from
463 the non-regenerated trunk (Supplementary Data 7, part B).
464
465
466
467
468
469
470
<figure><img src="image_12.png" /><figcaption>Figure 3. Mosaic transgenesis reveals developmental compartment restrictions of PSCs in *Platynereis* posterior elongation.</figcaption></figure>

(a) Summary sketch of the protocol for creating large embryonic clones with transposase. (b-g) Examples of simple germ layer- or tissue-specific primary clones observed on posteriorly growing worms; 6 weeks, ventral views. (b) Ectodermal clone, no pygidial or internal cell labeled. (c) Mesodermal clone, only the muscles are clearly visible (d) Pygidial and median neural lineage clones. Most median neurites are emanating from pygidial sensory neurons. (e) Endodermal clone. (f-i) Dorsal views of a primary clone in ectoderm-derived PSCs. (f) General confocal stack projection, showing the position of the ectoderm-derived PSCs and uniformly labeled nascent segments; the pygidium is labeled with independent clones. (g-i) Magnified confocal section views of the SAZ region, at 2 µm z-depth (g), 6.5 µm z-depth (h) and at y-z section (i). (g-i) show the continuity of the clonal expression of the transgene in bottleneck-shaped ectoderm-derived PSCs with large nuclei-nucleoli (yellow arrowheads), transversely elongated columnar progenitor cells and squamous epidermal differentiated cells. For all panels, green labelings are cell membranes, magenta labelings are cell nuclei. White arrows: position of the PSCs. White asterisks: background staining. Scale bars: b-f: 100 µm; g-i: 10 µm.

471

472

473

474

475

476

477

478

479

480

481

482

483
<figure><img src="image_13.png" /><figcaption>**Figure 4.** Persistent labeling of cells within developmental compartments during regeneration. (a) Time lapse ventral confocal stack projections of the regenerating tail tip of a worm displaying clonal transgene expression in the ectodermal lineage. (b-d) magnified confocal sections of the same individual. (e-f) interpretative schemes of (c-d). The time-lapsed views illustrate the continuity of clonal expression of the transgene in epidermal cells (a, stage 1), undifferentiated blastema cells (b), regenerated PSCs (c-d) and progenitor cells (c-d). (g-l) Regeneration experiments on animals bearing simple clones. Dorsal views of confocal stack projections, with pre-amputation views on top and the matching full regenerates (3 weeks post amputation) on the bottom. This series illustrates the strict compartment restriction in the regeneration of ectoderm-derived and mesoderm-derived PSCs, as well as gut endodermal lineage. Pygidial ectoderm, entirely removed upon amputation, is regenerated exclusively from trunk ectoderm precursors (g, j). For all panels, green labelings are cell membranes, magenta labelings are cell nuclei. White arrows: position of rings of PSCs in the respective focal plane. Scale bars: a, 100 µm; b-c: 10 µm; d: 20 µm.</figcaption></figure>

484
485
486
487
488
489
490
491
492
493
494
495
Overall, we found that most individuals showed complex patterns of fluorescent primary clones. Although we cannot exclude that some of the patterns observed may be due to enhancer trapping, we see no indication that this phenomenon occurs significantly in our complete set of 61 transgenic individuals, presumably due to the relative strength of the ubiquitous promoter we have used (rps9). All six individual primary clonal patterns we deduce from observations are obtained multiple times (from 4 to 53 times, in 61 individuals, Supplementary Data 7, part C), practically excluding that they may be due to neighboring endogenous enhancers. The complexity of patterns likely results from a combination of reasons: Firstly, multiple blastomeres were transformed (Supplementary Data 7, part B, N09 and N35 for examples) resulting in combinations of tissues labeled. Secondly, only a part of a germ layer-derived tissue may be labeled. This is most evident in cases where only a bilateral half of the tissues is fluorescent because transgenesis happened in only one of the bilateral descendants of the germ layer founding blastomere (e.g. 4d divides bilaterally to give the precursors of the right and left mesoderm, Supplementary Data 7 part B, M24 and N23). Thirdly, some tissues were labeled in a stochastic, salt-and-pepper manner. This phenomenon is known as variegation⁵⁵ and presumably happens when a transgene is inserted near or within a heterochromatic region that imposes unstable transcriptional repression on it. This was particularly recurrent at the level of ectodermal tissues (Supplementary Data 7, part B, N25 and N33 for examples).

Despite this complexity, simpler patterns were also recovered in several individuals corresponding to the labeling of the whole trunk ectodermal tissues (Fig. 3b), the whole trunk mesodermal tissues (Fig. 3c) and the entire gut endoderm (Fig. 3e). The clonal nature of the ectodermal patterns is indicated by the continuity of expression of the transgene in PSCs, segmental precursors and differentiated segmental cells (Fig. 3f-3i). Ectodermal PSCs, corresponding in location and cytological characteristics to the ring of cells identified by molecular signature before (Gazave et al, 2013), are easily identifiable (Fig. 3h). Potential mesodermal PSCs are also tentatively imaged in locations already identified molecularly (Supplementary data 7, part B, M03). These primary clones support the aforementioned concept that separate pools of precursor cells generate these sets of tissues during the life-long process of posterior addition of segments. As for the endoderm, so far, no endodermal PSCs have been identified by molecular signature, and it is possible that endodermal precursors or stem cells are spread in a diffuse way along the length of the trunk⁵⁶.

In addition to the trunk germ layer-derived tissues, several primary clonal patterns were obtained repeatedly either alone or in combination with others (Supplementary Data 7). The pygidial ectoderm was often labeled independently of the trunk ectoderm (Fig. 3d). This demonstrates that the pygidial ectoderm is derived from blastomeres different from the trunk ectoderm and that the anterior border of the pygidial ectoderm with the trunk ectoderm is a compartment border with no contribution of the pygidial cells to the growth of the trunk
ectoderm (Fig. 3b, d). The one exception to the pygidium/trunk compartmentalization is the presence of a median neural lineage (Fig. 3d), composed of two pairs of cells per new segment, that is also identified alone, sometimes unilaterally (Supplementary Data 7, part B, M09, M10, N04, N11, N14, N26, N40 and O15). These cells are probably produced by independent median specialized posterior stem cells that segregate from the 2d lineage in the early embryo. Lastly, a lineage of amoeboid, presumably phagocytic cells, possibly derived from anterior embryonic mesoderm, was observed several times (Supplementary Data 7, part B, M09, N03, N05, N22).

Most importantly, germ-layer compartmentalization is fully conserved during regenerative events (Fig. 4), with each germ layer of the regenerate originating exclusively from cells of its kind in the neighboring non-regenerated trunk. The clonal nature of the transgene expression is again illustrated by the continuous transgene expression in the differentiated epidermal cells, blastemal cells, and the regenerated PSCs (Fig. 4a-f). Ectodermal regenerated PSCs are clearly identifiable as soon as 4 days post amputation (Fig. 4c-d). Lineage restrictions in the regeneration blastema (Fig. 4g-l) are in agreement with the distinct source populations of stem cells suggested by our scRNAseq analyses. A diagram of the whole set of primary clones obtained fully supports this interpretation of compartmentalization (Supplementary Data 7, part C).

While these transgenic clones do not demonstrate the embryonic germ layer origins, they show that tissues remain strictly compartmentalized during posterior segment addition, similar to embryonic/larval development. Taken together, all these results are compatible with the presence of the two rings of ectodermal and mesodermal PSCs immediately anterior to the pygidium/trunk border, while the unsegmented endoderm may grow diffusely or through the activity of specific endodermal PSCs yet to be identified. After amputation (which removes all PSCs), ectodermal and mesodermal PSCs, as well as endoderm, are regenerated exclusively from precursors of their kind in the uncut segments, either from dedifferentiating cells, or from unknown resident lineage restricted precursor cells, in complete agreement with the single-cell transcriptomics clustering.

TOR signaling is required for successful activation of PSCs and regeneration

The protein kinase Target Of Rapamycin (TOR) has been implied in wound response and blastemal signaling in planarians, zebrafish and axolotl <sup>57-61</sup>, reviewed in <sup>62</sup>. Our *in silico* analysis revealed increased expression of TOR- related transcripts in cells as they acquire PSC identity in response to injury in *Platynereis* (Supplementary Data 4). These include the *Platynereis* orthologs of genes encoding TOR (Supplementary Data 6) as well as components of the regulator complex (lamtor 1, 2, 3, 4 and 5), which is involved in TOR
574 complex activation and localisation, and therefore might influence cell metabolism and
575 proliferation ⁶³. Additionally, many biological processes known to be controlled by TOR
576 activity were found enriched in our GO-term analysis of genes associated with high
577 CytoTRACE scores (e.g. translation, rRNA processing, ribosome biogenesis, see
578 Supplementary data 4).

579
580 Moreover, increased TOR signaling has also been observed in hypertranscriptomic cells ⁴⁵,
581 as we observe them in the *Platynereis* regeneration process, and TOR complex activity has
582 been shown to be a key requirement for maintaining a hypertranscriptomic state in embryonic
583 stem cells ⁶⁴. We therefore investigated whether posterior regeneration in *Platynereis*
584 *dumerilii* also required a functional TOR signaling system.

585
586 In our single-cell atlas, *Platynereis tor* was broadly expressed, including in the tentative PSC
587 subpopulations (Fig. 5a-c). To assess whether or not TOR signaling was required for
588 regenerating PSCs after amputation, we treated amputated animals with the ATP
589 competitive TOR inhibitor AZD8055 ⁶⁵ and compared their regenerative success to DMSO-
590 treated controls (Fig. 5d-l). Already at 24 hpa, so before the formation of a significant
591 blastema or a strong increase in cell proliferation ²¹, *in situ* HCR revealed that *myc* expression
592 was strongly reduced and *hox3* expression was completely undetectable in treated animals
593 (Fig. 5e,f), whereas control animals successfully established a zone of *myc*⁺ and *hox3*⁺ cells
594 (Fig. 5i,j). Additionally, treated animals did not reach a stage 3 regenerate at 72 hpa (Fig.
595 5g,h). DMSO-treated control animals progressed normally and regenerated a blastema and
596 early developing anal cirri within the same timespan (Fig. 5k,l). We therefore conclude that,
597 upon TOR inhibition, *Platynereis* fails to regenerate PSCs, and subsequently does not
598 develop a blastema or differentiated posterior tissues.
<figure><img src="image_14.png" /><figcaption>Figure 5. TOR signaling is necessary for re-establishing stem cell gene expression profiles and morphological regeneration upon injury.</figcaption></figure>

(a-c) UMAP visualization of *tor* expression; (a) comparison between 0 hpa and 12-72 hpa; (b,c) enlarged views of cluster 0 and cluster 1 in 12-72 hpa samples. (d) Scheme of posterior amputation, TOR inhibition and posterior regeneration after 24 and 72 hours, highlighting region used for assessing stem cell gene expression 24 hpa. (e-h) Analysis of amputated animals (n=6) treated with AZD8055 TOR inhibitor. (e,f) Confocal images of *in situ* HCR stainings detecting expression of *hox3* and *myc* at 24 hpa; (g,h) brightfield images at 72 hpa; (i-l). Equivalent analyses in DMSO-treated controls. (i,j) Confocal images of *in situ* HCR stainings for *hox3* and *myc* at 24 hpa; (k,l) brightfield images of posterior regenerates at 72 hpa. Scale bars: 25 µm (e,f,i,j); 250 µm (g,h,k,l).

599
600
601
602
603
604
605
606
607
608
609 Discussion

610 As outlined above, our work is consistent with the classical proposal that formation of the 611 regenerative blastema of *Platynereis dumerilii* involves a process of injury-induced “re- 612 embryonalisation” of wound-adjacent cells²³. We advance this model to cell-type resolution, 613 find molecular similarities to vertebrate blastema formation and present a clonal analysis 614 furthering our understanding of lineage restriction during this process. Our data are 615 consistent with both morphallactic repatterning processes and multiple parallel 616 dedifferentiation events, and provide the molecular fingerprint of distinct groups of stem cells 617 in posterior regeneration. These findings complement observations based on candidate 618 genes and transcriptomic analyses in *Platynereis* and other annelid systems²¹,⁶⁶, and offer a 619 fresh perspective on fundamental regenerative processes. 620

621 Both our transcriptomic and clonal analyses argue that, unlike planarians that exhibit 622 pluripotent stem cells capable of regenerating all cell types of the adult ⁶⁷, *Platynereis 623* regeneration relies on cells with limited potency that respect the distinction between cells 624 arising from different germ layers in development. In both of these spiralian species, 625 however, there appears to be a continuity of potency mechanisms between normal growth 626 and regeneration processes: In planarians, pluripotent neoblasts are not only relevant for 627 regeneration, but also homeostasis and growth ⁶⁸. Likewise, in *Platynereis*, lineage restriction 628 applies to transverse growth, posterior growth, and regeneration. The dissimilarity of stem 629 cell potencies within the clade of spiralians is reminiscent of the diversity of growth and 630 regeneration mechanisms also found in cnidarians, where pluripotent stem cells are found in 631 *Hydractinia* ⁶⁹, whereas *Hydra* employs lineage-restricted progenitors ⁷⁰. As single-cell 632 analyses in other annelid species are becoming available ⁶⁶,⁷¹, we expect that the availability 633 of time-resolved cellular and molecular data in the *Platynereis* model will help to more easily 634 delineate differences and commonalities for regeneration-relevant stem cell mechanisms 635 also in other spiralian species. 636

637 A recent single-cell study on the stem cell system in *Pristina leidyi* ⁷¹ found evidence for piwi- 638 positive stem cells spread throughout the adult body of this annelid. The analysis identified 639 a single, potentially pluripotent pool of stem cells at the root of all adult tissues. However, 640 transcriptional heterogeneity was detected in this *piwi* positive population, and lineage- 641 restriction could not be ruled out. Unlike *Platynereis*, *Pristina* reproduces by fission, and a 642 large population of *piwi* positive cells was detected in a developing fission zone. As the 643 experiments in *Pristina* were not conducted in a regeneration context, further experiments 644 will be needed to allow direct comparisons of stem cell systems between these two more 645 closely related species. Such comparisons could reveal important insights into the evolution 646 of asexual reproduction and how it affects stem cell potency and availability. 647
As the labeled clones we obtain by zygotic injections are primarily large, they are well suited to provide a clear view of germ-layer-restricted lineages, but cannot yield experimental access to smaller lineages in both posterior growth and regeneration. Our single-cell transcriptomic atlas corroborates multiple distinct clusters of progenitors that are confined to individual germ layers, but also exhibit further subdivisions. It is thus possible that there are even more restricted lineage compartments currently not accessible to experimental validation. In turn, not every transgenically labeled compartment contributes to its regenerated counterpart. One example is the bilateral neural lineage that we identify, which is continuous with the pygidium before amputation, but does not visibly contribute to the regenerate. The existence of such a developmental compartment is consistent with the idea that there might be distinct subsets of hox3-positive PSCs in the ring-like segment addition zone, possibly reflecting the existence of distinct neurogenic columns in posterior growth<sup>72</sup>. More refined mapping techniques will be required to assess if such subsets exist in regular development, and if they are reconstituted in the process of regenerative growth.

Our data not only provide insight into the likely source and restriction of PSCs in *Platynereis* regeneration, but also into molecular factors involved in the emergence of blastemal cells and their possible conservation. Based on our findings and existing literature, we propose a working model of regeneration in *Platynereis* consisting of the activation and dedifferentiation of wound-adjacent cells, their acquisition of distinct, lineage restricted stem cell properties and ultimately their proliferation and contribution to regenerating tissue. While dedifferentiation as a source of blastemal stem cells in annelids has previously been proposed<sup>8,10,20,21,23,25</sup>, we report cell-based molecular data consistent with this concept. We observed multiple distinct populations of cells responding in similar ways: they start expressing *myc* which, besides its general role in stem cell activity, has been shown to be involved in mammalian dedifferentiation and pluripotency<sup>73,74</sup>, as well as several genes of the germline multipotency programme (e.g. *piwi*, *vasa*, *nanos*), which are also expressed in *Platynereis* PSCs during regular growth. These cells show hypertranscription, a known feature of active adult stem cells<sup>44,45</sup>, strong expression of genes involved in epigenetic reprogramming (e.g. *chd3/4/5b*, *dnmt1*, *chd1*), and start to proliferate. Both *myc* and *chd1* have previously been shown to play a central role in stem cell activation and hypertranscription in many species, such as the endothelial to hematopoietic stem and progenitor transition in mouse development<sup>44,75</sup>.

Together, these findings strengthen the argument for multiple, parallel dedifferentiation events underlying regeneration in *Platynereis*. Our data do not exclude the possibility that resident stem cells or dedicated progenitors among heterogeneous pools of differentiated cells could also contribute to the regenerate, as has been proposed or observed in multiple regeneration models including annelids<sup>5,8,10</sup>. Our findings of *piwi* expression and high CytoTRACE value in a subset of smooth muscle cells before injury might indicate the
existence of a progenitor-like cell state in this particular tissue. However, the fast de novo establishment of the molecular stem cell signature within 12 to 24 hpa, before a detectable increase in proliferation commences, argues that such a contribution may only account for a limited set of blastemal cells, or specific tissues, as suggested for gut cells during regeneration in a recent publication<sup>76</sup>.

Apart from those more general processes involved in the regeneration programme, the notion that PSCs resulting from epidermal and coelomic mesodermal cells are molecularly distinct will also be helpful in more clearly delineating possible parallels to established, dedifferentiation-based regeneration mechanisms in other systems. Indeed, the expression of the *sp9* homologue *sp/btd* in epidermis-derived PSCs of *Platynereis* is reminiscent of the expression of *sp9* in the dedifferentiating epidermis of axolotl blastemas<sup>77</sup>. In turn, similar to the axolotl *msx-2* gene that becomes refined to the mesenchymal part of the blastema<sup>78</sup>, we identify its *Platynereis* ortholog *msx* to be present in the *bona fide* mesodermal PSC clusters. Likewise, our work revealed a previously uncharacterized *Platynereis prrx1* orthologue that is expressed in the mesodermal PSCs. Vertebrate *prrx1* genes are prominently expressed in mesenchymal cells during limb development of chicken<sup>79</sup>, and mouse<sup>80</sup>, and have also been characterized as part of the connective tissue progenitor cells in axolotl and frog blastemas<sup>22,78,81</sup>. It has previously been argued that evolutionary understanding of blastema-based regeneration will require a more detailed understanding of the underlying genetic circuitry<sup>3</sup>. Our work establishes *Platynereis* as a promising candidate for such analyses and provides a first comprehensive set of data towards this end.

The prevalent expression of ribosome- and cellular growth related genes in PSC-like cells during regeneration warranted an investigation of the role of TOR signaling in the activation or dedifferentiation or activity of stem cells in our model. As discussed above, TOR signaling has previously been implied in regeneration in many species, with a recent article demonstrating its crucial, regulatory role upstream of axolotl limb regeneration<sup>57</sup>. While the exact role this pathway plays in this process is not well understood, its activity seems to be generally required for regenerative stem cell proliferation. Interestingly, the formation of stem cells through dedifferentiation occurs during a period of lower TOR activity and high autophagy (which TOR usually inhibits)<sup>62</sup>. We found that impaired TOR signaling in *Platynereis* not only affects proliferation and the morphological formation of a blastema, but directly blocks the otherwise reliable establishment of PSCs as early as 24 hpa, suggesting an early, central role of TOR kinase activity in regulating the dedifferentiation of cells in response to injury.

Lastly, we expect our methodological advances presented in this manuscript to be of broader use in the establishment of additional resources for comparative regeneration biology. Using a widely applicable cell fixation method and parallel processing of all samples allowed us to
generate a merged, temporally resolved dataset without having to rely on computational batch effect removal strategies. Similarly, whereas regular pre-processing would normalize cellular transcriptomes to comparable levels, we suggest that the hypertranscriptomic state of cells at later regenerative timepoints reflects a biological feature of PSCs. Finally, our clonal analysis approach offers a direct way to observe clonogenic lineages in development and regeneration as well as new insights into *Platynereis* lineage restriction, without requiring stable expression of transgenic constructs beyond G0. Taken together, our manuscript therefore provides a framework and methodological toolkit for future projects aimed at acquiring and analyzing the data required to compare regeneration across species and ultimately advance our understanding of blastema-based regeneration.

738
739 **Methods**

740 **Animal culture**

741 *Platynereis dumerilii* were kept in laboratory culture at temperatures between 18° and 742 20°C in a 16:8-hour light-5 dark (LD) cycle, and maintained under previously published 743 conditions ¹⁷,⁸², adhering to the applicable national legislation.

744

745 **Posterior amputation surgery**

746 To perform posterior trunk amputation surgery, animals were anesthetized in 7.5% MgCl₂ 747 diluted 1:1 with sea water. For bulk- and single cell transcriptomics and for all *in situ* HCR 748 labelings shown, animals of 40-60 segments size and 3-6 months age showing no signs of 749 sexual maturation and no prior injuries were sampled. Amputations were done by 750 performing a transverse section posterior of segment 30, using surgical scalpels (Swann- 751 Morton, Type 11). For regeneration time courses, animals were then rinsed in sea water and 752 transferred to fresh culture boxes for recovery.

753

754 **Bulk RNA sequencing of regenerating tissue**

755 Posterior surgeries were performed as described above. Tissue was then harvested at each 756 sampling time point by anesthetizing animals again as described above, followed by a 757 transverse cut anterior of the wound-adjacent segment, right at the segment boundary. 758 Tissue pieces were transferred to sea water, pooling 8 pieces per replicate, on ice. After 759 tissue pieces sank to the bottom of the reaction tube, the supernatant was removed and the 760 samples were frozen in liquid nitrogen and stored at -80° C.

761 RNA extractions were performed using a commercial kit (Direct-zol RNA MiniPrep, Zymo 762 Research, USA), following the manufacturer's guidelines. RNA was eluted in 30 µl RNAse- 763 free H2O. Illumina sequencing libraries were prepared at the Vienna Biocenter Next 764 Generation Sequencing Facility, using NebNext Dual adaptors with dual indexing. Libraries 765 were then sequenced using the Illumina NovaSeq platform with S1 PE100 flowcells.

766

767 **Bulk RNA sequencing analysis**

768 Sequences were trimmed using cutadapt (v. 1.12) ⁸³ and analyzed for sequence quality 769 using fastQC (v. 0.11.9) ⁸⁴ and multiQC (v. 1.14) ⁸⁵. We used STAR aligner (v. 2.7.10b) ⁸⁶ to 770 generate a reference file from the *Platynereis* genome assembly draft (*genomeGenerate*) 771 and align sequencing reads (*alignReads*), then extracted a counts matrix using 772 featurecounts (v. 2.0.1) ⁸⁷. Data were then processed using DESeq2 (v. 1.36.0) ⁸⁸ and mfuzz 773 (v. 2.56.0) ⁸⁹, estimating ideal clustering variable and cluster number following the software 774 package guidelines. Cluster members (membership cutoff = 0.5) were then plotted using 775 ggplot2 (v. 3.4.2) ⁹⁰, with select genes of interest plotted in color (supplementary Fig. 1).

776
777 **Single cell transcriptome sequencing**

778 For single-cell RNA sequencing, we performed posterior amputations and regeneration
779 time courses similar to those described above. However, after sampling the wound-
780 adjacent segments, we transferred those to an acetic acid/ methanol (ACME) solution with
781 1% NAC for dissociation ²⁷. Cells were then dissociated over the course of 45 minutes,
782 interspersed with rigorous pipetting every 15 minutes using a P1000 pipette pre-coated in
783 1% BSA in PBS to reduce cell loss due to stickiness. Dissociated cells were centrifuged
784 (1000 g for 5 min at 4°C), resuspended in storage buffer (1% BSA in PBS, with 10% DMSO
785 and 1U/µl recombinant RNAse inhibitor, Takara Bio) and stored at -20° C for further
786 processing.

787 To remove debris and concentrate cells, we performed FACS on freshly thawed samples.

788 We first labeled nuclei (Hoechst 33342 at 5 µg/ml, for 15 minutes at room temperature),

789 then sorted 15,000 cells directly into 10X genomics chromium buffer, using FACS gates

790 (FSC-A vs FSC-H; DAPI-A) to exclude debris and clumped cells (BD FACS Aria IIIu).

791 Single cell barcoding droplet (GEM) production and library preparation was performed at

792 the Vienna BioCenter Next Generation Sequencing facility using the 10X genomics

793 Chromium platform according to manufacturer's instructions (10X 3' v3 chemistry, 10X

794 Dual Index Kit). Two independent experiments were performed (replicates a and b),

795 following the same strategy: all animals for one experiment were sampled from sibling- or

796 closely related batches of animals. Amputations were performed in parallel, and by

797 freezing ACME-dissociated cells, we were able to store sampled cells throughout the

798 regeneration time course. All samples were then sorted, and barcoded in parallel. Libraries

799 were sequenced on the Illumina NovaSeq platform (S4 lanes, PE150).

800

801 **Single cell data processing**

802 We used Cellranger software by 10X genomics (v. 7.0.1) to generate a custom genome
803 reference (*mkref* function) from the *Platynereis* genome (Genbank ID: GCA_026936325.1),
804 using gene annotations provided in ref. 91. We then assigned reads to cellular barcodes,
805 aligned them to the custom reference and generated a read barcode matrix for each sample
806 individually using the *cellranger count* function with *expect-cells* set to 10000.

807 Our main processing pipeline was based on the "Seurat" package for R 92 , with specific

808 modifications for merging multiple datasets. In brief, we imported the barcode matrices

809 (*Read10X* with min cells = 3 and min. features = 200) and followed standard pre-

810 processing steps. Outlier cells were removed based on manual inspection of scatterplots

811 (counts vs features), removing between 30 and 108 cells per dataset. Quality metrics and

812 cutoff values for all samples are available in (Supplementary Data 1).

813 We merged all datasets following an approach employed elsewhere 93 . We normalized the

814 data (LogNormalize with scale.factor = 10000) and identified the variable features for each

815 dataset individually (using FindVariableFeatures). We then used the union of all variable

816 features from all different timepoints to conserve features which might be variable only at a
certain timepoint, and used this set of features for the merged dataset. Next we scaled the
merged dataset and performed dimensionality reduction (first 50 dimensions in PCA
space). We then calculated the UMAP embedding and performed cell-type clustering. After
trying multiple clustering resolutions we settled on a resolution of 0.5 as it best reflected
known biological cell types and subpopulations.

822

823 **Single cell cluster annotation**

Marker genes were identified for each cluster using the Seurat FindAllMarkers function (only returning positive markers at a min.pct of 0.25 and a log-fold change threshold of 1). As the reference genome used in this manuscript lacks a gene name annotation, we annotated marker genes here and below using a table of best BLAST hits for each coding sequence identified on the genome (see "transcriptome annotation" below). The annotated table of markers for each cluster (Supplementary Data 3), combined with screening expression of an array of genes with known expression patterns in *Platynereis* (Supplementary Data 2) were then used to annotate the clusters.

832

833 **Bulk- and single cell sequencing data comparison**

For quality control, we correlated single cell and bulk RNA sequencing data. Due to the
differences in sequencing technologies, strong correlation is not necessarily expected.
However, mismatched correlation between bulk- and single cell timepoints might indicate
biological differences or technical issues. To this end, we extracted aggregate
("pseudobulk") counts from the single cell dataset (grouped by timepoint) using the Seurat
AggregateExpression function. Bulk sequencing counts were extracted using the DESeq2
counts function. All counts were then subset to only contain features identified as variable
in the single cell object, expressed in at least one replicate in both bulk and single cell data.
We then scaled all remaining features by division by the sum of each feature's expression.
Pearson correlation was calculated using the cor function (stats package v4.3.3) with
default parameters and visualized using the p heatmap package (v1.0.12) function
p heatmap, also at default parameters.

846

847 **Single cell doublet prediction**

Potential cell doublets (2 or more cells assigned the same cellular barcode) were estimated using the R package DoubletFinder (v2.0.3 - note that the latest version, 2.0.4., introduces a code-breaking change)²⁹. In brief, optimal parameters were determined and doublet scores were calculated for each dataset independently. Expected number doublets based on fluid dynamics in 10X Chromium devices was determined based on manufacturer instructions (https://kb.10xgenomics.com/hc/en-us/articles/360059124751-Why-is-the-multiplet-rate-different-for-the-Next-GEM-Single-Cell-3-LT-v3-1-assay-compared-to-other-single-cell-applications), rounding to the closest available number. For doublet prediction, 30 principal components and a pN value of 0.25 were used.
857

858 **Analysis of UMIs per cell**

859 UMI values of cells were compared between timepoints post amputation using the
860 Wilcoxon rank sum test with continuity correction (Supplementary. Fig. 3). To ensure these
861 results were not affected by outlier removal (see above), we performed the same test on
862 cells without removing outliers, yielding comparable results (0 hpa vs 24 hpa: p < 2.2e-16;
863 24 hpa vs 72 hpa: p <1.227e-11).

864

865 **CytoTRACE analysis**

866 To rank cells by their developmental potential, we used CytoTRACE (v.0.0.3). CytoTRACE
867 is a statistical method, which uses transcriptional diversity as a proxy for developmental
868 potential and assigns a CytoTRACE-score to each cell ⁴³. CytoTRACE scores were
869 calculated for each cluster independently, using default parameters, then transferred to a
870 metadata slot of the Seurat object. Several biologically similar clusters were merged for
871 this analysis (3, 6 and 12; 4 and 16; 8 and 14). While CytoTRACE has been shown to work
872 on a broad range of datasets and organisms, we focussed our analysis on clusters in which
873 known biological information (e.g. expression of established stem cell marker genes) could
874 be used to assess its results. Data for all clusters is available (Supplementary data 4), and
875 validations (i.e. CytoTRACE score matching expression of stemness-related genes) were
876 performed for clusters 0 and 1.

877

878 **Gene annotation**

879 Top genes of every cluster were annotated using an automated pipeline. For this, all
880 transcript sequences predicted from a given gene locus (XLOC ID) were used for sequence
881 searches using BLASTX ⁹⁴ against two protein databases: a version of the NCBI
882 Uniprot/Swissprot repository (accessed on June 16, 2021) and a database combining
883 entries of the more inclusive NCBI RefSeq repository (accessed on November 25, 2021).
884 For the latter one, all protein sequences available for a set of representative landmark
885 species and taxa were used: Annelida, the mollusks *Mytilus galloprovincialis*, *Crassostrea*
886 *gigas*, *Mizuhopecten yessoensis*, *Octopus bimaculoides*, *Pomacea canaliculata*, *Lymnaea*
887 *stagnalis*, *Biomphalaria glabrata*, *Aplysia californica*; the insects *Drosophila melanogaster*,
888 *Apis mellifera*, *Clunio marinus*, *Nasonia vitripennis*; and the chordates *Branchiostoma*, *Mus*
889 *musculus*, *Oryzias latipes*, *Danio rerio* and *Gallus gallus*. Best hits for each of these
890 searches were tabulated. For gene loci with multiple transcripts, the results for the
891 transcript that retrieved the highest score in the analyses was retained as reference, so that
892 each gene locus retrieved one annotation.

893

894 For investigation of specific genes, we assembled bona fide full length sequences
895 independently of the genome annotation, using available RNAseq data generated for the
896 laboratory strains (PIN, VIO) maintained in the laboratory ⁹. Sequences from individual
897 libraries were assembled using the CLC Main Workbench Software package (version
898 23.0.2), and predicted protein sequences subjected to domain analysis using SMART⁹⁵.

899 Assembled gene sequences for *Platynereis prrx*, *flrtl*, *p2x*, *epig1*, *ccdc134*, *tor*, *lamtor1* to 5,
900 and *smg1* were submitted to the NCBI Genbank repository.

901

902 Gene Ontology Analysis

903 To assess the CytoTRACE-scores further and look for potentially informative associated
gene expression patterns, we calculated Pearson-correlation values for each gene with the
904 CytoTRACE score of each cluster, using the CytoTRACE software with default parameters
905 ⁴³. We then ordered genes by this correlation and performed GO term enrichment analysis
906 for each cluster using CERNO ⁹⁶ as implemented in the tmod R-package (version 0.50.13)
907 ⁹⁷.

909

910 Pearson correlation scores with CytoTRACE scores were calculated for the full gene-set.

911 Because GO terms are not annotated for *Platynereis*, we identified the closest matching
912 human gene symbol (see "gene annotation" above, limited to human gene hits) and
913 translated these to entrez-ids for GO term analysis. Therefore, this analysis exclusively
914 focuses on genes with a close human orthologue. We then used the three human GO term
915 annotation sets as accessible through the org.Hs.egGO R-package (version 3.17.0) and
916 performed the CERNO enrichment test.

917

918 Phylogenetic analyses

919 For phylogenetic analyses of selected *Platynereis* proteins whose phylogeny was not yet
920 previously reported, we used the following strategy: We identified the top hits in selected
921 reference species representing key vertebrate phyla (mammals, birds, amphibians) as well
922 as invertebrate phyla (mollusks, insects) by performing BLASTP searches against the NCBI
923 clustered nr database. For identifying / completing matching sequences in the axolotl
924 (*Ambystoma mexicanum*), we made use of the Axolotl-omics web resource
925 (https://www.axolotl-omics.org/) that allowed access to the latest axolotl transcriptome
926 assembly (AmexT_v47). Proteins were aligned using the CLC Main Workbench Software
927 package (version 23.0.2) and cleaned of short sequences. Subsequently, alignments were
928 exported and used for phylogenetic analyses using IQ-Tree 1.6.12 ⁹⁸,⁹⁹, allowing for the
929 choice of the most suitable substitution model. Ultrafast bootstrap analysis ¹⁰⁰ with 1000
930 repetitions was used to assess confidence for individual branches. The most likely tree
931 topology was then visualized using the iTOL suite ¹⁰¹, available at https://itol.embl.de.

932

933

934 Sub-clustering populations with stem cell like properties

935 To identify markers specific to sub-populations of clusters with stem cell like properties, we
936 subset clusters 0 and 1 (epidermis and coelomic mesoderm) and re-processed these
937 transcriptomes as described above, but without identifying variable features for each
938 sample individually. Newly calculated clusters were then analyzed for their expression of
939 GMP and SAZ related transcripts as well as their UMIs per cell. Strongly positive
940 subpopulations were identified for both clusters. Marker genes for those subpopulations
941 were then calculated against the entire dataset (suppl. Fig. 4, 5; full marker gene table in
942 Supplementary Data 3).

943

## Plotting and visualization

944

All plots displaying single cell data were generated using the R package SCpubr (v. 1.1.2)
$^{102}$. The displayed values on gene expression UMAPs are log-transformed transcript counts
normalized by UMI.

945

946

947

948

## in situ Hybridization Chain Reaction (HCR)

949

For *in situ* visualization of gene expression, we sampled tissues of either growing or
regenerating animals as described above. Labeling was done following our previously
published protocol for *Platynereis* $^{16}$, with probes designed using the publicly available
algorithm HCR3.0 Probe Maker (v. 2021_0.3.2, described in ref. 103). All HCR probe
sequences are available (Supplementary Data 5).

950

951

952

953

954

955

## Whole Mount In Situ Hybridization (WMISH)

956

The gene sequences for *Platynereis prrx* and *flrtl* were amplified by PCR on cDNA of stage
7 regenerates (7 days post amputation) and cloned into pJet2.1. Primers introducing an Sp6
promotor sequence were used to generate the transcription templates. Digoxigenin-labeled
probes were synthesized by Sp6 *in vitro* transcription, cleaned using the RNeasy Kit
(Quiagen) and stored in hybridisation mix at -20°C. Nitro blue tetrazolium chloride/5-
bromo-4-chloro-3'-indolyphosphate (NBT/BCIP) WMISH was performed as previously
described $^{104}$. Samples were permeabilized with proteinase K for 45 seconds. Bright field
pictures for NBT/BCIP WMISH were taken on a Zeiss Z2 Imager, 20x objective.

957

958

959

960

961

962

963

964

965

## Primers to amplify gene sequences

966

prrx_for: CGGAATTGCCTCAGCTTACTACTCTC

967

prrx_rev: CTGAGCCATCTGGTGGTGGTGG

968

flrtl_for: GTTCCCTTGCAGTCACTTT

969

flrtl_rev: CACTGTTCCTCTTGCCTTTT

970

971

## Primers to generate antisense probe template

972

prrx_for: CGGAATTGCCTCAGCTTACTACTCTC

973

pJet2.1_sp6_rev: GGATTTAGGTGACACTATAGAACGACTCACTATAGGGAGAGCGGC

974

flrtl_for: GTTCCCTTGCAGTCACTTT

975

pJet2.1_sp6_rev: GGATTTAGGTGACACTATAGAACGACTCACTATAGGGAGAGCGGC

976
977

978 Microscopy and image analysis

979 Confocal images of *in situ* HCR labelings were taken using a Zeiss LSM700 confocal microscope with a Plan-Apochromat 40x/1.3 Oil DIC, WD 0.21 mm lens, using Zeiss Zen software. Images were then processed using FIJI software <sup>105</sup> for adjustment of contrast, LUT selection and creation of overlay images.

983

984 Quantification of nuclear and nucleolar size in regenerating tissue

985 To quantify the change in nuclear and nucleolar size of cells responding to posterior injury over time, animals at 0, 12 and 48 hpa were processed and imaged as described above.
986
987 Nuclei and nucleoli were manually selected as regions of interest (ROIs) in FIJI software by drawing an outline around the areas positive for the nuclear stain (nucleus) and the roughly circular areas within negative for the stain (nucleolus). 50 nuclei and corresponding nucleoli closest to the amputation site were counted per biological replicate (n = 3 for each timepoint); nuclei that did not fully span the focal plane were excluded from the analysis.
988
989
990
991 The data were plotted in GraphPad Prism v10.2.2, and the statistical significance of the differences in means between the timepoints was calculated with a one-way ANOVA test with multiple comparisons.
992
993
994

995

996 Molecular Cloning

997 The transgene rps9::H2A::mCherry::F2A::GFP::CAAX (simplified as pHCX) was engineered using the Gibson assembly protocol <sup>106</sup>. The donor plasmids for this construction were pEXPTol2-EGFP-CAAX, pEXPTol2-H2A-mCherry <sup>52</sup> and pTol2{rp-s9::egfp} <sup>15</sup>. The ribosome skip site coding sequence F2A was inserted between the two recombinant fluorescent protein coding sequences by adding it to the cloning primer. For the Gibson reaction, Gibson assembly master mix (NEB, France, E2611S) and NEB 5-alpha Competent E.coli (NEB C2987H) were used, following the manufacturer's protocol.

1004

1005 Generation and analysis of transgenic animals

1006 Tol2 transposase mRNA was synthetized using the SP6 mMessage kit from Ambion (AM1340). The manufacturer's protocol was followed until the end of DNase step (1ml DNase 15 mins at 37°C). For purification of mRNA, MEGAclear kit from Ambion (AM1908) was used, following RNA elution option two with the following modifications: elution buffer was heated to 72°C, this warmed elution buffer was applied to filter cartridge containing mRNA, the tubes were kept at 72°C heated plate for 5 min before centrifuging for elution.

1013

1014 For micro-injections, previous protocols were used <sup>52,107</sup>. Briefly, fertilized eggs were dejellified at 45 mins post fertilization, using a 80 mm nylon mesh. The egg cuticle was softened with a flash treatment with proteinase K diluted in seawater (100 mg/ml). After

1016
1017 abundant rinsing with sea water, the eggs were micro-injected with a mix of Tol2
1018 transposase mRNA (300 ng/ml) and plasmid pHCX (100 ng/ml). Injected eggs were
1019 incubated overnight at 28°C. Injected batches of larvae and juveniles were raised in a
1020 common polypropylene container with 800 ml of sea water until they reached 6 weeks.
1021 Worms were then relaxed and amputated as described before. Amputated posterior parts
1022 were kept in 7.5% MgCl₂ diluted 1:1 with sea water and mounted on slides using three
1023 layers of tapes as spacer. Confocal images were acquired on a Zeiss LSM 780 confocal
1024 scanning microscope. Amputated animals were dispatched in individual boxes and fed
1025 carefully to avoid fouling of the small amount of sea water. The operation was repeated
1026 twice after three weeks of regeneration. Some individuals however were not documented
1027 for two rounds of regeneration because they underwent sexual maturation, that stops
1028 regeneration.

1029

1030 AZD8055 treatment

1031 Animals were surgically amputated as described above. Regenerating animals were then
1032 kept in glass beakers in artificial sea water, either treated with 10µM AZD8055
1033 (MedChemExpress, USA) or with an equal amount of carrier control (DMSO).

1034
1035 **Data Availability**

1036 All primary data generated for this manuscript are available online. The bulk RNA sequencing
1037 data can be found under NCBI SRA BioProject PRJNA1060927 (SAMN39250368 to
1038 SAMN39250382), the single cell RNA sequencing data under NCBI SRA BioProject
1039 PRJNA1060254 (SAMN39223008 to SAMN39223016). The processed Seurat single cell
1040 dataset will be made available. The newly described *Platynereis* genes from this
1041 transcriptome are listed with their GenBank identifiers in Supplementary Data 2.

1042 **Code Availability**

1043 The code used for processing and visualizing the bulk- and single cell data presented in this
1044 manuscript will be made available on GitHub.

1045 **Acknowledgements**

1046 The authors are grateful to members of their respective research groups for continuous input
1047 into this project; Alison Cole (University of Vienna) and Simon Haendeler (CIBIV, University
1048 of Vienna) for advice on single-cell data processing; Kevin Nzumbi Mutemi and Detlev Arendt
1049 (EMBL, Heidelberg) for access to the *Platynereis dumerilii* genome sequence and primary
1050 annotations; Margaryta Borisova, Andrij Belokurov and Netsanet Getachew (University of
1051 Vienna) for animal supply; the Max Perutz Labs BioOptics Facility for access to advanced
1052 light microscopy and FACS; the ImagoSeine core facility of Institut Jacques Monod, a member
1053 of France Biolmaging (ANR-10-INBS-04) and certified IBiSA platform and the Next
1054 Generation Sequencing services at the Vienna BioCenter Core Facilities for service and
1055 advice.

1056 **Funding**

1057 This research has been supported by a joint grant from the Agence Nationale de Recherche
1058 (ANR) ANR-16-CE91-0007 (G.B.) and the Austrian Science Funds (FWF) I2972 (F.R.; doi:
1059 10.55776/I2972), the FWF Special Research Project F78 (F.R.; doi:10.55776/F78), the
1060 Fondation ARC pour la recherche sur le cancer (grant LSP 190375) (G.B.), the FWF doc.Funds
1061 PhD programme DOC 72 "Stem Cells, Tissues, Organoids – Dissecting Regulators of Potency
1062 and Pattern Formation (SCORPION)" (F.R.; doi:10.55776/DOC72), a post-doctoral fellowship
1063 of the Laboratory of Excellence (LABEX) "Who am I?" ANR-11-LABX-0071 (B.D.O.), the
1064 Austrian Academy of Sciences (ÖAW) DOC fellowship programme (A.W.S.), the German
1065 Academic Scholarship Foundation (L.A.), and the University of Vienna Research Platform
1066 "Single Cell Regulation of Stem Cells (SinCeReSt)" (F.R.). For open access purposes, F.R. has
1067 applied a CC BY public copyright license to any author accepted manuscript version arising

1068 from this submission.

1069

Competing interests

1070 The authors declare no competing interests.

1071
1072 References

1073 1. Bely, A. E. & Nyberg, K. G. Evolution of animal regeneration: re-emergence of a field.

1074 *Trends Ecol. Evol.* **25**, 161–170 (2010).

1075 2. Lai, A. G. & Aboobaker, A. A. EvoRegen in animals: Time to uncover deep conservation or convergence of adult stem cell evolution and regenerative processes. *Dev. Biol.* **433**, 118–131 (2018).

1078 3. Srivastava, M. Beyond Casual Resemblances: Rigorous Frameworks for Comparing Regeneration Across Species. *Annu. Rev. Cell Dev. Biol.* **37**, 1–26 (2021).

1080 4. Reddien, P. W. & Alvarado, A. S. Fundamentals of planarian regeneration. *Annu. Rev. Cell Dev. Biol.* 20, 725–757 (2004).

1082 5. Tanaka, E. M. & Reddien, P. W. The Cellular Basis for Animal Regeneration. *Dev. Cell* **21**, 172–185 (2011).

1084 6. Tanaka, E. M. The Molecular and Cellular Choreography of Appendage Regeneration. *Cell* **165**, 1598–1608 (2016).

1086 7. Tajer, B., Savage, A. M. & Whited, J. L. The salamander blastema within the broader context of metazoan regeneration. *Front. Cell Dev. Biol.* **11**, 1206157 (2023).

1088 8. Özpolat, B. D. & Bely, A. E. *Developmental and molecular biology of annelid regeneration: a comparative review of recent studies*. *Curr. Opin. Genet. Dev.* **40**, 144–153 (2016).

1091 9. Özpolat, B. D. et al. The Nereid on the rise: *Platynereis* as a model system. *EvoDevo* **12**, 10 (2021).

1093 10. Kostyuchenko, R. P. & Kozin, V. V. Comparative Aspects of Annelid Regeneration: Towards Understanding the Mechanisms of Regeneration. *Genes* **12**, 1148 (2021).

1095 11. Nikanorova, D. D., Kupriashova, E. E. & Kostyuchenko, R. P. Regeneration in Annelids: *Cell Sources, Tissue Remodeling, and Differential Gene Expression*. *Russ. J. Dev. Biol.* **51**, 148–161 (2020).

1098 12. Bely, A. E., Zattara, E. E. & Sikes, J. M. Regeneration in spiralians: evolutionary patterns and developmental processes. *Int. J. Dev. Biol.* **58**, 623–634 (2015).

1100 13. Zantke, J., Bannister, S., Rajan, V. B. V., Raible, F. & Tessmar-Raible, K. Genetic and Genomic Tools for the Marine Annelid *Platynereis dumerilii*. *Genetics* **197**, 19–31 (2014).

1102 14. Bannister, S. et al. TALENs Mediate Efficient and Heritable Mutation of Endogenous Genes in the Marine Annelid *Platynereis dumerilii*. *Genetics* 197, 77–89 (2014).

1104 15. Backfisch, B., Kozin, V. V., Kirchmaier, S., Tessmar-Raible, K. & Raible, F. Tools for Gene-Regulatory Analyses in the Marine Annelid *Platynereis dumerilii*. *PLoS ONE* **9**, e93076 (2014).

1107 16. Ćorić, A. et al. A Fast And Versatile Method for Simultaneous HCR, Immunohistochemistry And Edu Labeling (SHInE). *Integr. Comp. Biol.* **63**, 372–381 (2023).

1109 17. Hauenschild, C. & Fischer, A. *Platynereis dumerilii*. *Mikroskopische Anatomie, Fortpflanzung, Entwicklung*. *Großes Zoologisches Praktikum* **10b**, (1969).
1111 18. Gazave, E. et al. Posterior elongation in the annelid *Platynereis dumerilii* involves stem cells molecularly related to primordial germ cells. Dev. Biol. **382**, 246–267 (2013).

1113 19. Juliano, C. E., Swartz, S. Z. & Wessel, G. M. A conserved germline multipotency program. *Development* **137**, 4113–4126 (2010).

1115 20. Bely, A. E. Early Events in Annelid Regeneration: A Cellular Perspective. Am. Zoöl. **54**, 688–699 (2014).

1117 21. Planques, A., Malem, J., Parapar, J., Vervoort, M. & Gazave, E. Morphological, cellular and molecular characterization of posterior regeneration in the marine annelid *Platynereis dumerilii*. Dev. Biol. **445**, 189–210 (2019).

1120 22. Lin, T.-Y. et al. Fibroblast dedifferentiation as a determinant of successful regeneration. *Dev. Cell* **5**, 1541–1551.e6 (2021).

1122 23. Hofmann, D. K. Untersuchungen zur Regeneration des Hinterendes bei *Platynereis dumerilii*. Zool Jb Abt Allg Zool Physiol 374–430 (1966).

1124 24. Planques, A. et al. DNA methylation atlas and machinery in the developing and regenerating annelid *Platynereis dumerilii*. BMC Biol. **19**, 148 (2021).

1126 25. Paré, L. et al. Transcriptomic landscape of posterior regeneration in the annelid *Platynereis dumerilii*. BMC Genom. **24**, 583 (2023).

1128 26. Hicks, S. C., Townes, F. W., Teng, M. & Irizarry, R. A. Missing data and technical variability in single-cell RNA-sequencing experiments. *Biostatistics* **19**, 562–578 (2018).

1130 27. García-Castro, H. et al. ACME dissociation: a versatile cell fixation-dissociation method for single-cell transcriptomics. *Genome Biol.* **22**, 89 (2021).

1132 28. McInnes, L., Healy, J. & Melville, J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. *arXiv* (2018) doi:10.48550/arxiv.1802.03426.

1134 29. McGinnis, C. S., Murrow, L. M. & Gartner, Z. J. DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors. Cell Syst. **8**, 329–337.e4 (2019).

1137 30. Brunet, T. et al. The evolutionary origin of bilaterian smooth and striated myocytes. *eLife* **5**, e19607 (2016).

1139 31. Zakrzewski, A.-C. et al. Early Divergence, Broad Distribution, and High Diversity of Animal Chitin Synthases. *Genome Biol. Evol.* **6**, 316–325 (2014).

1141 32. Zakrzewski, A. Molecular characterization of chaetae formation in annelida and other Lophotrochozoa. (Freie Universität Berlin, Germany, 2011).

1143 33. Song, S. et al. Globins in the marine annelid *Platynereis dumerilii* shed new light on hemoglobin evolution in bilaterians. *BMC Evol. Biol.* **20**, 165 (2020).

1145 34. Kostyuchenko, R. P. & Kozin, V. V. Morphallaxis versus Epimorphosis? Cellular and Molecular Aspects of Regeneration and Asexual Reproduction in Annelids. *Biol. Bull.* **47**, 237–246 (2020).

1148 35. Kostyuchenko, R. P., Kozin, V. V., Filippova, N. A. & Sorokina, E. V. FoxA expression pattern in two polychaete species, *Alitta virens* and *Platynereis dumerilii*: Examination of the conserved key regulator of the gut development from cleavage through larval life,
1151 postlarval growth, and regeneration. *Dev. Dyn.* **248**, 728–743 (2019).

1152 36. Demilly, A., Steinmetz, P., Gazave, E., Marchand, L. & Vervoort, M. Involvement of the

1153 Wnt/β-catenin pathway in neurectoderm architecture in Platynereis dumerilii. *Nat.*

1154 *Commun.* **4**, 1915 (2013).

1155 37. Vanhoutte, D. et al. Thrombospondin expression in myofibers stabilizes muscle

1156 membranes. *eLife* 5, e17589 (2016).

1157 38. Orr, A. W., Pallero, M. A., Xiong, W.-C. & Murphy-Ullrich, J. E. Thrombospondin Induces

1158 RhoA Inactivation through FAK-dependent Signaling to Stimulate Focal Adhesion

1159 Disassembly*. *J. Biol. Chem.* **279**, 48983–48992 (2004).

1160 39. El-Kholy, S. E., Afifi, B., El-Husseiny, I. & Seif, A. Octopamine signaling via OctαR is

1161 essential for a well-orchestrated climbing performance of adult *Drosophila melanogaster*.

1162 *Sci. Rep.* **12**, 14024 (2022).

1163 40. Vega-Macaya, F., Manieu, C., Valdivia, M., Mlodzik, M. & Olguín, P. Establishment of the

1164 Muscle–Tendon Junction During Thorax Morphogenesis in *Drosophila* Requires the Rho-

1165 Kinase. *Genetics* **204**, 1139–1149 (2016).

1166 41. Pfeifer, K., Dorresteijn, A. W. C. & Fröbius, A. C. Activation of Hox genes during caudal

1167 regeneration of the polychaete annelid *Platynereis dumerilii*. *Dev. Genes Evol.* **222**, 165–

1168 179 (2012).

1169 42. Balavoine, G. Segment formation in Annelids: patterns, processes and evolution. *Int. J.*

1170 Dev. Biol. 58, 469–483 (2015).

1171 43. Gulati, G. S. et al. Single-cell transcriptional diversity is a hallmark of developmental

1172 potential. *Science* **367**, 405–411 (2020).

1173 44. Percharde, M., Bulut-Karslioglu, A. & Ramalho-Santos, M. Hypertranscription in

1174 Development, Stem Cells, and Regeneration. *Dev. Cell* **40**, 9–21 (2017).

1175 45. Kim, Y.-K. et al. Absolute scaling of single-cell transcriptomes identifies pervasive

1176 hypertranscription in adult stem and progenitor cells. *Cell Rep.* **42**, 111978 (2023).

1177 46. Choi, H. M. T. et al. Third-generation in situ hybridization chain reaction: multiplexed,

1178 quantitative, sensitive, versatile, robust. *Development* **145**, dev165753 (2018).

1179 47. Grimmel, J., Dorresteijn, A. W. C. & Fröbius, A. C. Formation of body appendages during

1180 caudal regeneration in *Platynereis dumerilii*: adaptation of conserved molecular toolsets.

1181 *EvoDevo* 7, 10 (2016).

1182 48. Raible, F. et al. Vertebrate-Type Intron-Rich Genes in the Marine Annelid *Platynereis*

1183 *dumerilii*. *Science* **310**, 1325–1326 (2005).

1184 49. Saudemont, A. et al. Complementary striped expression patterns of NK homeobox

1185 genes during segment formation in the annelid *Platynereis*. *Dev. Biol.* **317**, 430–443

1186 (2008).

1187 50. Ackermann, C., Dorresteijn, A. & Fischer, A. Clonal domains in postlarval *Platynereis*

1188 *dumerilii* (Annelida: Polychaeta). *J. Morphol.* **266**, 258–280 (2005).

1189 51. Fischer, A. H. L. & Arendt, D. Mesoteloblast-Like Mesodermal Stem Cells in the

1190 Polychaete Annelid *Platynereis dumerilii* (Nereididae). *J. Exp. Zoöl. Part B: Mol. Dev. Evol.*
1191 **320**, 94–104 (2013).

1192 52. Özpolat, B. D., Handberg-Thorsager, M., Vervoort, M. & Balavoine, G. Cell lineage and cell cycling analyses of the 4d micromere using live imaging in the marine annelid *Platynereis dumerilii*. *eLife* 6, e30463 (2017).

1195 53. Chou, H.-C., Pruitt, M. M., Bastin, B. R. & Schneider, S. Q. A transcriptional blueprint for a spiral-cleaving embryo. BMC Genom. 17, 552 (2016).

1197 54. Dorresteijn, A. W. C. Quantitative analysis of cellular differentiation during early embryogenesis of *Platynereis dumerilii*. *Roux's Arch. Dev. Biol.* **199**, 14–30 (1990).

1199 55. Elgin, S. C. R. & Reuter, G. Position-Effect Variegation, Heterochromatin Formation, and Gene Silencing in *Drosophila*. *Cold Spring Harb. Perspect. Biol.* **5**, a017780 (2013).

1201 56. Takashima, S., Aghajanian, P., Younossi-Hartenstein, A. & Hartenstein, V. Origin and dynamic lineage characteristics of the developing *Drosophila* midgut stem cells. Dev. Biol. **416**, 347–360 (2016).

1204 57. Zhulyn, O. et al. Evolutionarily divergent mTOR remodels translatome for tissue regeneration. *Nature* **620**, 163–171 (2023).

1206 58. Johnson, K., Bateman, J., DiTommaso, T., Wong, A. Y. & Whited, J. L. Systemic cell cycle activation is induced following complex tissue injury in axolotl. Dev. Biol. **433**, 461–472 (2018).

1209 59. Hirose, K., Shiomi, T., Hozumi, S. & Kikuchi, Y. Mechanistic target of rapamycin complex 1 signaling regulates cell proliferation, cell survival, and differentiation in regenerating zebrafish fins. BMC Dev. Biol. **14**, 42 (2014).

1212 60. Molinaro, A. M., Lindsay-Mosher, N. & Pearson, B. J. Identification of TOR-responsive slow-cycling neoblasts in planarians. *EMBO Rep.* **22**, e50292 (2021).

1214 61. Peiris, T. H. et al. TOR signaling regulates planarian stem cells and controls localized and organismal growth. *J. Cell Sci.* **125**, 1657–1665 (2012).

1216 62. Lund-Ricard, Y., Cormier, P., Morales, J. & Boutet, A. mTOR Signaling at the Crossroad between Metazoan Regeneration and Human Diseases. *Int. J. Mol. Sci.* **21**, 2718 (2020).

1218 63. Tsujimoto, K., Takamatsu, H. & Kumanogoh, A. The Ragulator complex: delving its multifunctional impact on metabolism and beyond. *Inflamm. Regen.* **43**, 28 (2023).

1220 64. Bulut-Karslioglu, A. et al. The Transcriptionally Permissive Chromatin State of Embryonic Stem Cells Is Acutely Tuned to Translational Output. *Cell Stem Cell* **22**, 369–383.e8 (2018).

1223 65. Chresta, C. M. et al. AZD8055 Is a Potent, Selective, and Orally Bioavailable ATP-Competitive Mammalian Target of Rapamycin Kinase Inhibitor with In vitro and In vivo Antitumor Activity. *Cancer Res.* **70**, 288–298 (2010).

1226 66. Shao, Y. et al. Genome and single-cell RNA-sequencing of the earthworm *Eisenia andrei* identifies cellular mechanisms underlying regeneration. Nat. Commun. 11, 2656 (2020).

1229 67. Wagner, D. E., Wang, I. E. & Reddien, P. W. Clonogenic Neoblasts Are Pluripotent Adult Stem Cells That Underlie Planarian Regeneration. Science **332**, 811–816 (2011).
1231 68. Reddien, P. W. The Cellular and Molecular Basis for Planarian Regeneration. Cell 175, 327-345 (2018).

1232 69. Varley, Á., Horkan, H. R., McMahon, E. T., Krasovec, G. & Frank, U. Pluripotent, germ cell competent adult stem cells underlie cnidarian regenerative ability and clonal growth. *Curr. Biol.* **33**, 1883-1892.e3 (2023).

1233 70. Holstein, T. W. The *Hydra* stem cell system – Revisited. *Cells Dev.* **174**, 203846 (2023).

1234 71. Álvarez-Campos, P. et al. Annelid adult cell type diversity and their pluripotent cellular origins. *Nat. Commun.* 15, 3194 (2024).

1235 72. Denes, A. S. et al. Molecular Architecture of Annelid Nerve Cord Supports Common Origin of Nervous System Centralization in Bilateria. *Cell* **129**, 277-288 (2007).

1236 73. Smith, K. N., Singh, A. M. & Dalton, S. Myc Represses Primitive Endoderm Differentiation in Pluripotent Stem Cells. *Cell Stem Cell* 7, 343-354 (2010).

1237 74. Bernabé-Rubio, M. et al. Myc-dependent dedifferentiation of Gata6+ epidermal cells resembles reversal of terminal differentiation. *Nat. Cell Biol.* **25**, 1426-1438 (2023).

1238 75. Koh, F. M. et al. Emergence of hematopoietic stem and progenitor cells involves a Chd1-dependent increase in total nascent transcription. *Proc. Natl. Acad. Sci.* **112**, E1734-E1743 (2015).

1239 76. Bideau, L. et al. Variations in cell plasticity and proliferation underlie distinct modes of regeneration along the antero-posterior axis in the annelid *Platynereis*. *Development* **151**, (2024).

1240 77. Satoh, A., Cummings, G. M. C., Bryant, S. V. & Gardiner, D. M. Neurotrophic regulation of fibroblast dedifferentiation during limb skeletal regeneration in the axolotl (*Ambystoma mexicanum*). *Dev. Biol.* 337, 444-457 (2010).

1241 78. Satoh, A., Gardiner, D. M., Bryant, S. V. & Endo, T. Nerve-induced ectopic limb blastemas in the axolotl are equivalent to amputation-induced blastemas. *Dev. Biol.* **312**, 231-244 (2007).

1242 79. Nohno, T. et al. A Chicken Homeobox Gene Related to *Drosophila* paired Is Predominantly Expressed in the Developing Limb. *Dev. Biol.* **158**, 254-264 (1993).

1243 80. Logan, M. et al. Expression of Cre recombinase in the developing mouse limb bud driven by a Prxl enhancer. *genesis* 33, 77-80 (2002).

1244 81. Gerber, T. et al. Single-cell analysis uncovers convergence of cell identities during axolotl limb regeneration. *Science* **362**, eeaq0681 (2018).

1245 82. Zantke, J. et al. Circadian and Circalunar Clock Interactions in a Marine Annelid. *Cell* Rep. 5, 99-113 (2013).

1246 83. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. *EMBnet* **17**, 10-12 (2011).

1247 84. Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).

1248 85. Ewels, P., Magnusson, M., Lundin, S. & Käller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. *Bioinformatics* **32**, 3047-3048 (2016).
1271 86. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics **29**, 15–21
1272 (2012).

1273 87. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for
1274 assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

1275 88. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion
1276 for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

1277 89. Kumar, L. & Futschik, M. E. Mfuzz: A software package for soft clustering of microarray
1278 data. *Bioinformation* **2**, 5–7 (2007).

1279 90. Wickham, H. Ggplot2: *Elegant Graphics for Data Analysis*. (Springer-Verlag, New York,
1280 2016).

1281 91. Mutemi, K. N. et al. A genome resource for the marine annelid Platynereis dumerilii.
1282 *bioRxiv* 2024.06.21.600153 (2024)

1283 92. Stuart, T. & Satija, R. Integrative single-cell analysis. *Nat. Rev. Genet.* **20**, 257–272
1284 (2019).

1285 93. Steger, J. et al. Single-cell transcriptomics identifies conserved regulators of
1286 neuroglandular lineages. Cell Rep. **40**, 111370 (2022).

1287 94. Zhang, Z., Schwartz, S., Wagner, L. & Miller, W. A Greedy Algorithm for Aligning DNA
1288 Sequences. *J. Comput. Biol.* **7**, 203–214 (2000).

1289 95. Letunic, I., Khedkar, S. & Bork, P. SMART: recent updates, new developments and status
1290 in 2020. *Nucleic Acids Res.* **49**, gkaa937- (2020).

1291 96. Yamaguchi, K. D. et al. IFN-β-regulated genes show abnormal expression in therapy-
1292 naïve relapsing–remitting MS mononuclear cells: Gene expression analysis employing all
1293 reported protein–protein interactions. *J. Neuroimmunol.* **195**, 116–120 (2008).

1294 97. Zyla, J. et al. Gene set enrichment for reproducible science: comparison of CERNO and
1295 eight other algorithms. *Bioinformatics* **35**, 5146–5154 (2019).

1296 98. Nguyen, L.-T., Schmidt, H. A., Haeseler, A. von & Minh, B. Q. IQ-TREE: A Fast and
1297 Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. *Mol. Biol. Evol.* **32**, 268–274 (2015).

1299 99. Trifinopoulos, J., Nguyen, L.-T., von Haeseler, A. & Minh, B. Q. W-IQ-TREE: a fast online
1300 phylogenetic tool for maximum likelihood analysis. *Nucleic Acids Res.* **44**, W232–W235
1301 (2016).

1302 100. Hoang, D. T., Chernomor, O., Haeseler, A. von, Minh, B. Q. & Vinh, L. S. UFBoot2:
1303 Improving the Ultrafast Bootstrap Approximation. *Mol. Biol. Evol.* **35**, 518–522 (2018).

1304 101. Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic
1305 tree display and annotation. *Nucleic Acids Res.* **49**, gkab301- (2021).

1306 102. Blanco-Carmona, E. Generating publication ready visualizations for Single Cell
1307 transcriptomics using SCpubr. *bioRxiv* 2022.02.28.482303 (2022)
doi:10.1101/2022.02.28.482303.

1309 103. Kuehn, E. et al. Segment number threshold determines juvenile onset of germline
1310 cluster expansion in *Platynereis dumerilii*. *J. Exp. Zoöl. Part B: Mol. Dev. Evol.* **338**, 225–240
1311 (2022).

1312 104. Tessmar-Raible, K., Steinmetz, P. R. H., Snyman, H., Hassel, M. & Arendt, D.

1313 Fluorescent two-color whole mount in situ hybridization in Platynereis dumerilii

1314 (Polychaeta, Annelida), an emerging marine molecular model for evolution and

1315 development. *Biotechniques* **39**, 460–464 (2005).

1316 105. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. *Nat.*

1317 *Methods* **9**, 676–682 (2012).

1318 106. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred

1319 kilobases. *Nat. Methods* 6, 343–345 (2009).

1320 107. Backfisch, B. et al. Stable transgenesis in the marine annelid *Platynereis dumerilii*

1321 sheds new light on photoreceptor evolution. *Proc. Natl. Acad. Sci.* 110, 193–198 (2013).