transgenesis (BestGene). Several independent transgenic lines were generated and tested, and one was kept (cyp-FLP).

For creating *cyp4g15-mtdTomato*, the *mtdTomato* DNA, which codes for a Tomato fluorescent protein tagged at the N-terminal end with Tag:MyrPalm (MGCCFSKT, directing myristoylation and palmitoylation) and at the C-terminal with 3 Tag:HA epitope, was amplified from genomic DNA extracted from *QUAS-mtdTomato* adult flies (BDSC30005, Chris Potter lab), as described in⁹⁶. This amplicon together with the *cyp4g15<sup>DSCP</sup>* enhancer were joined using the Multisite gateway system⁹⁴ in the destination vector pDESThaw sv40 gift from S. Stowers) in order to generate a *cyp4g15<sup>DSCP</sup>-FLP* construct. The construct was integrated in the fly genome at an attP2 or attP40 docking site through PhiC31 integrase-mediated transgenesis (BestGene). Several independent transgenic lines were generated and tested, and one was kept for each chromosome (*cyp-mtdTomato*).

For creating *cyp4g15-FRT-STOP-FRT-LexA*, a FRT STOP cassette was amplified from an UAS-FRT.STOP-Bxb1 plasmid (gift from MK. Mazouni) and the LexA sequence was amplified from the entry vector L2-LexA::p65-L5 (gift from M. Landgraf). The two amplicons were joined together by overlapping PCRs. This *FRT-STOP-FRT-LexA* amplification together with the *cyp4g15<sup>DSCP</sup>* enhancer were inserted in the destination vector pDESThaw sv40 using Multisite gateway system⁹⁴ to generate a *cyp4g15<sup>DSCP</sup>-FRT-STOP-FRT-LexA::p65* construct. The construct was integrated in the fly genome at an attP2 or attP40 docking sites through PhiC31 integrase-mediated transgenesis (BestGene). Several independent transgenic lines were generated and tested, and one was kept for each docking site.

See Supplementary Table 2 for all primers.

## Generation of UAS-Raeppli and LexAOp-Raeppli lines

The original construct (BDSC 55082), placing *Raeppli-CAAX* under the control of both UAS and LexAOp sequences, was crossed to a Cre recombinase line (BDSC 851) to randomly excise one of the two control sequences. The resulting lines were checked by PCR to determine whether they carried the UAS or LexAop version.

A similar protocol was followed to generate *UAS-Raeppli-NLS S3D* and *LexAOp-Raeppli NLS-S3D* constructs from the original line BDSC 55087.

## Fixed tissue Immunohistochemistry and imaging

For immunohistochemistry, CNS from staged larvae were dissected in PBS, fixed for 20 min in 4% formaldehyde diluted in PBS with 0.1% Triton X-100, washed two times in PBS-T (PBS + 0.3% Triton X-100) and incubated overnight at 4 °C with primary antibodies diluted in PBS-T. After washing three times in PBS-T, CNS were incubated overnight at 4 °C with secondary antibodies (dilution 1:200) and DAPI (1:1000) diluted in PBS-T. Brains were washed three times in PBS-T and mounted in Mowiol mounting medium on a borosilicate glass side (number 1.5; VWR International). Primary antibodies used were: guinea pig anti-Dpn (1:5000, in-house made, using pET29a-Dpn plasmid from J. Skeath for production), rabbit anti-Dpn (1:200, gift from R. Basto), chicken anti-GFP (1:2000, Abcam ab13970), rat anti-ELAV (1:100, 7E8A10-c, DSHB), mouse anti-Repo 1:100 (DSHB, 8D12-c), rabbit anti-Phosphohistone H3 (1:100, Millipore 06-570), rabbit anti-Dcp-1 (1/100, Cell Signalling 9578S), rat anti-mbc⁹⁷ (1/200, gift from S. Abmayr), guinea pig anti-kirre⁹⁸ (1/1000, gift from S. Abmayr) and rabbit anti-Mucin D⁹⁹ (1/1000, gift from AA. Kramerov). Fluorescently-conjugated secondary antibodies Alexa Fluor 405, Alexa Fluor 488, Alexa Fluor 546, and Alexa Fluor 633 (ThermoFisher Scientific) were all used at a 1:200 dilution. DAPI (4',6-diamidino-2-phenylindole, ThermoFisher Scientific 62247) was used to counterstain the nuclei (1:1000).

## Image acquisition and processing

Confocal images were acquired using a laser scanning confocal microscope (Zeiss LSM 880, Zen software (2012 S4)) with a Plan-

Apochromat 40×/1.3 Oil objective. All brains were imaged as z-stacks with each section corresponding to 0.3–0.5 µm. Images were subsequently analysed and processed using Fiji (Schindelin, 1.53c), Velocity 6.3 (Quorum technologies), the Open-Source software Icy v2.1.4.0 (Institut Pasteur and France Bioimaging, license GPLv3) and Photoshop 22.5.8 (Adobe Creative Cloud). Denoising was used for some images using the Despeckle or ROF denoise processes in Fiji and the Remove noise function (Fine filter) in Velocity. Images were assembled using Adobe Illustrator 25.4.6.

## Structured illumination microscopy (SIM)

The super-resolved images were acquired on a Elyra 7 Lattice SIM microscope (Carl Zeiss, Germany) using a 63×/1.46 oil alpha Plan Apo objective with a 1.518 refractive index oil (Carl Zeiss) and an sCMOS PCO Edge 4.2 camera for the detection. Thirteen images per plane per channel were acquired with a Z-distance of 0.101 µm to perform 3D-SIM images. The ZEN software was used to process the SIM images.

## Live imaging

For live imaging, culture chambers were prepared by adding 300 µl of 1% low-melting agarose prepared in Schneider's medium supplemented with pen-strep on a glass-bottom 35 mm dish (P35G-1.5-14-C, MatTek Corporation) and allowed to solidify. Circular wells of approximately 2 mm diameter were then cut out using a 200 µl pipet tip fitted with a rubber bulb. CNS from staged larvae were dissected in Schneider's *Drosophila* medium (21720-024, Gibco) supplemented with 10% heat-inactivated fetal bovine serum (10500, Gibco), penicillin (100 units ml⁻¹) and streptomycin (100 µg ml⁻¹) (penicillin-streptomycin 15140, Gibco). 4–6 CNS were placed inside small wells of a pre-prepared culturing chamber and covered with culture medium (Schneider's + 5% FBS + larval lysate (10 µl/ml) + pen/strep (1/100). Larval lysate is prepared by homogenising twenty 3rd instar larvae in 200 µl of Schneider's, spinning down once at 6000 rpm for 5 min at 4 °C, and recovering the supernatant. Brains were set in position and let to settle around 5–10 min before starting imaging. Brains were imaged on a laser scanning confocal microscope (Zeiss LSM 880, Zen software (2012 S4)) fitted with a temperature-controlled live imaging chamber (TC incubator for Zeiss Piezo stage, Gataca systems) using a Plan-Apochromat 40×/1.3 Oil objective. Four-dimensional z-stacks of 5–10 µm at 0.5 µm intervals were acquired every 2–3 min. Movies were performed on the ventral side of the ventral nerve cord. Images were subsequently analysed and processed using Fiji (Schindelin, J. 2012).

## Quantification of cortex glia nuclei and mitotic cortex glia

Wild-type brains expressing RFP or GFP-tagged (*Hist::RFP* or *Hist::YFP*, respectively) driven by *cyp4g15-GAL4*, were stained with phosphohistone H3 antibody to detect mitotic CG. Entire brains were imaged and quantification of total and mitotic CG nuclei numbers were performed in Velocity 6.3 (Quorum technologies) using adjusted protocols for detection of objects.

## Cell cycle analysis (FUCCI)

We used the Fly-FUCCI system⁴⁵ that allows to discriminate between different phases of the cell cycle by expressing truncated forms of E2F and Cyclin B (CycB) fused to EGFP and mRFP1, respectively (EGFP::E2F 1-230, mRFP1::CycB 1-266). We used the *cyp4g15-GAL4* driver to express *UAS-EGFP::E2F 1-230* and *UAS-mRFP1::CycB 1-266* in CG cells. Staging of larvae was performed at 25 °C and brains were dissected in PBS at ALHO, ALH24, ALH48, ALH72, and ALH96. Brains where immediately fixed in 4% formaldehyde diluted in PBS for 20 min, washed 3 times in PBS and mounted in Mowiol mounting medium on glass slides. Samples were imaged as described above and quantification of G1 (green), S (red) and G2/M CG nuclei was performed in Velocity 6.3 (Quorum technologies).
transgenesis (BestGene). Several independent transgenic lines were generated and tested, and one was kept (cyp-FLP).

For creating *cyp4g15-mtdTomato*, the *mtdTomato* DNA, which codes for a Tomato fluorescent protein tagged at the N-terminal end with Tag:MyrPalm (MGCCFSKT, directing myristoylation and palmitoylation) and at the C-terminal with 3 Tag:HA epitope, was amplified from genomic DNA extracted from *QUAS-mtdTomato* adult flies (BDSC30005, Chris Potter lab), as described in⁹⁶. This amplicon together with the *cyp4g15*<sup>DSCP</sup> enhancer were joined using the Multisite gateway system⁹⁴ in the destination vector pDESThaw sv40 gift from S. Stowers) in order to generate a *cyp4g15*<sup>DSCP-FLP</sup> construct. The construct was integrated in the fly genome at an attP2 or attP40 docking site through PhiC31 integrase-mediated transgenesis (BestGene). Several independent transgenic lines were generated and tested, and one was kept for each chromosome (*cyp-mtdTomato*).

For creating *cyp4g15-FRT-STOP-FRT-LexA*, a FRT STOP cassette was amplified from an UAS-FRT.STOP-Bxb1 plasmid (gift from MK. Mazouni) and the LexA sequence was amplified from the entry vector L2-LexA::p65-L5 (gift from M. Landgraf). The two amplicons were joined together by overlapping PCRs. This *FRT-STOP-FRT-LexA* amplification together with the *cyp4g15*<sup>DSCP</sup> enhancer were inserted in the destination vector pDESThaw sv40 using Multisite gateway system⁹⁴ to generate a *cyp4g15*<sup>DSCP-FRT-STOP-FRT-LexA::p65</sup> construct. The construct was integrated in the fly genome at an attP2 or attP40 docking sites through PhiC31 integrase-mediated transgenesis (BestGene). Several independent transgenic lines were generated and tested, and one was kept for each docking site.

See Supplementary Table 2 for all primers.

## Generation of UAS-Raeppli and LexAOp-Raeppli lines

The original construct (BDSC 55082), placing *Raeppli-CAAX* under the control of both UAS and LexAOp sequences, was crossed to a Cre recombinase line (BDSC 851) to randomly excise one of the two control sequences. The resulting lines were checked by PCR to determine whether they carried the UAS or LexAop version.

A similar protocol was followed to generate *UAS-Raeppli-NLS S3D* and *LexAOp-Raeppli NLS-S3D* constructs from the original line BDSC 55087.

## Fixed tissue Immunohistochemistry and imaging

For immunohistochemistry, CNS from staged larvae were dissected in PBS, fixed for 20 min in 4% formaldehyde diluted in PBS with 0.1% Triton X-100, washed two times in PBS-T (PBS + 0.3% Triton X-100) and incubated overnight at 4 °C with primary antibodies diluted in PBS-T. After washing three times in PBS-T, CNS were incubated overnight at 4 °C with secondary antibodies (dilution 1:200) and DAPI (1:1000) diluted in PBS-T. Brains were washed three times in PBS-T and mounted in Mowiol mounting medium on a borosilicate glass side (number 1.5; VWR International). Primary antibodies used were: guinea pig anti-Dpn (1:5000, in-house made, using pET29a-Dpn plasmid from J. Skeath for production), rabbit anti-Dpn (1:200, gift from R. Basto), chicken anti-GFP (1:2000, Abcam ab13970), rat anti-ELAV (1:100, 7E8A10-c, DSHB), mouse anti-Repo 1:100 (DSHB, 8D12-c), rabbit anti-Phosphohistone H3 (1:100, Millipore 06-570), rabbit anti-Dcp-1 (1/100, Cell Signalling 9578S), rat anti-mbc⁹⁷ (1/200, gift from S. Abmayr), guinea pig anti-kirre⁹⁸ (1/1000, gift from S. Abmayr) and rabbit anti-Mucin D⁹⁹ (1/1000, gift from AA. Kramerov). Fluorescently-conjugated secondary antibodies Alexa Fluor 405, Alexa Fluor 488, Alexa Fluor 546, and Alexa Fluor 633 (ThermoFisher Scientific) were all used at a 1:200 dilution. DAPI (4',6-diamidino-2-phenylindole, ThermoFisher Scientific 62247) was used to counterstain the nuclei (1:1000).

## Image acquisition and processing

Confocal images were acquired using a laser scanning confocal microscope (Zeiss LSM 880, Zen software (2012 S4)) with a Plan-

Apochromat 40×/1.3 Oil objective. All brains were imaged as z-stacks with each section corresponding to 0.3–0.5 µm. Images were subsequently analysed and processed using Fiji (Schindelin, 1.53c), Velocity 6.3 (Quorum technologies), the Open-Source software Icy v2.1.4.0 (Institut Pasteur and France Bioimaging, license GPLv3) and Photoshop 22.5.8 (Adobe Creative Cloud). Denoising was used for some images using the Despeckle or ROF denoise processes in Fiji and the Remove noise function (Fine filter) in Velocity. Images were assembled using Adobe Illustrator 25.4.6.

## Structured illumination microscopy (SIM)

The super-resolved images were acquired on a Elyra 7 Lattice SIM microscope (Carl Zeiss, Germany) using a 63×/1.46 oil alpha Plan Apo objective with a 1.518 refractive index oil (Carl Zeiss) and an sCMOS PCO Edge 4.2 camera for the detection. Thirteen images per plane per channel were acquired with a Z-distance of 0.101 µm to perform 3D-SIM images. The ZEN software was used to process the SIM images.

## Live imaging

For live imaging, culture chambers were prepared by adding 300 µl of 1% low-melting agarose prepared in Schneider's medium supplemented with pen-strep on a glass-bottom 35 mm dish (P35G-1.5-14-C, MatTek Corporation) and allowed to solidify. Circular wells of approximately 2 mm diameter were then cut out using a 200 µl pipet tip fitted with a rubber bulb. CNS from staged larvae were dissected in Schneider's *Drosophila* medium (21720-024, Gibco) supplemented with 10% heat-inactivated fetal bovine serum (10500, Gibco), penicillin (100 units ml⁻¹) and streptomycin (100 µg ml⁻¹) (penicillin-streptomycin 15140, Gibco). 4–6 CNS were placed inside small wells of a pre-prepared culturing chamber and covered with culture medium (Schneider's + 5% FBS + larval lysate (10 µl/ml) + pen/strep (1/100). Larval lysate is prepared by homogenising twenty 3rd instar larvae in 200 µl of Schneider's, spinning down once at 6000 rpm for 5 min at 4 °C, and recovering the supernatant. Brains were set in position and let to settle around 5–10 min before starting imaging. Brains were imaged on a laser scanning confocal microscope (Zeiss LSM 880, Zen software (2012 S4)) fitted with a temperature-controlled live imaging chamber (TC incubator for Zeiss Piezo stage, Gataca systems) using a Plan-Apochromat 40×/1.3 Oil objective. Four-dimensional z-stacks of 5–10 µm at 0.5 µm intervals were acquired every 2–3 min. Movies were performed on the ventral side of the ventral nerve cord. Images were subsequently analysed and processed using Fiji (Schindelin, J. 2012).

## Quantification of cortex glia nuclei and mitotic cortex glia

Wild-type brains expressing RFP or GFP-tagged (Hist::RFP or Hist::YFP, respectively) driven by *cyp4g15-GAL4*, were stained with phosphohistone H3 antibody to detect mitotic CG. Entire brains were imaged and quantification of total and mitotic CG nuclei numbers were performed in Velocity 6.3 (Quorum technologies) using adjusted protocols for detection of objects.

## Cell cycle analysis (FUCCI)

We used the Fly-FUCCI system⁴⁵ that allows to discriminate between different phases of the cell cycle by expressing truncated forms of E2F and Cyclin B (CycB) fused to EGFP and mRFP1, respectively (EGFP::E2F 1-230, mRFP1::CycB 1-266). We used the *cyp4g15-GAL4* driver to express *UAS-EGFP::E2F 1-230* and *UAS-mRFP1::CycB 1-266* in CG cells. Staging of larvae was performed at 25 °C and brains were dissected in PBS at ALHO, ALH24, ALH48, ALH72, and ALH96. Brains where immediately fixed in 4% formaldehyde diluted in PBS for 20 min, washed 3 times in PBS and mounted in Mowiol mounting medium on glass slides. Samples were imaged as described above and quantification of G1 (green), S (red) and G2/M CG nuclei was performed in Velocity 6.3 (Quorum technologies).
## Multicolour clonal analyses (Raepli)

Heat-inducible Raepli clones were generated by crossing *yw*; *UAS-Raepli-CAAX* 43E; *cyp4g15-Gal4/TM6B* or *yw*; *UAS-Raepli-nls* S3D; *cyp4g15-Gal4/TM6B* males to *hs-FLP* females. For knockdown experiments, chosen RNAi lines were crossed with *yw*, *hs-FLP*; *cyp-FRT-STOP-FRT-LexA/CyO*; *cyp4g15-GAL4*, *LexO-Raepli-CAAX* 43E. Freshly hatched larvae (ALHO) were heat shocked for 2 h at 37 °C and aged to ALH24, ALH48, ALH72 and ALH96 at 25 °C, or at 29 °C for RNAi experiments. For the visualisation of clones at ALHO, constitutively expressed *Cyp-FLP* females were crossed to *yw*; *UAS-Raepli-CAAX* 43E; *cyp4g15-Gal4/TM6B* males. Immunolabelling of NSCs for Fig. 1e was performed as described above. For all other experiments, CNS were dissected and fixed for 20 min in 4% formaldehyde in PBS and washed three times in PBS before mounting. Images were acquired as described above using the spectral mode of a Zeiss LSM880 confocal to promote fluorophore separation.

## Quantification of clone volumes for Raepli-CAAX

Raepli TFP1 clones were chosen for quantification as it is the strongest and sharpest of the four Raepli fluorophores. Only clones in the ventral nerve cord were measured. Volumes were measured in 3D images using Velocity 6.3 (Quorum technologies).

### Quantification of clone overlap for *Raepli-CAAX*

Z stacks of *Raepli-CAAX* S3E clones induced in CG were visualised in Icy v2.1.4.0 (Institut Pasteur and France Bioimaging, license GPLv3). Boundaries of all one-colour clones, for each of the 4 possible, were mapped manually and outlined with polygons. The same was done in the rare case of full colour overlap. Partial overlaps between clones (defined as an overlap between the colours of adjacent clones that do not cover fully any of the two clones) were then counted manually, with their position recorded on the stack by drawing an ellipse.

The clones were counted in the VNC only, stopping at the middle of the neuropile coming from the ventral side, as the great majority of NSCs are located ventrally.

The number of overlaps counted corresponds to the number of fusion events, that we then divided by the total number of clones to generate a "Number of events/clones".

### Quantification of clone number, size, and colour for *Raepli-NLS*

Z stacks of *Raepli-NLS* clones induced in CG were visualised in Icy v2.1.4.0 (Institut Pasteur and France Bioimaging, license GPLv3). The z dimension of the stack was reduced to encompass clones from the most ventral side up to the neuropile, then a max intensity projection was performed to get a 2D representation of the clones. Clone boundaries were mapped manually, based on changes in colour combination, and outlined with polygons. Boundaries were verified back on the 3D z-stack in case of ambiguity brought by the 2D projection. The total number of clones identified was then recorded (Number of clones), as well as the number of nuclei (Number of nuclei per clone) and the colour combination (Number of colours per clone) for each clone. These counts were obtained in the VNC only.

## Clonal analyses using CoinFLP

The recently described Coin-FLP method⁷¹ was used to generate red and green mosaics of CG cells. CoinFLP clones were generated by crossing *Cyp-FLP*; *CoinFLP* females to *yw*; *LexAop-mCherry*; *UAS-GFP* or *yw*; *LexAop-mCherry::mito*; *UAS-mito-GFP* males and maintained at 25 °C. Larvae were staged to ALH48-ALH72 at 25 °C. For fixed tissue analyses, brains were dissected and fixed for 20 min in 4% formaldehyde in PBS and washed three times in PBS before mounting. Images were acquired as described above. For live imaging and FLIP experiments (see below), CNS were dissected in Schneider's medium and mounted as described for live imaging.

For counting of clone overlap (Fig. 5c, e), only green clones were taken in account for the no overlap category, due to the bias in the CoinFLP system that generates very large connected clones in one colour (RFP in our case) and small sparse clones in the other colour (GFP),

## Fluorescence loss in photobleaching (FLIP)

FLIP experiments were performed in dissected larval brains mounted as described above for live imaging. Fluorescence in a selected region of interest (ROI) within a CG cell was repeatedly photobleached over time, and loss of fluorescence in nonbleached regions were monitored. Bleaching was performed on GFP expressed in CG using the *cyp4g15-GAL4* driver. Laser line 488 was used at 100%. Images were acquired as follows: one z-stack of 5–10 µm at 0.3–0.5 µm intervals before bleaching (Pre-bleach), followed by 100 continuous acquisitions at the bleaching plane during the bleaching (Bleach) and one z-stack of 5–10 µm at 0.3–0.5 µm intervals after bleaching (Post-bleach). Images were subsequently analysed and processed using Fiji.

### Quantification of fluorescence loss in photobleaching (FLIP)

Measures of fluorescence intensities over time (Fig. 6 and Supplementary Fig. 6c) were performed on Velocity 6.3 (Quorum technologies). For each region (GFP only, mCherry only, fused *H*<sub>GFP</sub> and fused *L*<sub>GFP</sub>), a ROI was drawn manually to follow the contours of the corresponding area at time T0. The same ROI was kept throughout, except for Fig. 6d, in which a slight x-shift of the ROI shape was performed at the last timepoint (T100) to adjust a restricted x-drift in the tissue. Mean intensities (*I*<sub>MEAN</sub>) were calculated for each channel in each ROI. The percentage of fluorescence loss in the ROI for each channel (%FL) was determined with the following formula: %FL = (I<sub>MEAN</sub> Tstart - I<sub>MEAN</sub> Tend)/I<sub>MEAN</sub> Tstart.

Due to the existence of (i) FLIP-independent decay in fluorescence due to imaging-related photobleaching, and (ii) of FLIP-independent variations in fluorescence over time (e.g., small tissue z-shifts, intracellular movements) as well as (iii) potential unknown effects of photobleaching of one fluorophore on the other one, we determined for each fluorophore the maximum percentage of loss in fluorescence under which it can be attributed to random variations, with a confidence level of 95%. %FL during a FLIP experiment exceeding this maximum can therefore be considered as a significant variation.

To do so, for each movie, we performed a Monte-Carlo analysis on %FL in the channel corresponding to the unbleached fluorophore (Fig. 6a: mCherry; 6b: GFP; 6c: GFP and 6d: mCherry). This was achieved by sampling %FL over ten thousand randomly positioned 10 × 10 µm squares. A Cumulative Distribution Function was then generated from the results and used to calculate the %FL value required for a 99% confidence level (i.e., if %FL exceeds this value, it is unlikely to be due to random variations, but can be attributed to the FLIP photomanipulation). For each fluorophore, as we treated two movies, we obtained two %FL values fitting the 95% confidence level (Supplementary Fig. 6b). We then kept the most stringent (i.e., higher) one. For GFP, the threshold is 19.1% and for mCherry, the threshold is 20.8%. As such, only %FL values above these thresholds were considered significant during the FLIP experiments for attributing the loss in fluorescence to the FLIP. The python script of this analysis was written with Python 3.6.15, numpy 1.17.3, and matplotlib 2.2.5, and is available on Zenodo, DOI: 10.5281/zenodo.6941645.

## Kaede photoconversion

Photoconversion experiments were performed in dissected larval brains mounted as described above for live imaging. GFP fluorescence in a selected ROI within a CG cell was illuminated with iterative pulses (each cycle) of a 405 nm diode. Diode power was between 3 and 4%. While single pulse achieved localised conversion in the ROI, it was not
## Multicolour clonal analyses (Raepli)

Heat-inducible Raepli clones were generated by crossing *yw*; *UAS-Raepli-CAAX* 43E; *cyp4g15-Gal4/TM6B* or *yw*; *UAS-Raepli-nls* S3D; *cyp4g15-Gal4/TM6B* males to *hs-FLP* females. For knockdown experiments, chosen RNAi lines were crossed with *yw*, *hs-FLP*; *cyp-FRT-STOP-FRT-LexA/CyO*; *cyp4g15-GAL4*, *LexO-Raepli-CAAX* 43E. Freshly hatched larvae (ALHO) were heat shocked for 2 h at 37 °C and aged to ALH24, ALH48, ALH72 and ALH96 at 25 °C, or at 29 °C for RNAi experiments. For the visualisation of clones at ALHO, constitutively expressed *Cyp-FLP* females were crossed to *yw*; *UAS-Raepli-CAAX* 43E; *cyp4g15-Gal4/TM6B* males. Immunolabelling of NSCs for Fig. 1e was performed as described above. For all other experiments, CNS were dissected and fixed for 20 min in 4% formaldehyde in PBS and washed three times in PBS before mounting. Images were acquired as described above using the spectral mode of a Zeiss LSM880 confocal to promote fluorophore separation.

## Quantification of clone volumes for Raepli-CAAX

Raepli TFP1 clones were chosen for quantification as it is the strongest and sharpest of the four Raepli fluorophores. Only clones in the ventral nerve cord were measured. Volumes were measured in 3D images using Velocity 6.3 (Quorum technologies).

### Quantification of clone overlap for Raepli-CAAX

Z stacks of *Raepli-CAAX* S3E clones induced in CG were visualised in Icy v2.1.4.0 (Institut Pasteur and France Bioimaging, license GPLv3). Boundaries of all one-colour clones, for each of the 4 possible, were mapped manually and outlined with polygons. The same was done in the rare case of full colour overlap. Partial overlaps between clones (defined as an overlap between the colours of adjacent clones that do not cover fully any of the two clones) were then counted manually, with their position recorded on the stack by drawing an ellipse.

The clones were counted in the VNC only, stopping at the middle of the neuropile coming from the ventral side, as the great majority of NSCs are located ventrally.

The number of overlaps counted corresponds to the number of fusion events, that we then divided by the total number of clones to generate a "Number of events/clones".

### Quantification of clone number, size, and colour for Raepli-NLS

Z stacks of *Raepli-NLS* clones induced in CG were visualised in Icy v2.1.4.0 (Institut Pasteur and France Bioimaging, license GPLv3). The z dimension of the stack was reduced to encompass clones from the most ventral side up to the neuropile, then a max intensity projection was performed to get a 2D representation of the clones. Clone boundaries were mapped manually, based on changes in colour combination, and outlined with polygons. Boundaries were verified back on the 3D z-stack in case of ambiguity brought by the 2D projection. The total number of clones identified was then recorded (Number of clones), as well as the number of nuclei (Number of nuclei per clone) and the colour combination (Number of colours per clone) for each clone. These counts were obtained in the VNC only.

## Clonal analyses using CoinFLP

The recently described Coin-FLP method⁷¹ was used to generate red and green mosaics of CG cells. CoinFLP clones were generated by crossing *Cyp-FLP*; *CoinFLP* females to *yw*; *LexAop-mCherry*; *UAS-GFP* or *yw*; *LexAop-mCherry::mito*; *UAS-mito-GFP* males and maintained at 25 °C. Larvae were staged to ALH48-ALH72 at 25 °C. For fixed tissue analyses, brains were dissected and fixed for 20 min in 4% formaldehyde in PBS and washed three times in PBS before mounting. Images were acquired as described above. For live imaging and FLIP experiments (see below), CNS were dissected in Schneider's medium and mounted as described for live imaging.

For counting of clone overlap (Fig. 5c, e), only green clones were taken in account for the no overlap category, due to the bias in the CoinFLP system that generates very large connected clones in one colour (RFP in our case) and small sparse clones in the other colour (GFP),

## Fluorescence loss in photobleaching (FLIP)

FLIP experiments were performed in dissected larval brains mounted as described above for live imaging. Fluorescence in a selected region of interest (ROI) within a CG cell was repeatedly photobleached over time, and loss of fluorescence in nonbleached regions were monitored. Bleaching was performed on GFP expressed in CG using the *cyp4g15-GAL4* driver. Laser line 488 was used at 100%. Images were acquired as follows: one z-stack of 5–10 µm at 0.3–0.5 µm intervals before bleaching (Pre-bleach), followed by 100 continuous acquisitions at the bleaching plane during the bleaching (Bleach) and one z-stack of 5–10 µm at 0.3–0.5 µm intervals after bleaching (Post-bleach). Images were subsequently analysed and processed using Fiji.

### Quantification of fluorescence loss in photobleaching (FLIP)

Measures of fluorescence intensities over time (Fig. 6 and Supplementary Fig. 6c) were performed on Velocity 6.3 (Quorum technologies). For each region (GFP only, mCherry only, fused $H_{GFP}$ and fused $L_{GFP}$), a ROI was drawn manually to follow the contours of the corresponding area at time T0. The same ROI was kept throughout, except for Fig. 6d, in which a slight x-shift of the ROI shape was performed at the last timepoint (T100) to adjust a restricted x-drift in the tissue. Mean intensities ($I_{MEAN}$) were calculated for each channel in each ROI. The percentage of fluorescence loss in the ROI for each channel (%FL) was determined with the following formula: %FL = ($I_{MEAN}$ Tstart - $I_{MEAN}$ Tend)/$I_{MEAN}$ Tstart.

Due to the existence of (i) FLIP-independent decay in fluorescence due to imaging-related photobleaching, and (ii) of FLIP-independent variations in fluorescence over time (e.g., small tissue z-shifts, intracellular movements) as well as (iii) potential unknown effects of photobleaching of one fluorophore on the other one, we determined for each fluorophore the maximum percentage of loss in fluorescence under which it can be attributed to random variations, with a confidence level of 95%. %FL during a FLIP experiment exceeding this maximum can therefore be considered as a significant variation.

To do so, for each movie, we performed a Monte-Carlo analysis on %FL in the channel corresponding to the unbleached fluorophore (Fig. 6a: mCherry; 6b: GFP; 6c: GFP and 6d: mCherry). This was achieved by sampling %FL over ten thousand randomly positioned 10 × 10 µm squares. A Cumulative Distribution Function was then generated from the results and used to calculate the %FL value required for a 99% confidence level (i.e., if %FL exceeds this value, it is unlikely to be due to random variations, but can be attributed to the FLIP photomanipulation). For each fluorophore, as we treated two movies, we obtained two %FL values fitting the 95% confidence level (Supplementary Fig. 6b). We then kept the most stringent (i.e., higher) one. For GFP, the threshold is 19.1% and for mCherry, the threshold is 20.8%. As such, only %FL values above these thresholds were considered significant during the FLIP experiments for attributing the loss in fluorescence to the FLIP. The python script of this analysis was written with Python 3.6.15, numpy 1.17.3, and matplotlib 2.2.5, and is available on Zenodo, DOI: 10.5281/zenodo.6941645.

## Kaede photoconversion

Photoconversion experiments were performed in dissected larval brains mounted as described above for live imaging. GFP fluorescence in a selected ROI within a CG cell was illuminated with iterative pulses (each cycle) of a 405 nm diode. Diode power was between 3 and 4%. While single pulse achieved localised conversion in the ROI, it was not
enough to visualise diffusion of the converted Kaede form in the CG units, which are of large size.

Images were acquired as follows: one z-stack of 30–40 µm at 0.5–1 µm intervals before photoconversion (Pre-photoconversion), followed by 50 continuous acquisitions at the bleaching plane during the photoconversion (Photoconversion) and one z-stack of 30–40 µm at 1 µm intervals after photoconversion (Post- photoconversion). Images were subsequently analysed and processed using Fiji.

For visualising *Raepli-NLS* and Kaede simultaneously, we used spectral imaging (Zeiss Quasar 34 channels) to acquire and distinguish between mTFP1, GFP, mOrange, mRFP and mKate.

## Quantitative analysis of CG nuclear volume and of CG ploidy by fluorescence in situ hybridisation (FISH) of chromosomes

The FISH protocol was performed as previously described⁴⁸ using oligonucleotide probes for chromosomes II and III labelled with 5'CY3 and FAM488 fluorescent dyes respectively (gift from R. Basto). FISH was performed in CNS expressing *NLS-LacZ* in CG and dissected in PBS at ALH0, ALH24, ALH48, ALH72, and ALH96. Briefly, dissected brains were fixed for 30 min in 4% formaldehyde prepared in PBS with 0.1% tween 20, washed three times/10 min in PBS, washed once 10 min in 2×SSCT (2×SSC (Sigma S6639) + 0.1% tween-20) and once in 2×SSCT 50% formamide (Sigma 47671). For the pre-hybridisation step, CNS were transferred to a new tube containing 2×SSCT 50% formamide pre-warmed at 92 °C and denatured 3 min at 92 °C. For the hybridisation step, the DNA probe (40–80 ng) was prepared in hybridisation buffer (20% dextran sulphate, 2×SSCT, 50% deionized formamide (Sigma F9037), 0.5 mg ml⁻¹ salmon sperm DNA) and denatured 3 min at 92 °C. Probes were added to the brains samples and hybridise 5 min at 92 °C followed by overnight hybridisation at 37 °C. Samples were washed with 60 °C pre-warmed 2×SSCT for 10 min, washed once 5 min in 2×SSCT at RT, and rinsed in PBS. CNS were mounted in Mowiol mounting medium and imaged as described above. Nuclei (*NLS-LacZ*) and chromosomes II and III (FISH signals) were quantified in randomly selected CG nuclei using adapted protocols for dots (chromosomes) inside objects (nuclei) detection in 3D images in Volocity 6.3 (Quorum technologies).

## Cortex glial membrane measurements

Each VNC was sampled with six cubes ($x = 150$ pixels; $y = 150$ pixels; $z = $ until the neuropile) devoid of trachea or nerve signal. NSC numbers within each cube were determined manually, and the CG membrane signal (using *Nrv2::GFP* as a proxy) was segmented using a HK-means thresholding (Icy v2.1.4.0, with $k=2$ or $k=4$, with $k$ kept constant between control and samples of the same experiment). The sum of selected pixels divided by NSC number defines the ratio of CG membrane to NSCs for each cube. A mean from the six cubes was calculated for each VNC, giving an estimation of the ratio of CG membrane per NSC within one brain. The different conditions were analysed via a one-way ANOVA.

## Quantification of individual NSC ensheathing

For each VNC the total number of NSCs was determined through HK-means segmentation in the corresponding channel (Icy v2.1.4.0) and corrected manually. When most of the NSCs did not appear individually encased (*dup RNAi*; *WASp RNAi*), the remaining number of NSCs that were still individually ensheathed by CG membrane was counted manually. For conditions in which most NSCs were still individually ensheathed (control; *mbc RNAi*), we recorded the number of chambers with more than one NSC, as well as the number of NSCs within each. This allowed us to subtract the number of NSCs not individually encased from the total NSC population. Ultimately, the ratio between the number of NSCs individually ensheathed and the total NSC population defines the percentage of individual NSC ensheathing. Taking in consideration the non-normal distribution of the control, the

significance of each condition compared to control was then determined through a generalised linear model (Binomial regression with a Bernoulli distribution).

## Statistics and reproducibility

Statistical tests used for each experiment and the number of biological samples (*n*) are stated in the figure legends. Statistical tests were performed using GraphPad Prism 7.0a. A minimum of two independent experiments were performed and a minimum total of 5 biological samples were observed, analysed or quantified except for Fig. 2b at ALH0; 3k; 5c; 6 (3 times, see main text); Supplementary Figs. 2b, d and 5a, b at ALH24. No statistical method was used to predetermine sample size. No data were excluded, except rare outliers detected through the ROUT method ($Q = 0.1\%$, GraphPad Prism 7.0a). The experiments were not randomised. The Investigators were not blinded to allocation during experiments and outcome assessment.

For all box and whisker plots, whiskers mark the minimum and maximum, the box includes the 25th–75th percentile, and the line in the box is the median. Individual values are superimposed.

## Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

## Data availability

The image datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request. Source data for all quantifications are provided as a Source data file. Source data are provided with this paper.

## Code availability

The python script used to perform a Monte-Carlo analysis for the analysis of FLIP data has been deposited on Zenodo, DOI: 10.5281/zenodo.6941645.

## References

1. Lander, A. D. et al. What does the concept of the stem cell niche really mean today? *BMC Biol.* **10**, 19 (2012).

2. Faigle, R. & Song, H. Signaling mechanisms regulating adult neural stem cells and neurogenesis. *Biochim. Biophys. Acta* **1830**, 2435–2448 (2013).

3. Stricker, S. H. & Götz, M. DNA-methylation: Master or slave of neural fate decisions? *Front. Neurosci.* **12**, 5 (2018).

4. Morante-Redolat, J. M. & Porlan, E. Neural stem cell regulation by adhesion molecules within the subependymal niche. *Front. Cell Dev. Biol.* https://doi.org/10.3389/fcell.2019.00102 (2019).

5. Paridaen, J. T. M. L. & Huttner, W. B. Neurogenesis during development of the vertebrate central nervous system. *EMBO Rep.* **15**, 351–364 (2014).

6. Bond, A. M., Ming, G. L. & Song, H. Adult mammalian neural stem cells and neurogenesis: Five decades later. *Cell Stem Cell* **17**, 385–395 (2015).

7. Götz, M., Nakafuku, M. & Petrik, D. Neurogenesis in the developing and adult brain—similarities and key differences. *Cold Spring Harb. Perspect. Biol.* **8**, a018853 (2016).

8. Martynoga, B. et al. Epigenomic enhancer annotation reveals a key role for NFIX in neural stem cell quiescence. *Genes Dev.* **27**, 1769–1786 (2013).

9. Bjornsson, C. S., Apostolopoulou, M., Tian, Y. & Temple, S. It takes a village: Constructing the neurogenic niche. *Dev. Cell* **32**, 435–446 (2015).

10. Silva-Vargas, V., Crouch, E. E. & Doetsch, F. Adult neural stem cells and their niche: A dynamic duo during homeostasis, regeneration, and aging. *Curr. Opin. Neurobiol.* **23**, 935–942 (2013).
enough to visualise diffusion of the converted Kaede form in the CG units, which are of large size.

Images were acquired as follows: one z-stack of 30–40 µm at 0.5–1 µm intervals before photoconversion (Pre-photoconversion), followed by 50 continuous acquisitions at the bleaching plane during the photoconversion (Photoconversion) and one z-stack of 30–40 µm at 1 µm intervals after photoconversion (Post- photoconversion). Images were subsequently analysed and processed using Fiji.

For visualising *Raepli-NLS* and Kaede simultaneously, we used spectral imaging (Zeiss Quasar 34 channels) to acquire and distinguish between mTFP1, GFP, mOrange, mRFP and mKate.

## Quantitative analysis of CG nuclear volume and of CG ploidy by fluorescence in situ hybridisation (FISH) of chromosomes

The FISH protocol was performed as previously described⁴⁸ using oligonucleotide probes for chromosomes II and III labelled with 5'CY3 and FAM488 fluorescent dyes respectively (gift from R. Basto). FISH was performed in CNS expressing *NLS-LacZ* in CG and dissected in PBS at ALHO, ALH24, ALH48, ALH72, and ALH96. Briefly, dissected brains were fixed for 30 min in 4% formaldehyde prepared in PBS with 0.1% tween 20, washed three times/10 min in PBS, washed once 10 min in 2×SSCT (2×SSC (Sigma S6639) + 0.1% tween-20) and once in 2×SSCT 50% formamide (Sigma 47671). For the pre-hybridisation step, CNS were transferred to a new tube containing 2×SSCT 50% formamide pre-warmed at 92 °C and denatured 3 min at 92 °C. For the hybridisation step, the DNA probe (40–80 ng) was prepared in hybridisation buffer (20% dextran sulphate, 2×SSCT, 50% deionized formamide (Sigma F9037), 0.5 mg ml⁻¹ salmon sperm DNA) and denatured 3 min at 92 °C. Probes were added to the brains samples and hybridise 5 min at 92 °C followed by overnight hybridisation at 37 °C. Samples were washed with 60 °C pre-warmed 2×SSCT for 10 min, washed once 5 min in 2×SSCT at RT, and rinsed in PBS. CNS were mounted in Mowiol mounting medium and imaged as described above. Nuclei (*NLS-LacZ*) and chromosomes II and III (FISH signals) were quantified in randomly selected CG nuclei using adapted protocols for dots (chromosomes) inside objects (nuclei) detection in 3D images in Volocity 6.3 (Quorum technologies).

## Cortex glial membrane measurements

Each VNC was sampled with six cubes ($x = 150$ pixels; $y = 150$ pixels; $z = $ until the neuropile) devoid of trachea or nerve signal. NSC numbers within each cube were determined manually, and the CG membrane signal (using *Nrv2::GFP* as a proxy) was segmented using a HK-means thresholding (Icy v2.1.4.0, with $k=2$ or $k=4$, with $k$ kept constant between control and samples of the same experiment). The sum of selected pixels divided by NSC number defines the ratio of CG membrane to NSCs for each cube. A mean from the six cubes was calculated for each VNC, giving an estimation of the ratio of CG membrane per NSC within one brain. The different conditions were analysed via a one-way ANOVA.

## Quantification of individual NSC ensheathing

For each VNC the total number of NSCs was determined through HK-means segmentation in the corresponding channel (Icy v2.1.4.0) and corrected manually. When most of the NSCs did not appear individually encased (*dup RNAi*; *WASp RNAi*), the remaining number of NSCs that were still individually ensheathed by CG membrane was counted manually. For conditions in which most NSCs were still individually ensheathed (control; *mbc RNAi*), we recorded the number of chambers with more than one NSC, as well as the number of NSCs within each. This allowed us to subtract the number of NSCs not individually encased from the total NSC population. Ultimately, the ratio between the number of NSCs individually ensheathed and the total NSC population defines the percentage of individual NSC ensheathing. Taking in consideration the non-normal distribution of the control, the

significance of each condition compared to control was then determined through a generalised linear model (Binomial regression with a Bernoulli distribution).

## Statistics and reproducibility

Statistical tests used for each experiment and the number of biological samples (*n*) are stated in the figure legends. Statistical tests were performed using GraphPad Prism 7.0a. A minimum of two independent experiments were performed and a minimum total of 5 biological samples were observed, analysed or quantified except for Fig. 2b at ALHO; 3k; 5c; 6 (3 times, see main text); Supplementary Figs. 2b, d and 5a, b at ALH24. No statistical method was used to predetermine sample size. No data were excluded, except rare outliers detected through the ROUT method ($Q = 0.1\%$, GraphPad Prism 7.0a). The experiments were not randomised. The Investigators were not blinded to allocation during experiments and outcome assessment.

For all box and whisker plots, whiskers mark the minimum and maximum, the box includes the 25th–75th percentile, and the line in the box is the median. Individual values are superimposed.

## Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

## Data availability

The image datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request. Source data for all quantifications are provided as a Source data file. Source data are provided with this paper.

## Code availability

The python script used to perform a Monte-Carlo analysis for the analysis of FLIP data has been deposited on Zenodo, DOI: 10.5281/zenodo.6941645.

## References

1. Lander, A. D. et al. What does the concept of the stem cell niche really mean today? *BMC Biol.* **10**, 19 (2012).

2. Faigle, R. & Song, H. Signaling mechanisms regulating adult neural stem cells and neurogenesis. *Biochim. Biophys. Acta* **1830**, 2435–2448 (2013).

3. Stricker, S. H. & Götz, M. DNA-methylation: Master or slave of neural fate decisions? *Front. Neurosci.* **12**, 5 (2018).

4. Morante-Redolat, J. M. & Porlan, E. Neural stem cell regulation by adhesion molecules within the subependymal niche. *Front. Cell Dev. Biol.* https://doi.org/10.3389/fcell.2019.00102 (2019).

5. Paridaen, J. T. M. L. & Huttner, W. B. Neurogenesis during development of the vertebrate central nervous system. *EMBO Rep.* **15**, 351–364 (2014).

6. Bond, A. M., Ming, G. L. & Song, H. Adult mammalian neural stem cells and neurogenesis: Five decades later. *Cell Stem Cell* **17**, 385–395 (2015).

7. Götz, M., Nakafuku, M. & Petrik, D. Neurogenesis in the developing and adult brain—similarities and key differences. *Cold Spring Harb. Perspect. Biol.* **8**, a018853 (2016).

8. Martynoga, B. et al. Epigenomic enhancer annotation reveals a key role for NFIX in neural stem cell quiescence. *Genes Dev.* **27**, 1769–1786 (2013).

9. Bjornsson, C. S., Apostolopoulou, M., Tian, Y. & Temple, S. It takes a village: Constructing the neurogenic niche. *Dev. Cell* **32**, 435–446 (2015).

10. Silva-Vargas, V., Crouch, E. E. & Doetsch, F. Adult neural stem cells and their niche: A dynamic duo during homeostasis, regeneration, and aging. *Curr. Opin. Neurobiol.* **23**, 935–942 (2013).
11. Conover, J. C. & Todd, K. L. Neuronal stem cell niches of the brain. *Biol. Eng. Stem Cell Niches* https://doi.org/10.1016/B978-0-12-802734-9-00006-8 (2017).

12. Lacar, B., Young, S. Z., Platel, J.-C. & Bordey, A. Gap junction-mediated calcium waves define communication networks among murine postnatal neural progenitor cells. *Eur. J. Neurosci.* **34**, 1895-1905 (2011).

13. Platel, J. C. & Bordey, A. The multifaceted subventricular zone astrocyte: From a metabolic and pro-neurogenic role to acting as a neural stem cell. *Neuroscience* **323**, 20-28 (2016).

14. Obernier, K. & Alvarez-Buylla, A. Neural stem cells: Origin, heterogeneity, and regulation in the adult mammalian brain. *Development* **146**, dev156059 (2019).

15. Conover, J. C. & Todd, K. L. Development and aging of a brain neural stem cell niche. *Exp. Gerontol.* **94**, 9-13 (2017).

16. Homem, C. C. F. & Knoblich, J. A. Drosophila neuroblasts: A model for stem cell biology. *Development* **139**, 4297-4310 (2012).

17. Mira, H. & Morante, J. Neurogenesis from embryo to adult—Lessons from flies and mice. *Front. Cell Dev. Biol.* **8**, 533 (2020).

18. Egger, B., Chell, J. M. & Brand, A. H. Insights into neural stem cell biology from flies. *Philos. Trans. R. Soc. L. B Biol. Sci.* **363**, 39-56 (2008).

19. Otsuki, L. & Brand, A. H. Cell cycle heterogeneity directs the timing of neural stem cell activation from quiescence. *Science* **360**, 99-102 (2018).

20. Britton, J. S. & Edgar, B. A. Environmental control of the cell cycle in Drosophila: Nutrition activates mitotic and endoreplicative cells by distinct mechanisms. *Development* **125**, 2149-2158 (1998).

21. Truman, J. W. & Bate, M. Spatial and temporal patterns of neurogenesis in the central nervous system of Drosophila melanogaster. *Dev. Biol.* **125**, 145-157 (1988).

22. Chell, J. M. & Brand, A. H. Nutrition-responsive glia control exit of neural stem cells from quiescence. *Cell* **143**, 1161-1173 (2010).

23. Sousa-Nunes, R., Yee, L. L. & Gould, A. P. Fat cells reactivate quiescent neuroblasts via TOR and glial insulin relays in Drosophila. *Nature* **471**, 508-512 (2011).

24. Spéder, P. & Brand, A. H. Gap junction proteins in the blood-brain barrier control nutrient-dependent reactivation of Drosophila neural stem cells. *Dev. Cell* https://doi.org/10.1016/j.devcel.2014.05.021 (2014).

25. Dumstrei, K., Wang, F. & Hartenstein, V. Role of DE-cadherin in neuroblast proliferation, neural morphogenesis, and axon tract formation in Drosophila larval brain development. *J. Neurosci.* **23**, 3325-3335 (2003).

26. Pereanu, W., Shy, D. & Hartenstein, V. Morphogenesis and proliferation of the larval brain glia in Drosophila. *Dev. Biol.* **283**, 191-203 (2005).

27. Spéder, P. & Brand, A. H. Systemic and local cues drive neural stem cell niche remodelling during neurogenesis in Drosophila. *Elife* **7**, 1-16 (2018).

28. Bailey, A. P. et al. Antioxidant role for lipid droplets in a stem cell niche of Drosophila. *Cell* **163**, 340-353 (2015).

29. Cheng, L. Y. et al. Anaplastic lymphoma kinase spares organ growth during nutrient restriction in Drosophila. *Cell* **146**, 435-447 (2011).

30. Morante, J., Vallejo, D. M., Desplan, C. & Dominguez, M. Conserved miR-8/miR-200 defines a glial niche that controls neuroepithelial expansion and neuroblast transition. *Dev. Cell* **27**, 174-187 (2013).

31. Plazaola-Sasieta, H. et al. Drosophila CLC-a is required in glia of the stem cell niche for proper neurogenesis and wiring of neural circuits. *Glia* **67**, 2374-2398 (2019).

32. Dong, Q. et al. Glial Hedgehog signalling and lipid metabolism regulate neural stem cell proliferation in Drosophila. *EMBO Rep.* https://doi.org/10.15252/embr.202052130 (2021).

33. de Torres-Jurado, A., Manzanero-Ortiz, S. & Carmena, A. Glial-secreted Netrins regulate Robo1/Rac1-Cdc42 signaling threshold

levels during Drosophila asymmetric neural stem/progenitor cell division. *Curr. Biol.* **32**, 2174-2188.e3 (2022).

34. Coutinho-Budd, J. C., Sheehan, A. E. & Freeman, M. R. The secreted neurotrophin spätzle 3 promotes glial morphogenesis and supports neuronal survival and function. *Genes Dev.* **31**, 2023-2038 (2017).

35. Read, R. D. Pvr receptor tyrosine kinase signaling promotes post-embryonic morphogenesis, and survival of glia and neural progenitor cells in drosophila. *Development* **145**, dev164285 (2018).

36. Yuan, X., Sipe, C. W., Suzawa, M., Bland, M. L. & Siegrist, S. E. Dilp-2-mediated PI3-kinase activation coordinates reactivation of quiescent neuroblasts with growth of their glial stem cell niche. *PLoS Biol.* **18**, 1-24 (2020).

37. Kiyoshi, C. & Zhou, M. Astrocyte syncytium: A functional reticular system in the brain. *Neural Regen. Res.* **14**, 595 (2019).

38. Ito, K., Urban, J. & Technau, G. Distribution, classification, and development of Drosophila glial cells in the late embryonic and early larval ventral nerve cord. *Dev. Genes Evol.* **204**, 284-307 (1995).

39. Beckervordersandforth, R. M., Rickert, C., Altenhein, B. & Technau, G. M. Subtypes of glial cells in the Drosophila embryonic ventral nerve cord as related to lineage and gene expression. *Mech. Dev.* **125**, 542-557 (2008).

40. Kanca, O., Caussinus, E., Denes, A. S., Percival-Smith, A. & Affolter, M. Raeppli: a whole-tissue labeling tool for live imaging of Drosophila development. *Development* **141**, 472-480 (2014).

41. Fox, D. T. & Duronio, R. J. Endoreplication and polyploidy: Insights into development and disease. *Development* **140**, 3-12 (2013).

42. Edgar, B. A., Zielke, N. & Gutierrez, C. Endocycles: A recurrent evolutionary innovation for post-mitotic cell growth. *Nat. Rev. Mol. Cell Biol. Vol.* https://doi.org/10.1038/nrm3756 (2014).

43. Orr-Weaver, T. L. When bigger is better: The role of polyploidy in organogenesis. *Trends Genet.* **31**, 307-315 (2015).

44. Avet-Rochex, A., Kaul, A. K., Gatt, A. P., McNeill, H. & Bateman, J. M. Concerted control of gliogenesis by InR/TOR and FGF signalling in the Drosophila post-embryonic brain. *Development* **139**, 2763-2772 (2012).

45. Zielke, N. et al. Fly-FUCCI: A versatile tool for studying cell proliferation in complex tissues. *Cell Rep.* **7**, 588-598 (2014).

46. Peterson, S. C., Samuelson, K. B. & Hanlon, S. L. Multi-scale organization of the Drosophila melanogaster genome. *Genes* **12**, 817 (2021).

47. Joyce, E. F., Erceg, J. & Wu, C. Pairing and anti-pairing: A balancing act in the diploid genome. *Curr. Opin. Genet. Dev.* **37**, 119-128 (2016). ting

48. Gogendeau, D. et al. Aneuploidy causes premature differentiation of neural and intestinal stem cells. *Nat. Commun.* **6**, 1-15 (2015).

49. Frawley, L. E. & Orr-Weaver, T. L. Polyploidy. *Curr. Biol.* **25**, R353-R358 (2015).

50. Øvrebø, J. I. & Edgar, B. A. Polyploidy in tissue homeostasis and regeneration. *Development* **145**, dev156034 (2018).

51. Piekny, A. J. & Maddox, A. S. The myriad roles of Anillin during cytokinesis. *Semin. Cell Dev. Biol.* **21**, 881-891 (2010).

52. Hu, C. K., Coughlin, M. & Mitchison, T. J. Midbody assembly and its regulation during cytokinesis. *Mol. Biol. Cell* **23**, 1024-1034 (2012).

53. Whittaker, A. J., Royzman, I. & Orr-Weaver, T. L. Drosophila double parked: A conserved, essential replication protein that colocalizes with the origin recognition complex and links DNA replication with mitosis and the down-regulation of S phase transcripts. *Genes Dev.* **14**, 1765 (2000).

54. Unhavaithaya, Y. & Orr-Weaver, T. L. Polyploidization of glia in neural development links tissue growth to blood-brain barrier integrity. *Genes Dev.* **26**, 31-36 (2012).

55. Hong, A. et al. The cyclin-dependent kinase inhibitor Dacapo promotes replication licensing during Drosophila endocycles. *EMBO J.* **26**, 2071-2082 (2007).
11. Conover, J. C. & Todd, K. L. Neuronal stem cell niches of the brain. *Biol. Eng. Stem Cell Niches* https://doi.org/10.1016/B978-0-12-802734-9-00006-8 (2017).

12. Lacar, B., Young, S. Z., Platel, J.-C. & Bordey, A. Gap junction-mediated calcium waves define communication networks among murine postnatal neural progenitor cells. *Eur. J. Neurosci.* **34**, 1895-1905 (2011).

13. Platel, J. C. & Bordey, A. The multifaceted subventricular zone astrocyte: From a metabolic and pro-neurogenic role to acting as a neural stem cell. *Neuroscience* **323**, 20-28 (2016).

14. Obernier, K. & Alvarez-Buylla, A. Neural stem cells: Origin, heterogeneity, and regulation in the adult mammalian brain. *Development* **146**, dev156059 (2019).

15. Conover, J. C. & Todd, K. L. Development and aging of a brain neural stem cell niche. *Exp. Gerontol.* **94**, 9-13 (2017).

16. Homem, C. C. F. & Knoblich, J. A. Drosophila neuroblasts: A model for stem cell biology. *Development* **139**, 4297-4310 (2012).

17. Mira, H. & Morante, J. Neurogenesis from embryo to adult—Lessons from flies and mice. *Front. Cell Dev. Biol.* **8**, 533 (2020).

18. Egger, B., Chell, J. M. & Brand, A. H. Insights into neural stem cell biology from flies. *Philos. Trans. R. Soc. L. B Biol. Sci.* **363**, 39-56 (2008).

19. Otsuki, L. & Brand, A. H. Cell cycle heterogeneity directs the timing of neural stem cell activation from quiescence. *Science* **360**, 99-102 (2018).

20. Britton, J. S. & Edgar, B. A. Environmental control of the cell cycle in Drosophila: Nutrition activates mitotic and endoreplicative cells by distinct mechanisms. *Development* **125**, 2149-2158 (1998).

21. Truman, J. W. & Bate, M. Spatial and temporal patterns of neurogenesis in the central nervous system of Drosophila melanogaster. *Dev. Biol.* **125**, 145-157 (1988).

22. Chell, J. M. & Brand, A. H. Nutrition-responsive glia control exit of neural stem cells from quiescence. *Cell* **143**, 1161-1173 (2010).

23. Sousa-Nunes, R., Yee, L. L. & Gould, A. P. Fat cells reactivate quiescent neuroblasts via TOR and glial insulin relays in Drosophila. *Nature* **471**, 508-512 (2011).

24. Spéder, P. & Brand, A. H. Gap junction proteins in the blood-brain barrier control nutrient-dependent reactivation of Drosophila neural stem cells. *Dev. Cell* https://doi.org/10.1016/j.devcel.2014.05.021 (2014).

25. Dumstrei, K., Wang, F. & Hartenstein, V. Role of DE-cadherin in neuroblast proliferation, neural morphogenesis, and axon tract formation in Drosophila larval brain development. *J. Neurosci.* **23**, 3325-3335 (2003).

26. Pereanu, W., Shy, D. & Hartenstein, V. Morphogenesis and proliferation of the larval brain glia in Drosophila. *Dev. Biol.* **283**, 191-203 (2005).

27. Spéder, P. & Brand, A. H. Systemic and local cues drive neural stem cell niche remodelling during neurogenesis in Drosophila. *Elife* **7**, 1-16 (2018).

28. Bailey, A. P. et al. Antioxidant role for lipid droplets in a stem cell niche of Drosophila. *Cell* **163**, 340-353 (2015).

29. Cheng, L. Y. et al. Anaplastic lymphoma kinase spares organ growth during nutrient restriction in Drosophila. *Cell* **146**, 435-447 (2011).

30. Morante, J., Vallejo, D. M., Desplan, C. & Dominguez, M. Conserved miR-8/miR-200 defines a glial niche that controls neuroepithelial expansion and neuroblast transition. *Dev. Cell* **27**, 174-187 (2013).

31. Plazaola-Sasieta, H. et al. Drosophila CLC-a is required in glia of the stem cell niche for proper neurogenesis and wiring of neural circuits. *Glia* **67**, 2374-2398 (2019).

32. Dong, Q. et al. Glial Hedgehog signalling and lipid metabolism regulate neural stem cell proliferation in Drosophila. *EMBO Rep.* https://doi.org/10.15252/embr.202052130 (2021).

33. de Torres-Jurado, A., Manzanero-Ortiz, S. & Carmena, A. Glial-secreted Netrins regulate Robo1/Rac1-Cdc42 signaling threshold

levels during Drosophila asymmetric neural stem/progenitor cell division. *Curr. Biol.* **32**, 2174-2188.e3 (2022).

34. Coutinho-Budd, J. C., Sheehan, A. E. & Freeman, M. R. The secreted neurotrophin spätzle 3 promotes glial morphogenesis and supports neuronal survival and function. *Genes Dev.* **31**, 2023-2038 (2017).

35. Read, R. D. Pvr receptor tyrosine kinase signaling promotes post-embryonic morphogenesis, and survival of glia and neural progenitor cells in drosophila. *Development* **145**, dev164285 (2018).

36. Yuan, X., Sipe, C. W., Suzawa, M., Bland, M. L. & Siegrist, S. E. Dilp-2-mediated PI3-kinase activation coordinates reactivation of quiescent neuroblasts with growth of their glial stem cell niche. *PLoS Biol.* **18**, 1-24 (2020).

37. Kiyoshi, C. & Zhou, M. Astrocyte syncytium: A functional reticular system in the brain. *Neural Regen. Res.* **14**, 595 (2019).

38. Ito, K., Urban, J. & Technau, G. Distribution, classification, and development of Drosophila glial cells in the late embryonic and early larval ventral nerve cord. *Dev. Genes Evol.* **204**, 284-307 (1995).

39. Beckervordersandforth, R. M., Rickert, C., Altenhein, B. & Technau, G. M. Subtypes of glial cells in the Drosophila embryonic ventral nerve cord as related to lineage and gene expression. *Mech. Dev.* **125**, 542-557 (2008).

40. Kanca, O., Caussinus, E., Denes, A. S., Percival-Smith, A. & Affolter, M. Raeppli: a whole-tissue labeling tool for live imaging of Drosophila development. *Development* **141**, 472-480 (2014).

41. Fox, D. T. & Duronio, R. J. Endoreplication and polyploidy: Insights into development and disease. *Development* **140**, 3-12 (2013).

42. Edgar, B. A., Zielke, N. & Gutierrez, C. Endocycles: A recurrent evolutionary innovation for post-mitotic cell growth. *Nat. Rev. Mol. Cell Biol. Vol.* https://doi.org/10.1038/nrm3756 (2014).

43. Orr-Weaver, T. L. When bigger is better: The role of polyploidy in organogenesis. *Trends Genet.* **31**, 307-315 (2015).

44. Avet-Rochex, A., Kaul, A. K., Gatt, A. P., McNeill, H. & Bateman, J. M. Concerted control of gliogenesis by InR/TOR and FGF signalling in the Drosophila post-embryonic brain. *Development* **139**, 2763-2772 (2012).

45. Zielke, N. et al. Fly-FUCCI: A versatile tool for studying cell proliferation in complex tissues. *Cell Rep.* **7**, 588-598 (2014).

46. Peterson, S. C., Samuelson, K. B. & Hanlon, S. L. Multi-scale organization of the Drosophila melanogaster genome. *Genes* **12**, 817 (2021).

47. Joyce, E. F., Erceg, J. & Wu, C. Pairing and anti-pairing: A balancing act in the diploid genome. *Curr. Opin. Genet. Dev.* **37**, 119-128 (2016). ting

48. Gogendeau, D. et al. Aneuploidy causes premature differentiation of neural and intestinal stem cells. *Nat. Commun.* **6**, 1-15 (2015).

49. Frawley, L. E. & Orr-Weaver, T. L. Polyploidy. *Curr. Biol.* **25**, R353-R358 (2015).

50. Øvrebø, J. I. & Edgar, B. A. Polyploidy in tissue homeostasis and regeneration. *Development* **145**, dev156034 (2018).

51. Piekny, A. J. & Maddox, A. S. The myriad roles of Anillin during cytokinesis. *Semin. Cell Dev. Biol.* **21**, 881-891 (2010).

52. Hu, C. K., Coughlin, M. & Mitchison, T. J. Midbody assembly and its regulation during cytokinesis. *Mol. Biol. Cell* **23**, 1024-1034 (2012).

53. Whittaker, A. J., Royzman, I. & Orr-Weaver, T. L. Drosophila double parked: A conserved, essential replication protein that colocalizes with the origin recognition complex and links DNA replication with mitosis and the down-regulation of S phase transcripts. *Genes Dev.* **14**, 1765 (2000).

54. Unhavaithaya, Y. & Orr-Weaver, T. L. Polyploidization of glia in neural development links tissue growth to blood-brain barrier integrity. *Genes Dev.* **26**, 31-36 (2012).

55. Hong, A. et al. The cyclin-dependent kinase inhibitor Dacapo promotes replication licensing during Drosophila endocycles. *EMBO J.* **26**, 2071-2082 (2007).
56. Lippincott-Schwartz, J., Altan-Bonnet, N. & Patterson, G. H. Photo-bleaching and photoactivation: Following protein dynamics in living cells. *Nat. Rev. Mol. Cell Biol.* **4**, 6–14 (2003).

57. Miyawaki, A. Proteins on the move: Insights gained from fluorescent protein technologies. *Nat. Rev. Mol. Cell Biol.* **12**, 656–668 (2011).

58. Mavrakis, M., Rikhy, R. & Lippincott-Schwartz, J. Plasma membrane polarity and compartmentalization are established before cellularization in the fly embryo. *Dev. Cell* **16**, 93–104 (2009).

59. Peterman, E. & Prekeris, R. The postmitotic midbody: Regulating polarity, stemness, and proliferation. *J. Cell Biol.* **218**, 3903–3911 (2019).

60. Haglund, K., Nezis, I. P. & Stenmark, H. Structure and functions of stable intercellular bridges formed by incomplete cytokinesis during development. *Commun. Integr. Biol.* **4**, 1 (2011).

61. McLean, P. F. & Cooley, L. Bridging the divide: Illuminating the path of intercellular exchange through ring canals. *Fly* **8**, 13–18 (2014).

62. Eikenes, Å. H. et al. ALIX and ESCRT-III coordinately control cytoskeletal abscission during germline stem cell division in vivo. *PLoS Genet.* **11**, e1004904 (2015).

63. Kramerova, I. A. & Kramerov, A. A. Mucinoprotein is a universal constituent of stable intercellular bridges in Drosophila melanogaster germ line and somatic cells. *Dev. Dyn.* **216**, 349–360 (1999).

64. Adams, R. R., Tavares, A. A. M., Salzberg, A., Bellen, H. J. & Glover, D. M. pavarotti encodes a kinesin-like protein required to organize the central spindle and contractile ring for cytokinesis. *Genes Dev.* **12**, 1483–1494 (1998).

65. Nemet, I., Ropelewski, P. & Imanishi, Y. Applications of photo-transformable fluorescent proteins for tracking the dynamics of cellular components. *Photochem. Photobiol. Sci.* **14**, 1787–1806 (2015).

66. Ando, R., Hama, H., Yamamoto-Hino, M., Mizuno, H. & Miyawaki, A. An optical marker based on the UV-induced green-to-red photo-conversion of a fluorescent protein. *Proc. Natl Acad. Sci. USA* **99**, 12651–12656 (2002).

67. Zito, F., Lampiasi, N., Kireev, I. & Russo, R. United we stand: Adhesion and molecular mechanisms driving cell fusion across species. *Eur. J. Cell Biol.* **95**, 552–562 (2016).

68. Brukman, N. G., Uygur, B., Podbilewicz, B. & Chernomordik, L. V. How cells fuse. *J. Cell Biol.* **218**, 1436–1451 (2019).

69. Hernández, J. M. & Podbilewicz, B. The hallmarks of cell-cell fusion. *Development* **144**, 4481–4495 (2017).

70. Kim, J. H. & Chen, E. H. The fusogenic synapse at a glance. *J. Cell Sci.* **132**, jcs213124 (2019).

71. Bosch, J. A., Tran, N. H. & Hariharan, I. K. CoinFLP: A system for efficient mosaic screening and for visualizing clonal boundaries in Drosophila. *Development* **142**, 597–606 (2015).

72. Abmayr, S. M. & Pavlath, G. K. Myoblast fusion: Lessons from flies and mice. *Development* **139**, 641–656 (2012).

73. Deng, S., Azevedo, M. & Baylies, M. Acting on identity: Myoblast fusion and the formation of the syncytial muscle fiber. *Semin. Cell Dev. Biol.* **72**, 45–55 (2017).

74. Lee, D. M. & Chen, E. H. Drosophila myoblast fusion: Invasion and resistance for the ultimate union. *Annu. Rev. Genet.* **53**, 67–91 (2019).

75. Richardson, B. E., Nowak, S. J. & Baylies, M. K. Myoblast fusion in fly and vertebrates: New genes, new processes, and new perspectives. *Traffic* **9**, 1050 (2008).

76. Haralalka, S. et al. Asymmetric Mbc, active Rac1 and F-actin foci in the fusioncompetent myoblasts during myoblast fusion in Drosophila. *Development* **138**, 1551–1562 (2011).

77. Venken, K. J. T. et al. MiMIC: A highly versatile transposon insertion resource for engineering Drosophila melanogaster genes. *Nat. Methods* **8**, 737–747 (2011).

78. Nagarkar-Jaiswal, S. et al. A library of MiMICs allows tagging of genes and reversible, spatial and temporal knockdown of proteins in Drosophila. *Elife* **2015**, 1–28 (2015).

79. Bosch, J. A., Sumabat, T. M. & Hariharan, I. K. Persistence of RNAi-mediated knockdown in Drosophila complicates mosaic analysis yet enables highly sensitive lineage tracing. *Genetics* **203**, 109–118 (2016).

80. Evans, C. J. et al. G-TRACE: Rapid Gal4-based cell lineage analysis in Drosophila. *Nat. Methods* **6**, 603–605 (2009).

81. Spéder, P. & Brand, A. H. Systemic and local cues drive neural stem cell niche remodelling during neurogenesis in Drosophila. *Elife* **7**, e30413 (2018).

82. Peterson, N. G. & Fox, D. T. Communal living: The role of polyploidy and syncytia in tissue biology. *Chromosom. Res.* **29**, 245–260 (2021).

83. Zielke, N., Edgar, B. A. & DePamphilis, M. L. Endoreplication. *Cold Spring Harb. Perspect. Biol.* **5**, a012948 (2013).

84. Greenbaum, M. P., Iwamori, T., Buchold, G. M. & Matzuk, M. M. Germ cell intercellular bridges. *Cold Spring Harb. Perspect. Biol.* **3**, 1–18 (2011).

85. Huynh, J.-R. Fusome as a Cell-Cell Communication Channel of Drosophila Ovarian Cyst. *Cell-Cell Channels*, (eds Baluska, F., Volkmann, D. & Barlow, P. W.) pp 217–235. Landes Biosciences. (Springer New York, 2006).

86. Willkomm, L. & Bloch, W. Cell Fusion: Overviews and Methods: Second Edition Vol. **1313**, 1–19 (Springer New York, 2015).

87. Peterson, N. G. et al. Cytoplasmic sharing through apical membrane remodeling. *Elife* **9**, 1–50 (2020).

88. Giaume, C., Koulakoff, A., Roux, L., Holcman, D. & Rouach, N. Astroglial networks: A step further in neuroglial and gliovascular interactions. *Nat. Rev. Neurosci.* **11**, 87–99 (2010).

89. Kiyoshi, C. M. & Zhou, M. Astrocyte syncytium: A functional reticular system in the brain. *Neural Regeneration Res.* **14**, 595–596 (2019).

90. Baldwin, K. T. et al. HepaCAM controls astrocyte self-organization and coupling. *Neuron* **109**, 2427–2442.e10 (2021).

91. Zhou, B., Zuo, Y. & Jiang, R. Astrocyte morphology: Diversity, plasticity, and role in neurological diseases. *CNS Neurosci. Ther.* **25**, 665 (2019).

92. Dias, M. C., Mapunda, J. A., Vladymyrov, M. & Engelhardt, B. Structure and junctional complexes of endothelial, epithelial and glial brain barriers. *Int. J. Mol. Sci.* **20**, 5372 (2019).

93. Pfeiffer, B. D. et al. Tools for neuroanatomy and neurogenetics in Drosophila. *Proc. Natl Acad. Sci. USA* **105**, 9715–9720 (2008).

94. Petersen, L. K. & Stowers, R. S. A Gateway MultiSite recombination cloning toolkit. *PLoS One* **6**, e24531 (2011).

95. Böttcher, R. et al. Efficient chromosomal gene modification with CRISPR/cas9 and PCR-based homologous recombination donors in cultured Drosophila cells. *Nucleic Acids Res.* **42**, e89 (2014).

96. Benmimoun, B. et al. An original infection model identifies host lipoprotein import as a route for blood-brain barrier crossing. *Nat. Commun.* **11**, 1–18 (2020).

97. Erickson, M. R. S., Galletta, B. J. & Abmayr, S. M. Drosophila myoblast city encodes a conserved protein that is essential for myoblast fusion, dorsal closure, and cytoskeletal organization. *J. Cell Biol.* **138**, 589–603 (1997).

98. Galletta, B. J., Chakravarti, M., Banerjee, R. & Abmayr, S. M. SNS: adhesive properties, localization requirements and ectodomain dependence in S2 cells and embryonic myoblasts. *Mech. Dev.* **121**, 1455–1468 (2004).

99. AA, K. et al. Mucin-type glycoprotein from Drosophila melanogaster embryonic cells: Characterization of carbohydrate component. *FEBS Lett.* **378**, 213–218 (1996).
56. Lippincott-Schwartz, J., Altan-Bonnet, N. & Patterson, G. H. Photo-bleaching and photoactivation: Following protein dynamics in living cells. *Nat. Rev. Mol. Cell Biol.* **4**, 6–14 (2003).

57. Miyawaki, A. Proteins on the move: Insights gained from fluorescent protein technologies. *Nat. Rev. Mol. Cell Biol.* **12**, 656–668 (2011).

58. Mavrakis, M., Rikhy, R. & Lippincott-Schwartz, J. Plasma membrane polarity and compartmentalization are established before cellularization in the fly embryo. *Dev. Cell* **16**, 93–104 (2009).

59. Peterman, E. & Prekeris, R. The postmitotic midbody: Regulating polarity, stemness, and proliferation. *J. Cell Biol.* **218**, 3903–3911 (2019).

60. Haglund, K., Nezis, I. P. & Stenmark, H. Structure and functions of stable intercellular bridges formed by incomplete cytokinesis during development. *Commun. Integr. Biol.* **4**, 1 (2011).

61. McLean, P. F. & Cooley, L. Bridging the divide: Illuminating the path of intercellular exchange through ring canals. *Fly* **8**, 13–18 (2014).

62. Eikenes, Å. H. et al. ALIX and ESCRT-III coordinately control cytoskeletal abscission during germline stem cell division in vivo. *PLoS Genet.* **11**, e1004904 (2015).

63. Kramerova, I. A. & Kramerov, A. A. Mucinoprotein is a universal constituent of stable intercellular bridges in Drosophila melanogaster germ line and somatic cells. *Dev. Dyn.* **216**, 349–360 (1999).

64. Adams, R. R., Tavares, A. A. M., Salzberg, A., Bellen, H. J. & Glover, D. M. pavarotti encodes a kinesin-like protein required to organize the central spindle and contractile ring for cytokinesis. *Genes Dev.* **12**, 1483–1494 (1998).

65. Nemet, I., Ropelewski, P. & Imanishi, Y. Applications of photo-transformable fluorescent proteins for tracking the dynamics of cellular components. *Photochem. Photobiol. Sci.* **14**, 1787–1806 (2015).

66. Ando, R., Hama, H., Yamamoto-Hino, M., Mizuno, H. & Miyawaki, A. An optical marker based on the UV-induced green-to-red photo-conversion of a fluorescent protein. *Proc. Natl Acad. Sci. USA* **99**, 12651–12656 (2002).

67. Zito, F., Lampiasi, N., Kireev, I. & Russo, R. United we stand: Adhesion and molecular mechanisms driving cell fusion across species. *Eur. J. Cell Biol.* **95**, 552–562 (2016).

68. Brukman, N. G., Uygur, B., Podbilewicz, B. & Chernomordik, L. V. How cells fuse. *J. Cell Biol.* **218**, 1436–1451 (2019).

69. Hernández, J. M. & Podbilewicz, B. The hallmarks of cell-cell fusion. *Development* **144**, 4481–4495 (2017).

70. Kim, J. H. & Chen, E. H. The fusogenic synapse at a glance. *J. Cell Sci.* **132**, jcs213124 (2019).

71. Bosch, J. A., Tran, N. H. & Hariharan, I. K. CoinFLP: A system for efficient mosaic screening and for visualizing clonal boundaries in Drosophila. *Development* **142**, 597–606 (2015).

72. Abmayr, S. M. & Pavlath, G. K. Myoblast fusion: Lessons from flies and mice. *Development* **139**, 641–656 (2012).

73. Deng, S., Azevedo, M. & Baylies, M. Acting on identity: Myoblast fusion and the formation of the syncytial muscle fiber. *Semin. Cell Dev. Biol.* **7**, 45–55 (2017).

74. Lee, D. M. & Chen, E. H. Drosophila myoblast fusion: Invasion and resistance for the ultimate union. *Annu. Rev. Genet.* **53**, 67–91 (2019).

75. Richardson, B. E., Nowak, S. J. & Baylies, M. K. Myoblast fusion in fly and vertebrates: New genes, new processes, and new perspectives. *Traffic* **9**, 1050 (2008).

76. Haralalka, S. et al. Asymmetric Mbc, active Rac1 and F-actin foci in the fusioncompetent myoblasts during myoblast fusion in Drosophila. *Development* **138**, 1551–1562 (2011).

77. Venken, K. J. T. et al. MiMIC: A highly versatile transposon insertion resource for engineering Drosophila melanogaster genes. *Nat. Methods* **8**, 737–747 (2011).

78. Nagarkar-Jaiswal, S. et al. A library of MiMICs allows tagging of genes and reversible, spatial and temporal knockdown of proteins in Drosophila. *Elife* **2015**, 1–28 (2015).

79. Bosch, J. A., Sumabat, T. M. & Hariharan, I. K. Persistence of RNAi-mediated knockdown in Drosophila complicates mosaic analysis yet enables highly sensitive lineage tracing. *Genetics* **203**, 109–118 (2016).

80. Evans, C. J. et al. G-TRACE: Rapid Gal4-based cell lineage analysis in Drosophila. *Nat. Methods* **6**, 603–605 (2009).

81. Spéder, P. & Brand, A. H. Systemic and local cues drive neural stem cell niche remodelling during neurogenesis in Drosophila. *Elife* **7**, e30413 (2018).

82. Peterson, N. G. & Fox, D. T. Communal living: The role of polyploidy and syncytia in tissue biology. *Chromosom. Res.* **29**, 245–260 (2021).

83. Zielke, N., Edgar, B. A. & DePamphilis, M. L. Endoreplication. *Cold Spring Harb. Perspect. Biol.* **5**, a012948 (2013).

84. Greenbaum, M. P., Iwamori, T., Buchold, G. M. & Matzuk, M. M. Germ cell intercellular bridges. *Cold Spring Harb. Perspect. Biol.* **3**, 1–18 (2011).

85. Huynh, J.-R. Fusome as a Cell-Cell Communication Channel of Drosophila Ovarian Cyst. *Cell-Cell Channels*, (eds Baluska, F., Volkmann, D. & Barlow, P. W.) pp 217–235. Landes Biosciences. (Springer New York, 2006).

86. Willkomm, L. & Bloch, W. Cell Fusion: Overviews and Methods: Second Edition Vol. **1313**, 1–19 (Springer New York, 2015).

87. Peterson, N. G. et al. Cytoplasmic sharing through apical membrane remodeling. *Elife* **9**, 1–50 (2020).

88. Giaume, C., Koulakoff, A., Roux, L., Holcman, D. & Rouach, N. Astroglial networks: A step further in neuroglial and gliovascular interactions. *Nat. Rev. Neurosci.* **11**, 87–99 (2010).

89. Kiyoshi, C. M. & Zhou, M. Astrocyte syncytium: A functional reticular system in the brain. *Neural Regeneration Res.* **14**, 595–596 (2019).

90. Baldwin, K. T. et al. HepaCAM controls astrocyte self-organization and coupling. *Neuron* **109**, 2427–2442.e10 (2021).

91. Zhou, B., Zuo, Y. & Jiang, R. Astrocyte morphology: Diversity, plasticity, and role in neurological diseases. *CNS Neurosci. Ther.* **25**, 665 (2019).

92. Dias, M. C., Mapunda, J. A., Vladymyrov, M. & Engelhardt, B. Structure and junctional complexes of endothelial, epithelial and glial brain barriers. *Int. J. Mol. Sci.* **20**, 5372 (2019).

93. Pfeiffer, B. D. et al. Tools for neuroanatomy and neurogenetics in Drosophila. *Proc. Natl Acad. Sci. USA* **105**, 9715–9720 (2008).

94. Petersen, L. K. & Stowers, R. S. A Gateway MultiSite recombination cloning toolkit. *PLoS One* **6**, e24531 (2011).

95. Böttcher, R. et al. Efficient chromosomal gene modification with CRISPR/cas9 and PCR-based homologous recombination donors in cultured Drosophila cells. *Nucleic Acids Res.* **42**, e89 (2014).

96. Benmimoun, B. et al. An original infection model identifies host lipoprotein import as a route for blood-brain barrier crossing. *Nat. Commun.* **11**, 1–18 (2020).

97. Erickson, M. R. S., Galletta, B. J. & Abmayr, S. M. Drosophila myoblast city encodes a conserved protein that is essential for myoblast fusion, dorsal closure, and cytoskeletal organization. *J. Cell Biol.* **138**, 589–603 (1997).

98. Galletta, B. J., Chakravarti, M., Banerjee, R. & Abmayr, S. M. SNS: adhesive properties, localization requirements and ectodomain dependence in S2 cells and embryonic myoblasts. *Mech. Dev.* **121**, 1455–1468 (2004).

99. AA, K. et al. Mucin-type glycoprotein from Drosophila melanogaster embryonic cells: Characterization of carbohydrate component. *FEBS Lett.* **378**, 213–218 (1996).
## Acknowledgements

We thank the Abmayr and Workman labs for the generous gift of the anti-Mbc and anti-Kirre antibodies; the Basto lab for the DNA FISH probes and the rabbit anti-Dpn; AA Kramerov for the gift of the anti-Mucin-D antibody; Steven Stowers and Matthias Landgraf for sharing plasmids for Multisite Gateway cloning; M'hamed Khalil Mazouni for the sequence of the FRT-STOP-FRT cassette; the Freeman lab for *almr-GAL4*; James Skeath for the Dpn plasmid; the Bloomington Drosophila Stock Centre and the Vienna Drosophila Research Centre for RNAi lines. We are grateful to Mateusz Trylinski for help with Fiji scripts and discussions for ploidy count; to Jean-Yves Tinevez (Image Analysis Hub, Institut Pasteur) and Francis Murphy for help with image processing and FLIP quantification; and to Elise Jacquemet (Biostatistics Hub, Institut Pasteur) for help with statistical analysis. We thank Audrey Salles of the UTechS PBI for the acquisition of SIM images. Julie Marc generated part of Fig. 1e. Laurence Arbogast built the *cyp4g15-FLP*, *cyp4g15-mtdTomato*, and *cyp4g15-FRT-STOP-FRT-LexA* constructs. We thank Jean-René Huynh, Juliette Mathieu and Romain Levayer for critical reading of the manuscript. This work has been funded by a starting package from Institut Pasteur/LabEx Revive, a JCJC grant from Agence Nationale de la Recherche (Neur-aSteNic, ANR-17-CE13-0010-01) and a Projet Fondation ARC from Fondation ARC pour la Recherche sur le Cancer to P.S. M.A.R. has been supported by a LabEx Revive postdoctoral fellowship and B.D. by an Amgen fellowship. UTechS PBI is part of the France-BioImaging infrastructure network (FBI) supported by the French National Research Agency (ANR-10-INBS-04; Investments for the Future), and acknowledges support from Institut Pasteur, ANR/FBI, the Région Ile-de-France (grant on infectious diseases DIM1HEALTH), and the French Government Investissement d'Avenir Programme—Laboratoire d'Excellence 'Integrative Biology of Emerging Infectious Diseases' (ANR-10-LABX-62-IBEID) for the use of ELYRA7 microscope (Carl Zeiss).

## Author contributions

M.A.R. performed all experiments, except for: Figs. 4g–h, 5f, g, 8b, c and Supplementary Figs. 4d, 5g, 9b, c performed by D.B.; Fig. 4c, d, and Supplementary Fig. 2e, f performed by B.D. under the supervision of M.A.R.; Parts of Fig. 2a and Supplementary Fig. 2h performed by J.M. under the supervision of P.S.; Figs. 2e–i, 3l–n, 4f, 9 and Supplementary

Figs. 2b, g, 3d–f, 4a, b, 10a, b performed by P.S. M.A.R., B.D., and P.S. quantified and analysed the data. M.A.R. and P.S. wrote the article and made the figures.

## Competing interests

The authors declare no competing interests.

## Additional information

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-32685-3.

**Correspondence** and requests for materials should be addressed to Pauline Spéder.

**Peer review information** *Nature Communications* thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

**Reprints and permission information** is available at http://www.nature.com/reprints

**Publisher's note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

© The Author(s) 2022
## Acknowledgements

We thank the Abmayr and Workman labs for the generous gift of the anti-Mbc and anti-Kirre antibodies; the Basto lab for the DNA FISH probes and the rabbit anti-Dpn; AA Kramerov for the gift of the anti-Mucin-D antibody; Steven Stowers and Matthias Landgraf for sharing plasmids for Multisite Gateway cloning; M'hamed Khalil Mazouni for the sequence of the FRT-STOP-FRT cassette; the Freeman lab for *almr-GAL4*; James Skeath for the Dpn plasmid; the Bloomington Drosophila Stock Centre and the Vienna Drosophila Research Centre for RNAi lines. We are grateful to Mateusz Trylinski for help with Fiji scripts and discussions for ploidy count; to Jean-Yves Tinevez (Image Analysis Hub, Institut Pasteur) and Francis Murphy for help with image processing and FLIP quantification; and to Elise Jacquemet (Biostatistics Hub, Institut Pasteur) for help with statistical analysis. We thank Audrey Salles of the UTechS PBI for the acquisition of SIM images. Julie Marc generated part of Fig. 1e. Laurence Arbogast built the *cyp4g15-FLP*, *cyp4g15-mtdTomato*, and *cyp4g15-FRT-STOP-FRT-LexA* constructs. We thank Jean-René Huynh, Juliette Mathieu and Romain Levayer for critical reading of the manuscript. This work has been funded by a starting package from Institut Pasteur/LabEx Revive, a JCJC grant from Agence Nationale de la Recherche (Neur-aSteNic, ANR-17-CE13-0010-01) and a Projet Fondation ARC from Fondation ARC pour la Recherche sur le Cancer to P.S. M.A.R. has been supported by a LabEx Revive postdoctoral fellowship and B.D. by an Amgen fellowship. UTechS PBI is part of the France-BioImaging infrastructure network (FBI) supported by the French National Research Agency (ANR-10-INBS-04; Investments for the Future), and acknowledges support from Institut Pasteur, ANR/FBI, the Région Ile-de-France (grant on infectious diseases DIM1HEALTH), and the French Government Investissement d'Avenir Programme—Laboratoire d'Excellence 'Integrative Biology of Emerging Infectious Diseases' (ANR-10-LABX-62-IBEID) for the use of ELYRA7 microscope (Carl Zeiss).

## Author contributions

M.A.R. performed all experiments, except for: Figs. 4g–h, 5f, g, 8b, c and Supplementary Figs. 4d, 5g, 9b, c performed by D.B.; Fig. 4c, d, and Supplementary Fig. 2e, f performed by B.D. under the supervision of M.A.R.; Parts of Fig. 2a and Supplementary Fig. 2h performed by J.M. under the supervision of P.S.; Figs. 2e–i, 3l–n, 4f, 9 and Supplementary

Figs. 2b, g, 3d–f, 4a, b, 10a, b performed by P.S. M.A.R., B.D., and P.S. quantified and analysed the data. M.A.R. and P.S. wrote the article and made the figures.

## Competing interests

The authors declare no competing interests.

## Additional information

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-32685-3.

**Correspondence** and requests for materials should be addressed to Pauline Spéder.

**Peer review information** *Nature Communications* thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

**Reprints and permission information** is available at http://www.nature.com/reprints

**Publisher's note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

© The Author(s) 2022