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# Asymmetric microtubule nucleation from Golgi stacks promotes opposite microtubule polarity in axons and dendrites

Akila Yagoubat, Paul T Conduit

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Akila Yagoubat, Paul T Conduit. Asymmetric microtubule nucleation from Golgi stacks promotes opposite microtubule polarity in axons and dendrites. Current Biology, 2025. hal-04970298

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Asymmetric microtubule nucleation from Golgi stacks promotes
opposite microtubule polarity in axons and dendrites

Akila Yagoubat¹ and Paul T. Conduit¹,²

¹Université Paris Cité, CNRS, Institut Jacques Monod, F-75013 Paris, France.

²Corresponding author

Paul T. Conduit

Institut Jacques Monod

CNRS - Université Paris Cité

15 rue Hélène Brion

75013 Paris

France

0033 (1) 57 27 80 95

paul.conduit@ijm.fr

ORCID: 0000-0002-7822-1191
18 **Summary**

19 The neuronal microtubule cytoskeleton is highly polarised, with most microtubules
20 growing away from the soma in axons (plus-end-out) but many microtubules growing
21 towards the soma in dendrites (minus-end-out). This differential microtubule polarity
22 allows directional trafficking of specific organelle, vesicles and molecules into either
23 axons or dendrites but how it is established and maintained remains unclear. We
24 showed previously that microtubules are nucleated asymmetrically from Golgi stacks
25 within the soma of *Drosophila* neurons, with their plus ends growing preferentially
26 towards and into axons and away from dendrites. Here, we show that this microtubule
27 nucleation asymmetry correlates with a cis-to-trans orientation of specific Golgi stacks
28 towards the axon and depends on microtubule nucleating γ-TuRCs at the cis-Golgi
29 and the plus-end-stabilising protein CLASP at the trans-Golgi. Depleting CLASP or
30 reducing γ-TuRC localisation to the Golgi by depleting the Golgin protein GMAP
31 perturbs asymmetric microtubule nucleation and growth within the soma and results
32 in polarity changes in proximal axons and dendrites. We propose that the plus ends of
33 microtubules nucleated by γ-TuRCs at the cis-Golgi are stabilised by CLASP at the
34 trans-Golgi to promote the growth of microtubules along the cis-to-trans Golgi axis.
35 This, coupled with orientated Golgi stacks, promotes microtubule growth towards and
36 into axons and away from dendrites, helping promote plus-end-out microtubule
37 polarity in axons and maintain minus-end-out microtubule polarity in dendrites.
## Introduction

Microtubules are dynamic polarised polymers that play essential roles within cells, including neurons¹. In neurons, microtubule networks extend from the soma to the neurite tips providing 'tracks' for motor-based transport of proteins, mRNA, vesicles and organelles between the soma and axon and dendrite terminals². Within axons, nearly all microtubules have their plus ends pointing away from the soma (plus-end-out), whereas in dendrites there is a significant proportion of minus-end-out microtubules, with the proportion varying between neuronal types and distance from the soma³⁻⁶. The difference in microtubule polarity between axons and dendrites is important for the differential motor-driven transport of cargoes into either the axon or dendrites and is therefore essential for neuronal development and function⁷⁻⁹.

Several mechanisms have been identified that contribute to this differential microtubule polarity. These include motor-driven sorting of microtubules⁶,¹⁰⁻¹⁴, guidance of growing microtubule plus ends¹⁵⁻¹⁷, polarity-related differences in microtubule stability¹⁸, selective interactions of motors based on specific microtubule modifications⁸, and the regulation of microtubule nucleation i.e. the spatiotemporal control of *de novo* microtubule assembly from α/β-tubulin dimers¹⁹.

The best characterised microtubule nucleators are multi-protein γ-tubulin ring complexes (γ-TuRCs), which provide templates for initial microtubule assembly²⁰⁻²². γ-TuRCs form in the cytosol but are activated when recruited to specific sites called microtubule organising centres (MTOCs). During nucleation, microtubule plus ends grow away from the γ-TuRCs, and thus away from MTOCs, while minus ends typically remain anchored at the MTOC. The spatial control of microtubule nucleation, including MTOC positioning, therefore contributes to overall microtubule polarity within the cell.

The centrosome is the major MTOC in dividing cells²³, but differentiated cells commonly employ non-centrosomal MTOCs, such as the surface of the Golgi, the nuclear envelope, endosomes, or mitochondria²⁴⁻²⁷. Several different MTOCs have been identified in neurons, with MTOC type varying with neuronal type and developmental stage. Centrosomes nucleate microtubules during early development, at least in mammalian neurons, but then appear to be downregulated²⁸. In mammalian neurons that have formed synapses, microtubules are nucleated from within axonal boutons in a neuronal activity dependent manner²⁹. Microtubules are also nucleated from the sides of pre-existing microtubules within both axons and dendrites in a manner that amplifies microtubule number, re-enforces microtubule polarity and promotes neurite growth³⁰⁻³³. In the dendrites of *C. elegans* and *Drosophila* neurons, MTOCs can be found at the dendrite tips and nucleate microtubules back towards the soma to promote minus-end-out polarity. In *C. elegans* ciliated sensory neurons, this MTOC is formed from a cloud of residual centrosomal proteins³⁴⁻³⁶, while in *C. elegans* PVD neurons the MTOC is formed from a collection of endosomes³⁷. The distal dendrite MTOCs observed in *Drosophila* dendritic arborisation (da) neurons remain to
be elucidated³⁷,³⁸, but endosomes and Golgi outposts have been identified as MTOCs at dendritic branchpoints⁵,³⁹⁻⁴⁴.

Recently, we showed that γ-TuRCs localise around the cis compartment of the multiple Golgi stacks within the soma of *Drosophila* da neurons and that microtubules originate asymmetrically from these Golgi stacks and grow preferentially towards the axon and away from dendrites¹⁷. This asymmetric microtubule nucleation from Golgi within the soma is reminiscent of that which occurs in motile human cells, where microtubules grow along the cis-to-trans axis of the large Golgi apparatus to generate an asymmetric microtubule network important for cell motility⁴⁵⁻⁴⁸. Here, γ-TuRCs also localise to the cis Golgi with the plus end stabilising CLASP proteins localising to the trans Golgi, with both sets of proteins being required for microtubule nucleation from the Golgi⁴⁵,⁴⁶. More recently, the Golgi within the soma of mammalian cortical projection neurons was identified as a site of microtubule nucleation and these microtubules were shown to be important for axonal growth and bundle thickness⁴⁹. It remains unclear, however, how asymmetric nucleation is regulated at the Golgi and whether it is important for differential microtubule polarity in axons and dendrites.

In this study, we find that the direction of microtubule growth from Golgi stacks correlates with the cis-to-trans orientation of the Golgi stacks. Golgi stacks positioned closer to the axon (axon-side Golgi) are oriented cis-to-trans towards the axon and consistently nucleate microtubules towards the axon. In contrast, while individual dendrite-side Golgi stacks nucleate microtubules in a consistent direction, they are not preferentially oriented and so collectively nucleate microtubules in random directions. We find that the ability of Golgi stacks to nucleate microtubules in a consistent direction relies on γ-TuRCs at the cis-Golgi and CLASP at the trans Golgi. Depleting CLASP, or reducing γ-TuRCs at the Golgi by depleting the Golgin GMAP, perturbs asymmetric microtubule nucleation from the Golgi, changes the proportion of microtubule plus ends that grow towards and into axons and dendrites, and results in microtubule polarity changes in proximal axons and dendrites. We propose that the plus ends of microtubules nucleated by γ-TuRCs at the cis-Golgi are stabilised by CLASP at the trans-Golgi to promote microtubule growth along the cis-to-trans Golgi axis. This, coupled with a cis-to-trans orientation of axon-side Golgi stacks towards the axon, causes microtubules to grow preferentially towards and into the axon while growing away from dendrites. We propose that this asymmetric microtubule growth helps promote plus-end-out microtubule polarity in proximal axons and maintain minus-end-out microtubule polarity in dendrites.
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# Results

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## Golgi stacks positioned closer to the axon are oriented with their cis-to-trans axis pointing preferentially towards the axon

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To understand the mechanism of asymmetric microtubule nucleation from the Golgi, we first examined the orientation of Golgi stacks with respect to the position of the axon within ddaE class I da neurons. In *Drosophila* cells, including class I da neurons, multiple mini-Golgi stacks are spread throughout the soma but each stack is still inherently asymmetric, with a cis, medial and trans compartment collectively forming the stack⁵⁰. We immunostained larval preparations for the cis-Golgi protein GM130 (Golgi matrix protein 130)⁵¹ and the trans-Golgi protein Golgin245⁵² and measured the angle between a line drawn along the cis-to-trans Golgi axis and a line drawn between the cis-Golgi and the axon entry site (Figure 1A,B). Small angles indicate a cis-to-trans orientation towards the axon. Note that we measured the angle of each Golgi relative to the axon (not the dendrites) irrespective of Golgi position within the soma. Note also that a small portion of Golgi stacks (~18%) were excluded because the GM130 and Golgin245 signals overlapped, presumably because the Golgi stacks were oriented along the z-axis of the microscope. Strikingly, there was a preference for the remaining Golgi stacks to be oriented cis-to-trans towards the axon, as shown by a large proportion of small angles (Figure 1C). Moreover, and quite unexpectedly, only the Golgi stacks closer to the axon (hereafter axon-side Golgi) had a strong bias to be oriented cis-to-trans towards the axon (Figure 1D), while “dendrite-side Golgi” (located closer to the dendrites) had only a very weak orientation bias towards the axon (Figure 1E). We confirmed this difference by analysing Golgi orientation using staining against γ-tubulin-GFP and Pericentrin-like-protein (Plp) (Figure S1), which we have previously shown localise to the cis and trans-Golgi, respectively¹⁷. Thus, Golgi stack orientation correlates with Golgi stack position; dendrite-side-Golgi have a very small, if any, orientation bias, while axon-side Golgi have a strong bias to be oriented cis-to-trans towards the axon.

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## Microtubule growth from Golgi stacks correlates with the cis-to-trans orientation of the Golgi stacks

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We next examined whether Golgi orientation correlated with the direction of initial microtubule growth. As in our previous study¹⁷, we filmed neurons expressing the microtubule plus end reporter EB1-GFP and the Golgi reporter ManII-mCherry and analysed the initial growth of EB1-GFP “comets” that emerged from Golgi stacks (Figure 2A,B; Supplementary Video 1). When combining axon- and dendrite-side Golgi data, there was an overall preference for microtubules to initially grow from Golgi stacks preferentially towards the axon (Figure 2C; Supplementary Video 1), as previously observed¹⁷. Strikingly, an asymmetric preference was present only for axon-side Golgi (Figure 2D) and absent for dendrite-side Golgi (Figure 2E), which correlates with the preferential cis-to-trans orientation of axon-side Golgi towards the axon and the random orientation of dendrite-side Golgi i.e. the data was consistent
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with microtubules growing along the cis-to-trans Golgi axis, as they do in motile human cells. In addition, we found that axon-side Golgi nucleated ~33% more microtubules than dendrite-side Golgi (Figure 2F).

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The frequency distributions of EB1-GFP comet orientation in Figures 2D,E combine measurements from multiple Golgi stacks. Thus, given dendrite-side Golgi are randomly oriented, the random distribution of comet directions observed for dendrite-side Golgi could occur even if individual dendrite-side Golgi nucleated microtubules in a consistent direction along their cis-to-trans Golgi axis (Figure 2G). To test this, we employed a "resultant vector analysis" that we described previously¹⁷ and that is explained in Figure 2H and Figure S2E,F. In this analysis, a "resultant vector" is produced for each Golgi stack and is expressed as an x,y coordinate whose position relates to the overall direction of the comets emerging from the Golgi stack (where the positive y axis points towards the axon) and whose length from the 0,0 coordinate provides a measure of the directional consistency of emerging comets. A length of 0 corresponds to comets growing in opposite directions and a length of 1 corresponds to comets all growing in the same direction. Plotting the resultant vectors for all Golgi stacks showed a cluster of resultant vectors close to the 0,1 coordinate, representing Golgi that consistently nucleated microtubules towards the axon (Figure 2I). These resultant vectors were mainly from axon-side Golgi (Figure 2J), while resultant vectors for dendrite-side Golgi stacks were distributed more evenly (Figure 2K). Nevertheless, many of the dendrite-side resultant vectors had a length value close to 1, showing that they had nucleated microtubules in a consistent direction, albeit not necessarily towards the axon. To test whether this was statistically significant, we plotted frequency distributions of resultant vector lengths for all Golgi (Figure S2B), axon-side Golgi (Figure S2C) and dendrite-side Golgi (Figure S2D) and compared each to a "random" frequency distribution. The "random" distributions were generated separately by replacing the experimentally measured comet angles with randomly generated angles between -180° and 180°. The random angle data was generated 20 times with each dataset being processed in the same way as the experimental data to produce 20 "random" frequency distributions. The average value for each "bin" was taken for the final distribution presented in the graphs. Note that it was important to "mirror" the experimental data with random data because resultant vector lengths generated from Golgi nucleating in random directions correlate with the number of nucleation events per Golgi, with fewer nucleation events resulting in larger resultant vector lengths by chance (Figure S2A). We found that in all cases (all Golgi, axon-side Golgi, and dendrite-side Golgi) the frequency distributions of real data resultant vectors were significantly different from the frequency distributions for random data, with many more real data resultant vectors having a length close to 1 (Figures S2B-D). Thus, both axon-side and dendrite-side Golgi have a preference to nucleate microtubules in a consistent direction, seemingly along the cis-to-trans Golgi axis. The
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difference is that only axon-side Golgi are oriented cis-to-trans towards the axon and so only axon-side Golgi nucleate microtubules preferentially towards the axon.

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CLASP localises around the trans compartment of Golgi stacks and is required for asymmetric nucleation

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Having determined that Golgi orientation correlates with the direction of microtubule growth, we next investigated the mechanism underlying cis-to-trans microtubule nucleation asymmetry. In fibroblasts and RPE1 cells, it has been proposed that the offset between γ-TuRCs at the cis-Golgi and CLASPs at the trans-Golgi<sup>45,46</sup> may be responsible for the cis-to-trans directionality of microtubule growth events<sup>48</sup>. We have already shown that γ-tubulin-GFP localises to the cis-Golgi of the Golgi stacks within da neurons<sup>32</sup> and so we tested whether the single CLASP homologue, known as either Orbit, MAST, or Chromosome bows, but hereafter referred to as CLASP, localises to the trans-Golgi. We generated a viable endogenously tagged homozygous CLASP-sfGFP line and found that CLASP-sfGFP did indeed localise to the trans-Golgi of the Golgi stacks within the soma of da neurons, colocalising with the trans-Golgi protein Golgin-245 and being offset from the cis-Golgi protein GM130 (Figure 3A,B).

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To test a role for CLASP in asymmetric microtubule nucleation from the Golgi, we depleted CLASP specifically from class I neurons using a UAS-CLASP-RNAi, the expression of which could strongly deplete CLASP-sfGFP in larval brain cells (Figure S3A). Somewhat surprisingly, CLASP-RNAi resulted in an increase in the frequency of EB1-GFP comets originating from the Golgi stacks (Figure 3C). We considered that the increase could be due to the induction of the DLK/JNK stress pathway, which can be activated in these neurons when microtubule associated proteins are depleted and which globally increases EB1-GFP comet frequency in a γ-TuRC dependent manner<sup>44,53</sup>. Consistent with this, we found that the nuclear fluorescence of the DLK/JNK stress pathway reporter Puc-GFP<sup>54,55</sup> was significantly increased in CLASP-RNAi neurons (Figure S3B). Thus, the increase in EB1-GFP comet frequency after CLASP depletion is likely due to activation of the DLK/JNK stress pathway rather than because CLASP restricts EB1-GFP comet growth. Our attempts to reduce stress using a DLK inhibitor, GNE-3511, were not very successful, in part because stress levels were increased by DMSO alone, even in controls, and in part because the addition of the drug did not strongly reduce stress levels (Figure S3C). We could therefore not find any suitable conditions with which to compare plus end dynamics, such as comet length, between control-RNAi and CLASP-RNAi neurons i.e. conditions where the experimental conditions (+/- DMSO/GNE-3511) and the stress levels were equivalent.

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Despite the caveat of stress induction, we could measure the orientation of initial EB1-GFP comet growth from Golgi when CLASP was strongly reduced or absent from the trans-Golgi. Strikingly, the preference for microtubules to be nucleated from Golgi stacks towards the axon was abolished, including when specifically analysing axon-
side Golgi (Figure 3D-F,J-L; Supplementary Video 2). This did not appear to be simply
due to an increase in comets that grew away from the axon, as there appeared to be
a reduction in comets that grew towards the axon (Figure S3D). Nor was it due to
separation of cis- and trans-Golgi compartments (Figure S3E) or a loss in the cis-to-
trans orientation of Golgi stacks (Figure 3G-I). Instead, the directional consistency of
nucleation events from individual Golgi stacks was lost. There was no longer a large
proportion of resultant vector lengths close to 1 (Figure 3J-L; Figure S3F-H), with the
distribution of resultant vectors for axon-side Golgi not significantly different from that
expected by chance (Figure S3G) and significantly different from control-RNAi
neurons (Figure S3I). We therefore conclude that CLASP is required for asymmetric
microtubule nucleation towards the axon by ensuring microtubules grow along the cis-
to-trans Golgi axis.

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247 GMAP is required for proper γ-TuRC localisation to the Golgi

248 We next wanted to understand which protein or proteins recruit γ-TuRCs to the cis-
249 Golgi. In mammalian cells, GM130 recruits the scaffolding protein AKAP450 to the cis-
250 Golgi<sup>56,57</sup>. AKAP450 can then recruit γ-TuRCs either directly or indirectly via binding
251 to the γ-TuRC binding proteins CDK5RAP2 and Myomegalin<sup>56-61</sup>. This robust pathway
252 of γ-TuRC recruitment to Golgi appears absent in *Drosophila* da neurons because the
253 homologue of CDK5RAP and Myomegalin, Cnn, does not localise to the Golgi in fly
254 neurons, while the homologue of AKAP450, Plp, localises to the trans-Golgi<sup>17</sup>;
255 moreover, both Cnn and Plp are dispensable for γ-TuRC accumulation at the cis-Golgi
256 in fly neurons<sup>17</sup>. Consistent with this, we found that the association of γ-tubulin-GFP
257 at the Golgi stacks was relatively normal in *gm130* null mutants (Figure S4A,B). We
258 therefore considered the Golgin protein GMAP (Golgi microtubule-associated protein)
259 because it localises to the cis-Golgi<sup>62</sup> and its mammalian homologue, GMAP-210, has
260 been implicated in γ-TuRC recruitment to the Golgi in certain cell lines<sup>63</sup> and has been
261 reported to associate with microtubule minus ends<sup>64</sup>. Consistent with GMAP being
262 involved in γ-TuRC recruitment in flies, there was a ~70% reduction in the signal of
263 Golgi-associated γ-tubulin-GFP in *gmap* mutants, with at least some of the displaced
264 γ-tubulin-GFP appearing as small Golgi-independent puncta within the cytosol (Figure
265 4A,B). This was not due to Golgi fragmentation, because there was only a ~4%
266 increase in Golgi size and no change in Golgi number in *gmap* mutants (Figure
267 S4C,D), which is consistent with previous observations in *gmap* mutants<sup>62,65</sup>, and
268 unlike when depleting Lava lamp, a Golgin that links the Golgi to the minus-end
269 directed motor complex Dynein<sup>66</sup> (Figure S4C,D). Thus, GMAP plays a role in
270 recruiting γ-TuRCs to the cis-Golgi in fly neurons. Depleting GMAP reduces, but does
271 not completely abolish, the localisation of γ-TuRCs to the cis-Golgi, and this effect is
272 independent of any role in Golgi cohesion.

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Reducing γ-TuRCs at the Golgi reduces asymmetric microtubule nucleation

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We next assessed the effect on Golgi microtubule nucleation in *gmap* mutants.

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Consistent with a role for γ-TuRCs in microtubule nucleation, we measured a

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statistically significant reduction in the frequency of microtubule nucleation from the

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Golgi stacks in *gmap* mutants compared to w1118 controls (hereafter controls) (Figure

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4C). Note that there was no apparent induction of the stress response pathway in

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*gmap* mutants (Figure S3B). There was also a reduction in the asymmetry of

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microtubule nucleation from axon-side-Golgi (Figure 4E,K), which contributed to a

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reduction in overall nucleation asymmetry (Figure 4D,J; Supplementary Video 3).

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Nucleation was still random from dendrite-side Golgi stacks (Figure 4F,L). The

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decrease in nucleation asymmetry at axon-side Golgi appeared to be due to fewer

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microtubules being nucleated towards the axon (Figure S4E). This was due, at least

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in part, to a reduction (but not elimination) in the cis-to-trans orientation of Golgi

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towards the axon (Figure 4G-I). The effect on the directional consistency of nucleation

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from individual Golgi stacks was less clear. There was a statistically significant

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difference between the distributions of real data and random data resultant vectors

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lengths for all Golgi stacks combined (suggesting directional consistency), but not for

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axon-side and dendrite-side Golgi separately (suggesting directional inconsistency)

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(Figure S4H-J). Moreover, there was no significant difference between the

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distributions of control and *gmap* mutant resultant vectors lengths for axon-side Golgi

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(Figure S4K; although we note that this comparison is not ideal due to the differences

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in nucleation frequency that will differentially affect the distributions, as explained

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above). There was also a significant difference between the distributions of *gmap*

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mutant and CLASP-RNAi resultant vectors lengths for axon-side Golgi (Figure S4L),

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consistent with the less severe effect on nucleation asymmetry in *gmap* mutants. In

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conclusion, microtubule nucleation asymmetry is reduced, but not abolished, in *gmap*

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mutants, where the level of γ-TuRCs at the Golgi is also reduced but not abolished.

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Asymmetric microtubule nucleation from the Golgi helps provide plus-end-out

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microtubules to the axon and maintain correct microtubule polarity in proximal

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dendrites

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While filming EB1-GFP comets emerging from Golgi stacks within the soma, we could

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observe comets originating from Golgi stacks and growing directly into the axon

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(Supplementary Video 4). Thus, asymmetric microtubule nucleation from the Golgi can

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directly contribute to plus-end-out microtubule polarity in proximal axons. Moreover,

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we found that ~14.6% of the EB1-GFP comets that originated in the soma of control

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neurons approached the axon while only ~6.9% approached dendrites (p<0.0001;

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Figure 5A,B; Supplementary Video 5), consistent with our previous observations¹⁷ and

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despite there being only one axon to two or three dendrites per soma. This bias was

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strongly reduced, or even lost, in *gmap* mutants (~15.5% and ~12.6% of comets

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approaching axons and dendrites, respectively; p=0.102; Figure 5B; Supplementary

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Video 6), where asymmetric microtubule nucleation from the Golgi is reduced. This
change in the bias of approaching comets was due to a significant increase in the proportion of comets that approached dendrites in *gmap* mutants compared to controls rather than a decrease in comets approaching the axon (Figure 5B). We observed an even stronger effect in CLASP-RNAi neurons, where, unlike in *gmap* mutants, the asymmetry in microtubule nucleation from the Golgi is completely abolished. Here, the bias in approaching comets was reversed, with only ~8.7% of comets approaching axons and ~12.1% approaching dendrites (Figure 5B; Supplementary Video 7); both measures were statistically different from those in control-RNAi neurons (Figure 5B; Supplementary Video 8). Thus, the strength of the effect seen on the asymmetric bias of microtubule growth towards axons correlates with the strength of the effect on asymmetric microtubule nucleation from the Golgi, suggesting these effects are linked i.e. *gmap* mutants mildly perturb asymmetric microtubule nucleation and growth, while CLASP-RNAi strongly perturbs both these parameters.

Along with showing that a higher proportion of comets approach axons than dendrites in control neurons, we also previously showed that a higher proportion of these approaching comets enter axons compared to dendrites¹⁷. This bias depends on Kinesin-2, which is known to bind to plus ends and guide them along the shafts and towards the plus ends of adjacent microtubules. Our conclusion was that Kinesin-2 on the plus ends of microtubules approaching dendrites would induce a backward stalling force when encountering microtubules with opposite polarity i.e. when encountering minus-end-out microtubules, which are abundant in control dendrites. Here, we found that the proportion of approaching comets that entered the dendrites in *gmap* mutant and CLASP-RNAi neurons significantly increased compared to controls (Figure 5C). Consistent with this, microtubule polarity changed dramatically in the proximal dendrites of *gmap* mutant and CLASP-RNAi neurons: from ~28.6% anterograde comets in control to ~62.6% in *gmap* mutant neurons, and from ~31.9% anterograde comets in control-RNAi to ~59.9% in CLASP-RNAi neurons (Figure 5D,E). In contrast to dendrites, there was no change in the proportion of approaching comets that entered axons in either *gmap* mutant and CLASP-RNAi neurons (Figure 5C). Axonal microtubule polarity was, however, slightly affected in *gmap* mutant neurons (~96.0% anterograde comets compared to ~100% in controls) and strongly affected in CLASP-RNAi neurons (~70.5% anterograde comets compared to ~100% in controls) (Figure 5D,E).

In summary, we find that conditions that perturb asymmetric microtubule nucleation from the Golgi perturb the bias in how microtubules grow preferentially towards axons rather than dendrites and increases the proportion of microtubules that grow into dendrites, reversing microtubule polarity in proximal dendrites. We therefore conclude that asymmetric microtubule nucleation from the Golgi is important for regulating microtubule polarity outside of the soma.
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Discussion

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We had previously shown that microtubules originate from the multiple Golgi stacks within the soma of class I da neurons and then grow preferentially towards and into the axon and away from dendrites¹⁷. In this paper, we show that Golgi stacks closer to the axon are oriented cis-to-trans towards the axon and that it is specifically these Golgi stacks that nucleate microtubules towards the axon (Figure 6B). We show that there is a spatial offset between γ-TuRCs at the cis-Golgi and CLASP at the trans-Golgi, which is similar to that observed in human cells⁴⁵,⁴⁶. Depleting CLASP or reducing γ-TuRC levels at the Golgi perturbs microtubule nucleation and growth asymmetry, as well as leading to microtubule polarity defects in proximal axons and dendrites. Based on these data, we propose that asymmetric microtubule nucleation from the Golgi is generated when the plus ends of microtubules nucleated by γ-TuRCs at the cis-Golgi are preferentially stabilised by CLASP at the trans-Golgi (Figure 6A) and that this asymmetry ultimately helps regulate microtubule polarity in axons and dendrites.

We do not yet understand why only axon-side Golgi are oriented cis-to-trans towards the axon and why this appears to depend, at least in part, on γ-TuRCs at the Golgi, or why axon-side Golgi appear to nucleate more microtubules than dendrite-side Golgi. Intriguingly, differences between Golgi stacks based on their position within the soma have been observed before in *Drosophila* imaginary disk cells. where subsets of glycosylation enzymes differ between Golgi stacks⁵⁰. Moreover, the cis-to-trans axis of these Golgi stacks appears to correlate with the apico-basal polarity of the cell⁵⁰. It is possible that having randomly oriented dendrite-side Golgi may be important, as this will allow at least some microtubules to grow towards and into dendrites to provide at least some plus-end-out microtubules, which may be necessary for dendrite function.

We imagine that asymmetric microtubule nucleation from the Golgi will also contribute to a stable but asymmetric microtubule network within the soma. This network would then allow plus end-associated Kinesin-2 to asymmetrically guide growing plus ends towards the axon (Figure 6B). Indeed, in class I da neurons this Kinein-2-dependent guidance, which has also been observed *in vitro*⁶⁷,⁶⁸, is important for plus end turning towards the soma in dendritic branch points⁴⁴ and plus end turning towards the axon within the soma¹⁷. This asymmetric network will also be enhanced by microtubules generated in dendrites that grow back into the soma, as these microtubules will by default be polarised with their plus ends pointing towards the axon (Figure 6B). In addition, we previously showed that Kinesin-2 restricts plus ends from growing into dendrites, presumably because it creates a backward stalling force when engaging with dendrite microtubules of opposite polarity (Figure 6B). We predict that there will be a balance between outward growing anterograde microtubules and inward growing retrograde microtubules due to the presence of plus-end-associated Kinesin-2. This
balance can presumably be shifted by increasing the number of plus ends that grow into the dendrites from the soma, which will increase when more microtubules grow towards the dendrites, such as when asymmetric microtubule nucleation is perturbed. Indeed, this is reflected in our data where we observe that, not only does the proportion of comets that approach the dendrites increase in CLASP-RNAi and *gmap* mutant neurons, but the proportion of these approaching comets that enter the dendrites also increases, ultimately causing a reversal of microtubule polarity in proximal dendrites.

We find that CLASP depletion results in a stronger effect on asymmetric microtubule nucleation (a complete loss) compared to GMAP depletion (partial loss), and this correlates with CLASP depletion leading to stronger effects on asymmetric microtubule growth within the soma (reversal of the bias) and microtubule polarity defects in proximal neurite (effects observed in both axons and dendrites). While it is possible that this is due to the severity of the effect on asymmetric microtubule nucleation, CLASP is likely to have a more general role in microtubule regulation in these neurons that would be affected after CLASP depletion, potentially leading to the stronger phenotypes we observe. Nevertheless, the strong microtubule polarity defects observed in the dendrites of *gmap* mutant neurons is revealing, as this phenotype must relate only to defects at the Golgi, which is almost entirely restricted to the soma in class I da neurons¹⁷,⁴⁴. We can therefore be confident that asymmetric microtubule nucleation from the Golgi is important for maintaining minus-end-out polarity in dendrites. We also observe microtubules growing from Golgi stacks directly into axons, showing that asymmetric microtubule nucleation does at least provide plus-end-out microtubules to axons.

Intriguingly, it was recently shown that microtubules are also nucleated from the Golgi within the soma of mouse cortical projection neurons ⁴⁹. This was shown to be required for proper axonal growth *in vitro* and for proper axon bundle thickness *in vivo*. Thus, nucleation from the somatic Golgi is a conserved feature in neurons and, in mice at least, is important for axon formation. Whether nucleation from the Golgi in these mouse neurons is asymmetric remains to be examined.

It will be important to address in future when and how asymmetric microtubule nucleation is established. Is it a cause or a consequence of axon specification? Our current data come from examining third instar larvae, where the neuron is well established. Moreover, protein depletion by genetic means may be masked by persistent maternal protein. It will therefore be important to develop new tools to study how asymmetric microtubule nucleation is established and how it may contribute to early neuronal development.

## Resource Availability

**Lead contact:**
Requests for further information and resources should be directed to and will be
fulfilled by the lead contact, Paul Conduit (paul.conduit@ijm.fr).

### Materials availability:

All unique reagents/fly lines generated in this study are available from the lead contact on reasonable request.

### Data and code availability

* Raw microscope data, original western blot images, and quantification data reported in this paper will be shared by the lead contact upon request.

* This paper does not report original code.

* Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

### Acknowledgements

This research was supported by the Centre National de la Recherche Scientifique
CNRS, Université Paris Cité, by a Chaire d'excellence grant from the IdEx Université
Paris Cité ANR-18-IDEX-0001 awarded to PTC, by an ATIP Avenir award funded by
the Fondation Bettencourt Schueller awarded to PTC, and by an Impulscience grant
funded by the Fondation Bettencourt Schueller awarded to PTC. We thank Anaelle
Taieb for generating the plasmids used for generating CLASP-sfGFP. We thank
Jordan Raff and Pascal Therond for kindly donating antibodies, Simon Bullock for
plasmids, Yuh-Nung Jan for the UAS-ManII-mCherry fly line and Melissa Rolls for the
Puc-GFP line. We thank Amrita Mukherjee, Corinne Tovey and Antoine Guichet, along
with members of the Conduit lab for their critical reading of the manuscript. The work
benefited from the ImagoSeine at the IJM, Paris. For the purpose of Open Access, the
author has applied a CC BY public copyright license to any Author Accepted
Manuscript version arising from this submission.

### Author contributions

Investigation, formal analysis, methodology, data curation, validation and writing –
review and editing were carried out by AY. Conceptualization, funding acquisition,
project administration, resources, supervision, visualisation, data curation, validation
and writing original draft were carried out by PTC.

### Declaration of Interests

The authors declare no competing interests.
475 Main figure titles and legends

476 Figure 1

477 Golgi stacks are preferentially oriented cis-to-trans towards the axon within the
478 soma of class I da neurons. (A) Diagram showing how the cis-to-trans Golgi
479 orientation angle was measured. (B) Confocal images showing a soma of a class I da
480 neuron immunostained for HRP (neuronal membranes, greyscale), GM130 (cis-Golgi,
481 magenta), Golgin-245 (trans-Golgi, green). Axon and dendrite entry points are
482 indicated. A line through the centre of the nucleus (as judged by the lack of signal) that
483 divides axon-side and dendrite-side Golgi is indicated. (C-E) Graphs show frequency
484 distributions for cis-to-trans angles of either all Golgi (C), axon-side Golgi (D) or
485 dendrite-side Golgi (E). Goodness of fit Chi-squared tests were used to compare the
486 observed distributions to those expected if Golgi orientation were random; p values
487 are shown. N=138 and 192 axon-side and dendrite-side Golgi stacks, respectively,
488 from 48 neurons. An additional 32 axon-side (~18.8%) and 41 dendrite-side (~17.6%)
489 Golgi stacks were excluded as the cis and trans-Golgi signals were not offset. Note
490 that axon-side Golgi have a very strong preference for low angles, indicating a cis-to-
491 trans orientation towards the axon. Related to Figure S1.
492

493 Figure 2

494 The orientation of microtubule nucleation correlates with the cis-to-trans Golgi
495 axis. (A) Wide-field images from a movie of a class I da neuron expressing EB1-GFP
496 (greyscale) and ManII-mCherry (Golgi, magenta) showing two examples of EB1-GFP
497 comets that originate from Golgi stacks and move towards the axon. Axon and
498 dendrite entry points are indicated. (B) Diagram showing how the angle of initial EB1-
499 GFP comet growth was measured in relation to the axon entry site. (C-E) Graphs show
500 frequency distributions for the initial angle of EB1-GFP comet growth relative to the
501 axon for either all Golgi (C), axon-side Golgi (D) or dendrite-side Golgi (E). Goodness
502 of fit Chi-squared tests were used to compare the observed distributions to those
503 expected if initial EB1-GFP comet orientations were random; p values are shown.
504 N=309 and 239 comets from axon-side and dendrite-side Golgi stacks, respectively,
505 from 39 neurons. Note that axon-side Golgi have a very strong preference for low
506 angles, indicating nucleation towards the axon. (F) Graph showing how microtubule
507 nucleation is more frequent from axon-side Golgi than dendrite-side Golgi. Mean with
508 standard error of the mean are displayed. A two-sided unpaired t-test was used to
509 compare the datasets. N=39 neurons. (G) Diagrams show two possibilities for why
510 there is an observed random orientation of microtubule nucleation from dendrite-side
511 Golgi. Note that the overall numbers and directions of the arrows are the same
512 between the options. (H) Diagram shows how resultant vectors are generated; the
513 direction of these vectors represents the "average" orientation of nucleation events
514 relative to the axon from an individual Golgi stack and the lengths of the vectors
515 represent the consistency in the orientation of these nucleation events. (I-K) Graphs
516

plot the resultant vectors for either all Golgi (I), axon-side Golgi (J) or dendrite-side Golgi (K). N= 85 and 61 axon-side and dendrite-side Golgi stacks, respectively, from 37 neurons. Related to Figure S2.

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520

Figure 3

521

CLASP is required for asymmetric microtubule nucleation from the Golgi but not for Golgi orientation. (A,B) Confocal images showing a soma of a class I da neuron expressing endogenously tagged CLASP-sfGFP immunostained for HRP (neuronal membranes, greyscale), GFP (green) and either GM130 (cis-Golgi, magenta) (A) or Golgin-245 (trans-Golgi, magenta) (B). Note that the CLASP-sfGFP signal is offset from the cis-Golgi, but not the trans-Golgi, marker. (C) Graph shows the frequency of microtubule nucleation events from either all Golgi, axon-side Golgi or dendrite-side Golgi in either control-RNAi (n=11 neurons) or CLASP-RNAi (n=10 neurons) neurons, as indicated. Mean with standard error of the mean are displayed.

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Two-sided unpaired t-tests were used to compare between control-RNAi and CLASP-RNAi for each Golgi type and p values are shown. (D-F) Graphs show frequency distributions for the initial angle of EB1-GFP comet growth relative to the axon for either all Golgi (D), axon-side Golgi (E) or dendrite-side Golgi (F) in either control-RNAi or CLASP-RNAi neurons, as indicated. Goodness of fit Chi-squared tests were used to compare the observed distributions to those expected if initial EB1-GFP comet orientations were random and p values for this are shown in the legends. Kolmogorov-Smirnov tests were used to compare the control-RNAi and CLASP-RNAi distributions for each Golgi type and p values are shown. N=85 and 58 comets from axon-side and dendrite-side Golgi stacks, respectively, from 11 control-RNAi neurons, and n=65 and 72 comets from axon-side and dendrite-side Golgi stacks, respectively, from 10 CLASP-RNAi neurons. Note that the asymmetry of microtubule nucleation from axon-side Golgi is lost in CLASP-RNAi neurons. (G-I) Graphs show frequency distributions for the cis-to-trans orientation of the Golgi stacks relative to the axon for either all Golgi (G), axon-side Golgi (H) or dendrite-side Golgi (I) in either control-RNAi or CLASP-RNAi neurons, as indicated. Goodness of fit Chi-squared tests were used to compare the observed distributions to those expected if Golgi were randomly oriented and p values for this are shown in the legends. Kolmogorov-Smirnov tests were used to compare the control-RNAi and CLASP-RNAi distributions for each Golgi type and p values are shown. Note that Golgi orientation is not affected in CLASP-RNAi neurons. N=60 and 81 axon-side and dendrite-side Golgi stacks, respectively, from 20 control-RNAi neurons, and n=101 and 111 axon-side and dendrite-side Golgi stacks, respectively, from 32 CLASP-RNAi neurons. In control-RNAi neurons, an additional 19 axon-side (~24.1%) and 23 dendrite-side (~22.1%) Golgi stacks were excluded as the cis- and trans-Golgi signals were not offset. In CLASP-RNAi, an additional 18 axon-side (~15.1%) and 39 dendrite-side (~26.0%) Golgi stacks were excluded. (J-L) Graphs plot the resultant vectors for either all Golgi (J), axon-side Golgi (K) or dendrite-side Golgi (L) from CLASP-RNAi cells. Note that there is no enrichment of resultant
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vectors close to the 0,1 coordinate (which would indicate consistent nucleation

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towards the axon), as there is in control neurons (compare with Figure 2I-K). N=33

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and 43 axon-side and dendrite-side Golgi stacks, respectively, from 17 neurons.

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Related to Figure S3.

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563

Figure 4

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**GMAP is required for proper γ-TuRC recruitment to the Golgi and for proper nucleation asymmetry and Golgi orientation.** (A) Confocal images showing somas

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of either control-*w1118* or *gmap* mutant class I da neurons expressing endogenously

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tagged γ-tubulin-GFP immunostained for HRP (neuronal membranes, greyscale),

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GFP (γ-tubulin, green) and GM130 (cis-Golgi, magenta). Note that the localisation of

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γ-tubulin-GFP to the Golgi is strongly reduced in *gmap* mutants, with small γ-tubulin-

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GFP foci appearing in the cytosol. (B) Graph shows the fluorescent signal of γ-tubulin-

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GFP at Golgi stacks in either control (n=30 neurons) or *gmap* mutant (n=34 neurons)

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class I da neurons. Note that the control data is the same as that shown in Figure S4B,

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as the experiments with *gmap* and *gm130* mutants were carried out at the same time,

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thus a one-way ANOVA with correction for multiple comparisons was used to compare

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the datasets. (C) Graph shows the frequency of microtubule nucleation events from

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either all Golgi, axon-side Golgi or dendrite-side Golgi in either control neurons (n=10

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neurons) or *gmap* mutant neurons (n=10 neurons), as indicated. Mean with standard

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error of the mean are displayed. Two-sided unpaired t-tests were used to compare

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between control and *gmap* mutants for each Golgi type and p values are shown. (D-

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F) Graphs show frequency distributions for the initial angle of EB1-GFP comet growth

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relative to the axon for either all Golgi (D), axon-side Golgi (E) or dendrite-side Golgi

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(F) in either control or *gmap* mutant neurons, as indicated. Goodness of fit Chi-squared

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tests were used to compare the observed distributions to those expected if initial EB1-

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GFP comet orientations were random and p values for this are shown in the legends.

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Kolmogorov-Smirnov tests were used to compare the control and *gmap* mutant

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distributions for each Golgi type and p values are shown. N=144 and 121 comets from

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axon-side and dendrite-side Golgi stacks, respectively, from 14 control neurons, and

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n=128 and 146 comets from axon-side and dendrite-side Golgi stacks, respectively,

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from 24 *gmap* mutant neurons. Note that the asymmetry of microtubule nucleation

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from axon-side Golgi is reduced but not abolished in *gmap* mutant neurons. (G-I)

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Graphs show frequency distributions for the cis-to-trans orientation of the Golgi stacks

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relative to the axon for either all Golgi (G), axon-side Golgi (H) or dendrite-side Golgi

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(I) in either control or *gmap* mutant neurons, as indicated. Goodness of fit Chi-squared

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tests were used to compare the observed distributions to those expected if Golgi were

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randomly oriented and p values for this are shown in the legends. Kolmogorov-

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Smirnov tests were used to compare the control and *gmap* mutant distributions for

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each Golgi type and p values are shown. N=78 and 111 axon-side and dendrite-side

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Golgi stacks, respectively, from 28 control neurons, and n=90 and 83 axon-side and
dendrite-side Golgi stacks, respectively, from 30 *gmap* mutant neurons. In controls, an additional 13 axon-side (~14.3%) and 18 dendrite-side (~14.0%) Golgi stacks were excluded as the cis and trans-Golgi signals were not offset. In *gmap* mutants, an additional 21 axon-side (~18.9%) and 32 dendrite-side (~27.8%) Golgi stacks were excluded. Note that Golgi orientation is partially reduced in *gmap* mutant neurons. (J-L) Graphs plot the resultant vectors for either all Golgi (J), axon-side Golgi (K) or dendrite-side Golgi (L) from *gmap* mutant cells. Compared to control neurons (see Figure 2I-K), note a reduction in both resultant vectors located far from the 0,0 coordinate (which indicates a reduction in consistency in nucleation direction) and a reduction in the proportion of resultant vectors that are close to the positive Y axis (which indicates a reduction in preferential growth towards the axon). N=41 and 48 axon-side and dendrite-side Golgi stacks, respectively, from 24 neurons. Related to Figure S4.

612

613 **Figure 5**

Perturbing asymmetric microtubule nucleation from Golgi can perturb microtubule polarity in axons and dendrites. (A) Diagram showing how we score whether EB1-GFP comets approach an axon or a dendrite and then whether these approaching comets enter the axon or dendrite. An entry zone ~0.5µm wide is defined – if a comet arrives in this zone it is scored as approaching; if the comet then travels past this zone it is scored as entering. (B,C) Graphs show results from control-*w1118*, control-RNAi, *gmap* mutant and CLASP-RNAi neurons displaying the proportion of EB1-GFP comets that had originated within the soma and that had approached either the axon or dendrite entry zones (B) and the proportion these approaching comets that had entered the axon or dendrites (C). Error bars represent 95% confidence intervals. For approaching data, n=1516, 2247, 828 and 818 comets analysed from 10, 10, 11 and 10 neurons for control-RNAi, CLASP-RNAi, control-*w1118*, and *gmap* mutant neurons, respectively. For entering axons data, n=197, 195, 262 and 233 comets analysed from 10, 10, 23 and 22 neurons for control-RNAi, CLASP-RNAi, control-*w1118*, and *gmap* mutant neurons, respectively. For entering dendrites data, n=70, 272, 173 and 211 comets analysed from 10, 10, 23 and 22 neurons for control-RNAi, CLASP-RNAi, control-*w1118*, and *gmap* mutant neurons, respectively. Fisher's exact tests were used to compare the proportions. (D) Graph shows the proportion of anterograde comets in either axons or dendrites in either control-*w1118*, control-RNAi, *gmap* mutant, or CLASP-RNAi neurons, as indicated. Error bars represent 95% confidence intervals. For axons and dendrites, respectively, n=193 and 262 comets from 16 neurons for control-*w1118* neurons, 151 and 160 comets from 17 neurons for control-RNAi neurons, 190 and 327 comets from 17 neurons for CLASP-RNAi, and 175 and 211 comets from 16 neurons for *gmap* mutants. Fisher's exact tests were used to compare the proportions. (E) Images show kymographs displaying the orientation of EB1-GFP comet growth in either proximal axons or dendrites from either
640

control-*w1118*, *gmap* mutant, control-RNAi or CLASP-RNAi neurons, as indicated.

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EB1-GFP comet growth away from the soma (anterograde) is to the right.

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643

**Figure 6**

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**A model for asymmetric microtubule nucleation from Golgi and its contribution to microtubule polarity in axons and dendrites.** (A) Diagrams conveying how we

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envisage that an offset between γ-TuRCs and CLASP at the Golgi mediates asymmetric microtubule nucleation. Assuming γ-TuRCs are not specifically oriented

themselves, a microtubule that happens to be nucleated in the direction of the trans-

Golgi will have a higher chance to associate with CLASP, which will bind and stabilise the plus end and allow continued microtubule growth. In contrast, a microtubule nucleated away from the trans-Golgi will have a lower chance to associate with

CLASP, making it more likely that the microtubule will depolymerise. (B) An overall model for how we envisage asymmetric microtubule nucleation from the Golgi helps

support microtubule polarity in axons and dendrites. Point 1: Axon-side Golgi stacks are oriented cis-to-trans towards the axon and thus nucleate microtubules

preferentially towards the axon. Point 2: the microtubules nucleated asymmetrically from Golgi provide asymmetric microtubule tracks along which other plus ends can be guided by plus-end-associated Kinesin-2 towards and into axons. Point 3:

microtubules that grow into the soma from the dendrites also provide asymmetric tracks along which plus-end-associated Kinesin-2 can guide plus ends towards the

axon. Point 4: dendrite-side Golgi are not preferentially oriented and so some microtubule plus ends grow towards the dendrite entry zones. Here, plus-end-associated Kinesin-2 will generate a backward stalling force if it encounters a microtubule of opposite polarity, preventing plus end entry. This stalling happens often

in control neurons, but less often in *gmap* mutant or CLASP-RNAi neurons because

the increased frequency of microtubule growth towards dendrites shifts the balance in microtubule polarity in the dendrites such that the chance of plus end entry increases.
668 STAR methods

669 Contact for Reagent and Resource Sharing

670 Further information and requests for resources and reagents should be directed to and
671 will be fulfilled by the Lead Contact, Paul Conduit (paul.conduit@ijm.fr).

672

673 EXPERIMENTAL MODEL AND SUBJECT DETAILS

674 All *Drosophila melanogaster* (RRID:NCBITaxon_7227) strains were maintained at 18
675 or 25°C on Iberian fly food made from dry active yeast, agar, and organic pasta flour,
676 supplemented with nipagin, propionic acid, pen/strep and food colouring.

677 The following fluorescent alleles were used in this study: γ-tubulin23C-sfGFP<sup>69</sup>, γ-
tubulin23c-eGFP<sup>17</sup>, CLASP-sfGFP (this study), UAS-EB1-GFP (BL 35512), UAS-
ManII-mCherry (gift from Yuh-Nung Jan), UAS-Puc-eGFP (gift from Melissa Rolls in
678 the form of UAS-CD8-RFP, UAS-Dicer2,221Gal4, Puc-eGFP). The following Gal4,
679 mutant and RNAi lines were used in this study: 221-Gal4 (BL 26259), UAS-Gal4-insc
680 (BL 8751), γ-tubulin37C-RNAi (BL32513), UAS-Dicer2 (BL 24646), CLASP-RNAi (BL
681 34669), Dp115-RNAi (VRDC 103350), UAS-Rtn12-RNAi (BL 58208), GM130 mutant
682 (BL 65255), GMAP mutant (BL 10130), Patronin-RNAi (BL 36659) and Lava lamp-
683 RNAi (NIG:6450R-1).
684
685

686 For examining the endogenous localisation of γ-tubulin23C under different conditions,
687 we always used flies expressing endogenously tagged γ-tubulin23C-sfGFP and γ-
688 tubulin23C-eGFP i.e. 2 copies of γ-tubulin23C-GFP in the absence of the untagged
689 allele. This is because using only one copy of a GFP tagged construct is not sufficient
690 to observe the GFP signal at the Golgi. For examining the localisation of γ-tubulin23C-
691 GFP while also expressing an RNAi construct, we used flies expressing two copies of
692 γ-tubulin23C-(sf/e)GFP in combination with one copy of the RNAi construct and one
693 copy of UAS-Dicer2 expressed under the control of one copy of 221-Gal4. For
694 examining the localisation of γ-tubulin23C-GFP in mutant flies, we used flies
695 expressing two copies of γ-tubulin23C-(sf/e)GFP (as above) in combination with two
696 copies of the mutant allele (e.g. a homozygous mutant background).

697 For examining the direction of initial microtubule growth from Golgi in "control" flies in
698 Figure 2, we combined 3 control datasets. For all datasets, we used flies expressing
699 one copy of UAS-ManII-mCherry and one copy of UAS-EB1-GFP expressed under
700 the control of one copy of 221-Gal4. For one of the datasets, we additionally included
701 one copy of the control RNAi construct UAS-γ-tubulin37C-RNAi – this is commonly
702 used as a control RNAi in da neurons because the γ-tubulin37C gene is a maternally
703 expressed. For another dataset we additionally included both the UAS-γ-tubulin37C-
704 RNAi and a UAS-Dicer2.

705 For examining microtubule dynamics under RNAi conditions, we used flies expressing
706 one copy of UAS-ManII-mCherry, one copy of UAS-EB1-GFP, and one copy of the
707 RNAi allele, expressed under the control of one copy of 221-Gal4. For *gmap* mutants,
708 we expressed the one copy of UAS-ManII-mCherry and one copy of UAS-EB1-GFP,
709 using one copy of 221-Gal4, with two copies of the *gmap* mutant allele. We compared
710 each dataset to the appropriate control described above.

711

712 METHOD DETAILS

713

714 DNA cloning

715 5-alpha competent *E. coli* (high efficiency) (NEB) cells were used for bacterial
716 transformations, DNA fragments were purified using QIAquick gel extraction kits
717 (Qiagen), plasmid purification was performed using QIAprep spin miniprep kits
718 (Qiagen). Phusion high-fidelity PCR master mix with HF Buffer (ThermoFisher
719 Scientific) was used for PCRs.

720

721 **Generating endogenously-tagged CLASP-sfGFP fly lines**

722 CLASP-sfGFP endogenously-tagged lines were made using CRISPR combined with
723 homologous recombination, by combining the presence of a homology-repair vector
724 containing the linker-sfGFP, an appropriate guide RNA and Cas9. The homology
725 vectors were made by HiFi assembly (NEB) of PCR fragments generated from the
726 following templates: pBS (for the backbone); genomic DNA prepared from nos-Cas9
727 flies (using MicroLYSIS, Client Life Science) (for the upstream homology arm and the
728 downstream homology arms: ~1kbp each); plasmid 1314 from DGRC, containing the
729 sfGFP tag. The following guide RNA sequence was used:
730 TGATTGCGGGAGCCCTTAAT. The guide sequence was cloned into the pCFD3
731 vector using the method described in⁷⁰. The homology and guide vectors were co-
732 injected into the nos-Cas9 fly line (Bloomington: 54591). Injections were performed by
733 the Department of Genetics Fly Facility, Cambridge, UK. Injected flies were screened
734 in the lab by PCR using the following primers (5' to 3'): GCACCATCCTTGCCTCTGG
735 and GCCCAGGATGTTGCCATCC. After balancing, healthy homozygous stocks were
736 established and maintained.

737

738 Antibodies

739 The following primary antibodies were used: mouse monoclonal anti-GFP at 1:250
740 (Roche, 11814460001), rabbit polyclonal anti-Plp at 1:500 (gift from the Raff Lab),
741 rabbit polyclonal anti-GMAP at 1:500 (from Pascal Therond Lab), goat polyclonal anti-
742 Golgin 245 at 1:500 (DSHB, AB_2569587), goat polyclonal anti-HRP Alexa-647-
743 conjugated at 1:500 (Jackson, RRID: AB_2338967), rabbit polyclonal anti-GM130 at
744 1:300 (Abcam, 30637), mouse monoclonal anti-GFP at 1:500 (Roche, Cat#
745 11814460001, AB_390913), and mouse monoclonal anti-actin at 1:500 (Merck,
746 A3853). The following secondary antibodies were used: Goat Anti-Mouse IgG H&L
747

(Alexa Fluor 488) preadsorbed at 1:500 (Abcam, ab150117), Goat anti-Rabbit IgG (H+L) (Alexa Fluor 568), Highly Cross-Adsorbed at 1:500 (ThermoFisher, Cat#A-11036, AB_10563566), Donkey anti-Goat IgG (H+L) (Alexa Fluor 488) Cross-Adsorbed at 1:200 (ThermoFisher, Cat#A-11055, AB_2534102), HRP-conjugated anti-mouse (Immunoreagents, Cat#GtxMu-003-DHRPX), and HRP-conjugated anti-rabbit at 1:2000 (Immunoreagents, Cat#GtxRb-003-DHRPX).

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## Immunostaining

756

Larvae were dissected as described previously¹⁷. Briefly, the fillet preparations were fixed in freshly prepared 4% formaldehyde for 20 minutes at room temperature and were then washed four times for 10 minutes in PBS. The preparations were then blocked in PBST (PBS + 0.2% TritonX-100) + 5% BSA for 1 hour at room temperature and incubated with the appropriate primary antibodies diluted in PBST-BSA overnight at 4°C. After washing in PBST for ~8 hours, changing washes every 1 hour, samples were incubated in secondary antibodies diluted in PBST-BSA overnight at 4°C. The fillet preparations were then washed for ~8 hours, changing washes every 1 hour in PBST before mounting in Moviol. They were directly imaged or stored at -20°C until imaging.

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## Fixed and live cell imaging

768

All imaging was carried out at ambient room temperature (~21°C). For live larval samples, wandering L3 larvae were first washed in a PBS 1X drop then placed in a drop of glycerol before being flattened between a slide and a 22X22mm coverslip, held in place by tape, and then imaged immediately. Imaging of EB1-GFP and ManII-mCherry was performed either on a Leica DMi8 inverted wide-field microscope controlled by µManager software and coupled to a BSI Prime Express monochrome camera (QImaging) and a CoolLED pE-300 Ultra light source using a 63×1.3NA oil objective (Leica 11506384). Single Z-plane images were acquired every 5 seconds. All images were processed using Fiji (ImageJ). Fixed cell imaging was carried out on a Zeiss Axio Observer.Z1 inverted CSU-X1 Yokogowa spinning disk system with 2 ORCA Fusion camera (Hamamatsu) run by Zeiss Zen2 acquisition software using a 60×1.4NA oil immersion lens (Zeiss). Z-stacks with 0.5mm spacing were acquired.

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## Puc-GFP imaging and treatment with GNE-3511

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For all Puc-GFP analysis, flies were raised in cages on apple juice/agar/sucrose plates that had a drop of yeast paste added. Yeast paste was made by mixing 18g of dried yeast powder with 30 ml of autoclaved water. During drug treatments, a solution of DMSO+GNE-3511 was added to a final concentration of 50µM. An equivalent amount of DMSO was added when analysing DMSO-only controls. Larvae were initially grown on normal yeast paste for two days, then they were transferred to new plates with

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yeast containing either DMSO or DMSO+GNE-3511. The larvae were then allowed to
grow for another day before 3-day old larvae were imaged as described above.

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**Electrophoresis and western blotting**

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For each condition, 10 larval brains were dissected in 1X PBS and boiled at 95°C for 10 minutes in 20µl 2x Laemmli sample buffer (BioRad) supplemented with beta-mercaptoethanol. Samples were run on 4-20% TGX pre-cast Gels (Bio-Rad) alongside 5 µl Precision Plus Western C Standard markers (Bio-Rad, 1610367). For Western blotting, semi-dry blotting was performed using TransBlot Turbo 0.2-µm nitrocellulose membrane transfer packs (Bio-Rad). Membranes were blocked in milk solution for 1 h at RT. Sections of blots were incubated with appropriate primary antibodies. Blots were incubated with HRP-conjugated anti-mouse or anti-rabbit, secondary antibodies (1:2000 in PBST + 4% milk powder; ImmunoReagents) as appropriate for 45 min at RT, washed in PBST three times for 15 min each, and then incubated with ECL substrate (Bio-Rad ECL Clarity or Thermo Fisher Scientific SuperSignal West Femto Max) for 5 min. Membranes were imaged using a Bio-Rad ChemiDoc.

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**Image analysis**

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All images were analysed in Fiji (ImageJ). Data was processed in Microsoft Excel.

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To define axon-side and dendrite-side Golgi stacks, we drew a line through the centre of the nucleus (which can be seen due to the absence of fluorescent signal) that split the soma such that the axon and dendrites were on opposite sides of the line. Any Golgi stacks that fell on this line were excluded from axon-side and dendrite-side Golgi analysis, but were still included for all Golgi analysis. The numbers excluded were as follows: when analysing Golgi orientation using GM130 and Golgin245, 0 out of 403 Golgi; when analysing Golgi orientation using γ-tubulin-GFP and Plp, 0 out of 228 Golgi; when analysing microtubule nucleation from Golgi in control-w1118 cells, 5 out of 60 Golgi; when analysing microtubule nucleation from Golgi in control-RNAi cells, 7 out of 147 Golgi; when analysing microtubule nucleation from Golgi in CLASP-RNAi cells, 3 out of 57 Golgi; when analysing microtubule nucleation from Golgi in *gmap* mutant cells, 1 out of 143 Golgi.

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For the analysis of Golgi orientation, maximum intensity Z-plane projections were made and Golgi that did not appear to be oriented along the Z-axis (no offset between cis and trans marker) were removed. We used either anti-GM130 to mark cis-Golgi and Golgin 245 to mark trans-Golgi, or γ-tubulin-GFP to mark cis Golgi and anti-Plp to mark trans Golgi. The angle of each Golgi stack was measured using the angle tool within ImageJ. Lines were drawn from the axon entry site to the centre of the cis-Golgi
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marker and then from here to the centre of trans-Golgi marker. The angle tool
measures the angle between these lines.

For analysing nucleation frequency from Golgi, the total number of comets that originated from the type of Golgi stack in question was divided by the number of Golgi stacks and the time of the movie in minutes and then multiplied by 10 to calculate the frequency of comets per Golgi stack per 10 mins for a particular neuron. These data were plotted in the graphs. Each movie was 5 minutes long.

Tracking and analysis of EB1-GFP comets was carried as described previously (Mukherjee et. al., 2020). Briefly, comets that were present within the first timepoint (and thus may not represent newly growing microtubules) were excluded. Tracking was carried out using the Manual Tracking plugin in Fiji. The angle of initial comet growth was measured using the angle tool within ImageJ. Comets were scored as Golgi nucleation events when the comet originated within or immediately adjacent to the ManII-mCherry signal. For the frequency distribution of comet angles, the negative angles were made positive, so as not to distinguish between comets growing either side of the axon entry site, creating a distribution between 0° and 180°. For the vector analysis, only Golgi stacks that generated 2 or more comets were analysed and both positive and negative angles were maintained (between -180° and 180°). Vectors for individual comets from a single Golgi stack were summed and then the value was normalised by dividing by the number of comets, such that the maximum possible length of the resultant vector would be 1, irrespective of comet number. Random datasets were generated by using the random number generator tool in Excel to replace each “real data” comet angle with a randomly generated number between -180 and 180. This was repeated 19 more times to generate the 20 random datasets for each condition. Note that the random datasets are specific to a particular condition and so take into account precisely how many comets were nucleated from each Golgi in each neuron in each condition. This is important as there is a correlation between resultant vector length and the number of comets nucleated by a Golgi stack (see Figure S2).

To measure microtubule polarity in proximal axons and dendrites, we generated Kymographs in Fiji based on the regions of the neurites that were in focus and manually counted anterograde and retrograde EB1-GFP comets.

For assessing whether comets that originated within the soma approached and entered axons or dendrites, we performed the analysis as described previously (Mukherjee et. al., 2020). Briefly, we defined a zone (~0.5µm wide) across the entrance to the axon or dendrite and any comets that entered this region were scored as comets that had approached, while any comets that crossed this region were scored as comets that entered (see Figure 5A). Note that to acquire sufficient numbers
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of comets for the 'entering' analysis, we analysed extra neurons for the control-*w1118*

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and *gmap* mutant genotypes.

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For the analysis of the γ-tubulin-GFP signal at somatic Golgi stacks under different conditions, maximum intensity Z-plane projections were made and ROIs were drawn around individual Golgi stacks. Sum fluorescence intensities for each Golgi stack were calculated and then background corrected using overall mean cytosolic intensity measurements. The mean "corrected" intensity was calculated for individual neurons and plotted.

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For Puc-GFP, a maximum intensity projection from 3 to 5 Z-planes around the centre of the nucleus was taken for each datapoint.

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## QUANTIFICATION AND STATISTICAL ANALYSIS

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Statistical analysis and graph production were performed using GraphPad Prism.

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Details of N numbers and the statistical tests used can be found in the Figure Legends.

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Briefly, goodness of fit Chi-squared tests were used to compare whether observed distributions were different from those expected by chance; Kolmogorov-Smirnov tests were used to test whether two distributions were different from each other; two-sided unpaired t-tests were used to compare two datasets that were normally distributed (as determined by the 4 normality tests offered by GraphPad Prism); one-way ANOVA with correction for multiple comparisons were used to compare the means of more than 2 datasets. Fishers exact tests were used to compare proportions. 95% Clopper-Pearson confidence intervals for individual proportions were obtained from https://www.medcalc.org/index.php.

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895 Supplemental video titles and legends

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897 Supplementary Video 1

898 Microtubules are nucleated asymmetrically from Golgi stacks in control-RNAi neurons. Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale), ManII-mCherry (magenta) and control-RNAi. Left panel shows EB1-GFP alone; right panel shows EB1-GFP and ManII-mCherry overlayed with comet tracks that were manually assigned in Fiji. Only selected EB1-GFP comet tracks that originated from Golgi stacks are shown. Note that microtubules tend to grow towards the axon from axon-side Golgi stacks but are more randomly oriented from dendrite-side Golgi stacks. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 7 frames per second.

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909 Supplementary Video 2

910 Microtubules are nucleated in random directions from Golgi stacks in CLASP-RNAi neurons. Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale), ManII-mCherry (magenta) and CLASP-RNAi. Left panel shows EB1-GFP alone; right panel shows EB1-GFP and ManII-mCherry overlayed with comet tracks that were manually assigned in Fiji. Only selected EB1-GFP comet tracks that originated from Golgi stacks are shown. Note that microtubules grow in random directions from both axon-side and dendrite-side Golgi stacks. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 7 frames per second.

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920 Supplementary Video 3

921 The asymmetry of microtubule nucleation from Golgi stacks is reduced in *gmap* mutant neurons. Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale) and ManII-mCherry (magenta) from *gmap* mutant animals. Left panel shows EB1-GFP alone; right panel shows EB1-GFP and ManII-mCherry overlayed with comet tracks that were manually assigned in Fiji. Only selected EB1-GFP comet tracks that originated from Golgi stacks are shown. Note that a significant proportion of microtubules grow away from the axon from axon-side Golgi stacks. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 7 frames per second.

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931 Supplementary Video 4

932 Microtubules nucleated from axon-side Golgi stacks can grow directly into axons. Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale), ManII-mCherry (magenta) and control-RNAi. Left panel shows EB1-GFP alone; right panel shows EB1-GFP and ManII-mCherry
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overlayed with comet tracks that were manually assigned in Fiji. Only selected EB1-GFP comet tracks that originated from Golgi stacks and grew directly into the axon are shown. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 8 frames per second.

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### Supplementary Video 5

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**EB1-GFP comet tracking in control-*w1118* class I da neurons.** Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale) and ManII-mCherry (not shown) from control-*w1118* animals. Left panel shows EB1-GFP alone; right panel shows EB1-GFP overlayed with comet tracks that were manually assigned in Fiji. Note that more microtubules approach and enter the axon than the dendrites. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 7 frames per second.

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### Supplementary Video 6

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**EB1-GFP comet tracking in *gmap* mutant class I da neurons.** Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale) and ManII-mCherry (not shown) from *gmap* mutant animals. Left panel shows EB1-GFP alone; right panel shows EB1-GFP overlayed with comet tracks that were manually assigned in Fiji. Note that many microtubules approach and enter dendrites. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 7 frames per second.

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### Supplementary Video 7

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**EB1-GFP comet tracking in CLASP-RNAi class I da neurons.** Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale), ManII-mCherry (not shown) and CLASP-RNAi. Left panel shows EB1-GFP alone; right panel shows EB1-GFP overlayed with comet tracks that were manually assigned in Fiji. Note that many microtubules approach and enter dendrites. Note also a significant proportion of retrograde microtubules in the axon that grow back into the soma. Time interval between frames is 5 seconds and time (min:s) is indicated in the video. The video is played at 7 frames per second.

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### Supplementary Video 8

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**EB1-GFP comet tracking in control-RNAi class I da neurons.** Single Z plane time-lapse wide-field imaging of a *Drosophila* class I da neuron expressing EB1-GFP (greyscale), ManII-mCherry (not shown) and control-RNAi. Left panel shows EB1-GFP alone; right panel shows EB1-GFP overlayed with comet tracks that were manually assigned in Fiji. Note that more microtubules approach and enter the axon than the dendrites. Note also that, while the majority of microtubules grow anterograde, there are occasionally some comets that grow retrograde in the axon. Time interval between

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57. Hurtado, L., Caballero, C., Gavilan, M.P., Cardenas, J., Bornens, M., and Rios, R.M. (2011). Disconnecting the Golgi ribbon from the centrosome prevents directional cell migration and ciliogenesis. J Cell Biology **193**, 917-933. https://doi.org/10.1083/jcb.201011014.

58. Roubin, R., Acquaviva, C., Chevrier, V., Sedjaï, F., Zyss, D., Birnbaum, D., and Rosnet, O. (2013). Myomegalin is necessary for the formation of centrosomal and Golgi-derived microtubules. Biol Open **2**, 238-250. https://doi.org/10.1242/bio.20123392.

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<table><caption>Key resources table</caption><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3">Antibodies</td></tr><tr><td>mouse monoclonal anti-GFP</td><td>Roche</td><td>Cat#11814460001</td></tr><tr><td>rabbit polyclonal anti-Plp (Plp-NTD)</td><td>Jordan Raff</td><td>N/A</td></tr><tr><td>rabbit polyclonal anti-GMAP</td><td>Pascal Therond</td><td>N/A</td></tr><tr><td>goat polyclonal anti-Golgin 245</td><td>DSHB</td><td>RRID:AB_2569587</td></tr><tr><td>goat polyclonal anti-HRP Alexa-647-conjugated</td><td>Jackson</td><td>Cat#123-605-021, RRID: AB_2338967</td></tr><tr><td>rabbit polyclonal anti-GM130</td><td>Abcam</td><td>Cat#30637</td></tr><tr><td>Donkey anti-Goat IgG (H+L) (Alexa Fluor 488) Cross-Adsorbed</td><td>ThermoFisher</td><td>Cat#A-11055, RRID: AB_2534102</td></tr><tr><td>Goat Anti-Mouse IgG H&amp;L (Alexa Fluor 488) preadsorbed</td><td>Abcam</td><td>RRID: AB_150117</td></tr><tr><td>Goat anti-Rabbit IgG (H+L) (Alexa Fluor 568), Highly Cross-Adsorbed</td><td>ThermoFisher</td><td>Cat#A-11036, AB_10563566</td></tr><tr><td>mouse monoclonal anti-GFP</td><td>Roche</td><td>Cat# 11814460001, AB_390913</td></tr><tr><td>mouse monoclonal anti-actin</td><td>Merck</td><td>A3853</td></tr><tr><td>HRP-conjugated anti-mouse</td><td>Immunoreagents</td><td>Cat#GtxMu-003-DHRPX</td></tr><tr><td>HRP-conjugated anti-rabbit</td><td>Immunoreagents</td><td>Cat#GtxRb-003-DHRPX</td></tr><tr><td colspan="3">Chemicals, peptides, and recombinant proteins</td></tr><tr><td>DLK inhibithor, GNE-3511</td><td>Merck</td><td>FR-30231716</td></tr><tr><td>Pierce 16% Formaldehyde (w/v), Methanol-free</td><td>ThermoFisher</td><td>Cat#28906</td></tr><tr><td colspan="3">Critical commercial assays</td></tr><tr><td>Mini prep kit</td><td>QIAGEN</td><td>Cat#27106</td></tr><tr><td>Gel extraction kit</td><td>QIAGEN</td><td>Cat#28704</td></tr><tr><td>Phusion master mix with HF buffer</td><td>NEB</td><td>Cat#F531</td></tr><tr><td>5-alpha competent E. coli (High Efficiency)</td><td>NEB</td><td>Cat#C2987I</td></tr><tr><td>HiFi mastermix</td><td>NEB</td><td>Cat#E2621</td></tr><tr><td colspan="3">Experimental models: Organisms/strains</td></tr><tr><td>D.melanogaster: nos-cas9</td><td>Bloomington</td><td>54591</td></tr><tr><td>D.melanogaster: gmap mutant</td><td>Bloomington</td><td>10130</td></tr><tr><td>γ-tubulin23C-sfGFP</td><td>Tovey et al.⁶⁹</td><td></td></tr><tr><td>γ-tubulin23c-eGFP</td><td>Mukherjee et al.¹⁷</td><td></td></tr><tr><td>CLASP-sfGFP</td><td>This study</td><td></td></tr><tr><td>UAS-EB1-GFP</td><td>Bloomington</td><td>35512</td></tr><tr><td>UAS-ManII-mCherry</td><td>Yuh-Nung Jan</td><td></td></tr><tr><td>UAS-Puc-eGFP</td><td>Melissa Rolls</td><td></td></tr><tr><td>221-Gal4</td><td>Bloomington</td><td>26259</td></tr><tr><td>UAS-Gal4-insc</td><td>Bloomington</td><td>8751</td></tr><tr><td>UAS-γ-tubulin37C-RNAi</td><td>Bloomington</td><td>32513</td></tr><tr><td>UAS-Dicer 2</td><td>Bloomington</td><td>24646</td></tr><tr><td>UAS-CLASP-RNAi</td><td>Bloomington</td><td>34669</td></tr><tr><td>UAS-Dp115-RNAi</td><td>VDRC</td><td>103350</td></tr><tr><td>UAS-Rtnl2-RNAi</td><td>Bloomington</td><td>58208</td></tr><tr><td>gm130 mutant</td><td>Bloomington</td><td>65255</td></tr><tr><td>UAS-Patronin-RNAi</td><td>Bloomington</td><td>36659</td></tr><tr><td>UAS-Lavalamp-RNAi</td><td>NIG</td><td>6450R-1</td></tr></tbody></table>
<table><thead><tr><th colspan="3">Oligonucleotides</th></tr></thead><tbody><tr><td>To clone Guide RNA:<br>GTCGTGATTGCGGGAGCCCTTAAT</td><td>This study</td><td>N/A</td></tr><tr><td>To clone Guide RNA:<br>AAACATTAAGGGCTCCCGCAATCA</td><td>This study</td><td>N/A</td></tr><tr><td>Screening for sfGFP: GCACCATCCTTGCCTCTGG</td><td>This study</td><td>N/A</td></tr><tr><td>Screening for sfGFP: GCCCAGGATGTTGCCATCC</td><td>This study</td><td>N/A</td></tr><tr><td colspan="3">Recombinant DNA</td></tr><tr><td>pCFD3</td><td>Gift from S. Bullock</td><td>Addgene 49410</td></tr><tr><td>pBS-KS-attB1-2-PT-SA-SD-2-sfGFP-FIAsh-StrepII-TEV-3x-FLAG</td><td>DGRC</td><td>1314</td></tr><tr><td>pBluescript SK+</td><td>Gift from S. Bullock</td><td>N/A</td></tr><tr><td colspan="3">Software and algorithms</td></tr><tr><td>Fiji (ImageJ)</td><td>Open source</td><td>N/A</td></tr><tr><td>Prism</td><td>GraphPad</td><td>N/A</td></tr><tr><td>Affinity designer</td><td>Affinity</td><td>N/A</td></tr><tr><td>SnapGene</td><td>SnapGene</td><td>N/A</td></tr><tr><td>PDF Studio</td><td>Qoppa software</td><td>N/A</td></tr><tr><td>Microsoft word</td><td>Microsoft</td><td>N/A</td></tr><tr><td>Microsoft excel</td><td>Microsoft</td><td>N/A</td></tr><tr><td>QuickTime</td><td>Apple</td><td>N/A</td></tr></tbody></table>
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<figure><img src="image_14.png" /><figcaption>EB1-GFP comet frequency from Golgi</figcaption></figure>

<figure><img src="image_15.png" /><figcaption>Control vs CLASP-RNAi: initial angles of EB1-GFP growth from the Golgi relative to axon entry site</figcaption></figure>

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<figure><img src="image_18.png" /><figcaption>Control vs CLASP-RNAi: cis-to-trans angles of Golgi stacks relative to axon entry site</figcaption></figure>

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A

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B

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C

EB1-GFP comet frequency from Golgi

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Control vs *gmap* mutant: initial angles of EB1-GFP growth from the Golgi relative to axon entry site

D

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Control vs *gmap* mutant: cis-to-trans angles of Golgi stacks relative to axon entry site

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<figure><img src="image_37.png" /><figcaption>Figure 5</figcaption></figure>
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<figure><img src="image_40.png" /><figcaption>Figure S1</figcaption></figure>

**Figure S1.** Different markers confirm that Golgi stacks are preferentially oriented cis-to-trans towards the axon. (A) Confocal images showing a soma of a class I da neuron expressing endogenously tagged γ-tubulin-GFP immunostained for HRP (neuronal membranes, greyscale), Plp (trans-Golgi, magenta), GFP (cis-Golgi, green). Axon and dendrite entry points are indicated. A line through the centre of the nucleus (as judged by the lack of signal) that divides axon-side and dendrite-side Golgi is indicated. (B-D) Graphs show frequency distributions for cis-to-trans angles of either all Golgi (B), axon-side Golgi (C) or dendrite-side Golgi (D). Goodness of fit Chi-squared tests were used to compare the observed distributions to those expected if Golgi orientation were random; p values are shown. N=82 and 83 axon-side and dendrite-side Golgi stacks, respectively, from 31 neurons. An additional 28 axon-side (~25.5%) and 35 dendrite-side (~29.9%) Golgi stacks were excluded as the cis and trans-Golgi signals were not offset. Note that axon-side Golgi have a very strong preference for low angles, indicating a cis-to-trans orientation towards the axon. Related to Figure 1.
Figure S2

Real control data vs data from random angles: resultant vector length (consistency of nucleation direction)

<figure><img src="image_41.png" /></figure>

**Figure S2.** Resultant vector lengths produced from random angle data correlate with the number of nucleation events from Golgi. (A) The graph shows resultant vector lengths that were produced when observed angles of nucleation were replaced with random angles plotted against the number of microtubules that were nucleated from the given Golgi stack. Note that resultant vector lengths are expected to be larger when fewer microtubules are nucleated. (B-D) Graphs show frequency distributions for resultant vector lengths for either all Golgi (B), axon-side Golgi (C) or dendrite-side Golgi (D). These frequency distributions of "real data" are compared to frequency distributions generated from random angle data (yellow) that would be expected by chance if there were no preference for microtubules to be nucleated in a particular direction. Goodness of fit Chi-squared tests were used for the comparisons, with the random angle data being used as the expected values; p values are shown. N= 85 and 61 axon-side and dendrite-side Golgi stacks, respectively, from 37 neurons. (E,F) Diagrams show how resultant vectors are calculated for each Golgi stack. In these mock examples, 3 comets emerge from each Golgi stack. In the example in (E), the comets all grow roughly towards the axon with small variations in their angles from the axon (the axon entry site is always positioned along the positive Y axis on the X,Y plot). In the example in (F), the comets emerge at very different angles to each other, with none of the comets growing towards the axon. For the resultant vector calculation, each comet is represented by a vector with a length of 1; the vector's position on the X,Y plot is determined by the angle from the axon with which the comet emerges from the Golgi. The vectors are added together to create a resultant vector that is then normalised by dividing by the number of comets added together. Thus, all normalised resultant vectors have a length between 0 and 1 and a position on the X-Y plot that depends on the directional consistency and overall directionality (with respect to the axon) of comet growth from the Golgi stack. Related to Figure 2.
<figure><img src="image_42.png" /><figcaption>Figure S3</figcaption></figure>

CLASP-RNAi vs data from random angles: resultant vector length (consistency of nucleation direction)

<figure><img src="image_43.png" /></figure>

**Figure S3.** CLASP-RNAi efficiently depletes CLASP-sfGFP from brain cells, which eliminates the ability of Golgi stacks to nucleate microtubules in a consistent direction. (A) A western blot showing the effect of expressing CLASP-RNAi in brain cells using insc-Gal4 on the levels of CLASP-sfGFP. Each lane contains 10 larval brains for the condition indicated. Anti-GFP was used to probe for CLASP-sfGFP and anti-Actin was used as a loading control. Note that the amount of CLASP-sfGFP is strongly reduced in cells expressing CLASP-RNAi (B, C) Graphs show the mean nuclear signals of Puc-GFP (a reporter of the DLK/JNK stress pathway) in neurons from larvae grown on normal food (B) and in neurons from larvae grown on food with or without DMSO and the DLK inhibitor GNE-3511, as indicated. Patr-RNAi is used as a positive control. Note that CLASP-RNAi, but not gmap mutants, leads to a significant increase in nuclear Puc-GFP signal. Note also that adding the DLK inhibitor has little effect on stress levels. Conditions were compared using one-way ANOVA. (D) Graph shows frequency of nucleation events per Golgi per 10 minutes in relation to the initial angle of EB1-GFP comet growth relative to the axon for axon-side Golgi of control-RNAi and CLASP-RNAi neurons. Note that this is not a frequency distribution graph, unlike in Figure 3E, and so a Kolmogorov-Smirnov test cannot be used to compare the conditions. Data collected from 39 Golgi within 11 neurons for Control-RNAi and 24 Golgi within 10 neurons for CLASP-RNAi. (E) Confocal images showing a soma of a class I da neuron expressing CLASP-RNAi immunostained for HRP (neuronal membranes, greyscale), GM130 (cis-Golgi, magenta), Golgin-245 (trans-Golgi, green). Note that the cis- and trans-Golgi offset is still visible. (F-H) Graphs show frequency distributions for resultant vector lengths for either all Golgi (F), axon-side Golgi (G) or dendrite-side Golgi (H) in CLASP-RNAi neurons. These frequency distributions of "real data" are compared to frequency distributions generated from random angle data (yellow) that would be expected by chance if there were no preference for microtubules to be nucleated in a particular direction. Goodness of fit Chi-squared tests were used for the comparisons, with the random angle data being used as the expected values; p values are shown. N=33 and 43 axon-side and dendrite-side Golgi stacks, respectively, from 10 neurons. Note that there is no significant difference between the real data and the random data, indicating that microtubules are nucleated in random directions in CLASP-RNAi neurons. (I) Graph compares the frequency distributions of resultant vector lengths for axon-side Golgi from control-RNAi neurons and CLASP-RNAi neurons. A Kolmogorov-Smirnov test was used to compare the distributions. N=43 and 33 Golgi stacks for control-RNAi and CLASP-RNAi, respectively. Related to Figure 3.
<figure><img src="image_44.png" /><figcaption>gmap mutant vs data from random angles: resultant vector length (consistency of nucleation direction)</figcaption></figure>

<figure><img src="image_45.png" /></figure>
**Figure S4. GM130 is not required for γ-TuRC recruitment to Golgi and Golgi assembly appears unaffected in gmap mutants (A)** Confocal images showing somas of either control or *gm130* mutant class I da neurons expressing endogenously tagged γ-tubulin-GFP immunostained for HRP (neuronal membranes, greyscale), GFP (γ-tubulin, green) and GMAP (cis-Golgi, magenta). Note that the localisation of γ-tubulin-GFP to the Golgi appears unaffected in *gm130* mutants. **(B)** Graph shows the fluorescent signal of γ-tubulin-GFP at Golgi stacks in either control (n=30 neurons) or *gm130* mutant (n=11 neurons) class I da neurons. Note that the control data is the same as that shown in Figure 5B, as the experiments with *gmap* and *gm130* mutants were carried out at the same time, thus a one-way ANOVA with correction for multiple comparisons was used to compare the datasets. **(C)** Graphs show Golgi size (as measured by HRP signal) under different conditions (as indicated). Left graph shows raw data, which is log normally distributed; right graph shows log transformed data, which is normally distributed and so can be compared using a one-way ANOVA; p values are shown. N= 251, 226, 235, 321 Golgi from 29, 30, 25, 20 neurons from control, *gmap* mutant, *gm130* mutant and Lava lamp-RNAi cells, respectively. Note that Golgi stacks are of similar size in control cells and *gmap* or *gm130* mutant cells, but are smaller in Lava lamp-RNAi cells. **(D)** Graph shows a frequency distribution of Golgi stack number under different conditions (as indicated). Kolmogorov-Smirnov tests were used to compare the control to the different mutant conditions and p values are shown. N= 251, 226, 235, 321 Golgi from 29, 30, 25, 20 neurons from control, *gmap* mutant, *gm130* mutant and Lava lamp-RNAi cells, respectively. Note that there is no significant difference in Golgi number between control cells and *gmap* or *gm130* mutant cells, but that there are more Golgi in Lava lamp-RNAi cells. **(E)** Graph shows frequency of nucleation events per Golgi per 10 minutes in relation to the initial angle of EB1-GFP comet growth relative to the axon for axon-side Golgi of control w1118 and *gmap* mutant neurons. Note that this is not a frequency distribution graph, unlike in Figure 4E, and so a Kolmogorov-Smirnov test cannot be used to compare the conditions. Data collected from 26 Golgi within 10 neurons for Control and 32 Golgi within 10 neurons for *gmap* mutant. **(F,G)** Confocal images showing somas of class I da neurons either from *gmap* mutants (F) or expressing Lava lamp-RNAi (G) immunostained for HRP (neuronal membranes, greyscale), GM130 (cis-Golgi, magenta), Golgin-245 (trans-Golgi, green). Note that in both cases the cis- and trans-Golgi offset is still visible but that in Lava lamp-RNAi neurons there are more than normal numbers of smaller Golgi stacks. **(H-J)** Graphs show frequency distributions for resultant vector lengths for either all Golgi (G), axon-side Golgi (H) or dendrite-side Golgi (I) in *gmap* mutant neurons. These frequency distributions of "real data" are compared to frequency distributions generated from random angle data (yellow) that would be expected by chance if there were no preference for microtubules to be nucleated in a particular direction. Goodness of fit Chi-squared tests were used for the comparisons, with the random angle data being used as the expected values; p values are shown. N=41 and 48 axon-side and dendrite-side Golgi stacks, respectively, from 24 neurons. **(K)** Graph compares the frequency distributions of resultant vector lengths for axon-side Golgi from control w1118 neurons and *gmap* mutant neurons. A Kolmogorov-Smirnov test was used to compare the distributions. N=42 and 41 Golgi stacks for control w1118 neurons and *gmap* mutant, respectively. **(L)** Graph compares the frequency distributions of resultant vector lengths for axon-side Golgi from CLASP-RNAi and *gmap* mutant neurons. A Kolmogorov-Smirnov test was used to compare the distributions. N=33 and 41 Golgi stacks for CLASP-RNAi and *gmap* mutant, respectively. Related to Figure 4.