Organ growth in animals is coupled to body growth in complex ways that are specific for both the organ and species (Huxley and Teissier, 1936). We first sought to determine the relationship between growth of the wing and body in Drosophila melanogaster. Although previous work has studied this relationship, none have provided a quantitative description of it. In this study, we focused on growth during the 36 hr-long early-to-late third instar stage since this stage experiences linear-like growth, and its termination coincides with growth cessation.

We measured body size by both wet weight and volume. As expected, measurements of body weight and body volume showed a strong correlation (Figure 1—figure supplement 1). To measure wing pouch volume, we generated a 3D stack of confocal microscopic sections of the wing disc, and we used morphological landmarks (tissue folds) to demarcate the border separating the wing pouch from the surrounding notum-hinge (Figure 1—figure supplement 2). We validated the efficacy of this method by comparing the landmark-defined boundary to the expression boundary of the vg gene (Kim et al., 1996). The landmark method gave wing pouch measurements that were within 95.5% of measurements made by vg expression (Figure 1—figure supplement 3).

Beginning at 3.0 days after egg laying (AEL), we measured third instar larval body weight every 12 hr until the larva-pupa transition. Larval body weight increased linearly from 3.0 to 4.0 days AEL, followed by a 12 hr period of slower growth, and thereafter weight remained constant (Figure 1B). The time point at which larvae stopped growing (4.5 days AEL) coincided with the time at which they stopped feeding and underwent a 12 hr non-feeding stage (Slaidina et al., 2009). We also monitored weight as larvae underwent their transition into pupae. Weight remained constant during the one-hr-long white pre-pupal (WPP) stage and also one hr later (WPP + 1 stage; Figure 1C).

We measured wing disc growth for 36 hr during the early-to-late third instar stage. Wing pouch volume appeared to increase linearly over time and continued to grow during the non-feeding larval stage (Figure 1D). Growth of the wing pouch ceased at the WPP stage (Figure 1E). End-of-growth of the wing pouch was confirmed by phospho-histone H3 (PHH3) staining, which marks mitotic cells. At the third instar larval stage, dividing cells were observed throughout the wing pouch (Figure 1—figure supplement 4A and B), whereas at the WPP stage, dividing cells were only found in a narrow zone where sensory organ precursor cells undergo two divisions to generate future sensory organs (Nolo et al., 2000 Figure 1—figure supplement 4C and D).

We also measured growth of the hinge/notum domain of the wing disc during the early-to-late third instar. A similar linear-like growth trajectory was observed for the notum-hinge as for the wing pouch, although the hinge/notum stopped growing during the non-feeding stage (Figure 1—figure supplement 5A and B). Overall, our volumetric measurements are consistent with earlier studies that found wing disc growth is linear-like, as measured by cell number, during the mid-to-late third instar (Fain and Stevens, 1982; Graves and Schubiger, 1982).

The scaling of organ growth relative to body growth during development is known as ontogenetic allometry. For most animal species, allometric growth of organs follows a power law (Huxley and Teissier, 1936), such that logarithmic transformation of the organ and body size measurements fits a linear relationship (Figure 1F). When the organ grows at the same rate as the body, it exhibits isometric growth (Huxley and Teissier, 1936). When the organ grows at a faster or slower rate than the body, it has positive or negative allometric growth, respectively (Figure 1F). Allometric organ growth in holometabolous insects such as Drosophila presents a special situation arising from the fact that many adult organs derive from imaginal discs, which are non-functional in larvae. For this reason, there are fewer constraints on relative scaling, and allometric growth of imaginal discs are potentially freer to deviate from simple scaling laws. For example, in the silkworm, its wing disc grows linearly with its body while the larva feeds, but then continues its linear growth after larvae have ceased feeding (Williams, 1980). Thus, its allometric growth has two phases: the first is isometric and the second is positively allometric.

Since ontogenetic allometric growth of the Drosophila wing disc has not been studied, we plotted wet-weight body measurements versus wing pouch volume (Figure 1G). As with silkworms, allometric growth of the wing pouch had two phases, both of which showed positive allometry. The inflection point was the time when larvae ceased feeding. Allometric growth of the notum-hinge also exhibited two phases, although growth in the second phase was more limited than that observed for the wing pouch (Figure 1—figure supplement 5C). Therefore, allometric growth control of the wing imaginal disc appears to be composed of multiple mechanisms.

One mechanism of wing growth control is through the atypical cadherin proteins Fat and Ds. Both are type I transmembrane proteins with extensive numbers of extracellular cadherin domains: 34 in Fat and 27 in Ds (Figure 2A). Qualitative measurements of ds gene expression found that cells transcribe the gene at different levels depending upon their position in the wing disc (Strutt and Strutt, 2002; Ma et al., 2003). We confirmed that there is graded transcription across the pouch by using single molecule fluorescence in situ hybridization (smFISH) (Figure 2—figure supplement 1A). A model hypothesized that this transcriptional gradient generates a Ds protein gradient across the wing pouch, and the gradient regulates growth by inducing Fat signaling in cells (Pan, 2010). If the Ds gradient becomes flattened, it leads to growth cessation.

If correct, the model predicts that the Ds protein gradient should become shallow as the wing pouch reaches its final size. To test this, we used quantitative confocal microscopy to measure endogenous Ds protein tagged with GFP at its carboxy-terminus (Figure 2A). Wing discs were co-stained with antibodies directed against Wg and Engrailed (En) proteins, which mark the wing pouch midlines (Figure 2—figure supplement 2A and B). Focusing on the mid-to-late third instar stage, we measured Ds-GFP levels along these two midlines to gain a Cartesian perspective of the wing pouch expression pattern. Image processing via surface detection enabled us to specifically measure Ds-GFP present in the wing pouch (disc proper) without bleed-through from Ds-GFP in the overlying peripodial membrane or signal distortion due to tissue curvature (Figure 1—figure supplement 2, Figure 2—figure supplement 2C).

There was a graded distribution of Ds-GFP along both anterior-posterior (AP) and dorsal-ventral (DV) axes of the wing pouch. Ds was high near the pouch border and low at the center of the pouch (Figure 2C and D). The gradient was asymmetric along the AP axis, being lower along the anterior pouch border than posterior border. As the pouch grew larger, the Ds gradient appeared to become progressively shallower. When we normalized all of the Ds-GFP profiles to their corresponding pouch sizes, the profiles along the AP axis collapsed together (Figure 2E). In contrast, along the DV axis the normalized profiles remained distinct because both maximum and minimum limits of Ds-GFP progressively diminished as the wing pouch grew (Figure 2F).

We next turned to quantitative analysis of Fat protein expression. Fat was thought to be uniformly expressed in the wing pouch, although it had also been described as enriched along the DV midline (Garoia et al., 2000; Mao et al., 2009). We measured endogenous Fat protein tagged at its carboxy-terminus with GFP (Figure 2A and Figure 2—figure supplement 2D and E). Surprisingly, Fat-GFP had a graded distribution along both the AP and DV axes of the wing pouch; low near the pouch border and high at the center of the wing pouch (Figure 2G and H). The gradient profile was opposite to the one we observed for Ds-GFP. As the pouch grew in size, the Fat gradient appeared to grow shallower, and it became flat along the AP axis at the WPP stage. When we normalized all the Fat-GFP profiles to their corresponding pouch sizes, the profiles did not collapse (Figure 2I and J). The minimum limit of Fat-GFP was conserved but the maximum limit of Fat-GFP progressively diminished as the wing pouch grew.

The graded distribution of Fat protein was surprising since it was reported that fat gene transcription is uniform (Garoia et al., 2000), which we confirmed by smFISH (Figure 2—figure supplement 1B). Therefore, we considered the possibility that the gradient is generated by a post-transcriptional mechanism. To test the idea, we expressed Fat under the control of an UAS promoter. Transcription was activated by da-Gal4 (Figure 2K), which is uniformly expressed in Drosophila tissues (Gilbert et al., 2006). da-Gal4 also activated transcription of UAS-Bazooka-mCherry as a control. Bazooka-mCherry protein distribution was uniform along the AP axis, reflecting its faithful expression downstream of da-Gal4 (Figure 2L). However, Fat protein was graded in a similar pattern to endogenous Fat (Figure 2L). Thus, the Fat gradient is generated by a post-transcriptional mechanism.

The kinase Fj is known to target Fat protein within cells and so it was possible that the Fat protein gradient was generated by Fj. However, the distribution of Fat was unchanged in a fj mutant (Figure 2—figure supplement 3C). Additionally, Ds levels were unchanged in the fj mutant (Figure 2—figure supplement 3D), and there was no difference in wing pouch volume in fj mutants compared to wildtype (Figure 2—figure supplement 3E).

Ds is known to physically interact with Fat protein through their extracellular and intracellular domains (Ma et al., 2003; Hale et al., 2015; Fulford et al., 2023). These heterophilic interactions affect Fat protein levels within cells (Ma et al., 2003). To test the effect of Ds on formation of the Fat gradient, we examined Fat-GFP distribution in the wing pouch of a ds mutant. The level of Fat-GFP at the wing pouch center was identical to wildtype but the level of Fat-GFP near the pouch border was abnormally high (Figure 2M). Furthermore, we did not observe the flattened Fat-GFP profile at the WPP stage (Figure 2—figure supplement 3A). Instead, the Fat-GFP profile remained weakly graded at the WPP stage and was flattened somewhat more by the WPP + 1 stage (Figure 2—figure supplement 3B).

These observations conflict with a previous study showing that junctional stability of Fat within wing disc cells is reduced in a ds mutant (Hale et al., 2015). However, Ma et al., 2003 observed upregulation of Fat along cell junctions between ds mutant cells of the pupal wing, which is consistent with our observations of Fat-GFP upregulation near the pouch border of a ds mutant disc (Figure 2M).

The Ds gradient scales with the size of the wing pouch as measured along the length of the AP axis of symmetry (Figure 2E). Since the wing pouch can be approximated as an ellipse, the scaling we measured was possibly one related to pouch area. However, the wing pouch is a 3D structure and so Ds gradient scaling might be coupled to wing volume rather than area. To test this idea, we altered the dimensions of the wing pouch without changing its volume. Perlecan is a basement membrane proteoglycan required for extracellular matrix functionality across many tissues (Gubbiotti et al., 2017). Knockdown of perlecan expression by RNAi causes wing disc cells to become thinner and more elongated due to the altered extracellular matrix in the wing disc (Kirkland et al., 2020). We used a Gal4 driver under the control of the actin5C promoter (actin5C-Gal4) to knock down trol gene expression via UAS-RNAi. The trol gene encodes perlecan. We measured the dimensions of the wing pouch at the WPP stage and observed that actin5C>trol(RNAi) caused a reduction in the area of the wing pouch and an increase in the thickness of the wing pouch (Figure 3A and B). The overall change in pouch dimensions had no effect on wing pouch volume (Figure 3C). We then measured the Ds-GFP profile at WPP stage and found actin5C>trol(RNAi) had no effect on the gradient (Figure 3D). Thus, Ds appears to scale with the volume and not the area of the wing pouch. We also examined Fat-GFP to see if its dynamics were altered, and found the gradient flattened normally at the WPP stage (Figure 3E).

The Ds gradient might directly scale to wing pouch volume or it might be a consequence of scaling to another feature such as cell number, which correlates with wing volume. To test this possibility, we decreased cell number while keeping total volume constant by over-expressing the cell cycle inhibitor RBF. Using a Gal4 driver under the control of the engrailed (en) promoter, a UAS-RBF transgene was overexpressed in the posterior (P) compartment of the wing disc. Previous work had found such overexpression resulted in half the number of cells in the P compartment but they were twofold larger in size, such that the P compartment size was unchanged relative to the anterior (A) compartment (Neufeld et al., 1998). We confirmed that en >RBF generated fewer and larger P cells, and the ratio of P/A compartment ratio was unchanged (Figure 3F and G). Nevertheless, the Ds gradient in the P compartment at WPP stage was indistinguishable from wildtype (Figure 3H). The Fat gradient also flattened normally at the WPP stage (Figure 3I). In summary, the Ds gradient appears to directly scale to wing pouch volume as the pouch grows in size. Fat gradient flattening also appears to be coupled to pouch volume rather than cell number or pouch area. Therefore, the dynamics of these atypical cadherins are coupled to a global physical feature of the wing.

We next wanted to understand how Fat and Ds regulate growth of the wing pouch. Prior work had shown that loss-of-function fat mutants delay the larva-pupa transition and overgrow the wing disc (Bryant et al., 1988). We applied our quantitative growth analysis pipeline on loss-of-function fat mutants. Mutant larvae did not stop growing at 4.5 days AEL as wildtype larvae did, but continued to increase in weight for another day until they entered the non-feeding stage and pupated (Figure 4A and B). The mutant larval notum and wing pouch grew at a faster rate than normal, and at the larva-pupa transition, the wing pouch continued to grow (Figure 4C and D and Figure 4—figure supplement 1A and B).

Loss-of-function ds mutants also delayed the larva-pupa transition but only by 12 hr. Mutant larvae continued to gain weight past the wildtype plateau, and they only ceased weight gain at the larva-pupa transition (Figure 4A and B). The mutant larval notum and wing pouch grew at a rate comparable to those of wildtype, but their growth period was extended (Figure 4C and Figure 4—figure supplement 1A). While the mutant notum ceased to grow prior to the larva-pupa transition, the wing pouch only stopped growing at the WPP + 1 stage (Figure 4D and Figure 4—figure supplement 1B).

Allometric growth of the fat and ds mutant wing pouch was significantly different from wildtype (Figure 4E). In wildtype, there are two linear phases to wing allometric growth (Figure 1G). Allometric growth of the ds and fat mutant wing pouches had a first phase that was more extended than normal and a second phase that was less extended than normal (Figure 4E). Similar trends were observed for allometric growth of the notum in these mutants (Figure 4—figure supplement 1C).

Fat and Ds proteins are extensively expressed throughout the developing Drosophila body, and their loss has clear effects on overall body growth (Mahoney et al., 1991; Clark et al., 1995). Therefore, we wished to know what the wing-autonomous effects of Fat and Ds are on allometric growth. We used the nubbin-Gal4 (nub-Gal4) driver, which is expressed in the wing pouch and distal hinge (Zirin and Mann, 2007), to knock down gene expression using UAS-RNAi (Figure 5A). RNAi against the ds gene resulted in near-complete depletion of Ds protein in the wing pouch (Figure 5—figure supplement 1A and B). As expected, knockdown of Ds in the wing pouch had no effect on body growth of larvae, and animals reached a normal final weight setpoint (Figure 5—figure supplement 2A and B). Thus, ds is not required in the wing to limit body growth. Notum growth in nub >ds(RNAi) animals was similar to controls, which would be expected if the gene was not required in the wing pouch for notum growth control (Figure 5—figure supplement 2D–F). However, the nub >ds(RNAi) wing pouch grew at a faster rate than normal. The wing pouch was 28% larger at the WPP stage and continued to grow until it was 42% larger at the WPP + 1 stage (Figure 5B and C).

Allometric growth of the wing pouch was also examined (Figure 5—figure supplement 2C). Knockdown of Ds in the wing pouch caused the entire allometric relationship to shift such that nub >ds(RNAi) wings were consistently bigger for their given body size. Thus, it appears that Ds is required in the wing pouch to tune down the allometric relationship of the wing to the body.

We next used nub-Gal4 driving UAS-GFP(RNAi) to knockdown GFP-tagged endogenous Fat in the wing pouch. There was virtually complete elimination of Fat-GFP expression (Figure 5—figure supplement 1C and D). Correcting for background fluorescence, we estimated that less than 5% of Fat-GFP remained after RNAi treatment (Figure 5—figure supplement 3A). Knockdown of Fat-GFP had a weak effect during mid third instar (Figure 5D), but the wing pouch was 15% larger than normal by the WPP stage, and 42% larger than normal by the WPP + 1 stage (Figure 5E and Figure 5—figure supplement 2G). The nub >fat-GFP(RNAi) wing pouch was of comparable size to the nub >ds(RNAi) wing pouch at WPP + 1 stage (Figure 5—figure supplement 2H). Adult wings from nub >fat-GFP(RNAi) individuals were also 40% larger than controls (Figure 5—figure supplement 2I). Thus, Fat and Ds are autonomously required to inhibit wing pouch growth during the mid-to-late third instar and its transition to the pupal stage.

To further explore the autonomous requirements for Fat and Ds, we used ap-Gal4 to specifically drive ds RNAi in the dorsal (D) compartment of the wing disc (Figure 5F). This allowed us to measure growth effects by comparing the affected D compartment to the unaffected ventral (V) compartment, serving as an internal control. As expected, RNAi resulted in undetectable Ds protein in the D compartment, though it was detected in the V compartment (Figure 5—figure supplement 1E). We measured the final set-point size of each compartment in the wing pouch. Knockdown of ds caused the D/V ratio of compartment size to increase by 60% (Figure 5G). Overall wing pouch size was unaffected by ap >ds(RNAi) knockdown (Figure 5H) since there are mechanisms in which the compartments sense overall pouch size, resulting in undergrowth of one compartment when there is overgrowth in the other compartment (Diaz-Benjumea and Cohen, 1993). We also used an en-Gal4 driver to specifically generate RNAi of fat or ds in the posterior (P) compartment of the wing disc (Figure 5K). RNAi resulted in strong knockdown of Fat and Ds proteins in the P compartment but not the anterior (A) compartment (Figure 5—figure supplement 1F and G and Figure 5—figure supplement 3B). After knockdown, the P/A ratio of compartment size was increased by 63% and 23% in en >ds(RNAi) and en >fat(RNAi) wing pouches, respectively (Figure 5L). en >fat ds(RNAi) showed an increase in the P/A ratio by 193%, an effect greater than the sum of effects from knockdown of each individual gene alone (Figure 5L). en >fat(RNAi), en >ds(RNAi), and en >fat ds(RNAi) affected overall wing pouch size to a lesser extent, with respective 10%, 19%, and 32% increases (Figure 5M).

In conclusion, we found that Fat and Ds have autonomous effects on wing pouch growth consistent with fat and ds mutant phenotypes. However, the autonomous RNAi knockdown phenotypes were less severe than those of whole-body loss of fat and ds, suggesting there might be additional, non-autonomous requirements for Fat/Ds in wing growth.

To determine whether Ds regulates cell number, cell size or both, we segmented cells in the imaged wing pouch of ap >ds(RNAi) WPP animals using E-cadherin tagged with mCherry to outline the apical domains of cells. We used a computational pipeline that segments imaginal disc cells with >99% accuracy (Gallagher et al., 2022). The number of ds(RNAi) cells in the D compartment was 42% higher than the wildtype control (Figure 5I). The average size of ds(RNAi) cells in the D compartment, as measured by apical domain area, was unchanged (Figure 5J). Thus, the enhanced size of ds(RNAi) wing pouches is primarily driven by an increase in cell number.

Ds might autonomously regulate wing cell number by stimulating apoptosis or by inhibiting cell proliferation. There is little to no apoptosis reported to occur in the third instar larval wing pouch (Milán et al., 1997), which we confirmed by anti-caspase 3 staining (data not shown). To monitor cell proliferation, we developed a method to infer the average cell cycle time from fixed and stained wing discs. Discs were stained with anti-PHH3, which exclusively marks cells in M phase of the cell cycle. During the third instar larval stage, sporadic PHH3-positive cells are uniformly distributed throughout the wing pouch, as expected for uniform asynchronous proliferation (Figure 1—figure supplement 5A and B). Using manual and computational segmentation of the images, we identified and counted the number of wing cells in M phase and also counted the total number of wing cells. The ratio of number of M-phase cells to total cells is known as the mitotic index (MI). We found the average time for third instar larval wing pouch cells to transit M phase to be 20.5 min or 0.34 hr (Figure 6—figure supplement 1), which is highly similar to previous measurements (Wartlick et al., 2011). Therefore, the average cell cycle timeT_CC can be inferred asTcc=0.34hrMI

We then estimated the average cell cycle time for the wing pouch at various times during the third instar larval stage. It had been previously reported that there was a progressive lengthening of the cell cycle over developmental time (Fain and Stevens, 1982; Wartlick et al., 2011). Our results corroborated these reports but also expanded upon them, finding that the average cell cycle time linearly scales with wing pouch volume during the mid-to-late third instar (Figure 6A). The estimated scaling coefficient (slope of the linear fit) predicts that the cell cycle length increases 16 hr as wing pouch volume increases by 1 nL.

We then estimated T_cc for the wing pouch in which ds was knocked down by nub-Gal4 driven RNAi. The nub >ds(RNAi) cell cycle time linearly scaled with wing pouch volume (Figure 6B). However, the scaling coefficient for ds(RNAi) cells was much smaller than wildtype (Figure 6—source data 1; p=6.2 × 10^–4). This meant that cell cycle duration was not lengthening as rapidly as normal and so cell cycle times were consistently shorter. We also examined the scaling relationship between cell cycle time and wing pouch volume when Fat was knocked down by nub >fat-GFP(RNAi) (Figure 6C). The scaling coefficient for nub >fat-GFP(RNAi) cells was also much smaller than wildtype (Figure 6—source data 1; p=3.1 × 10^–4).

The diminished cell cycle scaling coefficient caused by Fat and Ds knockdown could possibly account for their larger wing pouch size (Figure 5C and E). To more fully explore this possibility, we adapted a modeling framework (Wartlick et al., 2011) that relates instantaneous growth rates of cells to tissue growth. Assuming exponential cell growth, the average cell cycle time can be converted to instantaneous cell growth rate r, using the formular=ln⁡(2)Tcc

We plotted our T_cc measurements as a function of larval age and found that the average cell cycle time linearly scales with age (Figure 6—source data 2). Using this fit, we converted T_cc to r as a function of time. We then used this relationship to simulate growth in cell number over time. Assuming that cell size remains invariant, cell number proportionally converts to tissue volume, allowing us to simulate growth in wing pouch volume over time. We compared model simulations to our measured volumes of the wing pouch over time (Figure 6—figure supplement 2). Strikingly, the model predictions were very close to the observed pouch growth for wildtype wings and for wings in which either Fat or Ds were knocked down by RNAi. This agreement between quantitative model predictions and experiment indicates that during the mid-to-late third instar, cell cycle control primarily accounts for wing pouch growth, and the effects of Fat/Ds on wing pouch growth are primarily exerted by their regulation of cell cycle dynamics.

In summary, during the third instar, Fat and Ds regulate a mechanism that couples the duration of the cell cycle to overall wing pouch size. They are not essential for the coupling mechanism itself but rather they tune the mechanism so as to ensure the growth rate of the wing is attenuated relative to the body. This coordinates the relative scaling of the wing to the final body size.

Fat and Ds regulate the mechanism by which the cell cycle progressively lengthens as wing size increases, ensuring a proper allometric growth relationship between wing and body. As the wing grows in size, the complementary gradients of Fat and Ds protein across the wing pouch progressively diminish in steepness. These observations suggest a hypothesis that connects the two; namely, wing growth progressively slows because Fat/Ds expression gradients shallow.

To test the hypothesis, we first altered the Ds gradient. Using nub-Gal4, which drives expression high near the center of the wing pouch and low near the pouch border (Figure 7—figure supplement 1A and B), we misexpressed Ds with UAS-ds (Figure 7A). This drastically altered the Ds protein gradient (compare Figure 2C vs. Figure 7B and Figure 7—figure supplement 1C). The altered Ds gradient caused a change in the Fat gradient (Figure 7C). The gradient peak became skewed to the anterior, and the gradient did not flatten at the WPP stage. We then measured larval and wing pouch growth (Figure 7—figure supplement 1D–G). The growth curve of the third instar wing pouch was indistinguishable from wildtype, and wing growth ceased normally at the WPP stage of the larva-pupa transition (Figure 7—figure supplement 1F and G). This result suggests that drastically altering the Ds gradient does not impact wing growth.

We further manipulated the Ds gradient so that it was amplified relative to wildtype. This was done by overexpressing Ds using a Trojan-Gal4 driver. Trojan-Gal4 transgenes are constructed with a splice acceptor sequence followed by the T2A peptide, the Gal4 open-reading frame, and a stop codon (Diao et al., 2015). When the transgene is inserted into the intron of an endogenous gene, it simultaneously inactivates the endogenous open reading frame and hijacks the gene to produce Gal4. When such a Trojan-Gal4 construct drives a UAS version of the disrupted gene, it amplifies expression levels while retaining endogenous transcriptional control (Lee et al., 2018). We crossed a line with Trojan-Gal4 inserted into the ds gene (Lee et al., 2018) to a UAS-ds line. Ds expression in the wing pouch was strongly amplified while its gradient pattern was preserved (Figure 7D and Figure 7—figure supplement 2A). In such ds >Ds wing pouches, the Fat protein gradient resembled wildtype (Figure 7E and F). Interestingly, the wing pouch was approximately 12% larger than wildtype at the WPP stage, as well as in the adult (Figure 7—figure supplement 2B and C). We also measured the scaling coefficient between cell cycle time and wing pouch volume for ds >Ds (Figure 7—figure supplement 2D). Although the scaling coefficient was slightly smaller than wildtype, it was not significant (Figure 7—source data 1; p=0.108). Thus, graded overexpression of Ds only weakly affects growth. Overall, cells appear to be relatively insensitive to the levels and pattern of Ds expression in terms of their growth.

Alternatively, it was possible that growth is controlled by the flattening of the Fat gradient in the wing pouch, since flattening normally occurs at the WPP stage when growth stops. To test this idea, we expressed HA-tagged Fat using the nub-Gal4 driver without eliminating endogenous Fat-GFP (Figure 7G and Figure 7—figure supplement 3A). We monitored both transgenic and endogenous sources of Fat protein, and found both were distributed across the wing pouch in a gradient that was highest at the pouch center (Figure 7H, I). Strikingly, both transgenic and endogenous Fat gradients did not diminish in magnitude as larvae approached pupariation. Moreover, the gradients did not flatten at the WPP stage but only did so at the later WPP +1 stage. We then examined the growth properties in nub >fat HA animals. The relationship between the cell cycle time in the nub >fat HA wing pouch and wing pouch size was indistinguishable from wildtype (Figure 7J and Figure 7—source data 1). This was consistent with the observation that final wing pouch size in nub >fat HA animals was normal (Figure 7—figure supplement 3B). In summary, Fat and Ds gradient dynamics do not appear to play a significant role in wing growth control.

All newly created materials from this study are freely available to those who request them from the corresponding author. There are no restrictions on access if requests are compliant with federal regulations. Newly created code has been deposited and is freely available on Github (https://github.com/andrewliu321/ProteinIntensity, copy archived at Liu, 2023a and https://github.com/andrewliu321/LarvaSeg, copy archived at Liu, 2023b).

All source data associated with the figures and figure supplements have been deposited in the open-access Dryad repository at https://doi.org/10.5061/dryad.0k6djhb8d.

Drosophila melanogaster were raised at 25 °C under standard lab conditions on molasses-cornmeal fly food. Only males were analyzed in experiments. For staged collections, 100 adult females were crossed with 50 adult males and allowed to lay eggs for 4 hr (6 pm to 10 pm) in egg-laying cages with yeast paste. First-instar larvae that hatched between 7 and 9 pm the following day were collected, thus synchronizing age to a 2-hr hatching window. Approximately 200–300 larvae were transferred into a bottle. Third-instar larvae were collected from the bottle every 12 hours at 8 am and 8 pm, from 3.5 days after egg laying (AEL) until pupariation (i.e. 5 days for wildtype). We also collected animals at the white-prepupae (WPP) stage and the WPP + 1 stage. The WPP + 1 stage is 1 hr after the WPP stage onset, when the pupal case begins to turn brown.

Collected animals were weighed in batches of five individuals to account for instrument sensitivity. They were individually photographed using a Nikon SMZ-U dissection scope equipped with a Nikon DS-Fi3 digital camera at 1920x1200 resolution with a 8 µm x-y pixel size. Length and width were measured in a custom-built Matlab pipeline as follows. The outline of the body was recorded with manual inputs. The midline was calculated by the Matlab bwskel function and manually corrected. The midline was recorded as the length. At every pixel along the midline, a perpendicular line was computed, and the width recorded. The mean width was then calculated. We approximated the volume of each larva by treating it as a cylinder and using the measured length and average width of the larva for length and diameter, respectively.

Unless otherwise stated, wildtype genotype strain corresponded to w¹¹¹⁸, which is an eye pigment mutation present in the background of all other genotype strains used in this study. fat-GFP (Hale et al., 2015) and ds-GFP (Brittle et al., 2012) are tagged at their ORF carboxy-termini within the respective endogenous genes. This had been done using homologous recombination and pRK2 targeting vectors. The vg 5xQE-dsRed transgenic line expresses fluorescent protein specifically in wing pouch cells (Kim et al., 1996; Zecca and Struhl, 2007). To mark proneural cells in the wing pouch, we used sfGFP-sens (Giri et al., 2020), which is a N-terminal tag of GFP in the senseless (sens) gene. To count cell numbers we used either E-cadherin-GFP, which has GFP fused at the carboxy-terminus of the ORF in the endogenous shotgun gene, or E-cadherin-mCherry, which has mCherry fused at the endogenous carboxy-terminus (Huang et al., 2009).

Loss of function fat alleles used were: fat⁸, with a premature stop codon inserted at S981; and fat^G-rv, with a premature stop codon at S2929 (Matakatsu and Blair, 2006). Loss of function ds alleles used were: ds^33k, derived by X-ray mutagenesis and expected to produce a truncated protein without function; and ds^UAO71, derived by EMS mutagenesis and presumed to be amorphic (Clark et al., 1995; Adler et al., 1998). Loss of function fj alleles used were: fj^p1, in which P{LacW} is inserted into the 5’ UTR; and fj^d1 in which sequences accounting for the N-terminal 100 amino acids are deleted. For all experiments using loss of function mutants, we crossed heterozygous mutant parents to generate trans-heterozygous mutant offspring for study. This minimized the impact of secondary mutations on phenotypes.

To measure expression driven by nub-Gal4 (Bloomington Drosophila Stock Center BDSC # 42699), we used UAS-GFP-NLS (BDSC # 4776). To amplify the Ds expression gradient, ds-Trojan-Gal4 (BDSC # 67432) flies were crossed to fat-GFP; UAS-ds flies. UAS-ds (Matakatsu and Blair, 2004) was a gift from Ken Irvine. Ds-Trojan-Gal4 is an insertion of the T2A-Gal4 cassette into the endogenous ds gene such that it expresses Gal4 under ds control and inactivates the endogenous ds open reading frame (Lee et al., 2018). To alter the Ds expression gradient, fat-GFP, nub-Gal4 flies were crossed to fat-GFP; UAS-ds flies. To alter the Fat expression gradient, fat-GFP, nub-Gal4 flies were crossed to fat-GFP, UAS-fat-HA flies. UAS-fat-HA expresses Fat with a C-terminal HA tag (Sopko et al., 2009). To test whether Fat expression is transcriptionally regulated, fat-GFP; da-Gal4 flies were crossed to fat-GFP, UAS-fat-HA; UAS-Bazooka-mCherry. Da-Gal4 (BDSC # 55850) and UAS-Bazooka-mCherry (BDSC # 65844) were used.

To knockdown Fat in the wing pouch and distal hinge, fat-GFP, nub-Gal4 flies were crossed to fat-GFP; UAS-GFP-RNAi flies (BDSC # 9330). To knockdown Ds in the wing pouch and distal hinge, fat-GFP, nub-Gal4 flies were crossed to fat-GFP; UAS-ds-RNAi flies. The ds RNAi vector is a TriP Valium 20 (BDSC # 32964). To knockdown Fat specifically in the posterior compartment, fat-GFP, en-Gal4 flies were crossed to fat-GFP; UAS-fat-RNA flies. The RNAi vector is a TriP Valium 20 (BDSC # 34970). En-Gal4 flies were from BDSC # 30564. To knockdown Ds specifically in the posterior compartment, ds-GFP, en-Gal4 flies were crossed to ds-GFP; UAS-ds-RNAi flies. To knockdown both genes, fat-GFP; UAS-fat-RNAi, UAS-ds-RNAi were crossed to fat-GFP, en-Gal4 flies. To knockdown Ds specifically in the dorsal compartment, ds-gfp, ap-Gal4 flies (BDSC # 3041) were crossed to E-cadherin-mCherry; UAS-ds-RNAi flies.

To alter cell number, en-Gal4 flies were crossed to UAS-RBF (BDSC # 50747). The crosses also carried either ds-GFP or fat-GFP so that resulting animals had two copies of each gene. To alter wing disc area and thickness, actin5c-Gal4 (BDSC # 3954) flies were crossed to UAS-trol-RNAi flies. The RNAi line is a TriP Valium 10 (BDSC # 29440). The crosses also carried either ds-GFP or fat-GFP so that resulting animals had two copies of each gene.

Wing discs were fixed in 4% (w/v) paraformaldehyde in PBS at room temperature for 20 min and washed three times for 5–10 min each with PBS containing 0.1% (v/v) Triton X-100 (PBSTx). The following primary antibodies were used: rat anti-Ds (1:1,000, a gift from Helen McNeill), mouse anti-Wg (1:1000, Developmental Studies Hybridoma Bank DHSB # 4D4), mouse anti-En (1:15, DHSB # 4D9), rat anti-HA (1:1000, Roche), rat anti-E-cadherin (1:10, DHSB # Dcad2), and rabbit anti-PHH3 (1:400, Sigma # H0412). All antibodies were diluted in PBSTx and 5% (v/v) goat serum and incubated overnight at 4 °C. After five washes in PBSTx, discs were incubated at room temperature for 90 min with the appropriate Alexa-fluor secondary antibodies (Invitrogen #’s A11035, A48255, or A48265) diluted 1:200 in PBSTx and 5% goat serum. After three washes in PBSTx, between 5 and 40 wing discs were mounted in 40 µL of Vectashield Plus between a 18x18 mm number 1.5 coverslip (Zeiss # 474030-9000-000) and a 24x60 mm number 1.5 coverslip (VWR # 48393–251). Mounting between two coverslips allowed the samples to be imaged from both directions. The volume of mounting media used was critical so that discs were not overly compressed by the coverslips. Compression led to fluorescent signals from the peripodial membrane to be too close in z-space to the disc proper, making it difficult to distinguish the two during image processing.

A set of 45 non-overlapping oligonucleotide probes complementary to the GFP sense sequence were labeled with Alexa 633. The set is described in Bakker et al., 2020. We used the protocol of Bakker et al., 2020 to detect fat-GFP and ds-GFP mRNAs in wing discs. Discs were counterstained with DAPI to visualize nuclei and mounted in Vectashield.

Wing discs were dissected from third instar larvae bearing two copies of E-cadherin-GFP. These were cultured ex-vivo in live imaging chambers following the protocol exactly as described in Gallagher et al., 2022. The samples were imaged using an inverted microscope (Leica DMI6000 SD) fitted with a CSU-X1 spinning-disk head (Yokogawa) and a back-thinned EMCCD camera (Photometrics Evolve 512 Delta). Images were captured every 5 min with a 40 x objective (NA = 1.3) at 512x512 resolution with a 0.32 µm x-y pixel size.

All experiments with fixed tissues were imaged using a Leica SP8 confocal microscope. Whole wing discs were imaged using a 10 x air objective (NA = 0.4) and 0.75 x internal zoom at 1024x1,024 resolution, with a 1.52 µm x-y pixel size. Wing pouches were imaged using a 63 x oil objective (NA = 1.4) and 0.75 x internal zoom at 1024x1,024 resolution, with a 0.24 µm x-y pixel size and 0.35 µm z separation. Scans were collected bidirectionally at 600 MHz and were 3 x line averaged in the following channels to detect: anti-PHH3 (blue), Fat-GFP and Ds-GFP (green), anti-Wg and anti-En (red), and anti-HA or anti-Ds or anti-E-cadherin (far red). Wing discs of different genotypes and similar age were mounted on the same microscope slide and imaged in the same session for consistency in data quality.

Raw images were processed using a custom-built Matlab pipeline with no prior preprocessing. The pipeline consists of several modules: (1) peripodial membrane removal, (2) wing disc, pouch, and midline segmentation, (3) volume measurement, (4) fluorescence intensity measurement, (5) cell segmentation, (6) mitotic index measurement.

A modeling framework to simulate wing disc growth was previously developed to relate cell proliferation to tissue growth (Wartlick et al., 2011). We adapted this framework using our measurements for average cell cycle duration and for wing pouch volume. The average cell cycle time calculated as described in the previous section was plotted against larval age (time in hr). Linear regression of the data generated an equation that relates cell cycle time as a function of larval age (Figure 6—source data 2).Tcc=T0+β1t

where t is the larval age in hr, and T0 is the cell cycle time at t=0. The linear fits were significant (p<10^–4 for all fits). Assuming exponential cell growth, we converted average cell cycle time to instantaneous cell growth rate rr=ln⁡(2)Tcc

Combining the two equations allowed us to estimate the instantaneous cell growth rate at varying time points of larval age. We then used these estimates to simulate the growth of wing pouch volume using the following equation:Vt=(1+rt)×Vt−Δt

where Vt is wing pouch volume at time t, Vt-∆t is wing pouch volume at the earlier time t-∆t, and rt is the instantaneous growth rate at time t. For all simulations, we used Δt=1hr. For each wing pouch growth simulation, we initialized at a starting volume, V0 , which was taken from the earliest average wing pouch volume measurement made for wildtype and RNAi samples (Figure 5A–D). To estimate the error of these growth simulations, the uncertainty in the fitted slope between cell cycle duration and time using linear regression were propagated through the growth rate estimates onto pouch volume over time.

Adult males aged 1–2 days from uncrowded vials were collected. The right wing of each animal was dissected and mounted with the dorsal side up. They were individually photographed using a Nikon SMZ-U dissection scope equipped with a Nikon DS-Fi3 digital camera at 1920x1,200 resolution with a 1.4 µm x-y pixel size. Wing areas were measured by tracing the wing blade outlines in FIJI.

Samples were allocated into experimental groups according to a combination of their genotype and age. Sample sizes of replicates were not pre-determined. Sample sizes were determined to achieve either reasonable measurement precision or reasonable sampling variance. All replicates in the study are biological replicates. A biological replicate was considered to be a single larva, a cohort of larvae, a single imaged wing blade, or a single imaged wing disc, depending on the experiment. All replicate data that were collected has been included in the analysis. All experiments were repeated more than one time. Statistical tests included two-tailed Student’s t-tests to compare between genotypes. This was justified by the normal distribution of the data. We conducted linear regression modeling to fit pouch volume as an independent variable and cell cycle time as a dependent variable. To statistically test for differences between genotypes, we used a multiple linear regression model:Tcc=β0+(β1xVolume)+(β2xGenotype)+(β3xVolumexGenotype)

Genotype was entered into the model as a covariate to test for differences in intercepts of the fits. Interaction of volume x genotype was entered to test for differences in slope of the fits. Linear regression models were plotted with 95% confidence intervals.