Research Article

Neuroscience

The m⁶A reader YTHDF2 is a negative regulator for dendrite development and maintenance of retinal ganglion cells

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, China
SUSTech-HIT Joint Graduate Program, Southern University of Science and Technology, China
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, China
Department of Neurosurgery, Jinshan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Fudan University, China
Co-Innovation Center of Neuroregeneration, Nantong University, China

Feb 18, 2022

https://doi.org/10.7554/eLife.75827

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Accepted for publication after peer review and revision.

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Version of Record updated: April 4, 2022 (This version)
Version of Record updated: March 14, 2022 (Go to version)
Version of Record published: March 9, 2022 (Go to version)
Accepted Manuscript published: February 18, 2022 (Go to version)
Accepted: February 16, 2022
Preprint posted: December 7, 2021 (Go to version)
Received: November 24, 2021

1. Of interest
Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional components reduces dimensions for reinforcement learning

Huu Hoang, Shinichiro Tsutsumi ... Keisuke Toyama

Research Article Sep 27, 2023
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Abstract

The precise control of growth and maintenance of the retinal ganglion cell (RGC) dendrite arborization is critical for normal visual functions in mammals. However, the underlying mechanisms remain elusive. Here, we find that the N⁶-methyladenosine (m⁶A) reader YTHDF2 is highly expressed in the mouse RGCs. Conditional knockout (cKO) of Ythdf2 in the retina leads to increased RGC dendrite branching, resulting in more synapses in the inner plexiform layer. Interestingly, the Ythdf2 cKO mice show improved visual acuity compared with control mice. We further demonstrate that Ythdf2 cKO in the retina protects RGCs from dendrite degeneration caused by the experimental acute glaucoma model. We identify the m⁶A-modified YTHDF2 target transcripts which mediate these effects. This study reveals mechanisms by which YTHDF2 restricts RGC dendrite development and maintenance. YTHDF2 and its target mRNAs might be valuable in developing new treatment approaches for glaucomatous eyes.

Editor's evaluation

In this study, you propose a role for the m⁶A reader YTHDF2 in regulating the dendritic arbor size of retinal ganglion cells (RGCs). You show that retina-specific loss of Ythdf2 leads to the expansion of RGC dendritic arbors in the horizontal plane and a widening of the inner plexiform layer (IPL), with Ythdf2 conditional knockouts showing a modest increase in visual acuity in an optomotor assay. You point to a number of factors downstream of YTHDF2 not previously known to be involved in retinal dendritic development, and propose a role for YTHDF2 in a glaucoma model, in which loss of YTHDF2 is shown to prevent RGC loss. This study presents a careful phenotypic analysis of manipulation of YTHDF2 and provides a foundation for studies on how YTHDF2-mediated mechanisms are integrated into programs of dendritic development and RGC survival.

https://doi.org/10.7554/eLife.75827.sa0

Introduction

The mammalian retina is an ideal model system to study neuronal development and neural circuit formation. The retinal ganglion cells (RGCs) are the final and only output neurons in the vertebrate retina and their dendrites collect the electrical information concerning the visual signal from all other cells preceding them. One of the major focuses of research in the retina is to understand how RGC dendrite arborization arises during development (Prigge and Kay, 2018). Existing evidences supported that homotypic repulsion controls retinal dendrite patterning (Lefebvre et al., 2015). However, in mice which had most RGCs genetically eliminated, the dendrite size and shape of remaining RGCs appeared relatively normal (Lin et al., 2004). Thus, the fact that the dendrites of remaining RGCs did not expand to neighboring areas by the remaining RGCs supports the existence of the intrinsic limit for RGC dendrite patterning, which cooperates with the homotypic repulsion to determine the dendrite size of RGCs (Lefebvre et al., 2015). However, such intrinsic limiting mechanisms remain elusive.

Glaucoma is one of the leading causes for blindness. The major risk factors for glaucoma include increased intraocular tension. Studies have shown that glaucoma causes pathological changes in RGC dendrites before axon degeneration and soma loss were detected in different model animals (Weber et al., 1998; Shou et al., 2003; Morgan et al., 2006). Thus, elucidation of mechanisms governing RGC dendrite arbor maintenance bears clinical significance.

N⁶-methyladenosine (m⁶A) is the most widely distributed and extensively studied internal modification in mRNA (Dominissini et al., 2012; Meyer et al., 2012; Nachtergaele and He, 2018). m⁶A modification has been shown to regulate brain development and functions in the nervous system (Livneh et al., 2020; Yu et al., 2021a). By effectors, most of these studies have focused on its demethylases (‘m⁶A erasers’) and methyltransferases (‘m⁶A writers’). Since the fate of m⁶A-modified transcripts is decoded by the m⁶A-binding proteins (‘m⁶A readers’), how the readers mediate these functions and what are their neural target mRNAs remain to be elucidated. In addition, more precisely controlled spatial-temporal ablation of the m⁶A readers instead of null knockout is required to elucidate their functions and mechanisms in nervous system.

In this study, we identified an m⁶A-dependent intrinsic limiting mechanism for RGC dendrite arborization and maintenance. Conditional knockout (cKO) of the m⁶A reader YTHDF2 in the developing mouse retina increases RGC dendrite branching and improves visual acuity. YTHDF2 also mediates acute ocular hypertension (AOH)-induced RGC degeneration, the experiment model for glaucoma, and Ythdf2 cKO in the retina alleviates AOH-induced RGC dendrite shrinking and neuronal loss. The regulation of RGC dendrite development and maintenance by YTHDF2 is mediated by two distinct groups of m⁶A-modified target mRNAs which encode proteins that promote dendrite arborization during development and maintain dendrite tree during injury, respectively. Therefore, our study reveals mechanisms by which YTHDF2 restricts RGC dendrite development and maintenance, which sheds light on developing new treatment approaches for glaucomatous eyes.

Results

Knockdown of YTHDF2 leads to a robust increase of RGC dendrite branching

To examine whether m⁶A modification and its reader proteins play a role in the dendrite development, we utilized the retina as the model system. We first checked their expression patterns in the developing mouse retina. Immunostaining with a widely used m⁶A antibody demonstrated that RGCs had high m⁶A modification levels (Figure 1—figure supplement 1A). Consistent with the m⁶A distribution, the m⁶A reader YTHDF2 is highly expressed in RGCs (Figure 1A; Figure 1—figure supplement 1B). Conversely, the expression of YTHDF2 in other layers and cells of the retina is much lower or absent (Figure 1A; Figure 1—figure supplement 1B-D). Another two m⁶A readers YTHDF1 and YTHDF3 show similar expression patterns (Figure 1—figure supplement 1E, F). The strong expression of YTHDFs and high level of m⁶A modification in RGCs suggest that the m⁶A reader YTHDFs might play roles in RGC development. We dissected and dissociated the retinal cells and cultured in vitro. We generated lentiviral shRNAs against YTHDFs, which showed similarly efficient knockdown (KD) of YTHDFs in RGC cultures in vitro (Figure 1B; Figure 1—figure supplement 1G,H). In these YTHDF-deficient RGC cultures, the first and most obvious phenotype that we observed is the robust increase of dendrite branching of cultured RGCs treated by shYthdf2 (Figure 1C and D; Figure 1—figure supplement 1I,J). In contrast, the dendrite branching of RGCs with YTHDF1 KD using shYthdf1 was not significantly different from control shRNA (Figure 1—figure supplement 1K), while YTHDF3 KD using shYthdf3 caused a slight (statistically significant in several Sholl radii) decrease of RGC dendrite branching compared with control shRNA (Figure 1—figure supplement 1L). These results suggest that the m⁶A reader YTHDF2 might play an important role in controlling dendrite branching of RGCs.

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Knockdown (KD) of YTHDF2 leads to a robust increase of retinal ganglion cell (RGC) dendrite branching.

(A) Representative confocal images showing high expression of YTHDF2 in RGCs (marked by RBPMS) in P0 retina. Note that all RGCs marked by the pan-RGC marker RBPMS express YTHDF2 while all YTHDF2-expressing cells are RBPMS⁺ RGCs. GCL, ganglion cell layer. Scale bars: 20 μm. (B) Western blotting (WB) confirming efficient KD of YTHDF2 in cultured RGCs using shYthdf2. Data of WB quantification are mean ± SEM and are represented as dot plots: ***p = 0.00012 (n = 3 replicates); by unpaired Student’s t test. (C) Examination of RGC dendrite development after YTHDF2 KD. As shown, significantly increased branching of dendrites marked by MAP2 immunofluorescence was observed in cultured RGCs marked by Brn3a. Dendrite traces were drawn for the corresponding RGCs. Scale bar: 10 μm. (D) Quantification of dendrite branching (C) using Sholl analysis. As shown, numbers of interactions are significantly greater in shYthdf2 groups (n = 68 RGCs) than shCtrl groups (n = 72 RGCs) in Sholl radii between 10 and 30 μm. Data are mean ± SEM. ****p = 4.32E-05 (10 μm), ***p = 0.00038 (15 μm), ****p = 2.85E-05 (20 μm), ***p = 0.00084 (25 μm), *p = 0.020 (30 μm), by unpaired Student’s t test.

Figure 1—source data 1 Source data for Figure 1B. (A) Western blotting (WB) of anti-YTHDF2 after knockdown (KD) of YTHDF2. (B) WB of anti-β-actin after KD of YTHDF2.: https://cdn.elifesciences.org/articles/75827/elife-75827-fig1-data1-v4.zip
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Figure 1—source data 2 Source data for Figure 1B. Original file of the full raw unedited blot of anti-YTHDF2 after knockdown (KD) of YTHDF2.: https://cdn.elifesciences.org/articles/75827/elife-75827-fig1-data2-v4.zip
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Figure 1—source data 3 Source data for Figure 1B. Original file of the full raw unedited blot of anti-β-actin after knockdown (KD) of YTHDF2.: https://cdn.elifesciences.org/articles/75827/elife-75827-fig1-data3-v4.zip
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cKO of Ythdf2 in the retina increases RGC dendrite branching in vivo without disturbing sublaminar targeting

To further explore whether YTHDF2 physiologically regulates RGC dendrite branching in vivo, we generated Ythdf2 cKO mouse (Figure 2A). We used the Six3-cre mouse line (Furuta et al., 2000), which has been widely used in the field to generate retina-specific knockouts (Lefebvre et al., 2012; Riccomagno et al., 2014; Sapkota et al., 2014; Krishnaswamy et al., 2015). YTHDF2 expression is efficiently eliminated in the Ythdf2 cKO retina compared with their littermate controls at E12.5 (Figure 2—figure supplement 1A) and E15.5 (Figure 2B). Retina progenitors, amacrine cells, bipolar cells, photoreceptors, horizontal cells, Müller glia, or astrocytes were not affected in Ythdf2 cKO retina (Figure 2—figure supplement 1B-K; Figure 2—figure supplement 2A-D), suggesting that YTHDF2 is not involved in the generation or development of these cells. This is in line with the low or no YTHDF2 expression in these cells. The RGC number or density was not affected in the Ythdf2 cKO retina (Figure 2C and D), demonstrating that Ythdf2 knockout does not disturb RGC neurogenesis. We then cultured RGCs from the Ythdf2 cKO retina. The dendrite branching of Ythdf2 cKO RGCs was significantly increased compared with littermate controls (Figure 2E and F). RGCs include over 40 subtypes (Sanes and Masland, 2015; Baden et al., 2016). We thus examined the RGC dendrite branching within different subtypes. One of the RGC subgroups responds preferentially to movement in particular directions and is named the ON-OFF directionally selective RGCs (ooDSGCs). Expression of CART (cocaine- and amphetamine-regulated transcript), a neuropeptide, distinguishes ooDSGCs from other RGCs (Kay et al., 2011a). The dendrite branching of ooDSGCs marked by CART/Brn3a co-staining in Ythdf2 cKO retinal cultures also increased compared with control (Figure 2G and H). These data further confirm that the m⁶A reader YTHDF2 regulates dendrite branching of RGCs.

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Dendrite branching is dramatically increased in cultured retinal ganglion cells (RGCs) from *Ythdf2* conditional knockout (cKO).

(A) Schematic drawings of the genetic deletion strategy for *Ythdf2*. Exon 4 which contains YTH domain-coding sequence is deleted after Cre-mediated recombination. (B) Depletion of YTHDF2 protein in retina of *Six3-cre^+/-;Ythdf2^fl/fl* cKO mice. Anti-YTHDF2 immunostaining of E15.5 retina vertical sections confirmed cKO of YTHDF2 protein, compared with *Ythdf2^fl/fl* littermate controls. Scale bar: 20 μm. (**C, D**) RGC neurogenesis not affected in the *Ythdf2* cKO retina. Wholemount immunostaining using a Brn3a antibody was carried out in P20 retina (C). Numbers of Brn3a⁺ RGC per 10,000 μm² of retina were quantified and showed no difference between the *Ythdf2* cKO and their littermate controls (D). n = 12 confocal fields for each genotype. Data are represented as box and whisker plots: ns, not significant (p = 0.79); by unpaired Student’s t test. Scale bar: 25 μm. (E) Examination of RGC dendrite development in *Ythdf2* cKO RGCs. As shown, knockout of YTHDF2 was confirmed by YTHDF2 IF (green). Significantly increased branching of dendrites marked by MAP2 IF (red) was observed in cultured RGCs from the *Ythdf2* cKO retina compared with their littermate controls. Dendrite traces were drawn for the corresponding RGCs. Scale bar: 10 μm. (F) Quantification of RGC dendrite branching (E) using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in *Six3-cre^+/-,Ythdf2^fl/fl* groups (n = 68 RGCs) than *Ythdf2^fl/fl* groups (n = 42 RGCs) in Sholl radii between 10 and 30 μm: ***p = 0.00030 (10 μm), ****p = 1.19E-05 (15 μm), ***p = 0.00018 (20 μm), *p = 0.021 (25 μm), **p = 0.0022 (30 μm), by unpaired Student’s t test. (G) Examination of CART⁺ (cocaine- and amphetamine-regulated transcript) RGC dendrite development in *Ythdf2* cKO RGCs. Cultured CART⁺ RGCs from the *Ythdf2* cKO retina have significantly increased branching of dendrites marked by MAP2 IF (red) compared with their littermate controls. Dendrite traces were drawn for the corresponding RGCs. Scale bar: 10 μm. (H) Quantification of CART⁺ RGC dendrite branching (G) using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in *Six3-cre^+/-,Ythdf2^fl/fl* groups (n = 77 RGCs) than *Ythdf2^fl/fl* groups (n = 90 RGCs) in Sholl radii between 10 and 30 μm: ****p = 3.17E-05 (10 μm), ****p = 6.50E-11 (15 μm), ****p = 5.14E-12 (20 μm), ****p = 5.00E-07 (25 μm), ***p = 0.00020 (30 μm), by unpaired Student’s t test.

Next, we wanted to confirm this phenotype in vivo by checking specific RGC subtypes. Intravitreal injection of an AAV reporter expressing ZsGreen visualized the dendrite morphology of ooDSGCs marked by CART immunostaining (Figure 3A). ooDSGCs showed dramatically increased dendrite branching in Ythdf2 cKO retina compared with control retina by Sholl analysis (Figure 3A and B). The intrinsically photosensitive RGCs (ipRGCs) are unique and melanopsin-expressing cells, which exhibit an intrinsic sensitivity to light (Hattar et al., 2002). We analyzed the morphology of ipRGCs visualized by wholemount immunostaining of melanopsin and found that the dendrite branching of ipRGCs was significantly increased in the Ythdf2 cKO retina (Figure 3C and D; Figure 3—figure supplement 1A-E). A similar trend was observed in the SMI-32⁺αRGCs (Figure 3E and F). These results strongly indicate that the m⁶A reader YTHDF2 negatively regulates RGC dendrite branching in vivo and Ythdf2 cKO promotes RGC dendrite arborization.

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Dendrite branching of specific retinal ganglion cell (RGC) subtypes increases in *Ythdf2* conditional knockout (cKO) in vivo.

(A) Co-labeling of ON-OFF directionally selective RGCs (ooDSGCs) by AAV-ZsGreen and CART (cocaine- and amphetamine-regulated transcript) IF in vivo. Intravitreal injection of AAV-expressing ZsGreen reporter was performed at P17 and retinas were collected at P27. The white arrowheads indicate ooDSGCs co-labeled by ZsGreen and CART IF, which show dramatically increased dendrite branching in *Ythdf2* cKO compared with control. Dendrite traces were drawn for the corresponding RGCs shown. Scale bar: 20 μm. (B) Quantification of dendrite branching of ZsGreen⁺/CART⁺ ooDSGCs (A) using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in *Six3-cre^+/-,Ythdf2^fl/fl* groups (n = 15 RGCs) than *Ythdf2^fl/fl* groups (n = 18 RGCs) in Sholl radii between 50 and 120 μm: **p = 0.0041 (50 μm), **p = 0.0059 (60 μm), ***p = 0.00036 (70 μm), **p = 0.0058 (80 μm), **p = 0.0018 (90 μm), **p = 0.0064 (100 μm), **p = 0.0045 (110 μm), *p = 0.040 (120 μm), by unpaired Student’s t test. (C) Dendrites of intrinsically photosensitive RGCs (ipRGCs) visualized by wholemount immunostaining of P20 retina using a melanopsin antibody in vivo. Dendrite traces were drawn for the corresponding RGCs shown. Scale bar: 50 μm. (D) Quantification of dendrite branching of melanopsin⁺ ipRGCs (C) using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in *Six3-cre^+/-,Ythdf2^fl/fl* groups (n = 18 RGCs) than *Ythdf2^fl/fl* groups (n = 21 RGCs) in Sholl radii between 20 and 100 μm: **p = 0.0083 (20 μm), *p = 0.018 (40 μm), ***p = 0.00068 (50 μm), ***p = 0.00027 (60 μm), *p = 0.048 (70 μm), **p = 0.0048 (80 μm), **p = 0.0023 (100 μm), by unpaired Student’s t test. (E) Dendrites of αRGCs visualized by wholemount immunostaining of P20 retina using an SMI-32 antibody in vivo. Dendrite traces were drawn for the corresponding RGCs shown. Scale bar: 20 μm. (F) Quantification of dendrite branching of SMI-32⁺αRGCs (E) using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in *Six3-cre^+/-,Ythdf2^fl/fl* groups (n = 14 RGCs) than *Ythdf2^fl/fl* groups (n = 22 RGCs) in Sholl radii between 40 and 140 μm: **p = 0.0044 (40 μm), **p = 0.0035 (50 μm), ***p = 0.00021 (60 μm), ****p = 2.63E-05 (70 μm), ****p = 2.38E-06 (80 μm), ****p = 1.68E-06 (90 μm), ****p = 6.76E-06 (100 μm), ****p = 5.72E-05 (110 μm), **p = 0.0011 (120 μm), **p = 0.0032 (130 μm), *p = 0.047 (140 μm), by unpaired Student’s t test.

In the retina, RGCs target their dendrites in different sublaminae of the inner plexiform layer (IPL). Since the IPL sublaminar targeting of RGC dendrites is critical for normal visual functions, we wondered whether the increased dendrite branching caused by Ythdf2 cKO was also accompanied by altered sublaminar patterning of RGC dendrites. We used a Thy1-GFP reporter (line O) which labels a few RGCs (Feng et al., 2000). As shown in Figure 3—figure supplement 1F,G, GFP intensity is generally higher in IPL of the Ythdf2 cKO retina compared with their littermate controls, which further proves the increased RGC dendrite branching and density. However, the sublaminar pattern of GFP signals looks similar between cKO and littermate control (Figure 3—figure supplement 1F,G). Sublaminar dendrite patterning of the ipRGC subtype visualized by immunostaining of melanopsin also demonstrated the similar phenotype (Figure 3—figure supplement 1H,I). These data suggest that YTHDF2 has a general control of RGC dendrite branching but has no striking effect on the sublaminar targeting of RGC dendrite. These results are consistent with the previous findings that the RGC dendrite targeting is determined genetically and several transcription factors controlling laminar choice have been identified in RGCs and amacrine cells (Cherry et al., 2011; Kay et al., 2011b; Lefebvre et al., 2015; Liu et al., 2018).

IPL of Ythdf2 cKO retina is thicker and has more synapses

The increased dendrite branching of RGCs further prompted us to check whether Ythdf2 cKO changes IPL development. Immunostaining of P6 retina vertical sections using a MAP2 antibody demonstrated that IPL thickness significantly increased in Ythdf2 cKO retina (Figure 4A and B). As a control, the thicknesses of other retinal layers showed no difference between the Ythdf2 cKO and control mice (Figure 4—figure supplement 1A-D). Quantification of MAP2 IF intensity in IPL suggested that the IPL of Ythdf2 cKO retina became denser with dendrites (Figure 4A and C). These results suggest that the increased dendrite branching results in a thicker and denser IPL in the Ythdf2 cKO retina.

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Inner plexiform layer (IPL) of the *Ythdf2* conditional knockout (cKO) retina is thicker and has more synapses.

(A) Cross-sections of P6 *Six3-cre^+/-,Ythdf2^fl/fl* retina showing increased IPL thickness by MAP2 staining compared with littermate control. ONL, outer nuclear layer; OPL, outer plexiform layer; INL, inner nuclear layer; IPL, inner plexiform layer; GCL, granule cell layer. Scale bar: 20 μm. (**B, C**) Quantification showing increased IPL thickness and MAP2 IF intensity per area in IPL of the *Ythdf2* cKO retina (A). Quantification data are represented as box and whisker plots: ****p = 1.28E-07 for B (n = 12 sections for each genotype), by unpaired Student’s t test; **p = 0.0045 for C (n = 12 sections for each genotype), by paired Student’s t test. (**D, E**) Representative confocal images showing the excitatory synapses labeled by colocalization of Bassoon (presynaptic) and PSD-95 (postsynaptic) in the IPL of P30 retina (D). There are significantly more synapses in the *Ythdf2* cKO IPL compared with control. Quantification data are represented as box and whisker plots (E): n = 47 confocal fields for *Ythdf2^fl/fl*, n = 23 confocal fields for *Six3-cre^+/-,Ythdf2^fl/fl*; ****p = 1.63E-05; by unpaired Student’s t test. Scale bars: 10 μm (D) and 5 μm (inset in D).

The IPL of retina is concentrated with synaptic connections, which contain synapses among and between bipolar-amacrine-ganglion cells. The increased RGC dendrite branching and denser IPL in the Ythdf2 cKO retina prompted us to wonder whether there are changes in synaptic connections in IPL. We used co-staining of the presynaptic marker Bassoon and the postsynaptic marker PSD-95 to count the colocalization puncta of Bassoon⁺/PSD-95⁺. We found that the numbers of Bassoon⁺/PSD-95⁺ excitatory synapses in IPL of Ythdf2 cKO retina are significantly larger than that of control retina (Figure 4D and E). As a control, the numbers of the excitatory ribbon synapses marked by the colocalization of Bassoon⁺/PSD-95⁺ in OPL (outer plexiform layer) show no difference between Ythdf2 cKO and control retinas (Figure 4—figure supplement 1E,F).

All these data verify that the IPL of Ythdf2 cKO retina is thicker and has more synapses.

Visual acuity is improved for the Ythdf2 cKO mice

The features of RGC dendrites, including their size, shape, arborization pattern, and localization, influence the amount and type of synaptic inputs that RGCs receive, which in turn determine how RGCs respond to specific visual stimuli such as the direction of motion (Liu and Sanes, 2017). The increased dendrite branching, the thicker and denser IPL, and the more synapses in the IPL inspired us to further explore whether the visual responses of the Ythdf2 cKO mice were changed or not. Ythdf2 cKO mice looked normal and had similar body weight and size compared with control mice for either sex (male in Figure 5A and B; female in Figure 5C and D). The generally normal development of Ythdf2 cKO mice is consistent with the specific and limited expression of Six3-cre in retina (Figure 5—figure supplement 1A), and only sparse spots in ventral forebrain (Figure 5—figure supplement 1B; Furuta et al., 2000). We used an optomotor response (OMR)-based assay (Prusky et al., 2004; Umino et al., 2008; Shi et al., 2018) to monitor visual functions of Ythdf2 cKO mice (Figure 5E). Surprisingly, the Ythdf2 cKO mice showed modestly improved visual acuity compared with the control mice, measuring spatial frequency threshold as 0.45 ± 0.0043 c/deg (cycle per degree) and 0.43 ± 0.0085 c/deg, respectively (Figure 5F, male mice). Similar phenotype was observed in female mice (Figure 5G). These results suggest that the visual acuity is modestly improved in the Ythdf2 cKO mice.

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Visual acuity is improved for the *Ythdf2* conditional knockout (cKO) mice.

(**A–D**) Six3-Cre-mediated *Ythdf2* cKO showing normal animal development and body weight (male in A, female in C). Quantification data of body weight (**B, D**) are represented as box and whisker plots: p = 0.41 in B (male, n = 24 for control, n = 18 for cKO); P = 0.08 in D (female, n = 23 for control, n = 25 for cKO); ns, not significant; by unpaired Student’s t test. (E) The setup of optomotor response assay is illustrated by schematic drawing. (**F, G**) Optomotor response assay demonstrating improved visual acuity in the *Ythdf2* cKO mice. Quantification data are mean ± SEM: *p = 0.048 in F (male, n = 24 control, n = 16 cKO); *p = 0.015 in G (female, n = 21 control, n = 25 cKO); by unpaired Student’s t test.

This phenotype is most likely attributed to the increased RGC dendrite branching and thicker and denser IPL with more synapses because all other parts and processes of retina are not affected except RGC dendrite in the Ythdf2 cKO mediated by Six3-cre (Figure 2—figure supplement 1 and Figure 4—figure supplement 1). The eyes and optic fibers also showed no difference between Ythdf2 cKO and control mice (Figure 5—figure supplement 1C-E). We further checked the targeting of optic nerves to the brain by anterograde labeling with cholera toxin subunit B (CTB) and found no difference of retinogeniculate or retinocollicular projections between Ythdf2 cKO and control mice (Figure 5—figure supplement 1F, G), suggesting the guidance and central targeting of RGC axons are not affected in the Ythdf2 cKO.

YTHDF2 target mRNA were identified with transcriptomic and proteomic analysis

Next, we continued to explore the underlying molecular mechanisms of the effects on dendrite branching caused by Ythdf2 cKO in the retina. First, we wanted to know what transcripts YTHDF2 recognizes and binds. We carried out anti-YTHDF2 RNA immunoprecipitation (RIP) in the retina followed by RNA sequencing of the elute (RIP-Seq). Two biological replicates of anti-YTHDF2 RIP-Seq identified 1638 transcripts (Supplementary file 1). Functional annotation of YTHDF2 RIP targets revealed significant enrichment in cellular component terms such as neuron part and neuron projection, and biological process terms such as cellular component organization and neuron projection development. We further zoomed in to check neural terms in cellular component (Figure 6A) and biological process (Figure 6B). We found that substantial numbers of YTHDF2 target transcripts are involved in cytoskeleton, dendrite, and their organization and development (Figure 6A and B), which is consistent with the dendrite branching phenotype observed in the Ythdf2 cKO retina.

Figure 6

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YTHDF2 target mRNAs were identified with transcriptomic and proteomic analysis.

(**A, B**) Gene Ontology (GO) analysis of YTHDF2 target transcripts identified by anti-YTHDF2 RNA immunoprecipitation (RIP) in the retina followed by RNA sequencing (RIP-Seq). Neural terms were picked out in cellular component (A) and biological process (B). (C) GO analysis of proteins which are upregulated after YTHDF2 knockodwn (KD) by mass spectrometry (MS). (D) Verification of N⁶-methyladenosine (m⁶A) modification of YTHDF2 target mRNAs by anti-m⁶A pulldown followed by RT-qPCR. ND, not detected. Data are mean ± SEM and are represented as dot plots (n = 3 replicates): **p = 0.0016 for *Kalrn7*; ****p = 1.40E-08 for *Kalrn9*; ****p = 1.46E-06 for *Kalrn12*; ****p = 5.46E-06 for *Strn*; ****p = 4.90E-06 for *Ubr4*; by unpaired Student’s t test.

The working model for YTHDF2 is that it binds and destabilizes its m⁶A-modified target transcripts (Wang et al., 2014). Since the destabilization of mRNAs will eventually decrease their protein levels, we carried out proteome analysis using mass spectrometry (MS) in acute shYthdf2-mediated KD of cultured RGCs, in order to identify directly affected targets. Three biological replicates of YTHDF2 KD followed by MS (YTHDF2 KD/MS) identified 114 proteins which were upregulated by YTHDF2 KD (Supplementary file 2). Functional annotation of these proteins revealed significant enrichment in neuron development- and cytoskeleton-related terms (Figure 6C), which is similar to anti-YTHDF2 RIP-Seq results.

By overlapping the two gene lists screened from anti-YTHDF2 RIP-Seq (Supplementary file 1) and YTHDF2 KD/MS_upregulation (Supplementary file 2), we identified a group of potential YTHDF2 target mRNAs in RGCs (Supplementary file 3), including Kalrn, Strn, and Ubr4. m⁶A modification of these mRNAs was verified by anti-m⁶A pulldown (Figure 6D). Kalrn (Kalirin) gene generates three alternative splicing isoforms Kalrn7, Kalrn9, and Kalrn12 encoding guanine-nucleotide exchange factors for Rho GTPases, which have been shown to regulate hippocampal and cortical dendritic branching (Xie et al., 2010; Yan et al., 2015), and are required for normal brain functions (Penzes et al., 2001; Xie et al., 2007; Cahill et al., 2009; Russell et al., 2014; Lu et al., 2015; Herring and Nicoll, 2016). Strn (Striatin) was first identified in striatum, and functions as a B subunit of the serine/threonine phosphatase PP2A and is also a core component of a multiprotein complex called STRIPAK (striatin-interacting phosphatase and kinase complex) (Benoist et al., 2006; Li et al., 2018). Strn was reported to regulate dendritic arborization only in striatal neurons but not in cortical neurons (Li et al., 2018). However, whether and how Kalrn and Strn work in the retina was still unknown. Ubr4 (ubiquitin protein ligase E3 component N-recognin 4) is also known as p600 and has been shown to play roles in neurogenesis, neuronal migration, neuronal signaling, and survival (Parsons et al., 2015). However, whether Ubr4 regulates dendrite development remains elusive.

YTHDF2 controls the stability of its target mRNAs which encode proteins regulating RGC dendrite branching

MS analysis after YTHDF2 KD has shown that the protein levels of these target mRNAs were upregulated (Supplementary file 2). IF using antibodies against Strn and Ubr4 detected specific signals in the IPL which were increased in Ythdf2 cKO retina compared with control retina (Figure 7—figure supplement 1A). Enrichment of these proteins in IPL implies that these proteins might function locally in RGC dendrites to regulate dendrite development.

We next wanted to know whether YTHDF2 controlled the protein levels of these m⁶A-modified target mRNAs through regulation of translation or transcript stability. As shown in Figure 7—figure supplement 1B-E, the mRNA levels of Kalrn7, Kalrn9, Kalrn12, Strn, and Ubr4 were dramatically increased after KD of YTHDF2, KO of Ythdf2, or KD of METTL14, supporting that YTHDF2 might regulate stability of these target mRNAs. We further evaluated potential changes in the stability of these target mRNAs in an m⁶A-dependent manner. We further verified this by directly measuring the stability of these target mRNAs. As shown in Figure 7A, all the target mRNAs showed significantly increased stability in the Ythdf2 cKO retina compared with controls. These results suggest that YTHDF2 controlled the protein levels of its m⁶A-modifed target mRNAs by decreasing their stability.

Figure 7 with 1 supplement see all

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YTHDF2 target mRNAs mediate YTHDF2-controlled retinal ganglion cell (RGC) dendrite branching.

(A) YTHDF2 target mRNAs showing increased stability in the *Ythdf2* conditional knockout (cKO) retina. RGCs dissected from E14.5 *Ythdf2* cKO and control embryos were cultured, treated with actinomycin D (ActD), and collected at different timepoints. Data are mean ± SEM (n = 3 replicates). For *Kalrn7*, **p = 0.0057 (3 hr), *p = 0.014 (6 hr), ***p = 0.00039 (12 hr); for *Kalrn9*, **p = 0.0036 (3 hr), ***p = 0.00090 (6 hr), *p = 0.032 (12 hr); for *Kalrn12*, **p = 0.0012 (3 hr), *p = 0.010 (6 hr), **p = 0.0069 (12 hr); for *Strn*, *p = 0.014 (3 hr), *p = 0.012 (6 hr), *p = 0.016 (12 hr); for *Ubr4*, **p = 0.0077 (3 hr), **p = 0.0059 (6 hr), *p = 0.041 (12 hr); all by unpaired Student’s t test. (B) Knockdown (KD) of the target mRNAs causing decreased dendrite branching of cultured RGCs prepared from wild type (WT) E14.5 retina by Sholl analysis. Brn3a and MAP2 IF were used to mark RGCs and visualize dendrites. Data are mean ± SEM. For *Kalrn7* (n = 59 for siCtrl, n = 56 for siKalrn7), ****p = 2.33E-06 (10 μm), ****p = 5.85E-06 (15 μm), ****p = 8.67E-05 (20 μm), **p = 0.0045 (25 μm), **p = 0.0058 (30 μm), *p = 0.010 (35 μm); for *Kalrn9* (n = 59 for siCtrl, n = 46 for siKalrn9), ****p = 3.69E-05 (10 μm), ****p = 5.53E-05 (15 μm), ***p = 0.00020 (20 μm), ****p = 3.09E-06 (25 μm), ****p = 4.63E-06 (30 μm), ***p = 0.00059 (35 μm), **p = 0.0010 (40 μm), *p = 0.042 (45 μm); for *Kalrn12* (n = 59 for siCtrl, n = 39 for siKalrn12), **p = 0.0031 (10 μm), ***p = 0.00017 (15 μm), ****p = 6.56E-05 (20 μm), **p = 0.0017 (25 μm), *p = 0.017 (30 μm); for *Strn* (n = 51 for siCtrl, n = 57 for siStrn), ****p = 4.19E-05 (10 μm), ***p = 0.00067 (15 μm), **p = 0.0079 (20 μm), *p = 0.015 (30 μm); for *Ubr4* (n = 81 for siCtrl, n = 81 for siUbr4), ****p = 1.26E-08 (10 μm), ****p = 7.61E-10 (15 μm), ****p = 2.35E-08 (20 μm), ****p = 1.39E-05 (25 μm), **p = 0.0061 (30 μm); all by unpaired Student’s t test. (C) Increased dendrite branching of cultured RGCs prepared from E14.5 *Ythdf2* cKO (Y2 cKO) retina was rescued by KD of target mRNAs using siRNAs. Data are mean ± SEM. *Ctrl*, *Ythdf2^fl/fl; Y2* cKO, *Six3-cre^+/-,Ythdf2^fl/fl*. In C1,'*Ctrl,* siCtrl’ (n = 35 neurons) vs. ‘Y2 cKO, siCtrl’ (n = 52 neurons), *p = 0.038 (15 μm), *p = 0.045 (20 μm), **p = 0.0036 (30 μm); ‘Y2 cKO, siKalrn7’ (n = 55 neurons) vs. ‘Y2 cKO, siCtrl’, *p = 0.020 (15 μm), *p = 0.025 (20 μm), *p = 0.031 (25 μm); ‘Y2 cKO, siKalrn9’ (n = 66 neurons) vs. ‘Y2 cKO, siCtrl’, *p = 0.020 (10 μm), *p = 0.013 (15 μm), *p = 0.031 (20 μm), *p = 0.017 (25 μm), *p = 0.031 (30 μm), *p = 0.031 (45 μm); ‘Y2 cKO, siKalrn12’ (n = 80 neurons) vs. ‘Y2 cKO, siCtrl’, *p = 0.015 (10 μm), **p = 0.0018 (15 μm), *p = 0.015 (20 μm), *p = 0.027 (40 μm). In C2, '*Ctrl,* siCtrl’ (n = 50 neurons) vs. ‘Y2 cKO, siCtrl’ (n = 47 neurons), **p = 0.0031 (10 μm), **p = 0.0013 (15 μm), *p = 0.029 (20 μm), **p = 0.0015 (30 μm), *p = 0.014 (35 μm); ‘Y2 cKO, siStrn’ (n = 45 neurons) vs. ‘Y2 cKO, siCtrl’, ***p = 0.00016 (10 μm), **p = 0.0043 (15 μm), *p = 0.010 (20 μm), *p = 0.018 (30 μm); ‘Y2 cKO, siUbr4’ (n = 57 neurons) vs. ‘Y2 cKO, siCtrl’, ***p = 0.00084 (10 μm), ****p = 4.89E-05 (15 μm), **p = 0.0058 (20 μm), **p = 0.0045 (30 μm). All by unpaired Student’s t test. (D) Increased dendrite branching of RGC subtypes in *Ythdf2* cKO (Y2 cKO) retina was rescued by KD of target mRNAs through intravitreal injection of AAV shRNAs in vivo. Data are mean ± SEM. *Ctrl*, *Ythdf2^fl/fl; Y2* cKO, *Six3-cre^+/-,Ythdf2^fl/fl*. In D1 (CART⁺/eGFP⁺ ooDSGCs), ‘*Ctrl,* shCtrl’ (n = 10 neurons) vs. ‘Y2 cKO, shCtrl’ (n = 6 neurons), *p = 0.010 (10 μm), ***p = 0.00049 (20 μm), **p = 0.0021 (30 μm), **p = 0.0047 (40 μm), *p = 0.028 (50 μm), *p = 0.011 (60 μm), *p = 0.030 (90 μm), *p = 0.042 (110 μm); ‘Y2 cKO, shKalrn12’ (n = 8 neurons) vs. ‘Y2 cKO, shCtrl’, *p = 0.012 (20 μm), *p = 0.014 (30 μm); ‘Y2 cKO, shUbr4’ (n = 6 neurons) vs. ‘Y2 cKO, shCtrl’, *p = 0.011 (10 μm), **p = 0.0084 (20 μm), *p = 0.029 (30 μm). In D2 (SMI-32⁺αRGCs), ‘*Ctrl,* shCtrl’ (n = 14 neurons) vs. ‘Y2 cKO, shCtrl’ (n = 14 neurons), *p = 0.032 (40 μm), **p = 0.0019 (50 μm), **p = 0.0014 (60 μm), *p = 0.015 (70 μm), *p = 0.044 (90 μm); ‘Y2 cKO, shKalrn12’ (n = 26 neurons) vs. ‘Y2 cKO, shCtrl’, **p = 0.0023 (20 μm), ***p = 0.00076 (30 μm), ***p = 0.00030 (40 μm), ***p = 0.00020 (50 μm), *p = 0.015 (60 μm); ‘Y2 cKO, shUbr4’ (n = 15 neurons) vs. ‘Y2 cKO, shCtrl’, *p = 0.042 (30 μm), *p = 0.024 (40 μm), *p = 0.018 (50 μm). All by unpaired Student’s t test.

Next we explored the functions of these YTHDF2 target mRNAs in RGC dendrite development. We first generated siRNAs against these transcripts (Figure 7—figure supplement 1F). We then checked the effects on RGC dendrite branching after KD of these target mRNAs by siRNAs in cultured RGCs. As shown in Figure 7B, KD of Kalrn7, Kalrn9, Kalrn12, Strn, or Ubr4 led to significant decreases of RGC dendrite branching. Interestingly, the siCocktail against all these target mRNAs further significantly reduced the RGC dendrite branching compared with each individual siRNA (Figure 7—figure supplement 1G), suggesting that these targets may work in different pathways to regulate the RGC dendrite morphology. We further examined whether these target mRNAs mediate YTHDF2-regulated RGC dendrite branching. As shown in Figures 2E–H ,–3, cKO of Ythdf2 led to increased dendrite branching of RGCs both in vitro and in vivo. Transfection of siRNAs against these target mRNAs rescued dendrite branching increases in cultured Ythdf2 cKO RGCs (Figure 7C). We continued to generate and performed intravitreal injection of AAV viral shKalrn12 and shUbr4, which significantly rescued dendrite branching increases of CART⁺ ooDSGCs and SMI-32⁺αRGCs in Ythdf2 cKO retina in vivo (Figure 7D).

Taken together, we identified a group of YTHDF2 target mRNAs that encode proteins regulating RGC dendrite branching, which mediate YTHDF2-controlled RGC dendrite branching.

Ythdf2 cKO retina is more resistant to AOH

The glaucomatous eyes are symptomatized with progressive neurodegeneration and vision loss (Agostinone and Di Polo, 2015). High intraocular pressure is a major risk factor in glaucoma and has been shown to cause pathological changes in RGC dendrites before axon degeneration or soma loss is detected in different model animals (Weber et al., 1998; Shou et al., 2003; Morgan et al., 2006). Our findings that Ythdf2 cKO in retina promotes RGC dendrite branching during development inspired us to wonder whether YTHDF2 also regulates RGC dendrite maintenance in the acute glaucoma model caused by AOH. We utilized the AOH model made with control and Ythdf2 cKO mice to check whether Ythdf2 cKO in the retina could alter the pathology in the glaucomatous eyes. RGC dendrite branching is significantly decreased after AOH operation compared with non-AOH in either genotype (Figure 8—figure supplement 1A,B). Interestingly, the Ythdf2 cKO retina with AOH operation maintains significantly higher dendrite complexity compared with the glaucomatous eyes of Ythdf2^fl/fl control mice (Figure 8A and B). In addition, there are significant RGC neuron losses in both genotypes after AOH (Figure 8C and D). However, the reduction of RGC number in the Ythdf2 cKO retina is less than control retina (Figure 8C and D). These results support that Ythdf2 cKO protects retina from RGC dendrite degeneration and soma loss caused by AOH.

Figure 8 with 1 supplement see all

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*Ythdf2* conditional knockout (cKO) retina is more resistant to acute ocular hypertension (AOH).

(**A, B**) Better maintenance of retinal ganglion cell (RGC) dendrite arborization in *Ythdf2* cKO retina after AOH operation. AOH was performed using adult mice, and retinas were collected after AOH for wholemount immunostaining of melanopsin and SMI-32 to visualize the dendrite arbors of corresponding RGC subtype, respectively. Dendrite traces were drawn as previously shown and quantification of dendrite branching was done using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in *Six3-cre^+/-,Ythdf2^fl/fl* retina than *Ythdf2^fl/fl* control retina in both RGC subtypes after AOH: for melanopsin⁺ intrinsically photosensitive RGCs (ipRGCs) in A, *Ythdf2^fl/fl*/AOH (n = 51 RGCs) vs. cKO/AOH (n = 64 RGCs), ***p = 0.00015 (10 μm), **p = 0.0017 (20 μm), *p = 0.034 (30 μm), ***p = 0.00035 (40 μm), ****p = 3.02E-05 (50 μm), ****p = 2.63E-05 (60 μm), **p = 0.0029 (70 μm), **p = 0.0028 (80 μm), ***p = 0.00035 (90 μm), **p = 0.0032 (100 μm), **p = 0.0014 (110 μm), **p = 0.0043 (120 μm), **p = 0.0014 (130 μm), *p = 0.023 (140 μm), *p = 0.013 (150 μm); for SMI-32⁺αRGCs in B, *Ythdf2^fl/fl*/AOH (n = 21 neurons) vs. cKO/AOH (n = 15 neurons), **p = 0.0052 (40 μm), **p = 0.0057 (50 μm); all by unpaired Student’s t test. (**C, D**) *Ythdf2* cKO retina showing less severe RGC loss after AOH. AOH was performed using adult mice and retinas were collected after AOH for wholemount immunostaining using a Brn3a antibody (C). Numbers of Brn3a⁺ RGCs per 10,000 μm² of retina were quantified for different genotypes and conditions (confocal fields for analysis: n = 117 for *Ythdf2^fl/fl*/Ctrl; n = 98 for *Ythdf2^fl/fl*/AOH; n = 110 for cKO/Ctrl; n = 104 for cKO/AOH). Data are represented as box and whisker plots (D): ns, not significant (p = 0.16; *Ythdf2^fl/fl*/Ctrl vs. cKO/Ctrl); **p = 0.0077 (*Ythdf2^fl/fl*/AOH vs. cKO/AOH); by unpaired Student’s t test. Scale bar: 25 μm. (**E, F**) Overexpression (OE) of YTHDF2 targets *Hspa12a* and *Islr2* protecting retina from RGC dendrite degeneration in the AOH model. Wild type (WT) mice were intravitreally injected with AAV overexpressing *Hspa12a* or *Islr2* and then operated with AOH. Wholemount immunostaining of CART/ZsGreen and SMI-32/ZsGreen was carried out to visualize the dendrite arbors of corresponding RGC subtype, respectively. Dendrite traces were drawn as previously shown and quantification of dendrite branching was done using Sholl analysis. Data are mean ± SEM. Numbers of interactions are significantly greater in retina with OE of *Hspa12a* or *Islr2* than control retina in both RGC subtypes after AOH. For CART⁺ ON-OFF directionally selective RGCs (ooDSGCs) in E: OE-Ctrl/AOH (n = 11 RGCs) vs. OE-Hspa12a/AOH (n = 11 RGCs), *p = 0.014 (20 μm), **p = 0.0025 (30 μm), *p = 0.018 (40 μm); OE-Ctrl/AOH vs. OE-Islr2/AOH (n = 6 RGCs), *p = 0.024 (10 μm), ***p = 0.00031 (20 μm), **p = 0.0038 (30 μm), *p = 0.013 (40 μm). For SMI-32⁺αRGCs in F: OE-Ctrl/AOH (n = 49 neurons) vs. OE-Hspa12a/AOH (n = 46 neurons), **p = 0.0023 (30 μm), ***p = 0.00080 (40 μm), **p = 0.0059 (50 μm), **p = 0.0051 (60 μm), **p = 0.0036 (70 μm), ***p = 0.00070 (80 μm), **p = 0.0015 (90 μm), *p = 0.016 (100 μm), *p = 0.011 (110 μm); OE-Ctrl/AOH vs. OE-Islr2/AOH (n = 13 RGCs), *p = 0.010 (30 μm), **p = 0.0093 (40 μm), **p = 0.0019 (50 μm), ***p = 0.00085 (60 μm), ***p = 0.00067 (70 μm), ****p = 4.25E-05 (80 μm), ****p = 2.54E-05 (90 μm), ***p = 0.00020 (100 μm) , **p = 0.0016 (110 μm). All by unpaired Student’s t test. (G) OE of YTHDF2 targets *Hspa12a* and *Islr2* alleviating RGC loss in the AOH model. WT mice were intravitreally injected with AAV overexpressing *Hspa12a* or *Islr2* and then operated with AOH. Wholemount immunostaining of Brn3a was performed to label RGCs. Numbers of Brn3a⁺ RGCs per 10,000 μm² of retina were quantified for different conditions (confocal fields for analysis: n = 19 for OE-Ctrl; n = 26 for OE-Hspa12a; n = 24 for OE-Islr2). Data are represented as box and whisker plots: *p = 0.034 (OE-Hspa12a vs. OE-Ctrl; *p = 0.029 (OE-Islr2 vs. OE-Ctrl); by unpaired Student’s t test.

Next we wanted to know whether and how YTHDF2 target mRNAs mediate these effects in the AOH models. We first checked the expression of YTHDF2 target mRNAs identified in the developing retina (Supplementary file 3) in the adult Ythdf2 cKO and control retina. We found that two target mRNAs Hspa12a and Islr2 show upregulation in the adult Ythdf2 cKO retina compared with control (Figure 8—figure supplement 1C). m⁶A modification of Hspa12a and Islr2 mRNAs was further verified by anti-m⁶A pulldown (Figure 8—figure supplement 1D). Hspa12a encodes heat shock protein A12A which is an atypical member of the heat shock protein 70 family and has been shown to be downregulated in diseases such as ischemic stroke, schizophrenia, and renal cell carcinoma (Pongrac et al., 2004; Mao et al., 2018; Min et al., 2020). Islr2 encodes immunoglobulin superfamily containing leucine-rich repeat protein two and is poorly studied. Here, we found that Hspa12a and Islr2 are downregulated in the retina after AOH operation (Figure 8—figure supplement 1E), which is likely caused by upregulation of YTHDF2 in the AOH-treated retina (Figure 8—figure supplement 1F-H). We therefore hypothesized that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and soma loss. If this is the case, overexpression of Hspa12a and Islr2 might protect RGC dendrite from AOH-triggered degeneration. We thus generated AAV harboring overexpression constructs of Hspa12a and Islr2 which were intravitreally injected to wild type retinas. After the AOH induction, the retinas overexpressing Hspa12a and Islr2 maintain significantly more complex RGC dendrite arbor and show better RGC survival compared with control AAV (Figure 8E–G).

These data verify that loss-of-function of YTHDF2 and gain-of-function of its targets Hspa12a and Islr2 have neuroprotective roles in the glaucomatous retina.

Discussion

Functions and mechanisms of mRNA m⁶A modification in the dendrite development were not known. Here, we revealed a critical role of the m⁶A reader YTHDF2 in RGC dendrite development and maintenance. YTHDF2 have two phases of function to control RGC dendrite development first and then maintenance through regulating two sets of target mRNAs. In early postnatal stages, the target mRNAs Kalrn7, Kalrn9, Kalrn12, Strn, and Ubr4 mediate YTHDF2 functions to regulate RGC dendrite development. In the adult mice, another set of target mRNAs Hspa12a and Islr2 mediate YTHDF2 function to regulate RGC dendrite maintenance.

Positive and negative regulators for dendrite development

The general principle for dendrite arborization is that the dendrite arbor cannot be either too big or too small in order to precisely sample a presynaptic target area during neural circuit formation (Lefebvre et al., 2015). Numerous extrinsic and intrinsic mechanisms have been found to regulate dendritic arbor patterning, which involves both positive and negative factors to achieve balanced control of dendritic growth (Jan and Jan, 2010; Dong et al., 2015; Ledda and Paratcha, 2017). For the secreted and diffusible cues, BDNF promotes dendrite branching and complexity (Cheung et al., 2007); the non-canonical Wnt7b/PCP pathway is a positive regulator of dendrite growth and branching (Rosso et al., 2005); the non-canonical Wnt receptor Ryk works as a negative regulator by limiting the extent of dendritic branching (Lanoue et al., 2017). For the contact-mediated signals, the cadherins Celsr2 and Celsr3 regulate dendrite growth in an opposite manner in cortical pyramidal and Purkinje neurons, and hippocampal neurons, respectively (Shima et al., 2004; Shima et al., 2007). For the transcription factors, studies have shown that manipulation of Cux1 and Cux2 levels has distinct effects on apical and basal arbors of cortical dendrites (Cubelos et al., 2015); interestingly, the functions of Sp4 in dendrite development are dependent on the cellular context of its expression, for example, Sp4 promotes dendrite growth and branching in hippocampal dentate granule cells but limits dendrite branching in cerebellar granule cells (Ramos et al., 2007; Zhou et al., 2007). Here, we identified another negative regulator YTHDF2 which works posttranscriptionally, and loss-of-function of YTHDF2 increased dendrite complexity during development and protected RGC degeneration from AOH. We have validated this effect on several RGC subtypes. Since there are dozens of RGC subtypes, it is technically challenging but still interesting to test whether this effect is universal to all subtypes or there is specificity for RGC subtypes.

Posttranscriptional regulation of dendrite development

It is well established that mRNAs can be transported and targeted to specific neuronal compartments such as axons and dendrites. Local translation of these mRNAs enables exquisite and rapid control of local proteome in specific subcellular compartments (Ledda and Paratcha, 2017). Local translation is known to play roles in controlling dendrite arborization (Chihara et al., 2007), and is regulated by specific RNA-binding proteins (Jan and Jan, 2010). In Drosophila, the RNA-binding proteins Pumilio (Pum), Nanos (Nos), Glorund (Glo), and Smaug (Smg) regulate morphogenesis and branching of specific classes of dendritic arborization neurons through controlling translation of their target mRNAs including nanos mRNA itself (Ye et al., 2004; Brechbiel and Gavis, 2008). The mouse homologue of another RNA-binding protein Staufen, Stau1, regulates dendritic targeting of ribonucleoprotein particles and dendrite branching (Vessey et al., 2008). Here, we found that the m⁶A reader and RNA-binding protein YTHDF2 control stability of its target mRNAs and regulate dendrite branching in RGCs. It would be interesting to see whether these target mRNAs are localized into dendrites and whether YTHDF2 works in dendrites to control their stability and translation. Actually, Strn4 mRNA has been shown to be present in dendrites and locally translated (Lin et al., 2017). In addition, how the proteins encoded by these target mRNAs regulate RGC dendrite branching during development and maintenance remains to be explored and will be important future directions.

Neuroprotective genes in retinal injuries and degeneration

Transcriptome analyses have revealed differentially expressed genes after retinal injuries such as AOH-induced glaucoma and optic nerve crush (ONC), and the upregulated genes are of importance for discovering new treatment approaches (Jakobs, 2014; Tran et al., 2019). One of the previous studies has identified Mettl3, encoding the m⁶A writer, as an upregulated gene after ONC (Agudo et al., 2008). Here, we found Ythdf2, encoding an m⁶A reader, was also upregulated in the retina after AOH. We further found that Hspa12a and Islr2, two targets of YTHDF2 in adult retina, were downregulated in glaucomatous retinas. Overexpression of Hspa12a and Islr2 protected retina from AOH-caused RGC dendrite degeneration. Our findings in this study suggest that YTHDF2 and its neuroprotective target mRNAs might be valuable in developing novel therapeutic approaches to treat neurodegeneration caused by glaucoma and other retinal injuries.

Materials and methods

Key resources table

Reagent type (species) or resource	Designation	Source or reference	Identifiers	Additional information
Strain, strain background (mouse)	Mouse: Ythdf2^fl/fl	Yu et al., 2021b	N/A
Strain, strain background (mouse)	Mouse: Tg(Six3-cre)69Frty/GcoJ	Jackson Laboratory	Cat#: JAX_019755RRID: IMSR_JAX:019755
Strain, strain background (mouse)	Mouse: B6.Cg-Tg(Thy1-EGFP)OJrs/GfngJ	Jackson Laboratory	Cat#: JAX_007919RRID: IMSR_JAX:007919
Strain, strain background (mouse)	Mouse: B6.129 × 1-Gt(ROSA)26Sor^tm1(EYFP)Cos/J	Jackson Laboratory	Cat#: JAX_006148RRID: IMSR_JAX:006148
Antibody	Anti-GFP (Chicken polyclonal)	Abcam	Cat#: ab13970, RRID: AB_300798	IF (1:1000)
Antibody	Anti-MAP2 (Chicken polyclonal)	Abcam	Cat#: ab5392, RRID: AB_2138153	IF (1:10,000)
Antibody	Anti-RBPMS (Guinea pig polyclonal)	PhosphoSolutions	Cat#: 1832-RBPMS, RRID: AB_2492226	IF (1:1000)
Antibody	Anti-VAChT (Goat polyclonal)	Millipore	Cat#: ABN100, RRID: AB_2630394	IF (1:1000)
Antibody	Anti-β Actin (Mouse monoclonal)	Abcam	Cat#: ab6276, RRID: AB_2223210	WB (1:30,000)
Antibody	Anti-β Actin (Mouse monoclonal)	ABclonal	Cat#: AC004, RRID: AB_2737399	WB (1:30,000)
Antibody	Anti-AP2α (Mouse monoclonal)	DSHB	Cat#: 3B5, RRID: AB_2313947	IF (1:1000)
Antibody	Anti-Bassoon (Mouse monoclonal)	Enzo Life Sciences	Cat#: ADI-VAM-PS003, RRID: AB_10618753	IF (1:2500)
Antibody	Anti-Brn3a (Mouse monoclonal)	Millipore	Cat#: MAB1585, RRID: AB_94166	IF (1:300)
Antibody	Anti-Calbindin-D-28K (Mouse monoclonal)	Sigma-Aldrich	Cat#: C9848, RRID: AB_476894	IF (1:200)
Antibody	Anti-PKCα (Mouse monoclonal)	Santa Cruz Biotechnology	Cat#: sc-8393, RRID: AB_628142	IF (1:500)
Antibody	Anti-SMI-32 (Mouse monoclonal)	BioLegend	Cat#: 801701, RRID: AB_2564642	IF (1:200)
Antibody	Anti-Strn (Striatin) (Mouse monoclonal)	BD Biosciences	Cat#: 610838, RRID: AB_398157	IF (1:500)
Antibody	Anti-CART (Rabbit polyclonal)	Phoenix Pharmaceuticals	Cat#: H-003–62, RRID: AB_2313614	IF (1:2000)
Antibody	Anti m⁶A (Rabbit polyclonal)	Synaptic Systems	Cat# 202003, RRID: AB_2279214	IF (1:200)
Antibody	Anti-melanopsin (Rabbit polyclonal)	Thermo Fisher Scientific	Cat#: PA1-780, RRID: AB_2267547	IF (1:1000)
Antibody	Anti-PKCα (Rabbit polyclonal)	Cell Signaling	Cat#: CST-2056	IF (1:1000)
Antibody	Anti-PSD-95 (Mouse monoclonal)	Abcam	Cat#: ab2723, RRID: AB_303248	IF (1:500)
Antibody	Anti-Recoverin (Rabbit polyclonal)	Millipore	Cat#: AB5585, RRID: AB_2253622	IF (1:1000)
Antibody	Anti-YTHDF2 (Rabbit polyclonal)	Proteintech	Cat#: 24744–1-AP, RRID: AB_2687435	IF (1:1000)
Antibody	Anti-YTHDF1 (Rabbit polyclonal)	Proteintech	Cat#: 17479–1-AP, RRID: AB_2217473	IF (1:1000)
Antibody	Anti-YTHDF3 (Rabbit polyclonal)	Abcam	Cat#: ab103328, RRID: AB_10710895	IF (1:1000)
Antibody	Anti-Ubr4 (Rabbit polyclonal)	Abcam	Cat#: ab86738, RRID: AB_1952666	IF (1:300)
Antibody	Anti-Chx10 (Sheep polyclonal)	Exalpha	Cat#: X1179P	IF (1:1000)
Antibody	Anti-GFAP (Chicken polyclonal)	Millipore	Cat#: AB5541, RRID: AB_177521	IF (1:500)
Antibody	Anti-Lhx2 (Goat polyclonal)	Santa Cruz Biotechnology	Cat#: sc-19344, RRID: AB_2135660	IF (1:200)
Antibody	Anti-Lhx2 (Rabbit monoclonal)	Abcam	Cat#: ab184337	IF (1:500)
Antibody	Anti-chicken IgY (Alexa 488 donkey)	Jackson Immunoresearch	Cat#: 703-545-155, RRID: AB_2340375	IF (1:500)
Antibody	Anti-G. pig IgG (Alexa 488 donkey)	Jackson Immunoresearch	Cat#: 706-545-148, RRID: AB_2340472	IF (1:500)
Antibody	Anti-mouse IgG (Alexa 488 donkey)	Thermo Fisher Scientific	Cat#: A-21202, RRID: AB_141607	IF (1:500)
Antibody	Anti-rabbit IgG (Alexa 488 donkey)	Thermo Fisher Scientific	Cat#: A-21206, RRID: AB_141708	IF (1:500)
Antibody	Anti-goat IgG (Alexa 555 donkey)	Thermo Fisher Scientific	Cat#: A-21432, RRID: AB_2535853	IF (1:1000)
Antibody	Anti-mouse IgG (Alexa 555 donkey)	Thermo Fisher Scientific	Cat#: A-31570, RRID: AB_2536180	IF (1:1000)
Antibody	Anti-rabbit IgG (Alexa 555 donkey)	Thermo Fisher Scientific	Cat#: A-31572, RRID: AB_162543	IF (1:1000)
Antibody	Anti-sheep IgG (Alexa 555 donkey)	Thermo Fisher Scientific	Cat#: A-21436, RRID: AB_2535857	IF (1:1000)
Antibody	Anti-chicken IgY (Alexa 555 goat)	Thermo Fisher Scientific	Cat#: A-21437, RRID: AB_2535858	IF (1:1000)
Antibody	Anti-mouse IgG (Alexa 647 donkey)	Thermo Fisher Scientific	Cat#: A-31571, RRID: AB_162542	IF (1:200)
Antibody	Anti-mouse IgG (HRP donkey)	Abcam	Cat#: ab97030, RRID: AB_10680919	WB (1:2500)
Antibody	Anti-rabbit IgG (HRP donkey)	Abcam	Cat#: ab16284, RRID: AB_955387	WB (1:2500)
Antibody	Anti-mouse IgG (HRP VHH)	AlpaLife	Cat#: KTSM1321	WB (1:5000)
Antibody	Anti-rabbit IgG (HRP VHH)	AlpaLife	Cat#: KTSM1322	WB (1:5000)
Recombinant DNA reagent	Plasmid: pLKO.1-TRC	Addgene	Addgene plasmid #10878, RRID: Addgene_10878
Sequence-based reagent	shRNA targeting sequence of negative control	This paper	N/A	GCATCAAGGTG AACTTCAAGA
Sequence-based reagent	shRNA targeting sequence of mouse Ythdf2	Yu et al., 2018	N/A	GGACGTTCCC AATAGCCAACT
Sequence-based reagent	shRNA targeting sequence of mouse Ythdf1	This paper	N/A	GGACATTGGT ACTTGGGATAA
Sequence-based reagent	shRNA targeting sequence of mouse Ythdf3	This paper	N/A	GGATTTGGCAA TGATACTTTG
Sequence-based reagent	shRNA targeting sequence of mouse Mettl14#6	This paper	N/A	GCTGGACCTGG GATGATATTA
Sequence-based reagent	shRNA targeting sequence of mouse Mettl14#7	This paper	N/A	CCCAGCTTGT ACTTTGCTTTA
Sequence-based reagent	shRNA targeting sequence of negative control (AAV)	This paper	N/A	TTCTCCGAAC GTGTCACGTAA
Sequence-based reagent	shRNA targeting sequence of mouse Kalrn12	This paper	N/A	TGATGAGCTGA TGGAAGAA
Sequence-based reagent	shRNA targeting sequence of mouse Ubr4	This paper	N/A	AATGATGAGC AGTCATCTC
Sequence-based reagent	siRNA targeting sequence of negative control	Yu et al., 2018	N/A	UUCUCCGAAC GUGUCACGUTT
Sequence-based reagent	siRNA targeting sequence of mouse Kalrn7	Xie et al., 2007	N/A	AGUACAAUCCU GGCCAUGUTT
Sequence-based reagent	siRNA targeting sequence of mouse Kalrn9	Yan et al., 2015	N/A	ACUGGACUGG ACUUCUAUUTT
Sequence-based reagent	siRNA targeting sequence of mouse Kalrn12	Yan et al., 2015	N/A	CGAUGAGCUG AUGGAAGAATT
Sequence-based reagent	siRNA targeting sequence of mouse Strn	Breitman et al., 2008	N/A	GGUGAAGAUCG AGAUACAATT
Sequence-based reagent	siRNA targeting sequence of mouse Ubr4	Shim et al., 2008	N/A	AAUGAUGAGC AGUCAUCUATT
Sequence-based reagent	qPCR primers of mouse 18s	Wang et al., 2018	N/A	Fwd: GCTTAATTTGACT CAACACGGGARev: AGCTATCAATCTG TCAATCCTGTC
Sequence-based reagent	qPCR primers of mouse Gapdh	Mains et al., 2011	N/A	Fwd: TTGTCAGCAATG CATCCTGCACCACCRev: CTGAGTGGCAGT GATGGCATGGAC
Sequence-based reagent	qPCR primers of mouse Ythdf2	This paper	N/A	Fwd: GAGCAGAGA CCAAAAGGTCAAGRev: CTGTGGGCTC AAGTAAGGTTC
Sequence-based reagent	qPCR primers of mouse Kalrn7	Mains et al., 2011	N/A	Fwd: GATACCATATCCAT TGCCTCCAGGACCRev: CCAGGCTGCGC GCTAAACGTAAG
Sequence-based reagent	qPCR primers of mouse Kalrn9	Mains et al., 2011	N/A	Fwd: GCCCCTCGCC AAAGCCACAGCRev: CCAGTGAGT CCCGTGGTGGGC
Sequence-based reagent	qPCR primers of mouse Kalrn12	Mains et al., 2011	N/A	Fwd: CAGCAGCCA CGTGCCTGCAGCRev: TCTTGACATTGGG AATGGGCCGCAC
Sequence-based reagent	qPCR primers of mouse Strn	This paper	N/A	Fwd: TGAAGCCTG GAATGTGGACCRev: CTATTGGGC CTCTTCACCCC
Sequence-based reagent	qPCR primers of mouse Ubr4	This paper	N/A	Fwd: TGAGTGAGG ACAAGGGCAACRev: GGGTTGGAT CGAACGAAGGT
Sequence-based reagent	qPCR primer for mouse Hspa12a	This paper	N/A	Fwd: GGGTTTGCACA GGCTAAGGARev: TCTGATGGACG GTCAGGTCT
Sequence-based reagent	qPCR primer for mouse Islr2	This paper	N/A	Fwd: GAAGCTCCCTTA GACTGTCACCRev: CCCCATCGTGA CTCCTGCTG
Sequence-based reagent	PCR primer for mouse Hspa12a CDS	This paper	N/A	Fwd: ATGGCGGACAA GGAAGCTGGRev: GTAATTTAAGAA GTCGATCCCC
Sequence-based reagent	PCR primer for mouse Islr2 CDS	This paper	N/A	Fwd: ATGGGGCC CTTTGGAGCRev: GCCCGCTGTC TGCCTGTAG
Sequence-based reagent	Mouse genotyping primers for Ythdf2 loxp site 1	This paper	N/A	GCTTGTAGTTATG TTGTGTACCAC and GCAGCTCTGACT ATTCTAAAACCTCC
Sequence-based reagent	Mouse genotyping primers for Ythdf2 loxp site 2	This paper	N/A	CTCATAACATCC ATAGCCACAGG and CCAAGAGATAG CTTTCCTAATG
Sequence-based reagent	Mouse genotyping primers for Six3-cre	Chunqiao Liu’s lab	N/A	CCTTCCTCCCT CTCTATGTG and GAACGAACCT GGTCGAAATC
Sequence-based reagent	Mouse genotyping primers for Thy1-GFP	The Jackson Laboratory website	N/A	CGGTGGTGC AGATGAACTT and ACAGACACAC ACCCAGGACA
Sequence-based reagent	Mouse genotyping primers for Rosa-YFP mutant site	The Jackson Laboratory website	N/A	AGGGCGAGG AGCTGTTCA and TGAAGTCGAT GCCCTTCAG
Sequence-based reagent	Mouse genotyping primers for Rosa-YFP wild type site	The Jackson Laboratory website	N/A	CTGGCTTCT GAGGACCG and CAGGACAAC GCCCACACA
Peptide, recombinant protein	Insulin	Sigma	Cat#: I6634
Peptide, recombinant protein	Recombinant Human/Murine/Rat BDNF	PeproTech	Cat#: 450–02
Peptide, recombinant protein	Recombinant Human NT-3	PeproTech	Cat#: 450–03
Peptide, recombinant protein	Recombinant Murine EGF	PeproTech	Cat#: 315–09
Peptide, recombinant protein	Recombinant Human FGF-basic	PeproTech	Cat#: 100-18B
Commercial assay or kit	Pierce BCA Protein Assay Kit	Thermo Fisher Scientific	Cat#: 23227
Commercial assay or kit	GeneSilencer Transfection Reagent	Genlantis	Cat#: T500750
Commercial assay or kit	Magna MeRIP m⁶A Kit	Millipore	Cat#: 17–10499
Commercial assay or kit	EZ-Magna RIP RNA-Binding Protein Immunoprecipitation Kit	Millipore	Cat#: 17–701
Chemical compound, drug	cpt-cAMP, 8-(4-Chlorophenylthio) Adenosine 3':5'-CY	Sigma	Cat#: C3912
Chemical compound, drug	N-acetyl-L-cysteine (NAC)	Sigma	Cat#: A8199
Chemical compound, drug	Forskolin	Sigma	Cat#: F6886
Chemical compound, drug	Puromycin	Thermo Fisher Scientific	Cat#: A11138-03
Chemical compound, drug	Puromycin	Sigma	Cat#: P8833
Chemical compound, drug	Paraformaldehyde	Vetec	Cat#: V900894-100G
Chemical compound, drug	Triton X-100	Sigma	Cat#: V900502
Software, algorithm	GraphPad Prism 7.0	GraphPad	https://www.graphpad.com, RRID: SCR_002798
Software, algorithm	STAR v2.5	Dobin et al., 2013	https://github.com/alexdobin/STAR/ RRID:SCR_004463
Software, algorithm	HTSeq	Anders et al., 2015	https://pypi.org/project/HTSeq/
Software, algorithm	ImageJ (Fiji)	Schindelin et al., 2012	http://fiji.sc, RRID:SCR_002285
Software, algorithm	Matlab	Matlab	https://ww2.mathworks.cn
Other	TRIzol Reagent	Life	Cat#: 15596018
Other	PrimeScript RT Master Mix	Takara	Cat#: RR036B
Other	2× ChamQ Universal SYBR qPCR Master Mix	Vazyme	Cat#: Q711-02
Other	DMEM, high glucose	Gibco	Cat#: 11965–092
Other	Dulbecco’s Modified Eagle’s Medium, 10×, low glucose	Sigma	Cat#: D2429
Other	DMEM, high glucose	Hyclone	Cat#: SH30022.01
Other	Fetal Bovine Serum (FBS)	Gibco	Cat#: 10270–106
Other	Dulbecco’s Phosphate-Buffered Saline, 1× without calcium and magnesium (DPBS)	Corning	Cat#: 21–031-CVR
Other	Poly-D-lysine, Cultrex	Trevigen	Cat#: 3439-100-01
Other	Laminin (mouse), Culrex	Trevigen	Cat#: 3400-010-01
Other	DMEM/F-12, GlutaMAX	Gibco	Cat#: 10565–018
Other	Neurobasal Medium, minus phenol red	Gibco	Cat#: 12348–017
Other	Penicillin-Streptomycin	Life	Cat#: 15140–122
Other	B27 serum-free supplement, 50×	Life	Cat#: 17504044
Other	N-2 Supplement, 100×	Gibco	Cat#: 17502–048
Other	OCT Compound and Cryomolds, Tissue-Tek	SAKURA	Cat#: 4583
Other	ChemiBLOCKER	Millipore	Cat#: 2170
Other	CTB (Cholera Toxin Subunit B) conjugated by Alexa Fluor 555	Invitrogen	Cat#: C34776
Other	VECTASHIELD Antifade Mounting Medium with DAPI	Vector Laboratory	Cat#: H-1200
Other	Mounting Medium, antifading (with DAPI)	Solarbio	Cat#: S2110
Other	Normal Goat Serum	Novus	Cat#: NBP2-23475

Animals and generation of the Ythdf2 cKO mice

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Ythdf2^fl/fl mice were reported previously (Yu et al., 2021b). Six3-cre (Furuta et al., 2000), Thy1-GFP (Feng et al., 2000), and Rosa26-eYFP (Srinivas et al., 2001) mice were from Jackson Laboratory. For timed pregnancy, embryos were identified as E0.5 when a copulatory plug was observed. Genotyping primers are as following: the first Ythdf2-loxP site, 5’-GCTTGTAGTTATGTTGTGTACCAC-3’ and 5’-GCAGCTCTGACTATTCTAAAACCTCC-3’; the second Ythdf2-loxP site, 5’-CTCATAACATCCATAGCCACAGG-3’, and 5’-CCAAGAGATAGCTTTCCTAATG-3’.

Six3-cre site, 5’-CCTTCCTCCCTCTCTATGTG-3’ and 5’-GAACGAACCTGGTCGAAATC-3’.

Rosa26-eYFP wild type site, 5’-CTGGCTTCTGAGGACCG-3’ and 5’-CAGGACAACGCCCACACA-3’; the mutant site, 5’-AGGGCGAGGAGCTGTTCA-3’ and 5’-TGAAGTCGATGCCCTTCAG-3’. All experiments using mice were carried out following the animal protocols approved by the Laboratory Animal Welfare and Ethics Committee of Southern University of Science and Technology.

Retinal neuronal culture

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Retinal neurons were dissociated from E14.5 to 15.5 mouse embryos by papain in DPBS (1× Dulbecco’s phosphate-buffered saline [PBS], Corning, NY) following the previously described methods (Kechad et al., 2012), and neuronal suspension was plated on acid-washed glass coverslips pre-coated with poly-D-lysine (Trevigen, 100 μg/ml) for 1 hr and laminin (Trevigen, 5 μg/ml) overnight at 37°C. Culture medium was made up of half DMEM/F12 medium (Gibco) and half neurobasal medium (Gibco), supplemented with B27 supplement (Life, 0.5×), penicillin-streptomycin (Life, 1×), N-2 supplement (Gibco, 0.5×), N-acetyl-L-cysteine (Sigma, NAC 0.6 mg/ml), cpt-cAMP (Sigma, 100 μM), forskolin (Sigma, 10 μM), and insulin (Sigma, 25 μg/ml). EGF (PeproTech, 50 ng/ml), BDNF (PeproTech, 50 ng/ml), NT-3 (PeproTech, 25 ng/ml), and FGF-basic (PeproTech, 10 ng/ml) were freshly added before using.

KD using lentiviral shRNA, siRNA or AAV shRNA, and overexpression using AAV system

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Lentiviral KD plasmids encoding shRNA (shCtrl: 5’-GCATCAAGGTGAACTTCAAGA-3’; shYthdf2: 5’-GGACGTTCCCAATAGCCAACT-3’; shYthdf1: 5’- GGACATTGGTACTTGGGATAA-3’; shYthdf3: 5’- GGATTTGGCAATGATACTTTG-3’; shMettl14#6: 5’-GCTGGACCTGGGATGATATTA-3’; shMettl14#7: 5’-CCCAGCTTGTACTTTGCTTTA-3’) were generated from pLKO.1-TRC and lentivirus preparation process was described previously (Yu et al., 2018). All siRNAs were chosen from previous studies and the target sequences of siRNA are as following: siCtrl (RNAi negative control): 5’- UUCUCCGAACGUGUCACGUTT-3’ (Yu et al., 2018); siKalrn7: 5’- AGUACAAUCCUGGCCAUGUTT-3’ (Xie et al., 2007); siKalrn9: 5’-ACUGGACUGGACUUCUAUUTT-3’ (Yan et al., 2015); siKalrn12: 5’-CGAUGAGCUGAUGGAAGAATT-3’ (Yan et al., 2015); siStrn: 5’-GGUGAAGAUCGAGAUACAATT-3’ (Breitman et al., 2008); siUbr4: 5’-AAUGAUGAGCAGUCAUCUATT-3’ (Shim et al., 2008). AAV KD plasmids encoding shRNA (shCtrl: 5’-TTCTCCGAACGTGTCACGTAA-3’; shKalrn12: 5’-TGATGAGCTGATGGAAGAA-3’; shUbr4: 5’-AATGATGAGCAGTCATCTC-3’) were generated using pHBAAV-U6-MCS-CMV-EGFP and packaged in serotype-9 by Hanbio (1.5 × 10¹² genomic copies per ml). AAV overexpression plasmids of Hspa12a (NM_175199.3; PCR primer for mouse Hspa12a: 5’-ATGGCGGACAAGGAAGCTGG-3’ and 5’-GTAATTTAAGAAGTCGATCCCC-3’) and Islr2 (NM_001161541.1; PCR Primer for mouse Islr2: 5’-ATGGGGCCCTTTGGAGC-3’ and 5’-GCCCGCTGTCTGCCTGTAG-3’) were generated from pHBAAV-CMV-MCS-3flag-T2A-ZsGreen and packaged serotype-9 by Hanbio (1.2 × 10¹² genomic copies per ml).

GeneSilencer Transfection Reagent (Genlantis) was used in siRNA transfection following the manufacturer’s protocols. Culture medium was changed after 1 day of lentiviral shRNA infection or siRNA transfection. For lentiviral shRNA assay, puromycin (Thermo or Sigma, 1 μg/ml) was added after 2 days of infection. Immunofluorescence, RNA, or protein preparation was performed after shRNA or siRNA worked for 3 days. For AAV intravitreal injection, P0-P1 mouse pups were anesthetized in ice and then eyes were pierced at the edge of corneal by 30G × 1/2 needle (BD, 305106) under stereomicroscope. Then 1 μl AAV was intravitreally injected with 10 µl Syringe (Hamilton, 80330) following the pinhole. P15 or adult mice were anesthetized with 2.5% Avertin and then eyes were pierced at the side of corneal and the outer segment of sclera by 30G × 1/2 needle successively. Two μl AAV was intravitreally injected with 10 µl Syringe following the pinhole on the sclera. All subsequent experiments such as AOH operation and immunostaining were carried out after at least 3 weeks (10 days for ZsGreen/CART labeling of ooDSGCs in Ythdf2 cKO and control mice in Figure 3A).

RT-qPCR

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Total RNA was extracted from cells or tissues with TRIzol Reagent (Life) and then used for reverse transcription by PrimeScript RT Master Mix (TaKaRa). Synthesized cDNA was used for qPCR by 2× ChamQ Universal SYBR qPCR Master Mix (Vazyme) on StepOnePlus Real-Time PCR System (ABI) or BioRad CFX96 Touch Real-Time PCR system. Primers used for qPCR are as following: mouse Gapdh: 5’-TTGTCAGCAATGCATCCTGCACCACC-3’ and 5’-CTGAGTGGCAGTGATGGCATGGAC-3’ (Mains et al., 2011); mouse Kalrn7: 5’- GATACCATATCCATTGCCTCCAGGACC-3’ and 5’-CCAGGCTGCGCGCTAAACGTAAG-3’ (Mains et al., 2011); mouse Kalrn9: 5’- GCCCCTCGCCAAAGCCACAGC-3’ and 5’-CCAGTGAGTCCCGTGGTGGGC-3’ (Mains et al., 2011); mouse Kalrn12: 5’- CAGCAGCCACGTGCCTGCAGC-3’ and 5’-TCTTGACATTGGGAATGGGCCGCAC-3’ (Mains et al., 2011); mouse Strn: 5’-TGAAGCCTGGAATGTGGACC-3’ and 5’-CTATTGGGCCTCTTCACCCC-3’; mouse Ubr4: 5’- TGAGTGAGGACAAGGGCAAC-3’ and 5’-GGGTTGGATCGAACGAAGGT-3’; mouse Ythdf2: 5’-GAGCAGAGACCAAAAGGTCAAG-3’and 5’-CTGTGGGCTCAAGTAAGGTTC-3’; 18 s: 5’-GCTTAATTTGACTCAACACGGGA-3’ and 5’-AGCTATCAATCTGTCAATCCTGTC-3’ (Wang et al., 2018); mouse Hspa12a: 5’-GGGTTTGCACAGGCTAAGGA-3’ and 5’-TCTGATGGACGGTCAGGTCT-3’; mouse Islr2: 5’-GAAGCTCCCTTAGACTGTCACC-3’ and 5’-CCCCATCGTGACTCCTGCTG-3’.

Immunofluorescence and immunostaining

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For tissue sections, mouse embryonic eyes were fixed with 4% PFA (Sigma) in 0.1 M phosphate buffer (PB) for 30–45 min at room temperature (RT); eyes of mouse pups (<P10) were pre-fixed briefly and then eyecups were dissected and fixed for 45 min-1 hr at RT; for P20-30 or adult mice, eyecups were dissected after myocardial perfusion with 0.9% NaCl, followed by fixation for 1 hr. After PBS (3 × 5 min) washing, tissues were dehydrated with 30% sucrose in 0.1 M PB overnight at 4°C, then embedded with OCT (SAKURA) and cryosectioned at 12 μm (20 μm for Thy1-GFP section analysis) with Leica CM1950 Cryostat. Tissue sections were permeabilized and blocked with 10% ChemiBLOCKER (Millipore) and 0.5% Triton X-100 (Sigma) in PBS (PBST) for 1 hr at RT and incubated in PBST overnight at 4°C with following primary antibodies: chicken anti-GFP (1:1000, Abcam ab13970), chicken anti-MAP2 (1:10,000, Abcam ab5392), goat anti-VAChT (1:1000, Millipore ABN100), guinea pig anti-RBPMS (1:1000, PhosphoSolutions 1832-RBPMS), mouse anti-AP2α (1:1000, DSHB 3B5), mouse anti-Bassoon (1:2500, Enzo Life Sciences ADI-VAM-PS003), mouse anti-Brn3a (1:300, Millipore MAB1585), mouse anti-Calbindin-D-28K (1:200, Sigma C9848), mouse anti-PKCα (1:500, Santa Cruz sc-8393), rabbit anti-Strn (Striatin) (1:500, BD Biosciences 610838), rabbit anti-CART (1:2000, Phoenix Pharmaceuticals H-003–62), rabbit anti-m⁶A (1:200, Synaptic Systems 202003), rabbit anti-melanopsin (1:1000, Thermo PA1-780), rabbit anti-PKCα (1:1000, Cell Signaling CST-2056), rabbit anti-PSD95 (1:1000, Abcam ab18258), rabbit anti-Recoverin (1:1000, Millipore AB5585), rabbit anti-YTHDF2 (1:1000, Proteintech 24744–1-AP), rabbit anti-YTHDF1 (1:1000, Proteintech 17479–1-AP), rabbit anti-YTHDF3 (1:1000, Abcam ab103328), rabbit anti-Ubr4 (1:300, Abcam ab86738), sheep anti-Chx10 (1:1000, Exalpha X1179P), chicken anti-GFAP (1:500, Millipore AB5541), goat anti-Lhx2 (1:200, Santa Cruz Biotechnology sc-19344), rabbit anti-Lhx2 (1:500, Abcam ab184337). After three times of PBS washing, sections were incubated in PBST for 1 hr at RT with secondary antibodies: Alexa 488 donkey anti-chicken (1:500, Jackson 703-545-155), Alexa 488 donkey anti-guinea pig (1:500, Jackson 706-545-148), Alexa 488 donkey anti-mouse (1:500, Thermo A21202), Alexa 488 donkey anti-rabbit (1:500, Thermo A21206), Alexa 555 donkey anti-goat (1:1000, Thermo A21432), Alexa 555 donkey anti-mouse (1:1000, Thermo A31570), Alexa 555 donkey anti-rabbit (1:1000, Thermo A31572), Alexa 555 donkey anti-sheep (1:1000, Thermo A21436), Alexa 555 goat anti-chicken (1:1000, Thermo A21437), or Alexa 647 donkey anti-mouse (1:200, Thermo A31571) and then mounted with the VECTASHIELD Antifade Mounting Medium with DAPI (Vector Laboratory).

For cultured neurons, after twice of PBS washing, cells were fixed for 15 min with 4% PFA in 0.1 M PB at RT, then washed with PBS three times and blocked in PBST for 20 min at RT. Antibody incubation conditions are the same as tissue sections.

For wholemount immunostaining of retina, eyes were dissected after myocardial perfusion with 0.9% NaCl. Then retinas were separated from sclera and fixed with 4% PFA in 0.1 M PB for 1 hr at RT. Then retinas were blocked with 5% normal goat serum (Novus), 0.4% Triton X-100 in PBS overnight at 4°C. Primary antibodies such as chicken anti-GFP (1:1000, Abcam ab13970), mouse anti-Brn3a (1:300, Millipore MAB1585), mouse anti-SMI-32 (1:200, BioLegend 801701), or rabbit anti-Melanopsin (1:1000, Thermo PA1-780), rabbit anti-CART (1:2000, Phoenix Pharmaceuticals H-003–62) were diluted in 5% normal goat serum, 0.4% Triton X-100 in PBS and incubated overnight at 4°C. Then retinas were incubated with Alexa 488 donkey anti-chicken (1:500, Jackson 703-545-155), Alexa 488 donkey anti-mouse (1:500, Thermo A21202), Alexa 555 donkey anti-mouse (1:1000, Thermo A-31570) and Alexa 555 donkey anti-rabbit (1:1000, Thermo A31572) secondary antibodies in 5% normal goat serum (Novus), 0.4% Triton X-100 in PBS and finally mounted with the VECTASHIELD Antifade Mounting Medium with DAPI.

All images were captured on Nikon A1R confocal microscope or Zeiss LSM 800 confocal microscope with identical settings for each group in the same experiment. A region of interest, length or thickness in immunofluorescence experiments were obtained with ImageJ. The number of neurons in specific area was counted blindly and manually. To quantify RGC dendrite lamination in IPL with Thy1-GFP, z-stack and maximum projection were performed during the analysis. GFP intensity values across IPL depth were measured by ImageJ/Analyze/Plot Profile function (Liu et al., 2018). To quantify the numbers of Bassoon⁺/PSD-95⁺ excitatory synapses in IPL, the colocalization puncta was measured by ImageJ/Analyze/Puncta Analyzer as described previously (Ippolito and Eroglu, 2010).

Sholl analysis

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For confocal images of cultured RGCs, MAP2 signals in original format were analyzed with simple neurite tracer and then quantified with Sholl analysis (5 μm per distance from soma center) which was a widely used method in neurobiology to quantify the complexity of dendritic arbors using ImageJ (Schindelin et al., 2012; Binley et al., 2014). Retina wholemount data were captured in z-stack mode (0.5–1 μm per slide) with confocal microscopes. ZsGreen, eGFP, and SMI-32 signals were directly analyzed with simple neurite tracer and then z projection of all tracers was quantified with Sholl analysis (10 μm per distance from soma center), while melanopsin signals were maximum-projected before tracing.

OMR assay

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Ythdf2 cKO and control mice aged about 6 weeks were dark-adapted overnight before experiment and used in the OMR assay following the previously reported protocols (Douglas et al., 2005; Sergeeva et al., 2018). Using the Matlab program, 0.2 c/deg (15 s per direction of rotation) was first used for mice to adapt this experiment, and 0.3, 0.35, 0.4, 0.43, 0.45, 0.47, 0.5 and 0.55 c/deg (30 s per direction of rotation) were used in the following recordings. Mouse behaviors were analyzed in real time during the experiment and re-checked with video recordings. Finally, data for each mouse were determined by the minimal spatial frequency between left and right OMR.

CTB labeling of optic nerve

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To label RGC axon terminals in mouse brain, RGC axons were anterogradely labeled by CTB conjugated with Alexa Fluor 555 (Invitrogen, C34776) through intravitreal injection 48 hr before sacrifice. After PFA perfusion, the brains were fixed with 4% PFA in 0.1 M PB overnight, dehydrated with 15% sucrose and 30% sucrose in 0.1 M PB overnight at 4°C sequentially, embedded with OCT for coronal section, and cryosectioned at 12 μm with Leica CM1950 Cryostat. After PBS washing, the sections were mounted with VECTASHIELD Antifade Mounting Medium with DAPI (Vector Laboratory). The images were captured on Tissue Genostics with identical settings for each group in the same experiment with the TissueFAXS 7.0 software.

RIP and sequencing

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For RIP experiment, we used the EZ-Magna RIP RNA-Binding Protein Immunoprecipitation Kit (Millipore) following the manual with minor modifications. Briefly, 1 × 10⁷ retinal neurons were subjected to each 100 μl lysis buffer. The amount of YTHDF2 antibody (Proteintech, 24744–1-AP) and control IgG used for immunoprecipitation is 5 μg, respectively. RIP experimental steps, RNA sample preparation and sequencing, and sequence data analysis followed the procedures reported previously (Yu et al., 2021a).

MS analysis

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E15.5 retinal neurons were cultured and infected with lentiviral shYthdf2 or shCtrl. Sample collection and lysis, protein and peptide preparation were performed following procedures reported previously (Yu et al., 2021b). Proteins with fold changes greater than 1.3 and p values less than 0.05 were considered to be regulated by YTHDF2 KD with statistical significance.

Anti-m⁶A immunoprecipitation

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Total retinal RNA was extracted from P0 WT mouse pups. Immunoprecipitation of m⁶A-modified transcripts was carried out with Magna MeRIP m⁶A Kit (Merck-Millipore, 17–10499) following the manual. m⁶A antibody (Synaptic Systems, 202003) and corresponding control IgG were used in this experiment. The RNA samples pulled down from the experiment were used for RT-qPCR.

AOH model

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Mice were anesthetized with 5% chloral hydrate in normal saline (10 μl/g) based on body weight and the Compound Tropicamide Eye Drops were used to scatter pupil. The anterior chamber was penetrated using the 32G × 1/2’’ needles (TSK) and filled with the BBS Sterile Irrigating Solution (Alcon) which was hung at a high position to provide proper pressure. Intraocular pressure was measured with the Tonolab tonometer (icare) for every 10 min and maintained at 85–90 mmHg for 1 hr. Levofloxacin hydrochloride was used after the operation and mice were revived in a 37°C environment. Retinas were analyzed for gene expression of YTHDF2 1 day after AOH, gene expression of Hspa12a and Islr2 3 days after AOH, dendritic complexity and RGC number 3–7 days after AOH.

Statistical analysis

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All experiments were conducted at a minimum of three independent biological replicates (two biological replicates for the RIP assay) or three mice/pups for each genotype/condition in the lab. Data are mean ± SEM. Statistical analysis was preformed using GraphPad Prism 7.0. When comparing the means of two groups, an unpaired or paired t test was performed on the basis of experimental design. The settings for all box and whisker plots are: 25th-75th percentiles (boxes), minimum and maximum (whiskers), and medians (horizontal lines). A p value less than 0.05 was considered as statistically significant: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Data availability

The RIP-seq data have been deposited to the Gene Expression Omnibus (GEO) with accession number GSE145390. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD017775.

The following data sets were generated

1. Niu F
2. Yang L
3. Ji S
(2022) NCBI Gene Expression Omnibus
ID GSE145390. Anti YTHDF2 RIP-seq to identify YTHDF2 target mRNAs in P0 mouse retinas.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145390
1. Niu F
2. Ji S
(2022) PRIDE
ID PXD017775. Proteome analysis using mass spectrometry (MS) in acute shYthdf2-mediated knockdown of cultured RGCs.

https://www.ebi.ac.uk/pride/archive/projects/PXD017775

References

1. Agostinone J
2. Di Polo A
(2015) Retinal ganglion cell dendrite pathology and synapse loss: Implications for glaucoma
Progress in Brain Research 220:199–216.
https://doi.org/10.1016/bs.pbr.2015.04.012
- PubMed
- Google Scholar
(2008)
Time course profiling of the retinal transcriptome after optic nerve transection and optic nerve crush

Molecular Vision 14:1050–1063.
- PubMed
- Google Scholar
1. Anders S
2. Pyl PT
3. Huber W
(2015) HTSeq--a Python framework to work with high-throughput sequencing data
Bioinformatics (Oxford, England) 31:166–169.
https://doi.org/10.1093/bioinformatics/btu638
- PubMed
- Google Scholar
1. Baden T
2. Berens P
3. Franke K
4. Román Rosón M
5. Bethge M
6. Euler T
(2016) The functional diversity of retinal ganglion cells in the mouse
Nature 529:345–350.
https://doi.org/10.1038/nature16468
- PubMed
- Google Scholar
(2006) The striatin family: a new signaling platform in dendritic spines
Journal of Physiology, Paris 99:146–153.
https://doi.org/10.1016/j.jphysparis.2005.12.006
- PubMed
- Google Scholar
1. Binley KE
2. Ng WS
3. Tribble JR
4. Song B
5. Morgan JE
(2014) Sholl analysis: a quantitative comparison of semi-automated methods
Journal of Neuroscience Methods 225:65–70.
https://doi.org/10.1016/j.jneumeth.2014.01.017
- PubMed
- Google Scholar
1. Brechbiel JL
2. Gavis ER
(2008) Spatial regulation of nanos is required for its function in dendrite morphogenesis
Current Biology 18:745–750.
https://doi.org/10.1016/j.cub.2008.04.033
- PubMed
- Google Scholar
(2008) The armadillo repeat domain of the APC tumor suppressor protein interacts with Striatin family members
Biochimica et Biophysica Acta 1783:1792–1802.
https://doi.org/10.1016/j.bbamcr.2008.04.017
- PubMed
- Google Scholar
1. Cahill ME
2. Xie Z
3. Day M
4. Photowala H
5. Barbolina MV
6. Miller CA
7. Weiss C
8. Radulovic J
9. Sweatt JD
10. Disterhoft JF
11. Surmeier DJ
12. Penzes P
(2009) Kalirin regulates cortical spine morphogenesis and disease-related behavioral phenotypes
PNAS 106:13058–13063.
https://doi.org/10.1073/pnas.0904636106
- PubMed
- Google Scholar
1. Cherry TJ
2. Wang S
3. Bormuth I
4. Schwab M
5. Olson J
6. Cepko CL
(2011) NeuroD factors regulate cell fate and neurite stratification in the developing retina
The Journal of Neuroscience 31:7365–7379.
https://doi.org/10.1523/JNEUROSCI.2555-10.2011
- PubMed
- Google Scholar
1. Cheung ZH
2. Chin WH
3. Chen Y
4. Ng YP
5. Ip NY
(2007) Cdk5 is involved in BDNF-stimulated dendritic growth in hippocampal neurons
PLOS Biology 5:e63.
https://doi.org/10.1371/journal.pbio.0050063
- PubMed
- Google Scholar
(2007) Cytoplasmic and mitochondrial protein translation in axonal and dendritic terminal arborization
Nature Neuroscience 10:828–837.
https://doi.org/10.1038/nn1910
- PubMed
- Google Scholar
(2015) Cux1 and Cux2 selectively target basal and apical dendritic compartments of layer II-III cortical neurons
Developmental Neurobiology 75:163–172.
https://doi.org/10.1002/dneu.22215
- PubMed
- Google Scholar
1. Dobin A
2. Davis CA
3. Schlesinger F
4. Drenkow J
5. Zaleski C
6. Jha S
7. Batut P
8. Chaisson M
9. Gingeras TR
(2013) STAR: ultrafast universal RNA-seq aligner
Bioinformatics (Oxford, England) 29:15–21.
https://doi.org/10.1093/bioinformatics/bts635
- PubMed
- Google Scholar
(2012) Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq
Nature 485:201–206.
https://doi.org/10.1038/nature11112
- PubMed
- Google Scholar
1. Dong X
2. Shen K
3. Bülow HE
(2015) Intrinsic and extrinsic mechanisms of dendritic morphogenesis
Annual Review of Physiology 77:271–300.
https://doi.org/10.1146/annurev-physiol-021014-071746
- PubMed
- Google Scholar
1. Douglas RM
2. Alam NM
3. Silver BD
4. McGill TJ
5. Tschetter WW
6. Prusky GT
(2005) Independent visual threshold measurements in the two eyes of freely moving rats and mice using a virtual-reality optokinetic system
Visual Neuroscience 22:677–684.
https://doi.org/10.1017/S0952523805225166
- PubMed
- Google Scholar
1. Feng G
2. Mellor RH
3. Bernstein M
4. Keller-Peck C
5. Nguyen QT
6. Wallace M
7. Nerbonne JM
8. Lichtman JW
9. Sanes JR
(2000) Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP
Neuron 28:41–51.
https://doi.org/10.1016/s0896-6273(00)00084-2
- PubMed
- Google Scholar
1. Furuta Y
2. Lagutin O
3. Hogan BL
4. Oliver GC
(2000) Retina- and ventral forebrain-specific Cre recombinase activity in transgenic mice
Genesis (New York, N.Y 26:130–132.
https://doi.org/10.1002/(SICI)1526-968X(200002)26:2<130::AID-GENE9>3.0.CO;2-I
- PubMed
- Google Scholar
1. Hattar S
2. Liao HW
3. Takao M
4. Berson DM
5. Yau KW
(2002) Melanopsin-containing retinal ganglion cells: architecture, projections, and intrinsic photosensitivity
Science (New York, N.Y.) 295:1065–1070.
https://doi.org/10.1126/science.1069609
- PubMed
- Google Scholar
1. Herring BE
2. Nicoll RA
(2016) Kalirin and Trio proteins serve critical roles in excitatory synaptic transmission and LTP
PNAS 113:2264–2269.
https://doi.org/10.1073/pnas.1600179113
- PubMed
- Google Scholar
1. Ippolito DM
2. Eroglu C
(2010) Quantifying synapses: an immunocytochemistry-based assay to quantify synapse number
Journal of Visualized Experiments 2270.
https://doi.org/10.3791/2270
- PubMed
- Google Scholar
1. Jakobs TC
(2014) Differential gene expression in glaucoma
Cold Spring Harbor Perspectives in Medicine 4:a020636.
https://doi.org/10.1101/cshperspect.a020636
- PubMed
- Google Scholar
1. Jan YN
2. Jan LY
(2010) Branching out: mechanisms of dendritic arborization
Nature Reviews. Neuroscience 11:316–328.
https://doi.org/10.1038/nrn2836
- PubMed
- Google Scholar
1. Kay JN
2. De la Huerta I
3. Kim IJ
4. Zhang Y
5. Yamagata M
6. Chu MW
7. Meister M
8. Sanes JR
(2011a) Retinal ganglion cells with distinct directional preferences differ in molecular identity, structure, and central projections
The Journal of Neuroscience 31:7753–7762.
https://doi.org/10.1523/JNEUROSCI.0907-11.2011
- PubMed
- Google Scholar
(2011b) Neurod6 expression defines new retinal amacrine cell subtypes and regulates their fate
Nature Neuroscience 14:965–972.
https://doi.org/10.1038/nn.2859
- PubMed
- Google Scholar
1. Kechad A
2. Jolicoeur C
3. Tufford A
4. Mattar P
5. Chow RWY
6. Harris WA
7. Cayouette M
(2012) Numb is required for the production of terminal asymmetric cell divisions in the developing mouse retina
The Journal of Neuroscience 32:17197–17210.
https://doi.org/10.1523/JNEUROSCI.4127-12.2012
- PubMed
- Google Scholar
1. Krishnaswamy A
2. Yamagata M
3. Duan X
4. Hong YK
5. Sanes JR
(2015) Sidekick 2 directs formation of a retinal circuit that detects differential motion
Nature 524:466–470.
https://doi.org/10.1038/nature14682
- PubMed
- Google Scholar
1. Lanoue V
2. Langford M
3. White A
4. Sempert K
5. Fogg L
6. Cooper HM
(2017) The Wnt receptor Ryk is a negative regulator of mammalian dendrite morphogenesis
Scientific Reports 7:5965.
https://doi.org/10.1038/s41598-017-06140-z
- PubMed
- Google Scholar
1. Ledda F
2. Paratcha G
(2017) Mechanisms regulating dendritic arbor patterning
Cellular and Molecular Life Sciences 74:4511–4537.
https://doi.org/10.1007/s00018-017-2588-8
- PubMed
- Google Scholar
(2012) Protocadherins mediate dendritic self-avoidance in the mammalian nervous system
Nature 488:517–521.
https://doi.org/10.1038/nature11305
- PubMed
- Google Scholar
(2015) Development of dendritic form and function
Annual Review of Cell and Developmental Biology 31:741–777.
https://doi.org/10.1146/annurev-cellbio-100913-013020
- PubMed
- Google Scholar
1. Li D
2. Musante V
3. Zhou W
4. Picciotto MR
5. Nairn AC
(2018) Striatin-1 is a B subunit of protein phosphatase PP2A that regulates dendritic arborization and spine development in striatal neurons
The Journal of Biological Chemistry 293:11179–11194.
https://doi.org/10.1074/jbc.RA117.001519
- PubMed
- Google Scholar
1. Lin B
2. Wang SW
3. Masland RH
(2004) Retinal ganglion cell type, size, and spacing can be specified independent of homotypic dendritic contacts
Neuron 43:475–485.
https://doi.org/10.1016/j.neuron.2004.08.002
- PubMed
- Google Scholar
1. Lin L
2. Lo LH-Y
3. Lyu Q
4. Lai K-O
(2017) Determination of dendritic spine morphology by the striatin scaffold protein STRN4 through interaction with the phosphatase PP2A
The Journal of Biological Chemistry 292:9451–9464.
https://doi.org/10.1074/jbc.M116.772442
- PubMed
- Google Scholar
1. Liu J
2. Sanes JR
(2017) Cellular and Molecular Analysis of Dendritic Morphogenesis in a Retinal Cell Type That Senses Color Contrast and Ventral Motion
The Journal of Neuroscience 37:12247–12262.
https://doi.org/10.1523/JNEUROSCI.2098-17.2017
- PubMed
- Google Scholar
1. Liu J
2. Reggiani JDS
3. Laboulaye MA
4. Pandey S
5. Chen B
6. Rubenstein JLR
7. Krishnaswamy A
8. Sanes JR
(2018) Tbr1 instructs laminar patterning of retinal ganglion cell dendrites
Nature Neuroscience 21:659–670.
https://doi.org/10.1038/s41593-018-0127-z
- PubMed
- Google Scholar
(2020) The m⁶A epitranscriptome: transcriptome plasticity in brain development and function
Nature Reviews. Neuroscience 21:36–51.
https://doi.org/10.1038/s41583-019-0244-z
- PubMed
- Google Scholar
1. Lu J
2. Luo C
3. Bali KK
4. Xie RG
5. Mains RE
6. Eipper BA
7. Kuner R
(2015) A role for Kalirin-7 in nociceptive sensitization via activity-dependent modulation of spinal synapses
Nature Communications 6:6820.
https://doi.org/10.1038/ncomms7820
- PubMed
- Google Scholar
(2011) Kalrn promoter usage and isoform expression respond to chronic cocaine exposure
BMC Neuroscience 12:20.
https://doi.org/10.1186/1471-2202-12-20
- PubMed
- Google Scholar
1. Mao Y
2. Kong Q
3. Li R
4. Zhang X
5. Gui Y
6. Li Y
7. Li C
8. Zhao Y
9. Liu L
10. Ding Z
(2018) Heat shock protein A12A encodes a novel prosurvival pathway during ischaemic stroke
Biochimica et Biophysica Acta. Molecular Basis of Disease 1864:1862–1872.
https://doi.org/10.1016/j.bbadis.2018.03.006
- PubMed
- Google Scholar
1. Meyer KD
2. Saletore Y
3. Zumbo P
4. Elemento O
5. Mason CE
6. Jaffrey SR
(2012) Comprehensive analysis of mRNA methylation reveals enrichment in 3’ UTRs and near stop codons
Cell 149:1635–1646.
https://doi.org/10.1016/j.cell.2012.05.003
- PubMed
- Google Scholar
1. Min X
2. Zhang X
3. Li Y
4. Cao X
5. Cheng H
6. Li Y
7. Li C
8. Kong Q
9. Mao Q
10. Peng P
11. Ni Y
12. Li J
13. Duan Y
14. Liu L
15. Ding Z
(2020) HSPA12A unstabilizes CD147 to inhibit lactate export and migration in human renal cell carcinoma
Theranostics 10:8573–8590.
https://doi.org/10.7150/thno.44321
- PubMed
- Google Scholar
1. Morgan JE
2. Datta AV
3. Erichsen JT
4. Albon J
5. Boulton ME
(2006) Retinal ganglion cell remodelling in experimental glaucoma
Advances in Experimental Medicine and Biology 572:397–402.
https://doi.org/10.1007/0-387-32442-9_56
- PubMed
- Google Scholar
1. Nachtergaele S
2. He C
(2018) Chemical Modifications in the Life of an mRNA Transcript
Annual Review of Genetics 52:349–372.
https://doi.org/10.1146/annurev-genet-120417-031522
- PubMed
- Google Scholar
(2015) p600/UBR4 in the central nervous system
Cellular and Molecular Life Sciences 72:1149–1160.
https://doi.org/10.1007/s00018-014-1788-8
- PubMed
- Google Scholar
1. Penzes P
2. Johnson RC
3. Sattler R
4. Zhang X
5. Huganir RL
6. Kambampati V
7. Mains RE
8. Eipper BA
(2001) The neuronal Rho-GEF Kalirin-7 interacts with PDZ domain-containing proteins and regulates dendritic morphogenesis
Neuron 29:229–242.
https://doi.org/10.1016/s0896-6273(01)00193-3
- PubMed
- Google Scholar
1. Pongrac JL
2. Middleton FA
3. Peng L
4. Lewis DA
5. Levitt P
6. Mirnics K
(2004) Heat shock protein 12A shows reduced expression in the prefrontal cortex of subjects with schizophrenia
Biological Psychiatry 56:943–950.
https://doi.org/10.1016/j.biopsych.2004.09.005
- PubMed
- Google Scholar
1. Prigge CL
2. Kay JN
(2018) Dendrite morphogenesis from birth to adulthood
Current Opinion in Neurobiology 53:139–145.
https://doi.org/10.1016/j.conb.2018.07.007
- PubMed
- Google Scholar
(2004) Rapid quantification of adult and developing mouse spatial vision using a virtual optomotor system
Investigative Ophthalmology & Visual Science 45:4611–4616.
https://doi.org/10.1167/iovs.04-0541
- PubMed
- Google Scholar
1. Ramos B
2. Gaudillière B
3. Bonni A
4. Gill G
(2007) Transcription factor Sp4 regulates dendritic patterning during cerebellar maturation
PNAS 104:9882–9887.
https://doi.org/10.1073/pnas.0701946104
- PubMed
- Google Scholar
(2014) Cas adaptor proteins organize the retinal ganglion cell layer downstream of integrin signaling
Neuron 81:779–786.
https://doi.org/10.1016/j.neuron.2014.01.036
- PubMed
- Google Scholar
(2005) Wnt signaling through Dishevelled, Rac and JNK regulates dendritic development
Nature Neuroscience 8:34–42.
https://doi.org/10.1038/nn1374
- PubMed
- Google Scholar
1. Russell TA
2. Blizinsky KD
3. Cobia DJ
4. Cahill ME
5. Xie Z
6. Sweet RA
7. Duan J
8. Gejman PV
9. Wang L
10. Csernansky JG
11. Penzes P
(2014) A sequence variant in human KALRN impairs protein function and coincides with reduced cortical thickness
Nature Communications 5:4858.
https://doi.org/10.1038/ncomms5858
- PubMed
- Google Scholar
1. Sanes JR
2. Masland RH
(2015) The types of retinal ganglion cells: current status and implications for neuronal classification
Annual Review of Neuroscience 38:221–246.
https://doi.org/10.1146/annurev-neuro-071714-034120
- PubMed
- Google Scholar
1. Sapkota D
2. Chintala H
3. Wu F
4. Fliesler SJ
5. Hu Z
6. Mu X
(2014) Onecut1 and Onecut2 redundantly regulate early retinal cell fates during development
PNAS 111:E4086–E4095.
https://doi.org/10.1073/pnas.1405354111
- PubMed
- Google Scholar
1. Schindelin J
2. Arganda-Carreras I
3. Frise E
4. Kaynig V
5. Longair M
6. Pietzsch T
7. Preibisch S
8. Rueden C
9. Saalfeld S
10. Schmid B
11. Tinevez JY
12. White DJ
13. Hartenstein V
14. Eliceiri K
15. Tomancak P
16. Cardona A
(2012) Fiji: an open-source platform for biological-image analysis
Nature Methods 9:676–682.
https://doi.org/10.1038/nmeth.2019
- PubMed
- Google Scholar
(2018) Neurosteroid allopregnanolone reduces ipsilateral visual cortex potentiation following unilateral optic nerve injury
Experimental Neurology 306:138–148.
https://doi.org/10.1016/j.expneurol.2018.05.005
- PubMed
- Google Scholar
1. Shi C
2. Yuan X
3. Chang K
4. Cho KS
5. Xie XS
6. Chen DF
7. Luo G
(2018) Optimization of Optomotor Response-based Visual Function Assessment in Mice
Scientific Reports 8:9708.
https://doi.org/10.1038/s41598-018-27329-w
- PubMed
- Google Scholar
1. Shim SY
2. Wang J
3. Asada N
4. Neumayer G
5. Tran HC
6. Ishiguro K
7. Sanada K
8. Nakatani Y
9. Nguyen MD
(2008) Protein 600 is a microtubule/endoplasmic reticulum-associated protein in CNS neurons
The Journal of Neuroscience 28:3604–3614.
https://doi.org/10.1523/JNEUROSCI.5278-07.2008
- PubMed
- Google Scholar
1. Shima Y
2. Kengaku M
3. Hirano T
4. Takeichi M
5. Uemura T
(2004) Regulation of dendritic maintenance and growth by a mammalian 7-pass transmembrane cadherin
Developmental Cell 7:205–216.
https://doi.org/10.1016/j.devcel.2004.07.007
- PubMed
- Google Scholar
1. Shima Y
2. Kawaguchi S
3. Kosaka K
4. Nakayama M
5. Hoshino M
6. Nabeshima Y
7. Hirano T
8. Uemura T
(2007) Opposing roles in neurite growth control by two seven-pass transmembrane cadherins
Nature Neuroscience 10:963–969.
https://doi.org/10.1038/nn1933
- PubMed
- Google Scholar
1. Shou T
2. Liu J
3. Wang W
4. Zhou Y
5. Zhao K
(2003) Differential dendritic shrinkage of alpha and beta retinal ganglion cells in cats with chronic glaucoma
Investigative Ophthalmology & Visual Science 44:3005–3010.
https://doi.org/10.1167/iovs.02-0620
- PubMed
- Google Scholar
1. Srinivas S
2. Watanabe T
3. Lin CS
4. William CM
5. Tanabe Y
6. Jessell TM
7. Costantini F
(2001) Cre reporter strains produced by targeted insertion of EYFP and ECFP into the ROSA26 locus
BMC Developmental Biology 1:4.
https://doi.org/10.1186/1471-213x-1-4
- PubMed
- Google Scholar
1. Tran NM
2. Shekhar K
3. Whitney IE
4. Jacobi A
5. Benhar I
6. Hong G
7. Yan W
8. Adiconis X
9. Arnold ME
10. Lee JM
11. Levin JZ
12. Lin D
13. Wang C
14. Lieber CM
15. Regev A
16. He Z
17. Sanes JR
(2019) Single-Cell Profiles of Retinal Ganglion Cells Differing in Resilience to Injury Reveal Neuroprotective Genes
Neuron 104:1039–1055.
https://doi.org/10.1016/j.neuron.2019.11.006
- PubMed
- Google Scholar
(2008) Speed, spatial, and temporal tuning of rod and cone vision in mouse
The Journal of Neuroscience 28:189–198.
https://doi.org/10.1523/JNEUROSCI.3551-07.2008
- PubMed
- Google Scholar
1. Vessey JP
2. Macchi P
3. Stein JM
4. Mikl M
5. Hawker KN
6. Vogelsang P
7. Wieczorek K
8. Vendra G
9. Riefler J
10. Tübing F
11. Aparicio SAJ
12. Abel T
13. Kiebler MA
(2008) A loss of function allele for murine Staufen1 leads to impairment of dendritic Staufen1-RNP delivery and dendritic spine morphogenesis
PNAS 105:16374–16379.
https://doi.org/10.1073/pnas.0804583105
- PubMed
- Google Scholar
1. Wang X
2. Lu Z
3. Gomez A
4. Hon GC
5. Yue Y
6. Han D
7. Fu Y
8. Parisien M
9. Dai Q
10. Jia G
11. Ren B
12. Pan T
13. He C
(2014) N6-methyladenosine-dependent regulation of messenger RNA stability
Nature 505:117–120.
https://doi.org/10.1038/nature12730
- PubMed
- Google Scholar
1. Wang Y
2. Li Y
3. Yue M
4. Wang J
5. Kumar S
6. Wechsler-Reya RJ
7. Zhang Z
8. Ogawa Y
9. Kellis M
10. Duester G
11. Zhao JC
(2018) N⁶-methyladenosine RNA modification regulates embryonic neural stem cell self-renewal through histone modifications
Nature Neuroscience 21:195–206.
https://doi.org/10.1038/s41593-017-0057-1
- PubMed
- Google Scholar
(1998)
Morphology of single ganglion cells in the glaucomatous primate retina

Investigative Ophthalmology & Visual Science 39:2304–2320.
- Google Scholar
1. Xie Z
2. Srivastava DP
3. Photowala H
4. Kai L
5. Cahill ME
6. Woolfrey KM
7. Shum CY
8. Surmeier DJ
9. Penzes P
(2007) Kalirin-7 controls activity-dependent structural and functional plasticity of dendritic spines
Neuron 56:640–656.
https://doi.org/10.1016/j.neuron.2007.10.005
- PubMed
- Google Scholar
1. Xie Z
2. Cahill ME
3. Penzes P
(2010) Kalirin loss results in cortical morphological alterations
Molecular and Cellular Neurosciences 43:81–89.
https://doi.org/10.1016/j.mcn.2009.09.006
- PubMed
- Google Scholar
1. Yan Y
2. Eipper BA
3. Mains RE
(2015) Kalirin-9 and Kalirin-12 Play Essential Roles in Dendritic Outgrowth and Branching
Cerebral Cortex (New York, N.Y 25:3487–3501.
https://doi.org/10.1093/cercor/bhu182
- PubMed
- Google Scholar
1. Ye B
2. Petritsch C
3. Clark IE
4. Gavis ER
5. Jan LY
6. Jan YN
(2004) Nanos and Pumilio are essential for dendrite morphogenesis in Drosophila peripheral neurons
Current Biology 14:314–321.
https://doi.org/10.1016/j.cub.2004.01.052
- PubMed
- Google Scholar
1. Yu J
2. Chen M
3. Huang H
4. Zhu J
5. Song H
6. Zhu J
7. Park J
8. Ji SJ
(2018) Dynamic m6A modification regulates local translation of mRNA in axons
Nucleic Acids Research 46:1412–1423.
https://doi.org/10.1093/nar/gkx1182
- PubMed
- Google Scholar
1. Yu J
2. She Y
3. Ji SJ
(2021a) m⁶A Modification in Mammalian Nervous System Development, Functions, Disorders, and Injuries
Frontiers in Cell and Developmental Biology 9:679662.
https://doi.org/10.3389/fcell.2021.679662
- PubMed
- Google Scholar
1. Yu J
2. She Y
3. Yang L
4. Zhuang M
5. Han P
6. Liu J
7. Lin X
8. Wang N
9. Chen M
10. Jiang C
11. Zhang Y
12. Yuan Y
13. Ji SJ
(2021b) The m⁶ A Readers YTHDF1 and YTHDF2 Synergistically Control Cerebellar Parallel Fiber Growth by Regulating Local Translation of the Key Wnt5a Signaling Components in Axons
Advanced Science (Weinheim, Baden-Wurttemberg, Germany) 8:e2101329.
https://doi.org/10.1002/advs.202101329
- PubMed
- Google Scholar
1. Zhou X
2. Qyang Y
3. Kelsoe JR
4. Masliah E
5. Geyer MA
(2007) Impaired postnatal development of hippocampal dentate gyrus in Sp4 null mutant mice
Genes, Brain, and Behavior 6:269–276.
https://doi.org/10.1111/j.1601-183X.2006.00256.x
- PubMed
- Google Scholar

Decision letter

Carol A Mason

Reviewing Editor; Columbia University, United States
Catherine Dulac

Senior Editor; Harvard University, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "The m6A reader YTHDF2 is a negative regulator for dendrite development and maintenance of retinal ganglion cells" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

The reviewers have provided thorough assessment of your study proposing a role for the m6A reader YTHDF2 in regulating retinal ganglion cell (RGCs) dendritic arbor size, and maintenance of RGCs, with implications for retinal IPL morphology and for glaucoma. Unfortunately, as you can read in the reviews, the reviewers had a number of concerns that would each require additional work in a longer time frame required by eLife for revision (and recognizing the additional downtime due to the COVID crisis). The concerns include:

– Better phenotyping of the Ythdf2 cKO mouse model, including cross sections of retina in addition to horizontal views to more precisely measure layer dimensions, synapse number and dendritic extension; whether cells other than RGCs are affected; co-localization of YTHDF2 and RGC markers. Moreover, the connection between the dendrite development phenotype and the neuroprotective role of YTHDF2 is not clear from your analyses.

– in vivo evidence for the putative targets of YTHDF2, rather than simply in vitro, a better understanding of how the products produced by these mRNAs – kalirin, Strn and Ubr4 – contribute to the increase in dendrite branching in the Ythdf2 knockout; the mechanism of YTHDF2 upregulation induced by AOH and loss of Brn3a+ RGCs thereof.

– The use of the optomotor response is not an apt measure function, especially in the absence of connecting the response to the classes of direction-selective RGCs which one would expect might interface with OMR responses.

– Ythdf2 effects in the acute ocular hypertension (AOH) model: Is this related to the downstream mRNAs, or some other more general effect of loss of this m6 reader? And how is this related to RGC survival at a mechanistic level (and thus the relation to glaucoma)?

We hope that you can use the reviewer's comments to amend your manuscript for submission elsewhere.

Reviewer #1:

The authors report a functional-relevant role of YTHDF2 in mouse retina ganglion cells (RGCs) to negatively regulate dendrite development and maintenance of RGCs. Mechanistically, Kalrn, Strn, and Ubr4 mRNAs are selectively recognized and decay through the YTHDF2-mediated pathway, the subsequent downregulation of proteins encoded by those mRNAs negatively regulate dendrite development and maintenance of RGCs.

This work highlights regulatory roles of N6-methyladenosine (m6A) and YTHDF2 protein in retina and suggested YTHDF2 as one possible target in AOH-induced RGC loss. A few concerns will need to be addressed.

Concerns:

1. The authors showed YTHDF2 mRNA is upregulated by AOH and argued a loss of YTHDF2 in retina results in less severe AOH-induced loss of Brn3a+ RGCs. The mechanism of YTHDF2 upregulation induced by AOH and loss of Brn3a+ RGCs mediated by YTHDF2 upregulation are unclear. The first question might be harder to address but the second one is within the scope of this work.

2. In figure 7B, YTHDF2 expression in Brn3a+ RGCs was quantified. The figure showed that Brn3a was not detected in some cells. In figure 7C, mRNA level was quantified with an extraction method that did not separate Brn3a+ and Brn3a- cells.

3. The authors showed AOH-induced loss of Brn3a+ RGCs in mouse models. Supportive evidence at the phenotype level such as less severe loss of visual acuity in YTHDF2 cKO mice are required.

4. The authors showed knockdown of Kalrn, Strn, and Ubr4 are sufficient to impair dendrite growth. Rescue experiments will further back up their claim.

5. The authors suggested that m6A-YTHDF2 axis regulates the stability of Kalrn, Strn, and Ubr4 mRNAs. The authors will need to show these RNAs contain m6A by m6A-IP-qPCR. The effect on Kalrn, Strn, and Ubr4 mRNAs upon m6A writer complex knockdown can also be shown.

Reviewer #2:

This manuscript investigates the role of the m6A reader YTHDF2 during retinal ganglion cell (RGC) dendrite development and branching. The data presented in this study shows that deletion of YTHDF2 in the retina led to increased RGC dendrite branching and improved visual acuity. Based on high throughput analysis, YTHDF2 is suggested to regulate dendrite branching by reducing the stability of kalirin, Strn and Ubr4 mRNAs. Lastly, loss of YTHDF2 is shown to prevent RGC loss in a glaucoma model. The experimental designs were presented clearly, and the results were interpreted with the appropriate statistical tests. However, the phenotype of the Ythdf2 cKO mouse model is not well characterized and there lacks in vivo evidence for the putative targets of YTHDF2. It is also difficult to explain the connection, if any, between the dendritic role of YTHDF2 and its neuroprotective function.

1. The authors used RGC cultures to show that knockdown/knockout of YTHDF2 resulted in increased the dendrite branching based on the number of interactions in Sholl analysis. However, to determine the full extent of dendritic defect, it is important to perform detailed analysis of the dendrite structure, including the total dendritic length, number of total segments, maximum branch length, branch order and number of branches.

2. It is suggested in the manuscript that loss of YTHDF2 in the retina only affects dendrite development of RGCs, but not other cell types. This is based on the simple counting of the number of RPCs at E15 and bipolar and amacrine cells at P15, glossing over the vast complexity of the visual circuitry in the retina. At the very least, the authors should confirm that differentiation of all major retinal neurons and proper formation of the ribbon synapses were unaffected in the cKO mouse model of YTHDF2, which would other confound the interpretation of the RGC and visual acuity phenotype.

3. The in vivo characterisation of RGC dendrite morphology should be more thorough as previously mentioned, including the arbor shape, size and tiling pattern. The image quality of Melanopsin and SMI-32 staining is low. There are too many cells labelled, making it difficult to examine individual cells/dendrites. Higher resolution images from more sparsely labelled retina would be needed.

4. The authors provide evidence of increased synaptic density in the IPL using PSD-95 staining in the cKO mice compared to the control litter mates. It is important to investigate if there are any changes to the synaptic density in the OPL. In addition, it is also important to study the number of successful synapse formation by co-staining the tissues with presynaptic markers such as bassoon with PSD-95 and count for co-localisation.

5. The improved visual acuity in Six3Cre-mediated Ythdf2 cKO is solely attributed to the RGC dendrite defects. However, Six3Cre is widely expressed in the ventral telencephalon and ventral anterior hypothalamus, including the SCN and SPZ (PMID: 24767996). It is necessary to examine the retinocollicular projections of the RGC axons.

6. The Optomotor response (OMR)-based assay is not the most appropriate test to test the response of ganglion cells since the improved OMR could be attributed to other cell types as previously mentioned. A more targeted approach such as pattern ERG could provide more evidence to their claims.

7. The quality of the RIP-seq analysis is not clear. Is there an isotype antibody control? Are there biological replicates? What is the statistical significance of the top hits? There are similar concerns regarding the MS analysis and whether there is significant overlap between the target lists generated from RIP-Seq and MS studies.

8. The authors provide evidence in the RGC culture that stabilisation of kalirin, Strn and Ubr4 mRNAs could contribute to the increase in dendrite branching in Ythdf2 knockout. The regulation of these genes by Ythdf2 need to be validated in Ythdf2 cKO retina at the level of mRNA by qRT-PCR and at the level of protein by western blot. Functionally, the authors need to investigate if knockdown or knockout of these genes in retina indeed affect dendrite branching or even rescue Ythdf2 cKO phenotype.

9. Finally, there is not clear connection between the dendrite development phenotype and the neuroprotective role of YTHDF2. The authors need to clarify the rationale behind these experiments.

Reviewer #3:

In this study, the authors propose a role for the m6A reader YTHDF2 in regulating the dendritic arbor size of retinal ganglion cells (RGCs), and they extrapolate this to address issues in glaucoma and overall retina IPL morphology. They find that retina-specific loss of Ythdf2 leads to the expansion of RGC dendritic arbors in the horizontal plane and also a widening of the inner plexiform layer (IPL), with Ythdf2 cKOs showing a modest increase in visual acuity in an optomotor assay. They identify a number of factors downstream of YTHDF2 not previously known to be involved in retinal dendritic development, and they propose a role for Ythdf2 in a glaucoma model, providing a foundation for future studies into their functions in these contexts.

Although these data are sufficient to establish a role for Ythdf2 in RGC dendritic development and other more general aspects of retina morphology, many of the authors' specific claims are weakened by issues with the experiments, their analyses, and by weak effect sizes. Even if the points raised below were addressed, it remains unclear from this study how Ythdf2-mediated mechanisms are integrated into programs of dendritic development and RGC survival, diminishing the impact of this work. This study would be strengthened by, for example, identifying a developmental program that modifies the target mRNAs found in this study to promote recognition by YTHDF2, and also by providing better understanding of how the products produced by these mRNAs actually regulate dendrite morphology and synapse formation. Overall, while there are a number of promising findings in this study, the work required to address weaknesses falls well outside of the limits usually recommended by eLife, and it is suited for publication in a more specialized journal following attention to many of the points raised below.

1. The cell-type specific tracing in Figure 3 is difficult to assess due to the extremely high background in the melanopsin images and unclear signal in the SMI-32 images. This analysis would be improved by sparse viral labeling, with a fluorophore provided by the virus used for tracing and the melanopsin & SMI-32 antibodies used solely for establishing RGC subtype identity. Further, the authors emphasize that the defects they observe here are in the plane of retinal ganglion cell (RGC) dendritic arbors, but this is an over-interpretation of these data. One wonders why the authors did not examine in cross section the lamination within the IPL of the melanopsin-positive ipRGCs, since this would provide, at least for this RGC subclass, a direct assessment of this issue. Finally, the Thy-1-O line GFP distribution is quite general, and it really is not the correct line to use if one wants to investigate defects in lamination.

2. The authors repeatedly describe increased dendritic and synaptic density within the IPL in Ythdf2 cKOs, yet they only present absolute signal intensities to support these claims; without normalizing signal intensity to IPL width, it is impossible to determine whether changes in intensity are indeed due to increased density or from the IPL becoming enlarged with a similar density of dendrites and synapses. Further, they claim in the text that VGlut2 puncta numbers are changed in these mutants, however the analysis presented is only for general signal intensity. If claims are to be made regarding changes in synaptic specializations, higher resolution assessments of individual puncta using pre- and postsynaptic markers is required.

3. While Ythdf2 cKOs do show a statistically significant improvement in visual acuity (although for these male data it is unclear whether the control data distribution is sufficiently normal to use a t-test), the effect size is small enough to call into question how meaningful the improvement is. Further, what is the actual relationship between this modest improvement in optomotor response (OMR) and the morphological phenotypes observed here, in particular since they are not connected here to the classes of direction-selective RGCs one would expect might affect OMR responses.

4. Much clearer co-localization between YTHDF2 and RGC markers is needed, both in vivo and in vitro, to clearly demonstrate association with RGCs and not displaced amacrine cells or other retinal cell types.

5. The several mRNAs and their produces shown to be under YTHDF2 control do appear to play some role in regulating general RGC dendritic morphology, though of course from these data we do not know whether or not there is any RGC-subtype specificity. However, as presented, we really do not learn much at all about their mechanisms of action. At the very least, do they act in the same, or different, pathways….i.e. have any attempts been made to knock down more than one at a time and ask about independent pathway affiliations?

6. It is not clear how to interpret the Ythdf2 effects in the acute ocular hypertension (AOH) model. Is this related to the downstream mRNAs, or some other more general effect of loss of this m6 reader? And how is this related to RGC survival at a mechanistic level?

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "The m⁶A reader YTHDF2 is a negative regulator for dendrite development and maintenance of retinal ganglion cells" for further consideration by eLife. Your revised article has been evaluated by Catherine Dulac (Senior Editor) and Carol Mason as Reviewing Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below and in the appended reviews:

Reviewer 2 (previous Reviewer 1) was satisfied with the revisions of this resubmission as was Reviewer 3 (previous Reviewer (3) although the latter reviewer adds that "…we still are far from a mechanistic understanding of how these gene products regulate RGC dendritic arborization, and whether or not there is any specificity of these effects with regard to RGC subtypes."

Reviewer 1 (previous Reviewer 2) continues to have concerns: He summarized in the Public Review (this will not be made public as it is a resubmission) that "the phenotype of the Ythdf2 cKO mouse model is not well characterized and there lacks in vivo evidence for the putative targets of YTHDF2".

Two items he previously requested were not addressed: (1) to perform either qPCR or western blots of Ythdf2 cKO retina to confirm the regulation of Kalirin, Strn and Ubr4 by Ythdf2, and (2) to show that overexpression of Hspa12a and Islr2 alleviates loss of RGCs in the AOH model (See point #8 of previous Reviewer 2’s review). We ask that you address these two items that were raised in the first review, to the best of your ability, given time constraints. (Thus, these are not experiments newly requested by the reviewer(s)).

Current Reviewer 1 has also raised additional points not in the first review, that could be answered mostly textually:

1. Your stated exclusivity of YTHDF2 expression in RGCs, given that there is apparent staining in all cell layers in Suppl Figure 1B. He cited very "old"scRNAseq data indicating that YTHDF2 is found in all retinal cell types.

2. To verify that YTHDF2 is neuronal: determining YTHDF2 expression in Muller glia and astrocytes.

3. Addressing the utility of the Six3-Cre, by determining whether there is mosaic expression of Cre in the peripheral retina.

Reviewer #1:

The experimental designs were presented clearly and the results were interpreted with the appropriate statistical tests. However, the phenotype of the Ythdf2 cKO mouse model is not well characterized and there lacks in vivo evidence for the putative targets of YTHDF2. It is also difficult to explain the connection, if any, between the dendritic role of YTHDF2 and its neuroprotective function. Most importantly, whether Ythdf2 acts cell autonomously in the RGCs remains to be resolved.

1. The premise of this study is that Ythdf2 is cell autonomously required in RGCs for dendritic development. In the rebuttal letter, the authors even went as far as claiming that "all RGCs express YTHDF2 and all YTHDF2-expressing cells in retina are RGCs". However, this statement is belied by the strong YTHDF2 staining outside the RGC layers in Figure 1—figure supplement 1B. The YTHDF2 expression in non-RGC cells can also be seen in Figure 1A, although for unknown reason the staining intensity was weaker. In fact, numerous RNAseq studies have now thoroughly catalogued gene expression patterns in the retina throughout development and YTHDF2 expression can be found among all retinal cell types even from the earliest scRNAseq data (Macosko et al., 2015, Cell 161, 1202). The ubiquitous expression of YTHDF2 in the retina poses serious concerns regarding the usefulness of Six3-Cre mediated Ythdf2 cKO model and the validity of presumed Ythdf2 downstream targets in RGCs.

2. The revised manuscript presents data to show that retinal progenitors, amacrine cells, bipolar cells, photoreceptors, or horizontal cells were not affected in Ythdf2 cKO retina. It is also important for the authors to examine Müller glia and astrocyte, especially the latter which is known to have a strong influence on RGC activity and health.

3. The potential targets of YTHDF2 were mostly characterized in the RGC culture, which is not a good model for studying dendritic development because RGCs will evitable die in vitro. As previously requested by this reviewer, the authors need to perform either qPCR or western blos of Ythdf2 cKO retina to confirm the regulation of Kalirin, Strn and Ubr4 by Ythdf2. They also need to show whether siRNA knockdown or CRISPR knockout of these genes rescue the Ythdf2 cKO phenotype in vivo.

4. The authors propose that the better maintenance of RGC dendrite arborization in Ythdf2 cKO retina make it resistant to RGC death in AOH model and this is mediated by Hspa12a and Islr2 genes. To support this claim, the authors need to show that overexpression of Hspa12a and Islr2 alleviates loss of RGCs in the AOH model.

Reviewer #2:

The authors have responded to my comments and suggestions with several new experiments and some additional explanations. Though the effects of YTHDF2 described here are pleiotropic across RGC cell types, these defects in dendritic arborization are better described in this revised manuscript. In addition, further attention to the mRNAs regulated by YTHDF2 is given, and though we still are far from a mechanistic understanding of how these gene products regulate RGC dendritic arborization, and whether or not there is any specificity of these effects with regard to RGC subtypes, I find this revision to be a substantial improvement over the initial submission.

Reviewer #3:

The authors have addressed my comments.

https://doi.org/10.7554/eLife.75827.sa1

Author response

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Reviewer #1:

The authors report a functional-relevant role of YTHDF2 in mouse retina ganglion cells (RGCs) to negatively regulate dendrite development and maintenance of RGCs. Mechanistically, Kalrn, Strn, and Ubr4 mRNAs are selectively recognized and decay through the YTHDF2-mediated pathway, the subsequent downregulation of proteins encoded by those mRNAs negatively regulate dendrite development and maintenance of RGCs.

This work highlights regulatory roles of N6-methyladenosine (m6A) and YTHDF2 protein in retina and suggested YTHDF2 as one possible target in AOH-induced RGC loss. A few concerns will need to be addressed.

Concerns:

1. The authors showed YTHDF2 mRNA is upregulated by AOH and argued a loss of YTHDF2 in retina results in less severe AOH-induced loss of Brn3a+ RGCs. The mechanism of YTHDF2 upregulation induced by AOH and loss of Brn3a+ RGCs mediated by YTHDF2 upregulation are unclear. The first question might be harder to address but the second one is within the scope of this work.

We agree with the reviewer that the mechanism of YTHDF2 upregulation induced by AOH is beyond the scope of this work, which may require further investigation as a future direction.

As for the mechanism of loss of Brn3a⁺ RGCs mediated by YTHDF2 upregulation in AOH-treated retina, we tried to answer this question by expanding the scope of our study in the revised manuscript. We wanted to know whether YTHDF2 target mRNAs mediate these effects in the AOH models. AOH has been shown to cause pathological changes in RGC dendrites before axon degeneration or soma loss is detected in different model animals (Morgan et al., 2006; Shou et al., 2003; Weber et al., 1998), suggesting that RGC soma loss might be following dendrite degeneration. So we tested whether YTHDF2 upregulation mediates RGC dendrite degeneration in AOH-treated retina. We found that two target mRNAs Hspa12a and Islr2 show upregulation in the adult Ythdf2 cKO retina compared with control (Figure 8—figure supplement 1C). We further found that Hspa12a and Islr2 are downregulated in the retina after AOH operation (Figure 8—figure supplement 1E), which is likely caused by upregulation of YTHDF2 in the AOH-treated retina (Figure 8—figure supplement 1F-H). We therefore hypothesized that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and soma loss.

If this is the case, overexpression of Hspa12a and Islr2 might protect RGC dendrite from AOH triggered degeneration. We thus generated AAV harboring overexpression constructs of Hspa12a and Islr2 which were intravitreally injected to wild type retinas. After the AOH induction, the retinas overexpressing Hspa12a and Islr2 maintain significantly more complex RGC dendrite arbor compared with control AAV (Figure 8E,F).

These data support a model that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and eventually resulting in soma loss

2. In figure 7B, YTHDF2 expression in Brn3a+ RGCs was quantified. The figure showed that Brn3a was not detected in some cells. In figure 7C, mRNA level was quantified with an extraction method that did not separate Brn3a+ and Brn3a- cells.

We thank the reviewer for pointing out this. Brn3a is a major RGC marker but does not stain all RGCs. We also used the pan-RGC marker RBPMS. As shown ion Figure 1A, all RGCS marked by the pan-RGC marker RBPMS express YTHDF2 while all YTHDF2-expressing cells are RBPMS⁺ RGCs. These data suggest that all RGCs express YTHDF2 and all YTHDF2-expressing cells in retina are RGCs.

3. The authors showed AOH-induced loss of Brn3a+ RGCs in mouse models. Supportive evidence at the phenotype level such as less severe loss of visual acuity in YTHDF2 cKO mice are required.

We thank the reviewer for the suggestion. We have tried to do the OMR assay using the AOH model mice. Unfortunately, the AOH model mice are not eligible for the OMR assay to test their visual acuity. However, we did find that the Ythdf2 cKO retina with AOH operation maintains significantly higher dendrite complexity compared with the glaucomatous eyes of Ythdf2^fl/fl control mice (Figure 8A,B). In addition, the reduction of RGC number in the Ythdf2 cKO retina with AOH operation is less than control retina with AOH operation (Figure 8C,D). These results support that Ythdf2 cKO protects retina from RGC dendrite degeneration and soma loss caused by AOH.

4. The authors showed knockdown of Kalrn, Strn, and Ubr4 are sufficient to impair dendrite growth. Rescue experiments will further back up their claim.

We thank the reviewer for the suggestion. We have now further performed rescue experiments to examine whether these target mRNAs mediate YTHDF2-regulated RGC dendrite branching. As shown in Figure 2E-H and Figure 3, cKO of Ythdf2 led to increased dendrite branching of RGCs both in vitro and in vivo. Transfection of siRNAs against these target mRNAs rescued dendrite branching increases in cultured Ythdf2 cKO RGCs (Figure 7C). We continued to generate and performed intravitreal injection of AAV viral shKalrn12 and shUbr4, which significantly rescued dendrite branching increases of CART⁺ ooDSGCs and SMI-32⁺ αRGCs in Ythdf2 cKO retina in vivo (Figure 7D). These data suggest that these target mRNAs mediate YTHDF2-controlled RGC dendrite branching.

5. The authors suggested that m6A-YTHDF2 axis regulates the stability of Kalrn, Strn, and Ubr4 mRNAs. The authors will need to show these RNAs contain m6A by m6A-IP-qPCR. The effect on Kalrn, Strn, and Ubr4 mRNAs upon m6A writer complex knockdown can also be shown.

We thank the reviewer for the suggestion. We now verified the m⁶A modification of these mRNAs by m6A-IP-qPCR (Figure 6D). We also examined whether m⁶A modification regulates the expression levels of these target mRNAs. As shown in Figure 7—figure supplement 1D, the mRNA levels of Kalrn7, Kalrn9, Kalrn12, Strn and Ubr4 were dramatically increased after KD of METTL14, supporting that the stability of these target mRNAs is controlled in an m⁶A-dependent manner.

Reviewer #2:

This manuscript investigates the role of the m6A reader YTHDF2 during retinal ganglion cell (RGC) dendrite development and branching. The data presented in this study shows that deletion of YTHDF2 in the retina led to increased RGC dendrite branching and improved visual acuity. Based on high throughput analysis, YTHDF2 is suggested to regulate dendrite branching by reducing the stability of kalirin, Strn and Ubr4 mRNAs. Lastly, loss of YTHDF2 is shown to prevent RGC loss in a glaucoma model. The experimental designs were presented clearly, and the results were interpreted with the appropriate statistical tests. However, the phenotype of the Ythdf2 cKO mouse model is not well characterized and there lacks in vivo evidence for the putative targets of YTHDF2. It is also difficult to explain the connection, if any, between the dendritic role of YTHDF2 and its neuroprotective function.

1. The authors used RGC cultures to show that knockdown/knockout of YTHDF2 resulted in increased the dendrite branching based on the number of interactions in Sholl analysis. However, to determine the full extent of dendritic defect, it is important to perform detailed analysis of the dendrite structure, including the total dendritic length, number of total segments, maximum branch length, branch order and number of branches.

We thank the reviewer for the suggestions. We have now performed more detailed analysis of the dendrite structure of cultured RGCs after KD of YTHDF2. As shown in Figure 1—figure supplement 1G,H, the total dendrite length showed significant increase after YTHDF2 while the length of maximum branch was not changed.

We further focused on the physiological dendrite structures by checking the RGC dendrites in the Ythdf2 cKO retina in vivo. As shown in Figure 3—figure supplement 1A-E, the total dendrite length, number of branches, number of total segments, and number of segments in each branch order of melanopsin⁺ RGCs in the Ythdf2 cKO retina showed significant increases compared with control retina, while the length of maximum branch was not changed.

2. It is suggested in the manuscript that loss of YTHDF2 in the retina only affects dendrite development of RGCs, but not other cell types. This is based on the simple counting of the number of RPCs at E15 and bipolar and amacrine cells at P15, glossing over the vast complexity of the visual circuitry in the retina. At the very least, the authors should confirm that differentiation of all major retinal neurons and proper formation of the ribbon synapses were unaffected in the cKO mouse model of YTHDF2, which would other confound the interpretation of the RGC and visual acuity phenotype.

Retinal progenitors, amacrine cells, bipolar cells, photoreceptors, or horizontal cells were not affected in Ythdf2 cKO retina (Figure 2—figure supplement 1B-L), suggesting that YTHDF2 is not involved in the generation or development of these cells. This is in line with the low YTHDF2 expression in these cells. The RGC number or density was not affected in the Ythdf2 cKO retina (Figure 2C,D), indicating that Ythdf2 cKO does not disturb RGC neurogenesis. These data suggest that differentiation of all major retinal neurons was unaffected in the Ythdf2 cKO mouse model.

In addition, the numbers of the excitatory ribbon synapses marked by the colocalization of Bassoon⁺/PSD-95⁺ in OPL show no difference between Ythdf2 cKO and control retinas (Figure 4— figure supplement 1E,F).

3. The in vivo characterisation of RGC dendrite morphology should be more thorough as previously mentioned, including the arbor shape, size and tiling pattern. The image quality of Melanopsin and SMI-32 staining is low. There are too many cells labelled, making it difficult to examine individual cells/dendrites. Higher resolution images from more sparsely labelled retina would be needed.

We thank the reviewer for the suggestion. We now have repeated and chosen better representative images for melanopsin and SMI-32 staining of RGC dendrites in vivo in the revised manuscript (Figure 3C,E). As mentioned earlier, we performed more detailed analysis of the RGC dendrite structures in vivo. As shown in Figure 3—figure supplement 1A-E, the total dendrite length, number of branches, number of total segments, and number of segments in each branch order of melanopsin⁺ RGCs in the Ythdf2 cKO retina showed significant increases compared with control retina, while the length of maximum branch was not changed.

4. The authors provide evidence of increased synaptic density in the IPL using PSD-95 staining in the cKO mice compared to the control litter mates. It is important to investigate if there are any changes to the synaptic density in the OPL. In addition, it is also important to study the number of successful synapse formation by co-staining the tissues with presynaptic markers such as bassoon with PSD-95 and count for co-localisation.

We thank the reviewer for the suggestion. We now used co-staining of the presynaptic marker Bassoon and the postsynaptic marker PSD-95 to count the colocalization puncta of Bassoon⁺/PSD95⁺. We found that the numbers of Bassoon⁺/PSD-95⁺ excitatory synapses in IPL of Ythdf2 cKO retina are significantly larger than that of control retina (Figure 4D,E). As a control, the numbers of the excitatory ribbon synapses marked by the colocalization of Bassoon⁺/PSD-95⁺ in OPL show no difference between Ythdf2 cKO and control retinas (Figure 4—figure supplement 1E,F).

5. The improved visual acuity in Six3Cre-mediated Ythdf2 cKO is solely attributed to the RGC dendrite defects. However, Six3Cre is widely expressed in the ventral telencephalon and ventral anterior hypothalamus, including the SCN and SPZ (PMID: 24767996). It is necessary to examine the retinocollicular projections of the RGC axons.

We thank the reviewer for the suggestion. We checked the targeting of optic nerves to the brain by anterograde labeling with cholera toxin subunit B (CTB) and found no difference of retinogeniculate or retinocollicular projections between Ythdf2 cKO and control mice (Figure 5—figure supplement 1F,G), suggesting the guidance and central targeting of RGC axons are not affected in the Ythdf2 cKO.

6. The Optomotor response (OMR)-based assay is not the most appropriate test to test the response of ganglion cells since the improved OMR could be attributed to other cell types as previously mentioned. A more targeted approach such as pattern ERG could provide more evidence to their claims.

We tried to find a way to do pattern ERG, but unfortunately we do not have this and could not find reachable resources to do this, either. However, based on the analysis we have done so far, we believe that the improved OMR is most likely attributed to the increased RGC dendrite branching and thicker and denser IPL with more synapses because all other parts and processes of retina are not affected except RGC dendrite in the Ythdf2 cKO mediated by Six3-cre:

(1) As mentioned earlier, the neurogenesis of all major neuron types in retina is not affected by Ythdf2 cKO in retina (Figure 2C,D; Figure 2—figure supplement 1B-L).

(2) The increases of RGC dendrite branching in the Ythdf2 cKO retina were validated both in vitro and in vivo (Figure 2E-H; Figure 3).

(3)IPL thickness significantly increased in the Ythdf2 cKO retina (Figure 4A,B). As a control, the thicknesses of other retinal layers (ONL, OPL, INL, GCL) showed no difference between the Ythdf2 cKO and control mice (Figure 4—figure supplement 1A-D).

The numbers of Bassoon⁺/PSD-95⁺ excitatory synapses in IPL of Ythdf2 cKO retina are significantly larger than that of control retina (Figure 4D,E). As a control, the numbers of the excitatory ribbon synapses marked by the colocalization of Bassoon⁺/PSD-95⁺ in OPL show no difference between Ythdf2 cKO and control retinas (Figure 4—figure supplement 1E,F).

7. The quality of the RIP-seq analysis is not clear. Is there an isotype antibody control? Are there biological replicates? What is the statistical significance of the top hits? There are similar concerns regarding the MS analysis and whether there is significant overlap between the target lists generated from RIP-Seq and MS studies.

We are sorry that the related information was not clear or missing. For the RIP experiment: Yes, we used a control IgG and performed two biological replicates. To determine which gene is enriched, we computed the FPKM from RIP elute to input and any fold change greater than 2 (p value less than 0.05) was considered enriched. For MS analysis, we performed three biological replicates, and proteins with fold changes greater than 1.3 and p values less than 0.05 were considered to be regulated by YTHDF2 KD with statistical significance. By overlapping the two gene lists screened from anti-YTHDF2 RIP-Seq (Supplementary file 1) and YTHDF2 KD/MS_upregulation (Supplementary file 2), we identified a group of potential YTHDF2 target mRNAs in RGCs (Supplementary file 3).

As a summary, we now have added these information to the Materials and methods, and a new Supplementary file 3 in the revised manuscript.

8. The authors provide evidence in the RGC culture that stabilisation of kalirin, Strn and Ubr4 mRNAs could contribute to the increase in dendrite branching in Ythdf2 knockout. The regulation of these genes by Ythdf2 need to be validated in Ythdf2 cKO retina at the level of mRNA by qRT-PCR and at the level of protein by western blot. Functionally, the authors need to investigate if knockdown or knockout of these genes in retina indeed affect dendrite branching or even rescue Ythdf2 cKO phenotype.

As shown in Figure 7—figure supplement 1B, the mRNA levels of Kalrn7, Kalrn9, Kalrn12, Strn and Ubr4 were dramatically increased after KD of YTHDF2 by qRT-PCR. We further verified this by directly measuring the stability of these target mRNAs. As shown in Figure 7A, all the target mRNAs showed significantly increased stability in the Ythdf2 cKO retina compared with controls. These results suggest that YTHDF2 controls the levels of its m⁶A-modifed target mRNAs by decreasing their stability.

MS analysis after YTHDF2 KD has shown that the protein levels of these target mRNAs were upregulated (Supplementary file 2). For validation, we performed IF using antibodies against Strn and Ubr4 (unfortunately we could not find any convincing Abs against Kalrns after many attempts) and detected specific signals in the IPL which were increased in Ythdf2 cKO retina compared with control retina (Figure 7—figure supplement 1A), suggesting that Strn and Ubr4 are upregulated in Ythdf2 cKO retina at the level of protein.

We continued to explore the functions of these YTHDF2 target mRNAs in RGC dendrite development. We first generated siRNAs against these transcripts (Figure 7—figure supplement 1E). We then checked the effects on RGC dendrite branching after KD of these target mRNAs by siRNAs in cultured RGCs. As shown in Figure 7B, KD of Kalrn7, Kalrn9, Kalrn12, Strn or Ubr4 led to significant decreases of RGC dendrite branching. We further examined whether these target mRNAs mediate YTHDF2regulated RGC dendrite branching. As shown in Figure 2E-H, and Figure 3, cKO of Ythdf2 led to increased dendrite branching of RGCs both in vitro and in vivo. Transfection of siRNAs against these target mRNAs rescued dendrite branching increases in cultured Ythdf2 cKO RGCs (Figure 7C). We continued to perform intravitreal injection of AAV viral shKalrn12 and shUbr4, which significantly rescued dendrite branching increases of CART⁺ ooDSGCs and SMI-32⁺ αRGCs in Ythdf2 cKO retina in vivo (Figure 7D). These data support that knockdown of these genes indeed reduces the RGC dendrite branching, and can rescue the Ythdf2 cKO phenotype both in vitro and in vivo.

9. Finally, there is not clear connection between the dendrite development phenotype and the neuroprotective role of YTHDF2. The authors need to clarify the rationale behind these experiments.

We thank the reviewer for pointing out this. To answer this question, we now have expanded the scope of our study in the revised manuscript.

The pathological changes in RGC dendrites precede axon degeneration or soma loss in the glaucomatous eyes of different model animals (Morgan et al., 2006; Shou et al., 2003; Weber et al., 1998). Our findings that Ythdf2 cKO in retina promotes RGC dendrite branching during development inspired us to wonder whether YTHDF2 also regulates RGC dendrite maintenance in the acute glaucoma model caused by acute ocular hypertension (AOH).

We found that two target mRNAs Hspa12a and Islr2 show upregulation in the adult Ythdf2 cKO retina compared with control (Figure 8—figure supplement 1C). We further found that Hspa12a and Islr2 are downregulated in the retina after AOH operation (Figure 8—figure supplement 1E), which is likely caused by upregulation of YTHDF2 in the AOH-treated retina (Figure 8—figure supplement 1F-H). We therefore hypothesized that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and soma loss. If this is the case, overexpression of Hspa12a and Islr2 might protect RGC dendrite from AOH-triggered degeneration. We thus generated AAV harboring overexpression constructs of Hspa12a and Islr2 which were intravitreally injected to wild type retinas. After the AOH induction, the retinas overexpressing Hspa12a and Islr2 maintain significantly more complex RGC dendrite arbor compared with control AAV (Figure 8E,F). These data support a model that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and eventually resulting in soma loss.

The mechanistic link between the dendrite development phenotype and the neuroprotective role of YTHDF2 is that YTHDF2 has two phases of function to control RGC dendrite development first and then maintenance through regulating two sets of target mRNAs. In early postnatal stages, the target mRNAs Kalrn7, Kalrn9, Kalrn12, Strn and Ubr4 mediate YTHDF2 functions to regulate RGC dendrite development. In adult mice, another set of target mRNAs Hspa12a and Islr2 mediate YTHDF2 function to regulate RGC dendrite maintenance. We now added more discussion and explanation on the connection of the two phases of YTHDF2 function in the revised manuscript.

Reviewer #3:

In this study, the authors propose a role for the m6A reader YTHDF2 in regulating the dendritic arbor size of retinal ganglion cells (RGCs), and they extrapolate this to address issues in glaucoma and overall retina IPL morphology. They find that retina-specific loss of Ythdf2 leads to the expansion of RGC dendritic arbors in the horizontal plane and also a widening of the inner plexiform layer (IPL), with Ythdf2 cKOs showing a modest increase in visual acuity in an optomotor assay. They identify a number of factors downstream of YTHDF2 not previously known to be involved in retinal dendritic development, and they propose a role for Ythdf2 in a glaucoma model, providing a foundation for future studies into their functions in these contexts.

Although these data are sufficient to establish a role for Ythdf2 in RGC dendritic development and other more general aspects of retina morphology, many of the authors' specific claims are weakened by issues with the experiments, their analyses, and by weak effect sizes. Even if the points raised below were addressed, it remains unclear from this study how Ythdf2-mediated mechanisms are integrated into programs of dendritic development and RGC survival, diminishing the impact of this work. This study would be strengthened by, for example, identifying a developmental program that modifies the target mRNAs found in this study to promote recognition by YTHDF2, and also by providing better understanding of how the products produced by these mRNAs actually regulate dendrite morphology and synapse formation. Overall, while there are a number of promising findings in this study, the work required to address weaknesses falls well outside of the limits usually recommended by eLife, and it is suited for publication in a more specialized journal following attention to many of the points raised below.

1. The cell-type specific tracing in Figure 3 is difficult to assess due to the extremely high background in the melanopsin images and unclear signal in the SMI-32 images. This analysis would be improved by sparse viral labeling, with a fluorophore provided by the virus used for tracing and the melanopsin & SMI-32 antibodies used solely for establishing RGC subtype identity. Further, the authors emphasize that the defects they observe here are in the plane of retinal ganglion cell (RGC) dendritic arbors, but this is an over-interpretation of these data. One wonders why the authors did not examine in cross section the lamination within the IPL of the melanopsin-positive ipRGCs, since this would provide, at least for this RGC subclass, a direct assessment of this issue. Finally, the Thy-1-O line GFP distribution is quite general, and it really is not the correct line to use if one wants to investigate defects in lamination.

We thank the reviewer for pointing out this. To answer this question, we now have expanded the scope of our study in the revised manuscript.

2. The authors repeatedly describe increased dendritic and synaptic density within the IPL in Ythdf2 cKOs, yet they only present absolute signal intensities to support these claims; without normalizing signal intensity to IPL width, it is impossible to determine whether changes in intensity are indeed due to increased density or from the IPL becoming enlarged with a similar density of dendrites and synapses. Further, they claim in the text that VGlut2 puncta numbers are changed in these mutants, however the analysis presented is only for general signal intensity. If claims are to be made regarding changes in synaptic specializations, higher resolution assessments of individual puncta using pre- and postsynaptic markers is required.

We are sorry that the information about increased dendritic and synaptic density within the IPL in Ythdf2 cKO was not clear. The MAP2 IF intensity shown in Figure 4C was already normalized to the IPL area. Considering the increased IPL thickness, the absolute signal intensities (MAP2 IF intensity per area × IPL area) would be even larger in the Ythdf2 cKO compared with the control. We have now made this (MAP2 IF intensity per area in IPL) clearer in the revised manuscript.

We thank the reviewer for the suggestion on quantifying synaptic puncta. We now used co-staining of the presynaptic marker Bassoon and the postsynaptic marker PSD-95 to count the colocalization puncta of Bassoon⁺/PSD-95⁺. We found that the numbers of Bassoon⁺/PSD-95⁺ excitatory synapses in IPL of Ythdf2 cKO retina are significantly larger than that of control retina (Figure 4D,E).

3. While Ythdf2 cKOs do show a statistically significant improvement in visual acuity (although for these male data it is unclear whether the control data distribution is sufficiently normal to use a t-test), the effect size is small enough to call into question how meaningful the improvement is. Further, what is the actual relationship between this modest improvement in optomotor response (OMR) and the morphological phenotypes observed here, in particular since they are not connected here to the classes of direction-selective RGCs one would expect might affect OMR responses.

The difference of 0.02 cycle/degree between young Ythdf2 cKO and control is small yet significant in both male and female mice in our study, and this difference is comparable with other studies in the field (Dietrich et al., 2019; Kang et al., 2013; Thangthaeng et al., 2017). Considering the fact that young wild-type (control) mice already have good visual acuity, this 0.02 cycle/degree increase is quite significant.

We thank the reviewer for suggesting checking direction-selective RGCs to enhance the relationship between the improvement in optomotor response (OMR) and the morphological phenotypes. The ON-OFF directionally selective RGCs (ooDSGCs) respond preferentially to movement in particular directions. Expression of CART (cocaine- and amphetamine-regulated transcript), a neuropeptide, distinguishes ooDSGCs from other RGCs (Kay et al., 2011). We now found that the dendrite branching of ooDSGCs marked by CART/Brn3a co-staining in Ythdf2 cKO retinal cultures increased compared with control in vitro (Figure 2G,H). Intravitreal injection of an AAV reporter expressing ZsGreen visualized the dendrite morphology of ooDSGCs marked by CART immunostaining in vivo (Figure 3A). We found that ooDSGCs showed dramatically increased dendrite branching in Ythdf2 cKO retina compared with control retina (Figure 3A,B). Thus, Ythdf2 cKO increased the dendrite branching of ooDSGCs both in vitro and in vivo, along with other data in this study supporting the improved optomotor response in the Ythdf2 cKO mice.

4. Much clearer co-localization between YTHDF2 and RGC markers is needed, both in vivo and in vitro, to clearly demonstrate association with RGCs and not displaced amacrine cells or other retinal cell types.

We now used the pan-RGC marker RBPMS. As shown ion Figure 1A, all RGCS marked by the pan-RGC marker RBPMS express high YTHDF2 while all YTHDF2-expressing cells are RBPMS⁺ RGCs. These data demonstrate the co-localization between YTHDF2 and the pan-RGC marker.

5. The several mRNAs and their produces shown to be under YTHDF2 control do appear to play some role in regulating general RGC dendritic morphology, though of course from these data we do not know whether or not there is any RGC-subtype specificity. However, as presented, we really do not learn much at all about their mechanisms of action. At the very least, do they act in the same, or different, pathways….i.e. have any attempts been made to knock down more than one at a time and ask about independent pathway affiliations?

We thank the reviewer for the suggestion. We now have prepared a cocktail of siRNAs against these target mRNAs and performed the KD assay to check the effect on RGC dendrite morphology. As shown in Figure 7—figure supplement 1F, the siCocktail further significantly reduced the RGC dendrite branching compared with each individual siRNA. These results suggest that these targets may work in different pathways to regulate the RGC dendrite morphology. We agree that the exploration of their working mechanisms is an important future direction.

6. It is not clear how to interpret the Ythdf2 effects in the acute ocular hypertension (AOH) model. Is this related to the downstream mRNAs, or some other more general effect of loss of this m6 reader? And how is this related to RGC survival at a mechanistic level?

We are sorry that this was not clear in the original manuscript. To answer this question, we now have expanded the scope of our study in the revised manuscript. We found that two YTHDF2 target mRNAs Hspa12a and Islr2 show upregulation in the adult Ythdf2 cKO retina compared with control (Figure 8—figure supplement 1C). We further found that Hspa12a and Islr2 are downregulated in the wildtype retina after AOH operation (Figure 8—figure supplement 1E), which is likely caused by upregulation of YTHDF2 in the AOH-treated retina (Figure 8—figure supplement 1F-H). We therefore hypothesized that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration. If this is the case, overexpression of Hspa12a and Islr2 might protect RGC dendrite from AOH-triggered degeneration. We thus generated AAV harboring overexpression constructs of Hspa12a and Islr2 which were intravitreally injected to wild type retinas. After the AOH induction, the retinas overexpressing Hspa12a and Islr2 maintain significantly more complex RGC dendrite arbor compared with control AAV (Figure 8E,F).

AOH has been shown to cause pathological changes in RGC dendrites before axon degeneration or soma loss is detected in different model animals (Morgan et al., 2006; Shou et al., 2003; Weber et al., 1998), suggesting that RGC soma loss might be following dendrite degeneration. Thus, these findings support a model that AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and eventually resulting in soma loss.

Summary

As a summary, we have now substantially expanded and improved our study to address all the concerns raised by the reviewers and summarized by the editor:

1. We have now done a better phenotyping of the Ythdf2 cKO mouse model by more precisely measuring the layer dimensions (Figure 4—figure supplement 1A-D), the synapse number (Figure 4D,E), the dendritic extension (Figure 1—figure supplement 1G,H; Figure 3—figure supplement 1A-E); checking cells other than RGCs in retina (Figure 2—figure supplement 1B-L); confirming colocalization of YTHDF2 and RGC markers (Figure 1A). We also explained the connection between the dendrite development phenotype and the neuroprotective role of YTHDF2 (please see our response to Reviewer #2’s major comment 9 for details).

2. We have now provided in vivo evidence to show that the YTHDF2 target mRNAs Kalirin, Strn and Ubr4 indeed contribute to the increase in dendrite branching in the Ythdf2 knockout. We generated and performed intravitreal injection of AAV viral shKalrn12 and shUbr4, which significantly rescued dendrite branching increases of CART⁺ ooDSGCs and SMI-32⁺ αRGCs in Ythdf2 cKO retina in vivo (Figure 7D). These data suggest that these target mRNAs mediate YTHDF2-controlled RGC dendrite branching. As for the mechanism of loss of Brn3a⁺ RGCs mediated by YTHDF2 upregulation in AOHtreated retina, please see our response to Reviewer #1’s comment 1 for details.

3. We have now included the analysis of the direction-selective RGCs to enhance the relationship between the improvement in optomotor response (OMR) and the morphological phenotypes (please see our response to Reviewer #3’s comment 3 for details).

4. By expanding the scope of our study, we have now more clearly interpreted the YTHDF2 effects in the acute ocular hypertension (AOH) model, which are mediated by the two YTHDF2 target mRNAs Hspa12a and Islr2 (please see our response to Reviewer #3’s comment 6 for details).

5. We used a model to explain the relationship among glaucoma, YTHDF2, and RGC survival: AOH upregulates YTHDF2 which in turn downregulates its targets Hspa12a and Islr2, thus causing RGC dendrite degeneration and eventually resulting in soma loss.

We think that the revised manuscript is substantially improved with these revisions and new data.

We would like to thank the reviewers for their comments and suggestions.

References

Dietrich, M., Hecker, C., Hilla, A., Cruz-Herranz, A., Hartung, H.P., Fischer, D., Green, A., and Albrecht, P. (2019). Using Optical Coherence Tomography and Optokinetic Response As Structural and Functional Visual System Readouts in Mice and Rats. J Vis Exp.

Feng, G., Mellor, R.H., Bernstein, M., Keller-Peck, C., Nguyen, Q.T., Wallace, M., Nerbonne, J.M., Lichtman, J.W., and Sanes, J.R. (2000). Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28, 41-51.

Kang, E., Durand, S., LeBlanc, J.J., Hensch, T.K., Chen, C., and Fagiolini, M. (2013). Visual acuity development and plasticity in the absence of sensory experience. J Neurosci 33, 17789-17796.

Kay, J.N., De la Huerta, I., Kim, I.J., Zhang, Y., Yamagata, M., Chu, M.W., Meister, M., and Sanes, J.R. (2011). Retinal ganglion cells with distinct directional preferences differ in molecular identity, structure, and central projections. J Neurosci 31, 7753-7762.

Morgan, J.E., Datta, A.V., Erichsen, J.T., Albon, J., and Boulton, M.E. (2006). Retinal ganglion cell remodelling in experimental glaucoma. Adv Exp Med Biol 572, 397-402.

Shou, T., Liu, J., Wang, W., Zhou, Y., and Zhao, K. (2003). Differential dendritic shrinkage of α and β retinal ganglion cells in cats with chronic glaucoma. Invest Ophthalmol Vis Sci 44, 3005-3010.

Thangthaeng, N., Rutledge, M., Wong, J.M., Vann, P.H., Forster, M.J., and Sumien, N. (2017). Metformin Impairs Spatial Memory and Visual Acuity in Old Male Mice. Aging Dis 8, 17-30.

Weber, A.J., Kaufman, P.L., and Hubbard, W.C. (1998). Morphology of single ganglion cells in the glaucomatous primate retina. Invest Ophthalmol Vis Sci 39, 2304-2320.

[Editors’ note: what follows is the authors’ response to the second round of review.]

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below and in the appended reviews:

Reviewer 2 (previous Reviewer 1) was satisfied with the revisions of this resubmission as was Reviewer 3 (previous Reviewer 2 although the latter reviewer adds that "…we still are far from a mechanistic understanding of how these gene products regulate RGC dendritic arborization, and whether or not there is any specificity of these effects with regard to RGC subtypes."

Reviewer 1 (previous Reviewer 2) continues to have concerns: He summarized in the Public Review (this will not be made public as it is a resubmission) that "the phenotype of the Ythdf2 cKO mouse model is not well characterized and there lacks in vivo evidence for the putative targets of YTHDF2".

We thank the reviewer for pointing out these important future directions. We have now added related discussions in the revised manuscript.

Two items he previously requested were not addressed:

(1) To perform either qPCR or western blots of Ythdf2 cKO retina to confirm the regulation of Kalirin, Strn and Ubr4 by Ythdf2.

We have now carried out qPCR for Kalirin, Strn, Ubr4 using the Ythdf2 cKO and control retina, confirming that Kalirin, Strn, and Ubr4 mRNA levels were upregulated in the Ythdf2 cKO retina compared with control (Figure 7—figure supplement 1C).

2) To show that overexpression of Hspa12a and Islr2 alleviates loss of RGCs in the AOH model (See point #8 of previous Reviewer 2’s review). We ask that you address these two items that were raised in the first review, to the best of your ability, given time constraints. (Thus, these are not experiments newly requested by the reviewer(s).

In the original manuscript, we have shown that the retinas overexpressing Hspa12a and Islr2 maintain significantly more complex RGC dendrite arbor compared with control AAV after the AOH induction (Figure 8E,F). We now have repeated this experiment to further check loss of RGCs. As shown in the revised Figure 8G, retinas overexpressing Hspa12a and Islr2 maintain significantly more Brn3a⁺ RGCs than control AAV after the AOH induction, suggesting that overexpression of Hspa12a and Islr2 alleviates loss of RGCs in the AOH model.

Current Reviewer 1 has also raised additional points not in the first review, that could be answered mostly textually:

1. Your stated exclusivity of YTHDF2 expression in RGCs, given that there is apparent staining in all cell layers in Suppl Figure 1B. He cited very "old"scRNAseq data indicating that YTHDF2 is found in all retinal cell types.

YTHDF2 is highly expressed in RGCs (Figure 1A; Figure 1—figure supplement 1B). Conversely, the expression of YTHDF2 in other layers of the retina is much lower (Figure 1A; Figure 1—figure supplement 1B). Though the expression of YTHDF2 could be detected by scRNAseq in other retinal cell types in a previous report as the reviewer mentioned, their YTHDF2 expression levels are much lower than RGCs. More importantly, consistent with the minimal or no expression of YTHDF2 in other retinal layers/cells, all other retinal layers/cells except IPL are not affected in the Ythdf2 cKO retina (Figure 2—figure supplement 1; Figure 2—figure supplement 2).

2. To verify that YTHDF2 is neuronal: determining YTHDF2 expression in Muller glia and astrocytes.

GFAP is reliable marker for astrocytes in the mammalian retina (Vecino et al., 2016). As shown in Figure 1—figure supplement 1C,D, YTHDF2 expression could not be detected in these cells at P20, suggesting that YTHDF2 expression in retina is neuronal (RGCs).

3. Addressing the utility of the Six3-Cre, by determining whether there is mosaic expression of Cre in the peripheral retina.

As reported previously, there is minimal mosaic absence of expression of Six3-Cre in the peripheral retina as shown in Figure 5—figure supplement 1A. The fact that the layer of Brn3a⁺ RGCs become thinner and thinner toward the edge of peripheral retina (Quina et al., 2005) makes the trace residual expression of YTHDF2 in the peripheral retina of Ythdf2 cKO mice negligible (Author response image 1). Indeed, YTHDF2 depletion in the Six3-Cre-mediated Ythdf2 cKO retina is robust and efficient (Figure 2B).

Author response image 1

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The trace residual expression of YTHDF2 in the peripheral retina of *Ythdf2* cKO mice.

The representative confocal images of YTHDF2 IF in E15.5 *Ythdf2* cKO retina shows the trace residual expression of YTHDF2 in the peripheral retina of *Ythdf2* cKO mice. Scale bar, 100 µm.

Reviewer #1:

The experimental designs were presented clearly and the results were interpreted with the appropriate statistical tests. However, the phenotype of the Ythdf2 cKO mouse model is not well characterized and there lacks in vivo evidence for the putative targets of YTHDF2. It is also difficult to explain the connection, if any, between the dendritic role of YTHDF2 and its neuroprotective function. Most importantly, whether Ythdf2 acts cell autonomously in the RGCs remains to be resolved.

1. The premise of this study is that Ythdf2 is cell autonomously required in RGCs for dendritic development. In the rebuttal letter, the authors even went as far as claiming that "all RGCs express YTHDF2 and all YTHDF2-expressing cells in retina are RGCs". However, this statement is belied by the strong YTHDF2 staining outside the RGC layers in Figure 1—figure supplement 1B. The YTHDF2 expression in non-RGC cells can also be seen in Figure 1A, although for unknown reason the staining intensity was weaker. In fact, numerous RNAseq studies have now thoroughly catalogued gene expression patterns in the retina throughout development and YTHDF2 expression can be found among all retinal cell types even from the earliest scRNAseq data (Macosko et al., 2015, Cell 161, 1202). The ubiquitous expression of YTHDF2 in the retina poses serious concerns regarding the usefulness of Six3-Cre mediated Ythdf2 cKO model and the validity of presumed Ythdf2 downstream targets in RGCs.

This has been addressed in the response to reviewer 1’s point 1 summarized by the editor.

2. The revised manuscript presents data to show that retinal progenitors, amacrine cells, bipolar cells, photoreceptors, or horizontal cells were not affected in Ythdf2 cKO retina. It is also important for the authors to examine Müller glia and astrocyte, especially the latter which is known to have a strong influence on RGC activity and health.

We now have checked Lhx2⁺ Müller glia and GFAP⁺ astrocytes in P20 Ythdf2 cKO retina. Neither of these two cell populations was affected in the Ythdf2 cKO retina (Figure 2—figure supplement 2), which is not surprising since these cells don’t express YTHDF2 (Figure 1—figure supplement 1C,D)

3. The potential targets of YTHDF2 were mostly characterized in the RGC culture, which is not a good model for studying dendritic development because RGCs will evitable die in vitro. As previously requested by this reviewer, the authors need to perform either qPCR or western blos of Ythdf2 cKO retina to confirm the regulation of Kalirin, Strn and Ubr4 by Ythdf2. They also need to show whether siRNA knockdown or CRISPR knockout of these genes rescue the Ythdf2 cKO phenotype in vivo.

This has been addressed in the response to the editor’s emphasized item (1). For the rescue experiments in vivo, these have been done (Figure 7D).

4. The authors propose that the better maintenance of RGC dendrite arborization in Ythdf2 cKO retina make it resistant to RGC death in AOH model and this is mediated by Hspa12a and Islr2 genes. To support this claim, the authors need to show that overexpression of Hspa12a and Islr2 alleviates loss of RGCs in the AOH model.

This has been addressed in the response to the editor’s emphasized item (2).

Reviewer #2:

The authors have responded to my comments and suggestions with several new experiments and some additional explanations. Though the effects of YTHDF2 described here are pleiotropic across RGC cell types, these defects in dendritic arborization are better described in this revised manuscript. In addition, further attention to the mRNAs regulated by YTHDF2 is given, and though we still are far from a mechanistic understanding of how these gene products regulate RGC dendritic arborization, and whether or not there is any specificity of these effects with regard to RGC subtypes, I find this revision to be a substantial improvement over the initial submission.

We thank the reviewer for pointing out these important future directions. We have now added related discussions in the revised manuscript.

References

de Melo, J., Zibetti, C., Clark, B.S., Hwang, W., Miranda-Angulo, A.L., Qian, J., and Blackshaw, S. (2016). Lhx2 Is an Essential Factor for Retinal Gliogenesis and Notch Signaling. J Neurosci 36, 2391-2405. 10.1523/jneurosci.3145-15.2016.

Quina, L.A., Pak, W., Lanier, J., Banwait, P., Gratwick, K., Liu, Y., Velasquez, T., O'Leary, D.D., Goulding, M., and Turner, E.E. (2005). Brn3a-expressing retinal ganglion cells project specifically to thalamocortical and collicular visual pathways. J Neurosci 25, 11595-11604. 10.1523/jneurosci.2837-05.2005.

Vecino, E., Rodriguez, F.D., Ruzafa, N., Pereiro, X., and Sharma, S.C. (2016). Glia-neuron interactions in the mammalian retina. Prog Retin Eye Res 51, 1-40. 10.1016/j.preteyeres.2015.06.003.

https://doi.org/10.7554/eLife.75827.sa2

Article and author information

Author details

Fugui Niu
1. School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China
2. SUSTech-HIT Joint Graduate Program, Southern University of Science and Technology, Shenzhen, China
Contribution
Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing

Competing interests
No competing interests declared
Peng Han

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization

Competing interests
No competing interests declared
Jian Zhang

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Formal analysis, Investigation, Methodology

Competing interests
No competing interests declared
Yuanchu She

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Formal analysis, Investigation, Methodology

Competing interests
No competing interests declared
Lixin Yang

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Formal analysis, Investigation, Methodology

Competing interests
No competing interests declared
Jun Yu

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Formal analysis, Investigation, Methodology

Competing interests
No competing interests declared
Mengru Zhuang

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Investigation, Methodology

Competing interests
No competing interests declared
Kezhen Tang

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Contribution
Investigation, Methodology

Competing interests
No competing interests declared
Yuwei Shi

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Investigation

Competing interests
No competing interests declared
Baisheng Yang

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Investigation

Competing interests
No competing interests declared
Chunqiao Liu

State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China

Contribution
Investigation, Resources

Competing interests
No competing interests declared
Bo Peng
1. Department of Neurosurgery, Jinshan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
2. Co-Innovation Center of Neuroregeneration, Nantong University, Nantong, China
Contribution
Conceptualization, Methodology, Resources, Software, Supervision, Writing – review and editing

For correspondence
peng@fudan.edu.cn

Competing interests
No competing interests declared

"This ORCID iD identifies the author of this article:" 0000-0003-4183-5939
Sheng-Jian Ji

School of Life Sciences, Department of Biology, Shenzhen Key Laboratory of Gene Regulation and Systems Biology, Brain Research Center, Southern University of Science and Technology, Shenzhen, China

Contribution
Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft, Writing – review and editing

For correspondence
jisj@sustech.edu.cn

Competing interests
No competing interests declared

"This ORCID iD identifies the author of this article:" 0000-0003-3380-258X

Funding

National Natural Science Foundation of China (31871038)

Sheng-Jian Ji

National Natural Science Foundation of China (31922027)

Bo Peng

Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions (2021SHIBS0002)

Sheng-Jian Ji

High-Level University Construction Fund for Department of Biology (G02226301)

Sheng-Jian Ji

Science and Technology Innovation Commission of Shenzhen Municipality (ZDSYS20200811144002008)

Sheng-Jian Ji

Program of Shanghai Subject Chief Scientist (21XD1420400)

Bo Peng

Innovative Research Team of High-Level Local University in Shanghai

Bo Peng

Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions (2019SHIBS0002)

Sheng-Jian Ji

National Natural Science Foundation of China (32170955)

Sheng-Jian Ji

National Natural Science Foundation of China (32170958)

Bo Peng

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Ke Wang and Kwok-Fai So (Jinan University) for help on the OMR assay. We thank Mengqing Xiang and Suo Qiu (Zhongshan Ophthalmic Center, Sun Yat-sen University) for help on AAV experiments. We thank other members of Ji laboratory for technical support, helpful discussions, and comments on the manuscript. This work was supported by National Natural Science Foundation of China (31871038 and 32170955 to S-JJ; 31922027 and 32170958 to BP), Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions (2021SHIBS0002, 2019SHIBS0002), High-Level University Construction Fund for Department of Biology (internal grant no. G02226301), Science and Technology Innovation Commission of Shenzhen Municipal Government (ZDSYS20200811144002008), Program of Shanghai Subject Chief Scientist (21XD1420400), and the Innovative Research Team of High-Level Local University in Shanghai (BP).

Ethics

All experiments using mice were carried out following the animal protocols approved by the Laboratory Animal Welfare and Ethics Committee of Southern University of Science and Technology (approval numbers: SUSTC-JY2017004, SUSTC-JY2019081).

Senior Editor

Catherine Dulac, Harvard University, United States

Reviewing Editor

Carol A Mason, Columbia University, United States

Version history

Received: November 24, 2021
Preprint posted: December 7, 2021 (view preprint)
Accepted: February 16, 2022
Accepted Manuscript published: February 18, 2022 (version 1)
Version of Record published: March 9, 2022 (version 2)
Version of Record updated: March 14, 2022 (version 3)
Version of Record updated: April 4, 2022 (version 4)

Copyright

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.