EMBO/soda-nel huggingface dataset:
Avidity-driven polarity establishment via multivalent lipid-GTPase module interactions (2018)
Figure 5

Figure 5. Multivalent protein-lipid interactions drive avid targeting of the Bem1-Cdc24 complex to anionic lipids.

A Scheme of Bem1 and Cdc24 proteins indicating the relative position of the mutations in the lipid tethering motifs (black x).

B Percentage of full-length Cdc24 and cdc24 ph domain mutant (cdc24 ph) associated with liposomes containing 75% PC 20% PS and 5% PI4P.

C Percentage of Cdc24 and cdc24 ph mutant associated with liposomes of the composition shown in (B) in the presence of the indicated bem1 protein. Note how additive mutations in the Bem1 lipid binding sequences reduce the percentage of Cdc24 associated with the liposomes.

D Percentage of Cdc24 and cdc24 ph associated with liposomes of the composition shown in (B) as a function of the indicated bem1 protein concentration. The curves denote the regression fit of the data to equation 2 in the materials and methods.

E Ten-fold serial dilutions and subsequent colony formation of the indicated mutant cells at the indicated temperatures.

F DIC images of the indicated bem1 and cdc24 mutants showing the increased morphological defects ensuing from loss of lipid tethering in the bem1 and cdc24 mutants.

G Western blots probed with anti-HA antibody to detect Cdc24 or cdc24 ph tagged with 3XHA in the indicated mutant strains (top panel). Detection of Ade13 was used as a loading control (bottom panel).

Data information: Values are means ± SD, Floatation assays were performed in triplicate in at least 3 independent experiments. Paired Student's t-tests were performed. ***P < 0.001, ****P < 0.0001. Scale bars = 2 µm.
Avidity-driven polarity establishment via multivalent lipid-GTPase module interactions (2018)
Figure 6

Figure 6. The Bem1 BC motifs are required for reduced Cdc42 diffusion, large nanoclusters and optimal Cdc42 activation at the cell pole.

A Scheme of the bem1 mutants used for imaging.

B Global average MSD curves of mEOS-Cdc42 in the strains indicated at the Pole (P) and Non-Pole (NP) of cells. Trajectories longer than 6 frames were analyzed. Number of trajectories analyzed: BEM1 (n = 11 cells: Non Pole: 1814 tracks; Pole: 706); bem1 bc-14E px (n = 10 cells: Non Pole: 1793 tracks; Pole: 908); bem1 bc-14E (n = 13 cells: Non Pole: 1714 tracks; Pole: 975). Error bars display s.e.m.

C D coefficients of mEOS-Cdc42 in the strains indicated (in box-plots displaying the median (line), the 25-75 percentiles (box) and the mean (cross)), which were compared using a non-parametric, two-tailed Mann-Whitney rank sum test.

D SR-Tesseler images of mEOS-Cdc42 nanocluster organization in BEM1 (5312 localizations shown in image) and bem1 bc-14E px cells (3739 localizations shown). Insets show mEOS-Cdc42 after 491 nm widelfield laser excitation to identify the cell pole. Scale bars: 2 μm. A zoom of the pole region shows the organization of the detected nanoclusters, circled in light blue, in the strains indicated. Scale bar in the zoom: 60 nm.

E Distribution of nanocluster area at the pole (P) and non-pole (NP) regions of BEM1 (diameter NP: 59 nm ± 1 nm (s.e.m); P: 74 nm ± 3.2 nm) (n = 16 cells. NP: 570 clusters; P: 162 clusters) and bem1 bc-14E px cells (diameter NP: 59 nm ± 1.5 nm (s.e.m); P: 57 nm ± 2.4 nm) (n = 15 cells. NP: 421 clusters; P: 141 clusters). Data are presented as scatter dot-plots displaying the median as a line and the 25-75 percentiles. Data were compared using non-parametric, two-tailed Mann-Whitney rank sum test.

F Active Cdc42-GTP levels were quantified in the strains indicated using a gic2(1-208)-yeGFP probe. Values are mean ± SD for n = 30 cells observed over 2 experiments. Data were compared using a Mann-Whitney test.

Data information: ns, P > 0.05, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
A Parkinson's disease CircRNAs Resource reveals a link between circSLC8A1 and oxidative stress (2020)
Figure 1

Figure 1: Brain region-specific mRNA profiles indicate multicellular PD-related processes (A) Brain region origin of tissues: SN (blue), MTG (green) and AMG (red).

(B) Non-supervised clustering heatmap plot indicates substantial clustering of transcripts from each tissue but not of transcripts from patients compared to controls. PD samples indicated in red. (C) PCA clustering of all RNA molecules in the SN control (green) and PD samples (blue).

(D) qPCR validation of TH levels in SN samples of PD and controls, normalized to beta-actin mRNA. T-test p*=0.025, Data presented as mean ± SD. n=18 for CT and 24 for PD.

(E) Top enriched GO pathways of DE genes in the SN of PD vs controls and the corresponding logP values, Wald test (DEseq2 analysis).

(F,G) Venn diagrams demonstrating cell type-specific DE genes in the SN of PD vs control tissues, up/down arrows indicate gene groups that were up/down regulated.

(H) Module-trait relationship of WGCNA analysis showing correlation and corrected P values (in brackets) for each gene module (indicated by colors) as related to the different external traits selected (disease condition, brain region, age and sex). Correlation test p-value calculated by WGCNA package.

(I) Module membership vs. gene significance in selected modules as reflecting external sample traits: disease condition (reflected in the brown and red modules), brain region (the blue module) and sex (the cyan module), regression-based p-value calculated by WGCNA analysis. n=8 for Amygdala control, 15 for Amygdala PD, 8 for MTG control and 13 for MTG PD, 10 for SN control and 15 for SN PD.

(J) Significant GO terms that emerged as associated with the blue, red and brown modules and the corresponding logP values, Fisher Exact P-Value.
A Parkinson's disease CircRNAs Resource reveals a link between circSLC8A1 and oxidative stress (2020)
Figure 3

Figure 3: CircRNA abundance is reduced in the PD SN and negatively correlates to RNA editing levels

(A) Total circRNAs detected in the SN, MTG and AMG of both PD and control donors, p*=0.02 p*=0.026 and p*=0.022 for comparison between PD and CT in SN, MTG and AMG. T-test for total SN vs MTG p*=2.27E-8 and SN vs AMG p*=5.86E-10. n=8 for Amygdala control, 15 for Amygdala PD, 8 for MTG control and 13 for MTG PD, 10 for SN control and 15 for SN PD. The box is drawn from Q1 to Q3 with a horizontal line drawn in the middle to denote the median and x marks the average. Whiskers mark minimum or maximum values. P value was calculated by T-test.

(B) Global editing levels in the 3 brain regions is based on the Alu editing index, representing the weighted average editing level across all expressed Alu sequences, Wilcoxon, corrected p*=0.038, 0.055 and 0.42 for Amygdala, MTG and SN. Wilcoxon test between the Alu editing index of control and PD samples.

(C) Global RNA editing levels based on the Alu editing index, studied only in Alu elements within circRNA exons and their flanking introns, in the 3 brain regions, for circRNAs corrected p*= 0.025 and 0.040 for the AMG and MTG and p=0.3 for SN. For flanking introns p*= 0.02 and 0.040 for AMG and MTG and p=0.34 for SN, Wilcoxon test. n=8 for Amygdala control, 15 for Amygdala PD, 8 for MTG control and 13 for MTG PD, 10 for SN control and 15 for SN PD. The box is drawn from Q1 to Q3 with a horizontal line drawn in the middle to denote the median and x marks the average. Whiskers mark minimum or maximum values.

(D) Negative correlation between total RNA editing and circRNA abundance, correlation = -0.37, Correlation test p value = 0.0015. (E) Adar1 expression levels in all tissues. The box is drawn from Q1 to Q3 with a horizontal line drawn in the middle to denote the median and x marks the average. Whiskers mark minimum or maximum values.

(F,G) Correlations between circRNAs detected in each sample and the age of the control (green, correlation = 0.68, p-value = 0.032) and PD donors (blue, correlation = -0.14 p value = 0.62).

(H) Volcano plot of DE circRNAs in PD vs control tissues, red dots indicate statistically significant DE circRNAs according to FDR correction of Wald test (DEseq2 analysis). CircSLC8A1 is marked is red.
A Parkinson's disease CircRNAs Resource reveals a link between circSLC8A1 and oxidative stress (2020)
Figure 4

Figure 4: CircSLC8A1 increases in the PD brain and upon PQ exposure are accompanied by suppression of the SLC8A1 protein.

(A) Graphic representation of circSLC8A1 and its post-transcriptional regulation in PD and under PQ exposure.

(B, C) CircSLC8A1 and linear SLC8A1 levels in the SN of control and PD brains, T-test p=0.025, p= 0.118 respectively.

(D) qPCR validations of circSLC8A1 and SLC8A1 mRNA changes in the SN, T-test p*=0.025. n=18 for CT and 24 for PD, x defines mean values.

(E) no difference in circSLC8A1 levels in females and males, T-test p=0.583 for control and p=0.262 for PD. n=15 females and 16 males. . The box is drawn from Q1 to Q3 with a horizontal line drawn in the middle to denote the median and x marks the average. Whiskers mark minimum or maximum values.

(F, G) CircSLC8A1 and linear SLC8A1 mRNA levels are correlated in control, R2=0.47 T-test p=0.0017 but not in PD samples, R2= 0.016, p>0.05. n=18 for CT and 23 for PD. Data presented as mean ± SD. Note that y-axis scales in F and G are different to allow better visualization.

(H) Increased CircSLC8A1 RNA levels in PQ-exposed SH-SY cells (normalized to Tubb3 and RPL19) while other circRNAs remain unchanged, T-test p*=0.028 and p*= 0.0215 for 25 µM and 50 µM respectively. n=4 biological replicas for each condition. Data presented as mean ± SD.

(I,J) Immunoblot decline (western blot and quantification) of the SLC8A1 protein in PQ-exposed SH-SY cells, with Tubulin as a loading control, T-test p*=0.015. n=3 biological replicas for each condition. Data presented as mean ± SD.
A Parkinson's disease CircRNAs Resource reveals a link between circSLC8A1 and oxidative stress (2020)
Figure 5

Figure 5: CircSLC8A1 is reduced under neuroprotection

(A) qPCR measurements of circSLC8A1 and SLC8A1 mRNA after SH-SY treatment of statins or the PF LRRK2 inhibitor, T-test p**=0.007 and p**=0.01 for PF-06447475 and p*=0.047 and p=*0.0136 for Statins for cirSLC8A1 and SLC8A1 mRNA respectively, n=3 biological replicas for each condition. Data presented as mean ± SD.

(B,C) Protein gel and quantification of SLC8A1 and Tubulin as a loading control in Statin and PF treated neuronal cell cultures, T-test p*=0.027 for Statins and p*=0.011 for PF-06447475, n=3 biological replicas for each condition. Data presented as mean ± SD.

(D) SLC8A1 immunostaining of statin-treated SH-SY cells.
A Parkinson's disease CircRNAs Resource reveals a link between circSLC8A1 and oxidative stress (2020)
Figure 6

Figure 6: Cytoplasmic circSLC8A1 binds Ago2 and regulates miR-128 targets

(A) Gene structure and conservation of the human and murine SLC8A1 gene. The box marks the second exon that circularizes to create circSLC8A1.

(B) qPCR quantification from nuclear/cytoplasmic fractionations of SH-SY cells, T-test p=0.005 for circSLC8A1, p=0.009 for NEAT1 and p=0.009 for Rpl19. n=3 biological replicas for each condition. Data presented as mean ± SD.

(C) qPCR quantification of Ago2-bound RNA, immunoprecipitated (IP)/Input values normalized to negative control for a known Ago2 target, circCDR1as and circSLC8A1, T-test p=0.029 for circSLC8A1 and p=0.001 for circCDR1as, n=3 biological replicas for each condition. Data presented as mean ± SD.

(D) schematic representation of circSLC8A1 with Ago2 binding sites from CLIP-seq and predicted miRNA binding sites.

(E) miRNAs predicted to bind circSLC8A1 with 3 sites and more.

(F) Schematic representation of circSLC8A1-Ago2 complex binding and its effect on miR-128 targets.

(G) relative expression of known miR-128 targets from SN RNA-seq, p**=0.0004 for BMI1, p*=0.011 for SIRT1 and p*=0.005 for AXIN1.

(H) relative expression of known miR-128 targets in SH-SY cells treated with Paraquat, T-test p*=0.03, p*=0.02 and p*=0.002 for AXIN1, BM1 and SIRT1 respectively, Data presented as mean ± SD with 4-6 biological replicas for each condition.

(I) miR enrichment analysis of DE genes in SN from validated miR-targets.

EV Figure legends
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 1

Figure 1. METTL3 protects METTL14 from degradation.

A, B RT-qPCR analysis of METTL3 and METTL14 expression (A) and immunoblot analysis of METTL3 and METTL14 protein levels (B) in shRNA knockdown METTL3 cells. Data are means±SEM from three biological replicates and were analyzed by two-tailed unpaired t-test. ***p < 0.001; n.s., not significant. β-actin was used as the loading control in the immunoblots. METTL3 or METTL14 /β-actin densitometric ratio was recorded by ImageJ.

C Immunoblots showing total METTL14 protein levels in HA-tagged METTL14-overexpressing cells. The total METTL14/β-actin densitometric ratio was recorded by ImageJ.

D Immunoblots showing the effects of cycloheximide (CHX) treatment on SK-Cha-1 cells. Cells with shRNA-mediated knockdown of METTL3 (sh-METTL3) and negative control (sh-NC) SK-Cha-1 cells were exposed to 100 μg/ml CHX. The METTL14 levels dramatically decreased in sh-METTL3 cells exposed to CHX compared to the negative control. β-actin was used as the loading control. The METTL14/β-actin densitometric ratio was recorded by ImageJ.

E Immunoblots showing the protein levels in the CHX assay in the METTL3 knockout cell line E14TG2a. After 4 hours of exposure to CHX, METTL14 levels dramatically decreased in METTL3 knockout (METTL3-KO) cells, whereas those in METTL3 wild-type (METTL3-WT) cells showed only a slight change. β-actin was used as the loading control. The METTL14/β-actin densitometric ratio was recorded by ImageJ.

F Immunoblots showing the protein level of METTL14 after transfection with the FLAG-METTL3 plasmid. β-actin was used as the loading control. The FLAG-METTL14/β-actin densitometric ratio was recorded by ImageJ.

G METTL14 protein levels detected under a concentration gradient of FLAG-METTL3 plasmids. The HA-METTL14/β-actin densitometric ratio was recorded by ImageJ.

H Schematic diagram of METTL3 showing the different domains. MTD, methyltransferase domain.

I HA-METTL14 Co-IP with FLAG-tagged METTL3 domain-deletion mutants. β-actin was used as the loading control.

J HA-METTL14 protein levels detected under a concentration gradient of plasmids encoding FLAG-tagged METTL3 domain-deletion mutants. β-actin was used as the loading control. The HA-METTL14 or FLAG-METTL3 mutants /β-actin densitometric ratio was recorded by ImageJ.
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 2

Figure 2. The ubiquitin-proteasome system regulates METTL14 protein stability.

A METTL14-GFP Co-IP assay in HEK293T cells. Silver staining identified the specific bands (red arrow) for METTL14-IP (black arrow).

B GO analysis of the METTL14 interactome.

C Co-IP of HA-METTL14 with the proteasome subunit PSMD3-myc in HEK293T cells.

D METTL14 protein levels increase significantly with increasing MG132 concentration. The FLAG-METTL14/β-actin densitometric ratio was recorded by ImageJ.

E METTL14 ubiquitination, as detected by IP of METTL14 with anti-FLAG antibody and immunoblotting with anti-Ub antibody. The accumulation of Ub and METTL14 was confirmed in whole-cell lysates. β-actin was used as the loading control.

F Immunoblot analysis of FLAG-METTL14, LC3-II, and β-actin in HEK293T cells exposed to the autophagy inhibitor Baf-A1 and activator Torin 1, respectively. The FLAG-METTL14 or LC3-II /β-actin densitometric ratio was recorded by ImageJ.

G Dot blots of m6A levels in the presence of MG132 in 293T, RBE, SK-Cha-1, and SK-N-SH cells.
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 3

Figure 3. STUB1 is the E3 ubiquitin ligase to promote METTL14 ubiquitination.

A List of E3 ligases in the METTL14 interactome identified by MS.

B Immunoblots showing METTL14 protein levels in cells with shRNA knockdown of UBR1, STUB1, UBR5, or TRIM33. The METTL14 /β-actin densitometric ratio was recorded by ImageJ.

C Co-IP assays between FLAG-METTL14 and STUB1 or URB1.

D Immunofluorescence of METTL14 (green) colocalized with that of STUB1 (red) in HEK293T cells. Nuclei were stained with DAPI (blue). Scale bar, 20 µm.

E Immunoblots showing the protein level of METTL14 after transfection with a plasmid encoding STUB1. β-actin was used as the loading control. The HA-METTL14/β-actin densitometric ratio was recorded by ImageJ.

F Schematic diagram of STUB1-domain-deletion mutants.

G, H HA-METTL14 Co-IP with FLAG-tagged STUB1-domain-deletion mutants.

I Immunoblots showing METTL14 ubiquitination assays under ectopic expression of STUB1 or the STUB1H260Q mutant, which encodes a protein that lacks E3 ligase activity.

J Immunoblots showing METTL14 ubiquitination assays under STUB1 siRNA knockdown.

K In vitro ubiquitination assays showing that purified METLL14 is ubiquitinated by purified STUB1-His. Ube1L2 and UbcH5b were the E1 and E2 enzymes, respectively, in the ubiquitination system. ATP and ubiquitin (UB) were also added to the assay.

L Immunoblots showing CHX assay in HEK293T cells. Negative control (NC; no transfected cells) and STUB1-FLAG plasmid-transfected HEK293T cells were exposed to 100 μg/ml CHX for 0, 4, 8, or 12 hours. β-actin was used as the loading control. The METTL14/β-actin densitometric ratio was recorded by ImageJ.

M, N Dot blot assays showing that enforced expression of wild-type STUB1, but not the STUB1H260Q mutant, significantly decreases total m6A levels.
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 4

Figure 4. K148, K156, and K162 are the main sites of METTL14 ubiquitination by STUB1.

A Schematic diagram of METTL14-domain-deletion mutants. All mutants were HA-tagged.

B Immunoblots showing the abundance of METTL14 truncated mutants with or without 10 µM MG132 treatment. Histone H4 was used as the loading control. The HA-METTL14/β-actin densitometric ratio was recorded by ImageJ.

C METTL14 ubiquitination, as detected by IP of METTL14 truncated mutants with anti-HA antibody and immunoblotting with anti-ubiquitin (anti-Ub) antibody. Accumulation of Ub and METTL14 was confirmed in whole-cell lysates.

D, E METTL14 ubiquitination, as detected by IP of a series of mutants with lysine (K)-to-arginine (R) substitutions in the aa 111-285 portion of the protein. The accumulation of Ub and METTL14 was confirmed in the whole-cell lysates. WT, wild type; 3KR, K148, K156, and K162 all mutated to R.

F Immunoblots showing the levels of METTL14 protein after transfection with METTL14-3KR mutant plasmids with or without 10 µM MG132. β-actin was used as the loading control. The HA-METTL14/β-actin densitometric ratio was recorded by ImageJ.

G Immunoblots showing the protein level of METTL14 after transfection with METTL14-3KR mutant plasmids under STUB1 knockdown. β-actin was used as the loading control. The HA-METTL14/β-actin densitometric ratio was recorded by ImageJ.

H Immunoblots showing HEK293T cells in response to CHX treatment. HA-METTL14 and HA-METTL14-3KR plasmid-transfected HEK293T cells were exposed to 100 μg/ml CHX for 0, 4, 8, or 12 hours. β-actin was used as the loading control. The HA-METTL14/β-actin densitometric ratio was recorded by ImageJ.
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 5

Figure 5. METTL3 protects METTL14 from STUB1-mediated ubiquitination to maintain m6A homeostasis.

A Immunoblots showing METTL14 protein levels under METTL3 knockdown with or without 10 µM MG132 treatment. β-actin was used as the loading control. The METTL3 or METTL14/β-actin densitometric ratio was recorded by ImageJ.

B METTL14 ubiquitination, as detected by IP of METTL3 truncated mutants with anti-HA antibody. The accumulation of Ub and METTL14 was confirmed in whole-cell lysates. β-actin was used as the loading control.

C Immunoblots showing METTL14 protein levels, as detected by IP in response to METTL3 truncated mutants and STUB1-FLAG. β-actin was used as the loading control.

D Dot blot assays showing the activities of METTL3 truncated mutants and STUB1-FLAG in regulating m6A levels.
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 6

Figure 6. STUB1-mediated degradation of METTL14 suppresses tumorigenesis.

A Morphology of colonies of SK-Cha-1 cells overexpressing STUB1-FLAG. Data are means ± SEM of three biological replicates and were analyzed by two-tailed unpaired t-test. (**p < 0.01).

B CCK-8 assays showing cell viability in SK-Cha-1, RBE, and QBC939 cells overexpressing STUB1-FLAG. Data are means ± SEM of three biological replicates and were analyzed by two-way ANOVA (**p < 0.01, ***p < 0.001).

C Immunoblots showing METTL14 protein levels in SK-Cha-1 cells with STUB1 knockdown and METTL14 knockdown (left panel). β-actin was used as the loading control. The METTL14 or STUB1 /β-actin densitometric ratio was recorded by ImageJ. CCK-8 assays showing cell viability upon the function of METTL14 activity in STUB1 knockdown cells (right panel). Data are means ± SEM of three biological replicates and were analyzed by two-way ANOVA (***p < 0.001).

D CCK-8 assays showing cell viability upon the function of METTL3 in STUB1 knockdown or overexpression cells. Data are means ± SEM of three biological replicates and were analyzed by two-way ANOVA (*p < 0.05, **p < 0.01).

E-G Following the subcutaneous inoculation of SK-Cha-1-NC (left) and SK-Cha-1-STUB1-FLAG (right) cells into the flanks of male NOD-SCID mice (E), overexpression of STUB1-FLAG inhibited malignant cell proliferation (F) and reduced subsequent tumor size and growth (G) in vivo. Data are means ± SEM. Statistical significance was analyzed by two-way ANOVA (F) or two-tailed unpaired t-test (G) (Five mice, *p < 0.05; **p < 0.01).

H-J Following the subcutaneous inoculation of SK-Cha-1-sh-NC (left) and SK-Cha-1-sh-STUB1-1 (right) cells into the flanks of male nude mice (H), STUB1 knockdown promoted malignant cell proliferation (I) and increased subsequent tumor size and growth (J). Data are means ± SEM. Statistical significance was analyzed by two-way ANOVA (I) or two-tailed unpaired t-test (J). (Six mice, *p < 0.05; **p < 0.01; ***p < 0.001).

K, L Immunoblots (K) and dot blots (L) showing METTL14 protein levels and m6A levels under STUB1-FLAG overexpression in five pairs of mouse tumors. β-actin was used as the loading control. The METTL14 or STUB1-FLAG /β-actin densitometric ratio was recorded by ImageJ.
METTL3 protects METTL14 from STUB1-mediated degradation to maintain m6A homeostasis (2022)
Figure 7

Figure 7. STUB1-mediated degradation of METTL14 has potential clinical relevance.

A METTL14 and STUB1 expression show a strong negative correlation in the TGCA data sets consisting of 72 CCA patient samples (Pearson coefficient: -0.4698, p < 0.001).

B Immunoblot analysis showing STUB1 protein levels in eight pairs of CCA patient samples. N, adjacent non-tumor tissue; T, tumor tissue. β-actin was used as the loading control. The STUB1/β-actin densitometric ratio was recorded by ImageJ.

C The 5-year disease-free survival of patients with high expression levels of METTL14 (p = 0.0366) and low expression levels of STUB1 (p = 0.0803) in the Fudan University intrahepatic cholangiocarcinoma (FU-iCCA) cohort among patient samples within the 5-95% ranges of STUB1 and METTL14 protein levels.

D Working model for the role of the competitive interaction of METTL3 and STUB1 in maintaining METTL14 levels and the subsequent regulation of m6A homeostasis.

Expanded View Figure legends