Dnmt2 mediates intergenerational transmission of paternally acquired metabolic disorders through sperm small non-coding RNAs

Abstract

The discovery of RNAs (for example, messenger RNAs, non-coding RNAs) in sperm has opened the possibility that sperm may function by delivering additional paternal information aside from solely providing the DNA ¹ . Increasing evidence now suggests that sperm small non-coding RNAs (sncRNAs) can mediate intergenerational transmission of paternally acquired phenotypes, including mental stress^2,3 and metabolic disorders^4-6. How sperm sncRNAs encode paternal information remains unclear, but the mechanism may involve RNA modifications. Here we show that deletion of a mouse tRNA methyltransferase, DNMT2, abolished sperm sncRNA-mediated transmission of high-fat-diet-induced metabolic disorders to offspring. Dnmt2 deletion prevented the elevation of RNA modifications (m⁵C, m²G) in sperm 30-40 nt RNA fractions that are induced by a high-fat diet. Also, Dnmt2 deletion altered the sperm small RNA expression profile, including levels of tRNA-derived small RNAs and rRNA-derived small RNAs, which might be essential in composing a sperm RNA 'coding signature' that is needed for paternal epigenetic memory. Finally, we show that Dnmt2-mediated m⁵C contributes to the secondary structure and biological properties of sncRNAs, implicating sperm RNA modifications as an additional layer of paternal hereditary information.

Figure 1. Body weight and metabolic parameters of F0 males (Dnmt2^+/+ and Dnmt2^−/−) under HFD and ND

(a) Dnmt2^+/+ and Dnmt2^−/− F0 males were fed a ND (10% fat) or HFD (60% fat) from the age of 6 weeks to 6 months. (b) Body weight of F0 males in each group at 6 months of age. Each dot represents one mouse, data pooled from 7 experiments. Statistical analysis was performed by two-tailed, one-way Anova, uncorrected Fisher’s LSD (n=mouse number in each group). (c) Blood glucose during the GTT. n=mice number in each group, data pooled from 7 experiments. Statistical analysis was performed by two-tailed, two-way Anova, uncorrected Fisher’s LSD. ****P < 0.0001 (Dnmt2^+/+ HFD versus Dnmt2^+/+ ND); ^##P < 0.01, ^####P < 0.0001 (Dnmt2^−/− HFD versus Dnmt2^−/− ND); ^★★P < 0.01 (Dnmt2^+/+ HFD versus Dnmt2^−/− HFD). (d) Relative blood glucose during the ITT. n=mice number in each group, data pooled from 7 experiments. Statistical analysis was performed by two-tailed, two-way Anova, uncorrected Fisher’s LSD. ****P < 0.0001 (Dnmt2^+/+ HFD versus Dnmt2^+/+ ND); ^###P < 0.001, ^####P < 0.0001 (Dnmt2^−/− HFD versus Dnmt2^−/− ND). (e) Serum insulin during the GTT. n=mice number in each group, data pooled from 4 experiments. Statistical analysis was performed by two-tailed, two-way Anova, uncorrected Fisher’s LSD. *P < 0.05, **P < 0.01 ****P < 0.0001 (Dnmt2^+/+ HFD versus Dnmt2^+/+ ND); ^##P < 0.01, ^###P < 0.001, ^####P < 0.0001 (Dnmt2^−/− HFD versus Dnmt2^−/− ND). (f,g,h) Area under the curve (AUC) statistics for (c,d,e) respectively. Statistical analysis was performed by two-tailed, one-way Anova, uncorrected Fisher’s LSD; NS: not significant. All data are plotted as mean±SEM. All statistic source data and P values are provided in Supplementary Table 1.

Figure 2. Body weight and metabolic parameters of F1 males generated by zygotic injection of sperm total RNAs or 30–40nt RNAs, fed on a ND

(a–d) Body weight and metabolic phenotypes of F1 males generated from sperm total RNAs injection. (a) Body weight. Each dot represents one mouse, data pooled from 10 experiments. *P < 0.05, **P < 0.01 (n=mouse number in each group). (b) Blood glucose during GTT. n=mice number in each group, data pooled from 10 experiments. *P < 0.05, **P < 0.01, ***P < 0.001 (Dnmt2^+/+ HFD F1 versus Dnmt2^+/+ ND F1); ^##P < 0.01, ^####P < 0.0001 (Dnmt2^+/+ HFD F1 versus Dnmt2^−/− HFD F1); (c) Relative blood glucose during ITT. n=mice number in each group, data pooled from 8 experiments. (d) Serum insulin during GTT. n=mice number in each group, data pooled from 7 experiments. *P < 0.05, **P < 0.01 (Dnmt2^+/+ HFD F1 versus Dnmt2^+/+ ND F1); ^#P < 0.05, ^##P < 0.01(Dnmt2^+/+ HFD F1 versus Dnmt2^−/− HFD F1); (i,j,k) AUC statistics for (b,c,d) respectively. (e–h) Body weight and metabolic phenotypes of F1 males generated from sperm 30–40nt RNAs injection. (e) Body weight. Each dot represents one mouse, data pooled from 10 experiments (n=mouse number in each group). (f) Blood glucose during GTT. n=mice number in each group, data pooled from 10 experiments. **P < 0.01, ****P < 0.0001 (Dnmt2^+/+ HFD F1 versus Dnmt2^+/+ ND F1); ^#P < 0.05, ^####P < 0.0001 (Dnmt2^+/+ HFD F1 versus Dnmt2^−/− HFD F1); ^▲P < 0.05 (Dnmt2^−/− HFD F1 versus Dnmt2^−/− ND F1). ^★P < 0.05 (Dnmt2^−/− HFD F1 versus control injection F1); (g) Relative blood glucose during ITT. n=mice number in each group, data pooled from 7 experiments. (h) Serum insulin during GTT. n=mice number in each group, data pooled from 7 experiments. *P < 0.05, **P < 0.01 (Dnmt2^+/+ HFD F1 versus Dnmt2^+/+ ND F1); ^##P < 0.01, ^###P < 0.001 (Dnmt2^+/+ HFD F1 versus Dnmt2^−/− HFD F1); (l,m,n) AUC statistics for (f,g,h) respectively. All data are plotted as mean±SEM. Statistical analyses were performed by two-tailed, one-way Anova (a,e,i–n) or two-way Anova (b–d,f–h), uncorrected Fisher’s LSD. NS: not significant. All statistic source data and P values are provided in Supplementary Table 1.

Figure 3. Altered RNA modifications in different sperm RNA fractions from F0 Dnmt2^+/+ and Dnmt2^−/− males under ND and HFD

(a) The relative level of m⁵C in different sperm RNA fractions (15–25nt, 30–40nt, 40–100nt and >100 nt). (b) The relative level of m²G in different sperm RNA fractions (15–25nt, 30–40nt, 40–100nt and >100 nt). (c) The relative level of m¹A in different sperm RNA fractions (15–25nt, 30–40nt, 40–100nt and >100nt). Value for each dot are generated from pooled sperm RNAs from 8 mice, in order to reach optimal RNA amount in each fraction to perform LC-MS/MS. All data are plotted as mean±SEM with n =number of biologically independent experiments (each dot in the figure represents one experiment), which is also detailed in Supplementary Table 1. All statistical analysis was performed by two-tailed, one-way Anova, uncorrected Fisher’s LSD. NS: not significant. All statistic source data and P values are provided in Supplementary Table 1.

Figure 4. Dnmt2-depended m⁵C modification regulate sperm tsRNA level and biological properties of tsRNA

(a) Dnmt2-dependent C38 methylation in sperm. Bisulfite sequencing maps for the three known tRNA targets of DNMT2 (tRNA-Asp, tRNA-Glu and tRNA-Gly) in mouse sperm (Dnmt2^+/+ and Dnmt2^−/−). Each row represents one sequence read, each column a cytosine residue. Yellow boxes represent unmethylated cytosine residues; blue boxes indicate methylated cytosine residues (m⁵C), sequencing gaps are shown in white. Numbers above the maps indicate the number of reads. Cytosine C38 is labeled in red, other cytosine sites are in black. (b) Northern blot analyses of 5′tsRNA-Gly, 3′tsRNA-Gly and rsRNA-28S (shown by arrow heads) in Dnmt2^+/+ ND, Dnmt2^+/+ HFD, Dnmt2^−/− HFD and Dnmt2^−/− ND sperm RNA. Sperm total RNAs extracted from two mice were mixed together for each lane in the experiment. Sperm total RNAs were run on a 15% denature PAGE gel shown as a loading control. Blots are shown as representatives of three independent experiments (for rsRNA-28S) or two independent experiments (for tsRNAs) with similar results. (c) The sequence of chemically synthesized 3′tsRNA-Gly that harbors five m⁵C according to the Dnmt2^+/+ condition (5 x m⁵C), 3′tsRNA-Gly with four m⁵C, lacking a Dnmt2-mediated m⁵C at C38 position (4 x m⁵C), and 3′tsRNA-Gly without any RNA modification (no m⁵C). (d) site-specific m⁵C alter the secondary structure of tsRNA, as well as their resilience against RNase degradation. In the native PAGE gel, it is shown that a lack of m⁵C at C38 position (with four m⁵C) significantly changed the secondary structure of tsRNA, and that the tsRNA with four m⁵C are more resilient to RNase degradation than those with no m⁵C or with five m⁵C, as tested by RNase A/T1 and 20% FBS (Fetal Bovine Serum, which contains a unique combination of RNases). Each panel is showed as representative of three independent experiments with similar results. (e) Illustration of the essential role of DNMT2 in shaping the sperm RNA ‘coding signature’ (consisting of RNA expression and modification profiles) to confer intergenerational transmission of HFD-induced paternal metabolic disorders.