A SET domain-containing protein and HCF-1 maintain transgenerational epigenetic memory

Domain: chemistry
Published: 2026-01-09
Editorial outcome: major_revision

Abstract
Transgenerational epigenetic inheritance (TEI) allows epigenetic information to pass across generations through mechanisms such as small RNAs and histone modifications. Histone methylation is often deposited by SET domain-containing methyltransferases. Some SET proteins lack catalytic activity but still regulate chromatin and gene expression. Here, we characterize SET-24, a catalytically inactive SET domain protein that localizes to germline nuclei and is essential for germline immortality in Caenorhabditis elegans. In set-24 mutants, small RNA-mediated epigenetic silencing is impaired. Proteomic, yeast two-hybrid, and pull-down assays show that SET-24 interacts with HCF-1, a chromatin factor linked to complexes like COMPASS, which deposits H3K4me3. Loss of SET-24 leads to increased H3K4me3 at transcription start sites of hundreds of genes. Although transcription remains largely unchanged, small RNA production is disrupted for about 30% of these genes. We propose that SET-24 preserves germline epigenetic memory by sustaining a chromatin environment that supports small RNA biogenesis across generations.

Introduction
RNA interference (RNAi) is a highly conserved gene silencing mechanism present in a wide array of organisms, safeguarding genome integrity and modulating gene expression1,2. This process can be triggered by both exogenous small interfering RNAs (exo-siRNAs) and endogenous small RNAs, including endo-siRNAs and Piwi-interacting RNAs (piRNAs). In the nematode Caenorhabditis elegans, RNAi involves the synthesis of primary siRNAs, which cleave their target mRNAs within the cytoplasm. This initiates the amplification of secondary siRNAs, also known as 22G-RNAs, bound to Argonaute proteins, thereby amplifying the signal and leading to post-transcriptional gene silencing3. Additionally, within the nucleus, small RNAs and Argonaute proteins can promote the deposition of histone modifications such as H3K9me3 and H3K27me3, resulting in transcriptional gene silencing of target genes4–8.

Both exogenous and endogenous RNAi cause heritable gene silencing. For example, the silencing effects initiated by GFP-targeting double-stranded RNAs (dsRNAs) can last for multiple generations9,10. Argonaute-bound siRNAs and histone modifications such as H3K9me3, H3K23me3, and H3K27me3 have been implicated in the transmission of silencing across generations, a phenomenon also known as transgenerational epigenetic inheritance (TEI)4,6,7,10–16. Numerous factors related to histone modifications, such as H3K27me3 demethylation factors, the PRC2 complex, the putative H3K9 methyltransferases MET-2, SET-25, and SET-32, as well as SET-21, which methylates H3K23 in conjunction with SET-32, are involved in TEI12,17–24.

In transgenic C. elegans with a gfp::h2b sequence controlled by a germline-specific promoter, exposure to gfp dsRNA results in the silencing of GFP, which is typically inherited for multiple generations9. Previous research has proposed three distinct steps to small RNA-driven TEI: initiation, establishment, and maintenance18. The establishment of TEI relies on essential chromatin modifiers, specifically SET-25 and SET-3218. Other factors, such as HRDE-1, are involved in both the establishment and maintenance of TEI25–27.

The mortal germline (Mrt) phenotype in C. elegans is a heritable trait characterized by progressive sterility across successive generations28,29. Over the past decades, numerous Mrt mutants have been identified, many of which are associated with RNAi and TEI27. For instance, mutations in the WAGO-4/ZNFX-1 complex, SET-25, and SET-32, and some nuclear RNAi pathway factors such as HRDE-1, lead to Mrt phenotype in C. elegans grown at 25°C17–19,25,30–32. It has been hypothesized that RNAi machinery might promote germline immortality by establishing an epigenome conducive to germ cell quiescence30. However, the underlying mechanisms for defects in nuclear RNAi or TEI, simultaneous to temperature-sensitive Mrt phenotype, remain unclear. For piRNA-driven silencing, aberrant silencing of histone genes in piRNA mutants was proposed to underlie their Mrt defect33.

Wild isolates of C. elegans offer a rich source of natural genetic variation for investigating worm behaviours, phenotypes, and their underlying mechanisms. Some wild isolates exhibit a temperature-sensitive Mrt phenotype at 25°C34. In a previous study, a deletion of the set-24 gene was identified in the wild C. elegans isolate MY10, which displayed a Mrt phenotype35. SET-24 encodes a protein that contains a conserved SET domain, originally identified from Su(var)3-9, Enhancer of zeste, and Trithorax histone methyltransferases (HMTs)36. SET domain-containing proteins are a well-characterized group of histone-modifying factors that play a critical role in gene regulation processes. Dysfunction of these factors is frequently associated with diseases, including cancer, developmental disorders, and aging-related pathologies37. Unlike the well-established functions of C. elegans SET-25 and SET-32 in H3K9 methylation and TEI, the function and mechanism of SET-24 remain elusive.

In this study, we investigated the function of SET-24. The SET domain of SET-24 shares similarity with the catalytically inactive SET domain of MLL5 in Homo sapiens (HsMLL5), which belongs to the Saccharomyces cerevisiae (ScSET3) subfamily. Accordingly, in vitro methyltransferase assays indicated that SET-24 does not show apparent methyltransferase activity. Animals with deletions in the coding sequence of set-24 exhibit a Mrt phenotype at 25°C, indicating that SET-24 is required to maintain germline immortality across generations. GFP RNAi inheritance assay demonstrated that SET-24 plays a role in the maintenance of transgenerational gene silencing. We also found that SET-24 is a germline-specific factor. We identified HCF-1 as a direct interacting partner of SET-24, and the two proteins colocalize in the nucleus. Although HCF-1 also regulates TEI, its depletion produces enhanced RNAi inheritance, the opposite phenotype to SET-24 depletion. Through chromatin and small RNA profiling, we found that SET-24 is required to regulate H3K4me3 and 22G-RNA levels in a subset of genes targeted by small RNA pathways. In summary, our findings reveal that SET-24, a factor with a catalytically inactive SET domain interacts with HCF-1 and is required at the interface between chromatin modifications and small RNA production, maintaining TEI.

Results
SET-24 is a member of the ScSet3 SET subfamily and lacks histone methyltransferase activity

The C. elegans genome encodes dozens of SET domain-containing proteins20,38,39. By aligning the SET domain sequences of these proteins and constructing a phylogenetic tree, we found that the SET domain of SET-24 is most similar to those of SET-9 and SET-26, paralogs with over 90% sequence similarity40 (Fig. 1a). The SET domains of SET-9 and SET-26 are likely homologous to the SET domains of SET3 in Saccharomyces cerevisiae (ScSET3), UpSET in Drosophila melanogaster (DmUpSET), and MLL5 in Homo sapiens (HsMLL5), all of which belong to the ScSet3 subfamily of SET domains41–43. We also aligned the SET domain sequence of SET-24 with those of human proteins containing SET domains. Among all these proteins, the SET domain of SET-24 shares the highest similarity with those of HsMLL5 and HsSETD5 (Fig. 1b).

Members of the ScSet3 subfamily are generally considered catalytically inactive in regard to methyltransferase activity42. To further investigate this, we aligned the sequence of SET-24’s SET domain with archetypal active and inactive SET domain-containing proteins. Like the ScSet3 subfamily members, the SET domain of SET-24 lacks several key residues that are crucial for catalytic activity (reviewed in refs. 42,44,45). For instance, the asparagine-histidine (NH) motif, essential for hydrogen bonding of the methyl donor SAM and the tyrosine (Y) motif, which functions by positioning target lysine in the catalytic site, are absent in SET-24 (Fig. 1c). These similarities to the ScSet3 subfamily and the absence of conserved motifs indicate that SET-24 is a member of the ScSet3 subfamily. To further validate this, we tested the methyltransferase activity of SET-24 on histones in vitro using a non-radioactive methyltransferase assay (Fig. 1d). We purified MBP-tagged full-length C. elegans SET-24 (CeSET-24) and S. cerevisiae SET2 (ScSET2), an active H3K36me3 methyltransferase, as a positive control46,47 (Supplementary Fig. 1a). While the assay confirmed the methyltransferase activity of ScSET2, SET-24 did not exhibit apparent activity on any of the four core histones, indicating that SET-24 lacks histone methyltransferase activity (Fig. 1e). Besides SET-9/24/26, three other SET domains, of SET-5/22/28, lack catalytic residues and are therefore also members of the ScSet3 subfamily (Supplementary Fig. 1b). This suggests that the SET domains in the branch highlighted in Fig. 1a are likely catalytically inactive.

Most members of the ScSet3 subfamily possess a conserved PHD domain and a SET domain within their sequences48 (Supplementary Fig. 2a). While the SET-24 sequence lacks the PHD domain, it contains two SPK domains (associated with SET, PHD, and Protein Kinase) of unknown function49 (Supplementary Fig. 2a). Proteins containing SPK domains are predominantly found in nematodes, with some present in C. elegans (Supplementary Fig. 2b). We used AlphaFold3 to predict the structures of the SPK domains (SPK1 and SPK2) in SET-24 and conducted a search for similar structures with Foldseek. The folds of the SET-24 SPK domains are very similar to the MYB-like domains of the telomere-binding proteins C. elegans TEBP-1 and TEBP-2, which can bind directly to double-stranded telomeric DNA sequences using their third MYB-like domain50,51 (Supplementary Fig. 2c).

Set-24 mutants display germline abnormalities and occasional escape from sterility

To explore the role of SET-24 in C. elegans, we first characterized the phenotypic impact of set-24 mutations. To address this, we created two alleles in a wild-type N2 background: set-24(mj617), an allele with a deletion of the entire coding sequence of set-24 and set-24(syb7014), a recreation of the set-24 allele mf123 from a previously described wild isolate that encodes a truncated version of the protein due to an early STOP codon after the 188th amino acid35 (Supplementary Fig. 3a). When grown at 25°C, the reference N2 strain could survive and usually be maintained for an indefinite number of generations, while the nuclear RNAi-defective mutant hrde-1 worms became sterile after 1 to 8 generations, showing a Mrt phenotype25. Similarly, when set-24(syb7014) and set-24(mj617) mutants were cultured at 25°C, the worms exhibited the Mrt phenotype and became sterile after 1 to 8 generations (Fig. 2a, b). Remarkably, certain set-24 lines escaped the Mrt phenotype and remained fertile at 25°C for more than 20 generations. We referred to these lineages as “escapees” (Fig. 2a, b).

After growing the worms at 25°C for several generations (G1-G3, from a parental P0), the germline of set-24 mutant strains displayed abnormalities, such as a short or atrophied gonad, or even an empty germline, which were not observed in the germline of wild-type worms. The percentage of set-24 mutant worms with abnormal germline increased from the parental P0 to G3. However, beyond G4, most set-24 mutant worms lack any observable germline defects (Figs. 2c, and Supplementary 3b, c), likely because the “escapees” became the dominant population and remained fertile in later generations. In conclusion, set-24 mutants show a Mrt phenotype that is associated with defects in germline development, but some set-24 lines escape sterility.

SET-24 is required to sustain heritable RNAi

Germline immortality is subject to genetic regulation. Previous studies have demonstrated that the absence of various factors associated with nuclear RNAi and TEI contributes to germline immortality4,16,17,22,24–26,31,32,52–55. Additionally, several SET-containing genes have been implicated in TEI27. Thus, we aimed to investigate if set-24 mutants exhibit defects in RNAi inheritance. We explored SET-24’s involvement in TEI using a previously described GFP::H2B transgenic strain10 (Fig. 3a). In this strain, GFP is consistently expressed in germline and embryo nuclei. This transgene can be silenced by feeding worms with bacteria expressing dsRNAs targeting the gfp sequence. Even after removing the RNAi trigger, the silencing persists in subsequent generations10 (Fig. 3b).

In worms with defective hrde-1, exposure to gfp dsRNA did not lead to heritable silencing of GFP::H2B, consistent with previous findings25 (Fig. 3b). In set-24 mutant strains, the silencing gradually decreased over a few generations after the removal of the RNAi bacteria (Fig. 3b). This decline was evaluated by determining the percentage of worms expressing GFP and measuring the relative expression level of spliced GFP mRNA using quantitative polymerase chain reaction (qPCR) (Fig. 3b, c). Given the roles of secondary siRNAs (22G-RNAs) in inheritable RNAi, we assessed the abundance of anti-GFP 22G-RNAs, which accumulate during the establishment of silencing. Anti-GFP siRNAs in set-24 mutant worms did not persist at the same levels as in wild-type worms, one and four generations after the removal of the silencing trigger (Fig. 3d). These findings highlight the critical role of SET-24 in the maintenance of dsRNA-triggered TEI.

The piRNA pathway safeguards the germline against transposons, by recognizing their transcripts and eliciting 22G-RNA biogenesis, which drive target silencing56–58. The piRNA sensor strain expresses an mcherry::his-58 fusion gene with a recognition site in the 3’ UTR for an abundant piRNA59. In a wild-type background, the sensor is silenced, but depletion of factors involved in the piRNA pathway, such as prg-1 and hrde-1, leads to its derepression. To investigate the potential role of set-24 in the piRNA pathway, we crossed set-24 mutants with the piRNA sensor strain. In contrast to the hrde-1 mutant, the depletion of set-24 did not derepress the piRNA sensor (Supplementary Figs. 4a, b). These findings suggest that set-24 is dispensable for the initiation of piRNA-dependent silencing.

Overall, these results demonstrate that in the absence of SET-24, siRNA signals do not persist across generations and RNAi inheritance is impaired. Also, piRNA-dependent silencing is not affected by SET-24.

SET-24 is a germline-specific factor and is localized to germline nuclei

Most TEI factors, such as the nuclear and perinuclear Argonautes, HRDE-1 and WAGO-4, respectively, are expressed in the germline17,25,31,32. This prompted the investigation of the expression pattern of SET-24. set-24 mRNAs have been previously detected in the C. elegans germline during the first larval stage60. In our RT-qPCR assay, set-24 mRNAs are predominantly detectable in embryo, L4, and adult stages, mirroring the mRNA expression pattern of the germline factor pie-1 (Supplementary Fig. 5a). set-24 mRNAs were not detecting glp-4(bn-2) worms grown at 25°C, which lack a germline at this restrictive temperature (Supplementary Fig. 5b). Moreover, set-24 mRNAs were still expressed in fem-1(hc17) and fog-2(q71) at the same temperature, despite the absence of sperm or oocytes respectively (Supplementary Fig. 5c). These mRNA expression patterns indicate that set-24 mRNA is confined to the C. elegans germline, both in spermatogenic and oogenic gonads.

Subsequently, we examined the localization of the SET-24 protein. We created an endogenously GFP-tagged SET-24 allele (Supplementary Fig. 3a). Similar to the wild-type strain, SET-24::GFP animals can survive and be maintained for numerous generations at 25°C, suggesting that the GFP at the C-terminus of SET-24 does not alter its function (Supplementary Fig. 5d, e). SET-24::GFP expression is restricted to germline nuclei (Fig. 4a and Supplementary Fig. 5f). Notably, unlike the germline perinuclear factor PGL-3, expressed throughout the entire gonad from the mitotic region to the diakinesis region in oocytes (Supplementary Fig. 5g), SET-24::GFP was only expressed between the mitotic and pachytene regions, with a clear fade in signal at the boundary of the pachytene and diplotene regions (Fig. 4a). In embryos, SET-24::GFP was solely expressed in germline-lineage cells, localized mainly to the nucleus, and showed partial overlap with PGL-3 (Fig. 4a).

To further examine the expression of SET-24, we analysed its colocalization with the histone marker H2B::mCherry and the synaptonemal complex marker tagRFP::SYP-1 using confocal microscopy in whole worms (Fig. 4b, c). Interestingly, SET-24::GFP form puncta in germline nuclei (Fig. 4b, c). While partial overlap between SET-24::GFP and H2B::mCherry was observed, likely on chromosomal regions, the large SET-24 puncta were distinct from chromosomes. (Fig. 4b, d). In summary, we conclude that SET-24 is a germline-specific nuclear factor, expressed up to the pachytene region that partially colocalizes with Histone H2B. We note that the pool of SET-24 protein localized to puncta does not seem to directly associate with chromosomes.

SET-24 contains a catalytically inactive SET domain (Fig. 1). To determine whether this domain influences the expression and localization of SET-24, we generated multiple mutations, including amino acid substitutions, in-frame and frame-shift deletions in the SET domain of set-24::gfp and set-24::3xflag strains (Fig. 4e and Supplementary Fig. 5h). Specifically, mj673 and mj677 introduce five amino acid substitutions in the region of the SET domain conserved throughout the ScSET3 subfamily (highlighted in the red frame in Fig. 1c; Fig. 4e and Supplementary Fig. 5h). The mj675 mutation deletes a sequence spanning both intronic and exonic regions, but remains in-frame, whereas mj674 and mj676 introduce frame-shift deletions in set-24::gfp and set-24::3xflag strains, respectively (Fig. 4e and Supplementary Fig. 5h).

Analysis of transcript levels of set-24 revealed that set-24(mj673)::gfp and set-24(mj677)::3xflag strains exhibit mRNA levels comparable to those of wild-type set-24::gfp and set-24::3xflag, while set-24(mj675)::3xflag displays reduced set-24 mRNA abundance, likely due to intron loss (Supplementary Fig. 5i). SET-24::GFP or SET-24::3xflag proteins were not detected in the in-frame deletion strain set-24(mj675)::3xflag or in the frame-shift mutants, set-24(mj674)::gfp and set-24(mj676)::3xfalg strains. Notably, although transcripts in set-24(mj673)::gfp and set-24(mj677)::3xflag are maintained at wild-type levels, GFP and FLAG signals are undetectable (Fig. 4f, g). These results indicate that the SET domain, and in particular the conserved amino acids within the ScSET3 subfamily (highlight in the red frame in Fig. 1c), are critical for protein stability in vivo, even though the domain itself is catalytically inactive.

SET-24 interacts with HCF-1 in vivo and in vitro

Given the nuclear localization of SET-24 and its partial colocalization with H2B (Fig. 4d), we inquired if SET-24 is able to bind to chromatin and interact with other chromatin factors in vivo. To investigate this, we performed a chromatin immunoprecipitation (ChIP) assay using both SET-24::3xFLAG and SET-24::GFP strains. These approaches yielded no detectable DNA enrichment (Supplementary Fig. 6a). This could be attributed to either lack of SET-24 binding to chromatin, or technical issues in our ChIP procedures.

Subsequently, we identified SET-24 binding partners through IP-MS (Immunoprecipitation and Mass Spectrometry) and Y2H (Yeast-two Hybrid) assays using young adult (YA) worms expressing SET-24::3xFLAG. Host Cell Factor 1 (HCF-1), the ortholog of human HCFC1 and HCFC2, was identified by the two assays (Fig. 5a, b, Supplementary Fig. 6b, Supplementary Data 1 and 2). Furthermore, a GST-pulldown assay demonstrated that recombinant GST-tagged full-length SET-24 physically interacts with MBP-tagged full-length HCF-1 in vitro, confirming that the interaction between SET-24 and HCF-1 is direct (Fig. 5c and Supplementary Fig. 6c).

HCF-1 is a highly conserved chromatin adapter protein that recruits histone-modifying complexes to chromatin61–63. It has been reported that HCF-1 plays a role in longevity and stress resistance in C. elegans63,64. In both whole worms and embryos, HCF-1 is a nuclear factor expressed in the germline and soma, while SET-24 is restricted to the germline64 (Fig. 4a, Supplementary Figs. 6d, e). In the gonad, HCF-1 does not show a decrease in signal at the boundary between the pachytene and diplotene regions, unlike SET-24::GFP (Supplementary Fig. 6f). In the germline nuclei, HCF-1::mKate2 also forms puncta and colocalizes with SET-24::GFP, with both factors showing partial overlap with BFP::H2B (Fig. 5d, e). Depletion of HCF-1 does not result in detectable alterations in the expression, localization, or puncta formation of SET-24. Reciprocally, depletion of SET-24 does not affect HCF-1 localization within the germline (Supplementary Figs. 6g, h). The data show that SET-24 and HCF-1 directly interact and colocalize in germline nuclei, but do not affect each other’s expression or localization.

In humans, HCF-1 interacts with MLL5 through HCF-1’s Kelch domain and MLL5’s HCF-1 binding motif (HBM)65. In C. elegans, the MLL5 homologs SET-9 and SET-26 contain the HBM, but the SET-24 protein does not encode a sequence identical to HBM63 (Supplementary Fig. 2a). To identify the regions responsible for the HCF-1-SET-24 interaction, we purified MBP- and GST- tagged truncated forms of HCF-1 and SET-24, respectively (Fig. 5f, g). The H1 N-terminal fragment of HCF-1 (1-378 aa), which primarily contains the Kelch domain, but not the C-terminal fragment (379–782 aa), directly interacts with full-length SET-24 (Fig. 5h and Supplementary Fig. 7a). Conversely, all SET-24 constructs containing the N-terminal region (1–239 aa), which include the SET domain and its flanking sequences, interacted with the H1 fragment of HCF-1 (Fig. 5i, Supplementary Figs. 7b, c). To further map the HCF-1 binding site of SET-24, we focused on its 1-239 aa N-terminal region containing the SET domain. We created one construct with the SET domain alone (fragment S7), and another version of SET-24 fragment S5 in which the SET domain was deleted in-frame (fragment S8; Fig. 5g). Interestingly, the HCF-1 fragment H1 interacted both with fragments S7 and S8 (Fig. 5j, k, Supplementary Figs. 7d–f). Together, these data suggest the HCF-1 Kelch domain directly interacts with the SET domain of SET-24, while the SET domain of SET-24 and its flanking sequences both contribute to the interaction with HCF-1.

HCF-1 inhibits the maintenance of heritable silencing

To investigate the roles of HCF-1, we obtained two alleles, ok559 and pk924. The ok559 allele carries an in-frame deletion in the Kelch domain, whereas pk924 is a frameshift mutation66 (Supplementary Fig. 6g). Both hcf-1 mutants exhibited a reduced brood size at 20°C and are nearly sterile at 25°C within one or two generations, without producing “escapees”, contrasting with the weaker phenotype of set-24 mutants (Fig. 6a). We next examined the brood size of set-24; hcf-1 double mutants and found that their brood sizes were comparable to those of the hcf-1 single mutants (Fig. 6a).

To assess if HCF-1 plays a role in TEI, we conducted a RNAi inheritance assay. Heterozygous set-24 or hcf-1 worms with a GFP::H2B transgene were fed gfp dsRNA, and the inheritance of silencing was monitored in subsequent generations (Fig. 6b). In this experimental setup, set-24 mutants lost silencing faster than wild-type animals (Supplementary Figs. 8a, b), which is consistent with previous findings (Fig. 3b). In contrast, it takes more generations for hcf-1 mutants to lose silencing compared to wild-type worms (Fig. 6c, d, Supplementary Fig. 8b). These results indicate that HCF-1 inhibits the maintenance of heritable silencing.

Next, heterozygous +/set-24; +/hcf-1 worms carrying the GFP::H2B transgene were fed gfp dsRNA and the inheritance of GFP silencing was monitored in progeny with different genotypes (either wild-type, set-24 or hcf-1 single mutants, and set-24; hcf-1 double mutants; Fig. 6e). Consistent with prior observations (Figs. 3b and 6b-d, Supplementary Figs. 8a, b), silencing was lost in fewer generations in set-24 single mutants and was maintained for more generations in hcf-1 single mutants (Fig. 6f, g). Importantly, the RNAi inheritance in set-24; hcf-1 double mutants phenocopied hcf-1 single mutants (Fig. 6f, g). To further validate these findings, heterozygous +/set-24; hcf-1/hcf-1 or set-24/set-24; +/hcf-1 worms carrying the GFP::H2B transgene were silenced, and the single mutants were compared with set-24; hcf-1 double mutants (Supplementary Figs. 8c-f). Again, set-24; hcf-1 double mutants maintain silencing similar to hcf-1 single mutants, and for more generations than set-24 single mutants (Supplementary Figs. 8c-f), corroborating previous results (Fig. 6f, g).

Together, these results indicate that HCF-1 and SET-24 both mediate TEI but display opposite inheritance phenotypes, with HCF-1 acting epistatically to SET-24 in this process.

SET-24 is required to modulate H3K4me3 and small RNA levels

SET domain proteins are known to influence histone modifications67. Human HCF-1 interacts with mixed-lineage leukemia (MLL) and the H3K4 methyltransferase Set162,68,69. In C. elegans, HCF-1 associates with the COMPASS complex, where the H3K4 methyltransferase SET-2 serves as an essential component63,70,71. To investigate if the depletion of set-24 affects the global levels of histone modifications, we conducted a western blot assay using antibodies specific to various histone methylation and acetylation marks in YA worms. This assay was performed on worms either grown at 20°C or for three generations at 25°C. There were no observable changes in set-24 mutants compared to wild-type worms (Supplementary Fig. 9a, b).

Since western blotting lacks the sensitivity to detect local changes in histone modification levels, we performed a ChIP-seq assay using an H3K4me3 antibody on both wild-type and set-24 mutant YA worms grown at 20°C. Overall, the H3K4me3 peak profiles were highly similar between strains (Supplementary Fig. 10a). However, ~10% of peaks showed increased H3K4me3 signal in set-24(syb7014) mutants, and most of these peaks overlapped with protein-coding genes (Supplementary Figs. 10b, c). In both strains, H3K4me3 was enriched at transcription start sites (TSS) of protein-coding genes (Fig. 7a), consistent with known patterns of this modification72. Importantly, the increase in H3K4me3 was not genome-wide but was restricted to genes with TSSs already marked by H3K4me3 in the wild types (Fig. 7b). We identified a subset of genes with significantly elevated H3K4me3 levels in set-24(syb7014) mutants, hereafter referred to as H3K4me3-enriched genes (Fig. 7a-c). Notably, the increase in H3K4me3 extended both upstream and downstream of the TSS (Supplementary Fig. 10d). To assess if this was due to changes in nucleosome occupancy, we conducted histone H3 ChIP-seq and measured total H3 levels globally and at SET-24-regulated H3K4me3-enriched genes. H3 levels were unchanged between strains, indicating that the increase in H3K4me3 in set-24(syb7014) mutants reflects a true modification change rather than altered H3 abundance (Supplementary Figs. 10b, e). Cross-referencing with a published germline expression dataset revealed that ~90% of the 757 set-24-dependent H3K4me3-enriched genes are germline-expressed73 (Supplementary Fig. 10f), further supporting a role for SET-24 in regulating H3K4me3 in the germline.

H3K4me3 is generally considered a histone mark associated with transcriptional activation74. To assess if the observed increase in H3K4me3 levels influences gene expression, we performed mRNA sequencing on wild-type and set-24(syb7014) mutant YA worms and analysed the transcriptional changes across all genes (Supplementary Data 3). We identified 12 genes with both H3K4me3 enrichment and mRNA upregulation in set-24(syb7014) mutants (Fig. 7d and Supplementary Data 4). These genes are also regulated by components of the COMPASS complex, SET-2 and WDR-5, as determined through a WormExp enrichment analysis75 (Supplementary Data 5), further suggesting a role for SET-24 in H3K4me3 regulation through HCF-1 and its interaction with COMPASS. However, the majority of H3K4me3-enriched genes did not exhibit increased transcription in set-24(syb7014) mutants (Fig. 7d).

Because the role of SET-24 in the maintenance of heritable RNAi and inheritance of 22G-RNAs (Fig. 3b, d), we sought to investigate the potential link between SET-24 and 22G-RNA regulation. To do so, we sequenced small RNAs in wild-type and set-24 mutants and analysed 22G-RNAs mapping to protein-coding genes (Supplementary Figs. 11a-c). We identified genes with significant changes in 22G-RNA expression in set-24 mutants relative to wild-type (Supplementary Data 6) and classified them as set-24-regulated 22G-RNA targets. More such targets were identified in the syb7014 allele than in the mj617 allele, but the two datasets overlapped well (Supplementary Fig. 11c); therefore, subsequent analyses focused on syb7014 for consistency with other sequencing datasets. 22G-RNAs can be subdivided into distinct subpopulations, according to the Argonaute protein they associate with, the factors required for their biogenesis, and the genes targeted76. We found that the set-24-regulated 22G-RNA targets overlap with WAGO- and Mutator-regulated genes (Fig. 7e, Supplementary Fig. 11d, and Supplementary Data 7), suggesting SET-24 is required for silencing of a subset of endogenous WAGO and Mutator targets.

Because HCF-1 also regulates TEI, we analysed 22G-RNAs in hcf-1(pk924) mutants. 22G-RNA populations were altered in hcf-1(pk924) mutants (Supplementary Fig. 11b), and 55% of the identified hcf-1-regulated 22G-RNA targets showed germline expression, compared with 60% of set-24-regulated targets (Supplementary Fig. 11e). While some overlap was observed between the two datasets, most targets were distinct (Supplementary Fig. 11f). Although HCF-1 directly interacts with SET-24 and their depletion causes opposite phenotypes, the overlapping 22G-RNA targets did not consistently exhibit opposite modes of regulation (Supplementary Fig. 11g). Thus, HCF-1 regulates 22G-RNA populations, including of a subset of targets shared with SET-24.

Next, we examined the correlation between H3K4me3 enrichment and set-24-regulated 22G-RNA targets (Fig. 7f). In total, 220 out of 757 H3K4me3-enriched genes in set-24(syb7014) mutants exhibited disrupted 22G-RNA levels (81 upregulated and 139 downregulated), whereas only 13 out of 757 showed altered transcriptional levels (including 12 upregulated and 1 downregulated, Fig. 7d, f, Supplementary Data 4). Among the H3K4me3-enriched genes, few (e.g. Y39G8B.2 and dyf-3) exhibited both increased transcription and disrupted 22G-RNA expression (Supplementary Fig. 11h). However, a larger subset, including C18B2.4 and clec-24, showed disrupted 22G-RNA levels without corresponding transcriptional changes (Fig. 7f, g). These results suggest that SET-24 is dedicated to maintaining 22G-RNA levels.

Taken together, these results suggest that SET-24 modulates H3K4me3 and 22G-RNA levels in a subset of WAGO/mutator target genes.

Methods
Evolutionary and structural analysis of SET and SPK domains
As the hidden Markov model (HMM) for SET domains within Pfam-A.hmm (version 3.1.b2, Feb 2015)101 was not sensitive enough to retrieve the SET domain of SET-24 of C. elegans, we first constructed an alternative HMM. To do so, we first downloaded the protein sequences of the InterPro102 SET domain (IPR046341), and the metadata with the associated domain coordinates, filtering for all human SET domains, as well as the catalytically inactive SET proteins of Drosophila melanogaster (UpSET) and Saccharomyces cerevisiae Set3. Then, we used the domain coordinates to trim all these protein sequences, keeping only the sequences of the SET domains, which were used as input for multiple sequence alignment with MAFFT v7.475, using option --auto29,103. Then, the HMM profile was built with this alignment using hmmbuild of the HMMer package (v3.3, hmmer.org). The HMM profile was used to search the entire C. elegans proteome (Wormbase ParaSite, version WBPS16)104 for SET domains with hmmsearch of the HMMer package (version 3.3, hmmer.org), with option --nobias. The C. elegans SET domains were aligned with MAFFT v7.475103, using option --auto (model chosen L-INS-i). The resulting alignment was input to infer a maximum likelihood phylogenetic tree with IQ-TREE v2.1.2105 with 1000 bootstraps (option -B 1000)106. LG+G4 was the best fit model. We created an additional phylogenetic tree using the above-mentioned human SET domains, plus the SET domain of C. elegans SET-24. Alignments were conducted with MAFFT (L-INS-i was the chosen model), and a tree was constructed with IQ-TREE (LG+G4 was the best fit model) as above.

We obtained the sequences of all proteins with an SPK domain (IPR006570), and the coordinates of the SPK domains from InterPro102. Sequences were trimmed according to the SPK coordinates to leave only the SPK sequence. The SPK domains were subsequently aligned with MAFFT v7.475103, using option --auto (model chosen L-INS-i), and a maximum likelihood tree was constructed with IQ-TREE v2.1.2105,106 with option -B 1000, and with LG+G4 as the best fit model.

The structure of SET-24 was predicted with AlphaFold3107, and the regions corresponding to the annotated SPK domain coordinates were extracted and used as input in Foldseek108. The MYB domains of TEBP-1 and TEBP-2 were amongst the top hits identified by Foldseek. We used AlphaFold3107 to predict the structures of TEBP-1 and TEBP-2, and extracted the structures corresponding to their MYB domains, according to previously defined domain annotations51 and predicted secondary structure elements. ChimeraX109 was used to visualize predicted models and perform structural alignments.

Strains
The Bristol strain N2 was used as the standard wild-type strain. All strains were grown at 20°C unless otherwise specified. The strains used in this study are listed in Supplementary Data 8.

Construction of transgenic strains
Wild-type YA animals (N2 strain) were injected with a mixture of target gene HR repair template (IDT oligos) (1 mg/ml), target gene CRISPR crRNA (Dharmacon) (8 mg/ml) and His-Cas9 (in-house bacterial purification) (5 mg/ml) dissolved in injection buffer (10 mM KCL; 10 mM Tris–HCl at pH: 8.0). F1 animals were singled, allowed to produce homozygous F2 progeny by selfing and genotyped. All final strains were checked by Sanger sequencing and outcrossed twice. The set-24(syb7014) and the set-24::3xflag(syb4492) strains were made by Suny-Biotech. The set-24(mj617) and set-24::gfp(mj616) strains were made by standard CRISPR/Cas9 methods110. Fot the set-24::gfp(mj616) strain, the homologous repair template containing the GFP sequence generated by PCR from the AP625 plasmid (Addgene), and a guide RNA, TGATCATTTCGATGACAACG, were used. For the set-24(mj617) strain, two guide RNAs, TGATCATTTCGATGACAACG and ACAGCCGGTGAGAA TGTGTT, and the repair temple, AAAAAAAAACAAAGGAGAGATGCA TTAACTTGTAAGAAAATAATATTATCATTGAACATCCGGCGAATTTTG GAGAAAACTGGTGGTTTCGTTGAAATCCATGATTGTTCTTGTGAAATT ATACACTGAAAATAAATATTTATATGTATTACTTATTTTTAAATATTTA GT, were used. For generating the set-24(mj673)::gfp, set-24(mj674)::gfp, set-24(mj675)::3xflag, set-24(mj676)::3xflag, and set-24(mj677)::3xflag strains, pDD162, an injection marker, three plasmids expressing sgRNAs targeting the set-24 sequence, and/or a repair template were co-injected into the germline of set-24::gfp (mj616) or set-24::3xflag (syb7014) animals. For the Pmex-5::hcf-1::mKate2 (mjIS606) strain, pDD162, an injection marker, three sgRNA-expressing plasmids (GAAATCGCCGACTTGCGAGG, GCAATGACTAACCGATTTTC, and TTCGGGATAATTGAGATGAG) targeting the ttTi4348 site on Chromosome I, and a plasmid containing Pmex-5::hcf-1::mKate2::hcf-1 3′ UTR with repair templates were co-injected into the C. elegans germline. Mutants or transgenes were identified by PCR screening of F1 worms carrying the injection marker.

Germline mortality assay
Worms were maintained at 20°C prior to the start of the experiment. At least 10 L4-stage individuals per genotype, designated as the P0 (parental) generation, were transferred to HB101-seeded plates at 25°C and allowed to produce offspring. At each generation, one L3 larva per replicate per genotype was transferred to a new plate to produce the next generation. The number of sterile animals at each generation was recorded.

Brood size assay
L3 worms were individually placed onto fresh NGM plates. Offspring counting began once the progeny reached the L4 stage, and counted offspring were removed using a vacuum pump. The number of progeny was counted in each generation over the course of three consecutive days.

Transgenerational memory inheritance
One L4 larva per genotype was plated on either GFP RNAi-expressing bacteria or empty vector L4440 bacteria. G1 animals were examined under a fluorescence microscope, and one silenced animal per replicate per genotype was transferred onto plates seeded with standard HB101 bacteria. At each generation, a single silenced animal was isolated from each plate to produce the next generation, while the remaining adult progeny were analysed under a fluorescence microscope. At least 20 animals per replicate per genotype were counted at each generation unless otherwise specified. For Fig. 3b, germline nuclear GFP brightness was scored by visual inspection as 1 for “bright” and 0 for “dark”, with dim GFP expression also classified as 0. For Fig. 6c, d, f, and g, Supplementary Figs. 8a, c-f), nuclear GFP brightness was assessed visually, with “bright” scored as 1, “dark” scored as 0, and “dim” scored as 0.5. The percentage of derepressed worms was calculated as the sum of the scores divided by the total number of worms examined. Representative images were captured using a Leica SP8 fluorescence microscope at 40X magnification.

RNA extraction and real-time quantitative PCR
For wild-type and set-24 worms, we picked one repressed worm at each generation (when available) and extracted RNA from its progeny, after setting aside one repressed worm to propagate the next generation. For the hrde-1 mutant, we picked derepressed worms starting from G1. Total RNA was extracted using TRIzol reagent (Ambion, Life Technologies) and treated with Turbo DNase Kit (Invitrogen) according to the manufacturer’s instructions. 500 ng of total RNA per sample were reverse-transcribed with random hexamers (Invitrogen) at 50°C for 1 h using Superscript III (Invitrogen). Reactions lacking reverse transcriptase were systematically run in parallel as negative controls. Real-time quantitative PCR was performed on 1 ul of diluted (1/5) RT reactions using SYBR Green kit (Life Technologies) on a OneStepPlus thermocycler (Thermo Fisher). All samples were run in duplicates and expression levels normalized to the reference gene cdc-42 according to the ΔΔCt method111. qPCR primers used in this work are listed in Supplementary Data 9.

22G-RNA real-time quantitative PCR
50 ng of total RNA were reverse-transcribed with a TaqMan Small RNA Assay Kit (Thermo Fisher) containing a gene-specific RT primer and a TaqMan MicroRNA Reverse Transcription Kit (Thermo Fisher), according to the manufacturer’s instructions. Real-time quantitative PCR was performed on 1 ul of diluted (1/5) RT reactions using custom-made TaqMan probe (GUGUCCAAGAAUGUUUCCAUCU), TaqMan Universal Master Mix No AmpErase UNG (Life Technologies) on a OneStepPlus thermocycler (Thermo Fisher). All samples were run in triplicates. Expression levels were normalized to the reference gene U18 (#001764, TaqMan) according to the ΔΔCt method111.

Whole-mount DAPI staining
At every generation, synchronized adult worms were collected in M9, fixed in 70% ethanol for 1 h, centrifuged and washed twice with 0.1% Tween-20/PBS (PBST) and strained in 100 mg/mL DAPI/PBST for 30 minutes at room temperature on a rotating wheel. Worms were then washed twice with PBST, pipetted onto a microscope slide and mounted in Vectashield. Worms were classified in categories and manually counted (at least 50 animals per genotype per generation were counted) under a fluorescence microscope. Single-plan representative images were taken on a SP8 confocal fluorescence microscope (Leica) at 63X magnification.

Immunofluorescence staining
Worms were picked on glass slides and manually dissected to extrude the germlines. Germlines were subsequently freeze-cracked on dry ice and fixed in cold 100% methanol for 20 min. Fixed slides were then washed in 0.05% Tween/PBS and incubated with diluted (1:1,000) anti-GFP (Abcam #ab290) and diluted (1:1,000) anti-PGL-3 (a gift by Susan Strome) antibodies overnight. The following day, slides were washed in 0.05% Tween/PBS and incubated with diluted secondary antibodies for 1 h at room temperature and mounted in Vectashield with DAPI. Representative images were taken on a Leica SP8 fluorescence microscope with a 63X oil objective and 4X digital magnification. Single-plan images are shown.

Imaging
A 4% agarose pad was prepared on a glass slide. Gravid adult animals were picked into a droplet of M9 buffer to remove residual E. coli and then transferred to another droplet of M9 on the agarose pad supplemented with 5 mM tetramisole hydrochloride for immobilization. Images for Figs. 2c, 3b, and 4a, Supplementary Figs. 5g, 6d, and 6e were acquired using a Leica SP8 fluorescence microscope. Z-stack images for Figs. 4b, 4c, 4f and 5d, Supplementary Figs. 5f, 6f, and 6h were obtained using a Nikon Ti2-E inverted microscope (NIS-Elements AR v5.42.06) equipped with Plan Apo VC 20×/0.75 air and 60×/1.2 water objectives. Images were processed in Fiji v2.16 by adjusting brightness and contrast.

Co-localization was quantified in Fiji v2.16. Germline nuclear regions displaying SET-24::GFP signals were extracted from confocal images derived from more than four germlines, with 20 images analysed to calculate co-localization coefficients. Coefficients were determined from multiple confocal planes of the same nucleus. Pearson’s correlation coefficient was used for co-localization analysis, and results are reported in the main text.

SET-24::3XFLAG immunoprecipitation and mass spectrometry
Procedure was conducted as previously described19,50. Wild-type N2 and SET-24::3xFLAG animals were grown at 20oC in HB101 high-density plates synchronized by bleaching and overnight hatching of L1s in M9 buffer. L1s were plated and grown at 20oC for 51–55 h, until the YA stage. At this stage, worms were washed off plates, washed 3-4 times in M9 buffer, washed one last time with deionised water, and snap-frozen on dry ice. To prepare extracts, worm samples were thawed and mixed 1:1 with 2x Lysis Buffer (50 mM Tris/HCl pH 7.5, 300 mM NaCl, 3 mM MgCl2, 2 mM DTT, 0.2 % Triton X-100, and complete EDTA-free Mini protease inhibitors, Roche #11836170001). Lysis was subsequently performed by sonication in a Bioruptor Plus (Diagenode, on high level, 10 cycles of 30 seconds on and 30 seconds off). After sonication, the samples were centrifuged at 21,000 xg for 10 min to pellet cell debris, and the supernatant was transferred to a fresh tube. Protein concentrations were determined with Bradford Protein Assay (according to manufacturer’s instructions, Bio-Rad, #5000006). IPs were prepared in quadruplicates for each strain used. 30 µl of Dynabeads Protein G (Invitrogen, #10003D) were used per IP and washed three times with 1 ml Wash Buffer (25 mM Tris/HCl pH 7.5, 300 mM NaCl, 1.5 mM MgCl2, 1 mM DTT, and complete EDTA-free Mini protease inhibitors, Roche #11836170001). The beads were resuspended in Wash Buffer and combined with to 2 mg of complete protein extract, for a total volume of 500 µl. Finally, 2 µg of anti-FLAG antibody (Sigma-Aldrich, #F1804) were added, and the samples were incubated for 3 h 30 m, rotating at 4°C. After the incubation, the samples were washed five times with 1 ml Wash Buffer, followed by bead resuspension in 1x LDS/DTT, and boiling at 95°C for 10 min.

IP samples were boiled at 70°C for 10 minutes and separated on a 4–12% gradient Bis-Tris gel (Thermo Fisher Scientific, #NP0321) in 1x MOPS (Thermo Fisher Scientific, #NP0001) at 180V for 10 minutes. Then, samples were processed separately, first by in-gel digestion, followed by desalting with a C18 StageTip112,113. Afterwards, the digested peptides were separated on a heated 50-cm reverse-phase capillary (75 µm inner diameter) packed with Reprosil C18 material (Dr. Maisch GmbH). Peptides were eluted along a 90 min gradient from 6 to 40% Buffer B (see Stage Tip purification) with the EASY-nLC 1200 system (Thermo Fisher Scientific). Measurement was done on an Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific) operated with a Top 15 data-dependent MS/MS acquisition method per full scan. Four replicates were performed.

All raw files were processed with MaxQuant114 (version 1.6.5.0) and peptides were matched to the C. elegans Wormbase protein database (version WS269) including E. coli sequences (ASM1798v1). Raw data and detailed MaxQuant settings can be retrieved from the parameter files uploaded to the ProteomeXchange Consortium via the PRIDE repository, accession number PXD057349. Data analysis was completed in R. Statistical significance was assessed using a two-sided unpaired t-test.

Yeast-two hybrid screening
Yeast two-hybrid (Y2H) “prey” library construction, screening, and classification were performed by HYBRiGENiCS SERVICES. For “prey” library construction, mRNAs were purified from ~1 mg of total RNA extracted from mixed-stage C. elegans. The resulting cDNAs were ligated into the pP6 vector containing the LEU3 selectable marker. For “bait” construction, the full-length set-24 open reading frame was cloned into the Gateway pBD-GAL4 vector containing the TRP1 selectable marker. “Bait” and “prey” constructs were transformed into the yeast strain CG1945 and brought together by mating. Positive colonies were selected on dropout media lacking tryptophan, leucine, and histidine, and supplemented with 0.5 mM 3-amino-1,2,4-triazole to suppress weak self-activation by SET-24. Recovered “prey” clones were amplified by PCR, sequenced, annotated, and assigned a Predicted Biological Score (PBS) ranging from very high confidence (A) to lower confidence (D).

Protein purification and pulldown
The coding sequences of HCF-1, SET-24, and the truncations were amplified using cDNA template reversed transcribed from C. elegans total RNA and cloned into the pGEX6p (GST tag) and pMAL (MBP tag) plasmids. The plasmids were transformed into E. coli Rosetta (DE3) cells (Merck, #71403) for expression. The proteins were induced with 0.1 mM IPTG at 16oC for 16-20 h and collected by centrifugation. Rosetta (DE3) cells were resuspended in the purification buffer (50 mM Tris-HCl PH 7.5, 150 mM NaCl, 1 mM DTT, Protease inhibitor, and 1% Triton-X100) and lysed by sonication. The cell lysate was then centrifuged at 20,000 rpm for 20 minutes at 4oC. The supernatant was subjected to affinity purification using GST beads (Cytiva, #17527901) or MBP beads (NEB, #E8022L). Then, the beads were washed three times with washing buffer (50 mM Tris-HCl PH 7.5 and 150 mM NaCl). For the GST-tagged proteins, resuspend the beads with washing buffer + 10% glycerol. For the MBP tagged proteins, the bound proteins were eluted using MBP elution buffer (500 mM maltose, 50 mM Tris-HCl PH 7.5, 500 mM NaCl, and 1 mM DTT), and then dialysed with washing buffer + 10% glycerol. The concentrations of the eluted proteins were measured by Bradford assay (Thermo fisher, #A55866). The beads bound GST tagged proteins and the MBP tagged proteins were aliquoted, flash-frozen in liquid nitrogen, and stored at -80oC.

The GST-tagged proteins were immobilized on GST beads and incubated with MBP-tagged proteins in 500 µl binding buffer (20 mM Tris-HCl PH 7.5, 150 mM KCl, 2 mM MgCl2, 1 mM DTT, 0.01% Triton-X 100, and 5% Glycerol) on a rotator at room temperature for 1 hour. Then, the beads were washed with 1 mL binding buffer for 10 times and boiled with 5x loading buffer. The samples were separated with SDS-PAGE and the proteins were detected with Western blotting.

Western blotting
Synchronized YA stage worms either growing at 20°C or three generations at 25°C were harvested and washed three times with M9 buffer before being frozen at -80°C. Worm proteins were extracted by heating the samples at 95°C for 10 minutes in 1× protein dye (62.5 mM Tris pH 6.8, 10% glycerol, 2% SDS, 5% β-mercaptoethanol, 0.2% bromophenol blue). Samples were then spun at high speed for 1 minute to remove insoluble components, and the supernatant was quickly transferred to a new tube on ice. The samples were either immediately loaded onto a gel or stored at –80°C.

Proteins were separated by SDS-PAGE on gradient gels (10% separation gel, 5% spacer gel) and transferred onto a Hybond-ECL membrane. After washing with 1× TBST buffer (20 mM Tris pH 7.4, 150 mM NaCl, and 0.1% Tween 20) and blocking with 5% milk-TBST or BSA-TBST, the membrane was incubated overnight at 4°C with primary antibodies (listed below). The next day, the membrane was washed three times for 10 minutes each with 1× TBST, followed by incubation with secondary antibodies at room temperature for 2 h. After three additional 10-minute washes with 1× TBST, the signal was visualized.

For gel reblotting, membranes were stripped with strip buffer (62.5 mM Tris pH 6.8, 10% glycerol, 2% SDS, 0.7% β-mercaptoethanol) for 1 h and then washed three times with 1× TBST. The stripped membranes were subsequently blocked with 5% milk–TBST or BSA–TBST and incubated with primary and secondary antibodies as described above.

The primary antibodies used were β-actin (Beyotime, AF5003, 1:1000), H3 (Abcam, ab1791, 1:1000), H3K4me2 (Abcam, ab7766, 1:1000), H3K4me3 (Abcam, ab8580, 1:1000), H3K9me1 (Abcam, ab9045, 1:1000), H3K9me2 (Abcam, ab1220, 1:1000), H3K9me3 (Millipore, 07-523, 1:2000), H3K23me2 (Active Motif, 39653, 1:1000), H3K23me3 (Active Motif, 61499, 1:1000), H3K27me3 (Millipore, 07-449, 1:1000), H3K36me3 (Abcam, ab9050, 1:1000), H3K27Ac (Abcam, ab4729, 1:2000), H3PanAc (Abcam, ab47915, 1:1000), H4PanAc (Abcam, ab177790, 1:1000), H4 (Abcam, ab10158, 1:1000), Tubulin (Abcam, ab6160, 1:3000), FLAG (Sigma, F1804, 1:1000), GFP (Abcam, ab290, 1:1000), GST (Abcam, ab9085, 1:1000), MBP (Abcam, ab49923, 1:1000; Abcam, ab9084, 1:5000). The secondary antibodies used were goat anti-mouse (Beyotime, A0216, 1:5000; Abcam, ab6789, 1:5000), goat anti-rabbit (Abcam, ab205718, 1:20000; Abcam, ab6721, 1:20000), and goat anti-rat (Abcam, ab6734, 1:5000).

In vitro methyltransferase assays
This assay was performed using the non-radioactive MTase-Glo™ Methyltransferase Assay Kit (Promega, V7601). Briefly, purified proteins were incubated with histones (Roche #10223565001) (or non-histone controls) and SAM in reaction buffer (25 mM Tris-HCl pH 8.3, 50 mM KCl, 10 mM MgCl₂, 1 mM DTT, and 0.1 µg/µl BSA). The reactions were then incubated for 1 h at 30°C and terminated by addition of trifluoroacetic acid (TFA) to a final concentration of 0.125%. MTase-Glo reagent and MTase-Glo detection solution were subsequently added, and luminescence was measured following manufacture instructions.

ChIP and ChIP-seq analysis
ChIP protocol was based on a previously published protocol115. Synchronized worms at the YA stage were collected in M9 buffer and rapidly frozen in liquid nitrogen to create worm pellets. The worm pellets were transferred to a metallic grinder that had been pre-cooled in liquid nitrogen for 5 minutes. The worms were ground until broken into small pieces while keeping the nuclei intact. The resulting powder was transferred into a cold 50 mL Falcon tube. The crosslinking was performed on a 40 ml PBS solution containing 1% formaldehyde by shaking at room temperature for 8 minutes. Then, 4.6 mL of 1.25 M glycine was added to quench the reaction, and the mixture was gently shaken for another 8 minutes at room temperature. The sample was washed twice in PBS with protease inhibitor (PI, cOmplete Tablets, Mini EDTA-free, EASYpack, REF #04693159001) and once in FA buffer (50 mM Hepes/KOH pH 7.5, 1 mM EDTA, 1% Triton X-100, 0.1% sodium deoxycholate, and 150 mM NaCl) with PI. The worms were sonicated for 25 cycles of 30 seconds on and 30 seconds off. A 30 µL aliquot was crosslinked to be used as input. The remaining mixture was centrifuged at 4°C for 15 minutes, and the supernatant was transferred into a new tube and frozen at -80oC. The immunoprecipitation was done by adding antibody (2 ug of H3K4me3 antibody, Active Motif, #39159 or H3 antibody, Abcam, #ab1791), then rotated overnight at 4°C. Next, 40 µL of beads (Dynabeads™ Protein A, Invitrogen, REF #10004D) were taken and washed twice with 1 mL of FA+PI. The beads were resuspended in 1 mL of FA+PI+1% BSA+10 µL of tRNA and rotated overnight at 4°C. The beads were washed twice with FA+PI and then transferred into the extract/antibody solution, followed by rotation at 4°C for 2 h. The beads were then washed twice in FA+PI, once in FA with 500 mM NaCl, once in FA with 1 M NaCl, and twice in TEL buffer (0.25 M LiCl, 1% IGEPAL, 1% sodium deoxycholate, 1 mM EDTA, 10 mM Tris-HCl pH 8). The beads were eluted in 60 µL of ChIP elute buffer and incubated at 65°C for 15 minutes. The elution was transferred to a new tube as the IP. For decrosslinking, 2 µL of RNase (Roche, 1119915001) was added, and the mixture was incubated at 37°C for 1.5 h. Finally, 1.5 µL of proteinase K (20 mg/mL, NEB, P8107S) was added, and the mixture was incubated overnight at 65°C for decrosslinking. The DNA was purified from the solution using a PCR purification kit (Invitrogen, K31002).

DNA libraries were prepared and sequenced by Novogene. The purified DNA samples were treated with End Repair Mix (Novogene) and incubated at room temperature for 30 minutes. They were then purified using a PCR purification kit (Qiagen). The DNA was subsequently incubated with A-tailing mix at 37°C for 30 minutes. Next, the 3’-end adenylated DNA was ligated with the adapter in the ligation mix at 20°C for 15 minutes. The adapter-ligated DNA underwent several rounds of PCR amplification and was purified using a 2% agarose gel to recover the target fragments. The average fragment length was assessed using an Agilent 2100 Bioanalyzer (Agilent DNA 1000 Reagents) and quantified by qPCR (TaqMan probe). The libraries were further amplified on a cBot system to generate clusters on the flow cell and sequenced on an Illumina Novaseq X plus system (paired-end 50 base read length).

Adapter sequences were removed using Cutadapt 1.18116 in the pair-ended read mode. Reads were then mapped to the C. elegans genome (WBcel235) using the Burrows-Wheeler Aligner with the MEM algorithm (BWA 0.7.17-r1188)117. Mapped reads were indexed and sorted using Samtools 1.10118. Bam files were filtered with samtools to remove non-unique mappers, secondary alignments and low-quality pairs (MAPQ < 10). Duplicate reads were removed using Picard MarkDuplicates 3.1.0-3119 with the --REMOVE_DUPLICATES option. Peak calling was performed using Macs3 CallPeak (v3.0.0b1)120 with no cutoff (-q 1) and the options --extsize 200 and --nomodel. Differential binding analysis was conducted using DiffBind (v3.12.0)121 in R (v4.3.3) over a 200 bp sliding window with 10 bp shift across the entire genome. Counts were obtained without merging overlapping peaks and without computing summits. Normalization was performed using the DESeq2 method122, accounting for library size, and differential analysis followed DiffBind’s DESeq2 implementation.

BedGraph files displaying enrichment normalized to input for wild-type and set-24 mutants, along with fold-change between set-24 and wild-type enrichment, were generated using a custom Python script with a bin size of 10 bp. Metagene analysis was performed over all protein-coding genes identified in Ensembl’s annotation (release 112) for WBcel235. The average H3K4me3 enrichment at TSS was calculated within a ±500 bp window. Genes contributing to 80% of the total enrichment were selected for further analysis and classified as H3K4me3-enriched genes. All figures were generated using custom Python scripts. Analyses were performed using Python (v3.8.10) with Pandas (v2.0.1)123 for data management, NumPy (v1.23.5)124 for calculations, SciPy (v1.3.3)125 for statistical tests, and Matplotlib (v3.4.3)126 for figure generation.

mRNA-seq and sequencing analysis
mRNAs were purified from total RNA using PolyT oligo-attached beads and converted to cDNAs for library preparation. cDNA libraries were sequenced using a paired-end 150 bp sequencing strategy on an Illumina Novaseq X plus system. Raw reads were assessed for quality using FastQC, Picard Tools, and Samtools along with trimming of poor-quality reads using Trimmomatic (v0.39; paramters: SLIDINGWINDOW:4:20, MINLEN:36, ILLUMINACLIP:TruSeq2-PE.fa:2:30:10)118,127,128. Clean reads were processed to find transcript abundance counts with Salmon (v1.10.2; paramters: --gcBias, --seqBias)129. We used DESeq2 (v1.46.0; padj < 0.01) to identify differentially expressed genes in set-24 mutants compared to the WT122. Statistical significance was assessed using a two-sided unpaired t-test.

small RNA-seq and sequencing analysis
Total RNAs were treated with RppH (NEB #M0356S)130, and small RNA libraries were prepared with a small RNA-seq Kit v4 with UDIs (Nextflex #NOVA-5132-31). Libraries were sequenced using a single-end 50 bp sequencing strategy on a Novaseq 6000 platform. Adapters and reads shorter than 18 nucleotides were removed using CutAdapt v1.15131, with options -a TGGAATTCTCGGGTGCCAAGG --minimum-length 18. The quality of raw and trimmed reads was assessed with fastQC v0.11.9127. Subsequently, 22G-RNAs, defined as all reads between 21 and 23 nucleotides long starting with a G, were isolated. This filtering was conducted using a combination of CutAdapt v1.15131, with options --minimum-length 21 --maximum-length 23, and zcat/awk utilities. 22G-RNAs were mapped to the C. elegans genome (WBcel235) using STAR v2.7.3a132, with options --readFilesCommand zcat --outMultimapperOrder Random --outFilterMultimapNmax 100 --outFilterMismatchNmax 0 --alignIntronMax 1 --outSAMtype BAM SortedByCoordinate --outFilterType BySJout --winAnchorMultimapNmax 100 --alignEndsType EndToEnd --scoreDelOpen -10000 --scoreInsOpen -10000 --outSAMmultNmax 1. Subsequent quantification of counts and differential expression analysis were conducted as previously reported133. In short, featureCounts v2.0.0134 was used to calculate counts mapping to genes (-t exon), using the BAM files produced in the previous STAR alignment step as input. The resulting tables of counts were imported into R, and DESeq2122 and custom scripts (available online135) were used to obtain normalized counts and conduct statistical tests. The following R packages were used: tidyverse136, lattice137, eulerr138, genefilter139, reshape2140, ashr141, GenomicFeatures142. Genes with differentially expressed 22G-RNA levels in set-24(mj617) mutants, defined by fold change > 2 and 5% FDR, were overlapped with known target genes of specific small RNA populations using BioVenn143. Statistical significance was assessed using a two-sided unpaired t-test. We used previously described lists of known target genes144–148.

Generation of genome tracks
bedGraph files with ChIP-sequencing read counts normalized to library size and to input were converted to bigWig format using bedGraphToBigWig v2.8149. Small RNA and mRNA bigwig files and genome tracks were created as previously described133. In short, bigWigs were generated with bamCoverage v3.5.1150, using options --normalizeUsing CPM --binSize 5 (for small RNA) or –binSize 10 (for mRNA) and the BAM files with 22G-RNAs/mRNAs mapped to the C. elegans genome. All the replicates of the same strain, either wild-type N2, set-24(syb7014), or set-24(mj617) mutants, were combined using WiggleTools mean151 and wigToBigWig v4149. Genome tracks were plotted with custom scripts135, on an R framework (R Core Team 2021), using the Gviz152 and GenomicFeatures142 packages.

Statistics and Reproducibility
All experiments were conducted with independent C. elegans animals for the indicated n times. Statistical analysis was performed as indicated in the figure legends.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Overall thoughts\nThis paper identifies and characterizes a new gene (set-24) involved in transgenerational epigenetic inheritance. They start\nwith a bioinformatic analysis of the gene, using a couple of phylogenetic approaches to suggest that its SET domain is most\nlikely non-functional, and to identify two SPK domains. They next show that two different null mutants both display a mortal\ngermline, and are defective in epigentic inheritance – although the defect appears gradually over generations and is not as\nstrong as their control, hrde-1. Using a GFP-fusion protein and qPCR expression analysis they show that SET-24 is present\nin the germline from the mitotic region to the pachytene. They perform some IP-MS experiments which suggest that HCF-1\ninteracts with SET-24, and go on to show that hcf-1 mutants enhance TEI, rather than having a similar defect to set-24.\nFinally, the perform ChIP for H3K4me3, small RNA and mRNA seq on set-24 mutants, and show a relatively small change in\nH3K4me3, which is associated with very minimal mRNA changes, and slightly more sRNA changes. They suggest that\nSET-24 modulates H3K4me3 and 22G levels at a small subset of genes.\nThe work is interesting and the claims made are substantiated by the experiments shown (for the most part, with some small\nexceptions outlined in the specific figure notes below), and will be of interest to the field. But I find that the research opens up\na raft of further questions that must be answered to understand mechanistically how SET-24 functions.\nHow do you think HCF-1 interacts with SET-24? It doesn’t have any HCF-1 binding motifs (Fig 1d), and you didn’t identify\nSET-26 or SET-9 in your pull downs. It would be interesting to extend this analysis – for example: a pull down for SET-24\nyielded HCF-1. If you pulled down HCF-1, do you get SET-24? What are the regions of SET-24 that are required to interact\nwith HCF-1? Can you express SET-24 recombinantly and make various truncations to narrow down the region?\nHCF-1 modulates HDACS, do you see changes in histone acetylation in SET-24 mutants?\nAlong a similar vein, you speculate that the SPK domains may bind dsDNA binding. It would be nice to test this hypothesis,\nagain perhaps by using recombinantly expressed domains. What do you think that the SET domain is doing, if it isn’t a\nmethyltransferase – do you know if it’s important to the function of SET-24, or are other parts of the protein functional instead.\nYou could make mutants in worms and test them in your assays.\nGiven that HCF-1 and SET-24 display opposite phenotypes, yet you have evidence for interaction, what phenotypes do you\nsee in a double mutant in your TEI and mrt assays?\nThe escapees in the mrt assay are fascinating and I was glad to see that you mentioned them in your discussion, and I enjoy\nyour provocative alternative hypothesis. Have you considered characterising the escaped populations further? For example,\nif you take worms from the escaped population, or simply take the entire G10 cohort, and perform various omics analyses to\ncompare them to the P0 population, what do you see? Changes in chromatin state, for example? Or small RNA populations?\nPerforming these experiments would give a clearer idea of the mechanism by which SET-24 acts.\nSpecific notes on figures\nFigure 1d It’s a bit confusing to have ChrII written next to the gene structure, like the allele names are written next to the\nprotein cartoons. Could that be moved elsewhere for clarity? Also, it’s a minor point, but on my version the coloured boxes\nrepresenting the protein domains in the gene locus are tiny and very hard to see. Perhaps this needs to be made a little\nbigger.\nFigure S2C – this is interesting! Do you think that these can bind dsDNA? It would be good to express them recombinantly\nand test in some binding assays/gel shift experiments. Alternatively, could you use alphafold multimer to get some\ncomputational prediction of whether they may bind dsDNA?\nFigure 2a/b It is hard to tell from the methods section and figure legend, whether these experiments were performed with\nbiological replicates (the experiment repeated independently on different days) or whether all the replicates were performed\non the same day. As a small point, it might be worth pointing out in the legend or y axis of 1b that the offspring over only 3\ndays were counted, which is probably (hopefully) why there are less than expected in the wildtype control.\nFig 2c The images of the worms are lovely and clear and really make the point quite nicely… when they are enlarged. I\nwonder if you could shrink the quantification graphs and enlarge your representative images? Or otherwise rejig the figure,\nso that they can clearly be seen when printed.\nFigure 3b In the set-24 strains, you have around ~90-100% GFP silenced worms in the G1 and in the G3 around ~50% of\nsilenced worm. In the G3, you also had ~50% worms with a germline defect (Fig 2c). Can you confirm that the worms that\nhad no GFP expression did actually have a germline, and that they aren’t just GFP negative because they have no\ngermline? I couldn’t see this mentioned anywhere.\nFigure 3c This is an interesting way to try and quantify the GFP expression. What were the RNA samples tested? Were the\npopulations mentioned in the figure legend an entire plate at each generation, or a subset of a plate?\nFig 3d Nice! And interesting... At G1 neither set-24 allele is particularly defective in you visual GFP readout in 3b, nor\ndifferent at the mRNA from WT in 3c, yet for set-24(mf123) at least, the 22G tested is almost at hrde-1 levels. At G4, set-\n24(mj617) appears quite defective at this 22G, but not particularly defective (yet) at the GFP level. There’s a bit of a\ndisconnect here, between 22Gs supposed roles in heritable RNAi and these results, suggesting it’s not quite so clear cut. I\ndo not dispute the summary of the findings in lines 173-175, but perhaps the implications of them aren’t so clear cut.\nFigure 4 Lovely imaging. Given the creation of the GFP tagged strains, are the qRTPCRs in a&b really necessary to include\nin the main figure? Perhaps instead, you could look more closely at the overlap between SET-24::GFP and chromatin? It\nlooks like the DAPI signal and GFP signal overlaps well, but not completely. Could you do some analysis to determine the\namount of overlap/chromatin occupation? What about overlap with the X chromosome, is it consistently excluded (for\nexample)? You also show quite convincingly in the qPCR experiments that the expression of SET-24 is mostly germline\nspecific, but nonetheless, you do see some expression in the glp-4 mutants. It could be useful to look at imaging of the whole\nworm to look at potential other expression of SET-24 (i.e. is it expressed in neurons?)\nRelated to Figure 5 – around Line 250-252 you should probably also include a reference to the Lee lab’s recent paper on\nSET-26 and HCF-1 (already cited elsewhere as ref 61) because this paper has pretty good evidence suggesting a direct\ninteraction between SET-26 and HCF-1\nFigure 6 Here you’ve focused on protein coding genes, but do you see any changes globally? For example, if you call peaks\nin your WT and set-24 experiments, do they mostly overlap? Given the subtle increase in H3K4me3 signal in set-24 mutants,\nperhaps you see an increase in peaks at non-protein coding regions of the genome too?\nIt is difficult to understand how the analysis for determining H3K4me3 enriched genes has been carried out. From reading\nthe methods (lines 685-686) and figure legend, it seems that the H3K4me3 enriched genes have been determined based on\nenrichment over input in WT (i.e. the genes that are targeted by this mark in WT), and then this subset is shown to be further\nenriched in H3K4me3 in set-24 mutants. However, the text in lines 267-269 suggests that the H3K4 me enriched genes (note\ntypo in fig 6a top panel) enrichment was determined in set-24 mutants. Can this please be clarified?\nThe ChIP/mRNAseq/sRNA is performed in whole worms, while SET-24 is expressed in the germline, thus presumably\ndiluting/obscuring the signal. Could you perform these experiments on dissected germlines instead? Or could you take an\nalternative approach and look for changes in H3K4me3 in the germline by IF?\nTypo in 6f – I think the middle panel should read CPM (mRNA) and the bottom panel should be CPM (22G-RNA)", "reviewer_2": "In this manuscript the authors describe a function for SET-24 in the maintenance of transgenerational epigenetic inheritance\n(TEI) through the balance of DNA methylation and small RNA production. They emphasize two major findings that\ndistinguish SET-24 from previously described TEI factors: 1) SET-24 is a methyltransferase that lacks both the canonical\ncatalytic motif and the canonical DNA-binding PHD motif and 2) SET-24 is specifically required for maintenance but not for\nestablishment of TEI responses.\nMajor revisions are needed, specifically to strengthen the link between SET-24 and its actions on chromatin/DNA and to\nclarify how SET-24’s impacts on chromatin/small RNA contribute to the Mrt TEI phenotype.\nMajor points:\nUnfortunately, how SET-24 interacts with DNA seems murky at this point, a major missing link. Not only would an\nunderstanding of this interaction bridge the TEI phenotype to the downstream H3K4me3 and small RNAs mechanisms, it\nalso would provide a new perspective concerning how a catalytically inactive methyltransferase can act to influence\nchromatin state. The authors themselves propose a likely scenario –the SPK (MYB-like) domains participate in ds-telomeric\nDNA binding. The authors should (1) delete/mutate the SPK domains site-specifically and assay TEI; (2) delete/mutate the\nSPK domains site-specifically and check for SET-24 mislocalization from DNA regions using their fluorescently-tagged\nSET-24 strain; and/or (3) add to their AlphaFold data and look at potential DNA-binding conformations of SET-24.\nRelated to the above issue, SET-24 might be associating with HCF-1 to bind DNA (even though they are functional\nopposites phenotypically for TEI). Clarity about how SET-24 and HCF-1 affect each other besides being binding partners\nshould be addressed. Human MLL5 and HCFC1 have previously been shown to be interacting partners, and this fact should\nbe stated explicitly. The relevant citation, #78 is in the References but seems to be describing something else in the text. set-\n24 (lf) and hcf-1 (lf) do not affect each other’s localization as visualized. We recognize that the current reagents for localizing\nboth SET-24 and HCF-1 are both GFP-based, but the 5th paragraph of the main text is subtitled “The SET-24 interactor,\nHCF-1 …” and it is important to bolster this claim by one or more of the following experiments: (1) Imaging both SET-24 and\nHCF-1 at higher resolution to check for co-localization, which should be easily done, perhaps by imaging the HCF-1::GFP\nstrain with an antibody label (using a separate non-GFP green color) against the FLAG on the SET-24::3xFLAG and with\nDAPI to visualize the DNA. (2) SET-24 and HCF-1 are proposed to be interacting partners, yet they are shown to act in\nopposing directions for the TEI phenotype. To clarify how this interaction is regulated, a double mutant should be\nconstructed and tested for TEI or signs of epistasis in the pathway. (3) The authors might also check for the previously\nidentified (in human) HCF-1-binding motif (HBM) site in SET-24 as mentioned in reference #78 and perhaps give more\ninsight into how that motif fits in their AlphaFold models and implications for how the potential HCF-1 binding site interacts\nstructurally with the SET-24 SPK domains that supposedly bind DNA (e.g.,. do they occlude each other sterically, does the\nstructural orientation of the domains inform how the SET-24-HCF-1-DNA complex might work etc.). (4) An in vitro interaction\nassay, e.g., if purified SET-24 (using the FLAG IP) were found to bind HCF-1::GFP (GFP Ab IP) together with purified DNA\nthat would provide evidence for a SET-24-HCF-1-DNA interaction.\nThe H3K4me3 enrichment and any resultant effects on transcription in set-24(lf) mutants compared to wild-type worms\nappear mild. To support their claims that altered H3K4me3 levels and thus chromatin state is what SET-24 is affecting to\nregulate TEI , the authors should compare the levels of H3K4me3 and 22-G RNAs in the G3 set-24(lf) affected lines with\nthose in the “escapee” wild-type-looking lines at G4 to see if H3K4me3 and 22-G RNA levels return to normal. This\nexperiment might link proposed downstream molecular mechanistic effectors of 22G-RNA levels to the organismal Mrt\nphenotype with good (generational) temporal specificity. Such a finding would be of considerable interest given the\nproposed adaptive biological functions of SET-24 discussed in the last paragraph of the paper. Relatedly, such an\nexperiment could also be done with HCF-1 mutants, which show opposing TEI effects, to see if the H3K4me3 and 22G-RNA\nchanges identified in set-24(lf) mutants are corresponding opposed in hcf-1(lf) mutants thus demonstrating mechanistic\nbidirectionality in tying the phenotypic observations of TEI to the molecular players.\nMinor points:\nThe authors should explain why the wild-type responses for depressed GFP-RNAi differ quite dramatically between Fig 3b\n(<10-20% at G7) and Fig 5d (close to 100% at G7)?\nThe authors have presented a comprehensive characterization of the phenotypic TEI consequences of the loss of SET-24.\nThe authors make a case of the striking G3 vs G4 Mrt difference, attributing it to “escapee” takeover of the population. There\nshould be a more detailed population breakdown or description of this rather sharp transition reversal. If one were to pick\nMrt-displaying adult worms with degenerated germlines in G3 and assay their G4 progeny what would be the outcome?\nWould all G4 progeny be sterile/non-viable? As it stands the increase in animals having normal germlines past G4 might be\ndue to reversion or compensation mechanism being activated rather than “escapee” takeover and these scenarios could be\ndistinguished.\nSET-24’s germline-specific expression was previously established (albeit only for L1 stages) by Engert et al. (2018)\n(doi:10.1371/journal.pgen.1007295). Given the emphasis on SET-24 expression in this submitted manuscript, this fact\nshould be explicitly stated and this earlier paper should be cited.\nAre any of the identified WAGO and Mutator genes identified in this paper possible effectors of the Mrt phenotype?\nHave they appeared in screens / sequencing from studies involving the Mrt phenotype?", "reviewer_3": "In this manuscript from Zeng et al, the authors examined a SET-domain containing protein (SET-24) that plays roles in\ngermline immortality and TEI in C. elegans according to their previous published work. The SET domain is typically the\ncatalytic domain of histone methyltransferase. However, the authors showed that SET-24 shares sequence similarity with\nthe scSET3 superfamily members that are catalytic inactive. Therefore, whether SET-24 can methylate histone is unclear.\nInterestingly, SET-24 is expressed in germline lineage of the C.elegans, and is required for germline immortality and\nheritable RNAi, suggesting it plays important roles in epigenetic inheritance. Using IP-Mass Spec and yeast two-hybrid\nassay, the authors show that SET-24 interact with HCF-1, a key component of the COMPASS chromatin remodeling\ncomplex that regulate H3K4me3. The author then examine the role of SET-24 in regulating H3K4me3, mRNA and small\nRNA expression. In set-24 mutant, a mild increase of H3K4me3 is observed at a subset of transcription start sites(TSS), but\nfew corresponding mRNA changes were observed. In contrast, more small RNA changes are seen at these TSS, and these\nsmall RNAs belong to the WAGO and Mutator regulated genes.\nOverall, the manuscript provides strong evidence that SET-24 is required for germline immortality and TEI, offering valuable\ninsight into the field of epigenetic inheritance. However, the modest H3K4me3 changes at a subset of TSS in the set-24\nmutant also raise the questions about whether these loci are direct targets of SET-24/HCF-1(COMPASS complex). The\ngenome-wide analysis (ChIP-seq, mRNA-seq, small RNA-esq) lacks information regarding biological replicates and the\nallele used and requires major revision.\nSpecific comments:\n1. The structure-based phylogenetic analysis supports that key residues involving in catalytic activity in the SET domain are\nmissing in SET-24, SET-9, and SET-26. However, SET-26 has also been reported to have H3K9 HMT activity in vitro\n(PMID: 24685137). It remains possible that these SET domains utilize alternative residues for catalytic function.\n2. The SET-domain of SET-24 appears to end before the 144 a.a. (Fig. 1C, Fig. S1). The set-24 mf123/mj617 allele is\ntruncated after the 188 a.a. . (Fig. 1D). It is not clear if the SET-domain remained in this mutant.\n3. Fig. 4C: SET-24 form puncta in the embryo P-linage. Some SET-24 puncta appear to be cytoplasmic and is enriched in\nPGL-3 foci.\n4. Line 217-222, Fig. S6: ChIP might still work even without clear DNA enrichment. This could be due to higher background\n(since SET-24 only expressed in a subset of germline line cells) or fewer binding sites. Sequencing these samples might\nstill reveal the binding sites.\n5. The detection of HCF-1 in both the IP-MS and Y2H supports an interaction between SET-24 and HCF-1. How many\nbiological replicas were performed for these experiments? Were other COMPASS complex components identified in the IP-\nMS? Including a co-IP validation of SET-24 and HCF-1 would further strengthen the conclusion.\n6. Line 238, Fig5: Is the hcf-1(ok559) mutant a null mutant? More information on this allele is necessary to interpret HCF-1’s\nrole in the fertility assay and heritable RNAi assay.\n7. Which of the two set-24 mutants were used for the H3K4me3 ChIP-seq? Do both set-24 alleles exhibit the same changes\nin H3K4me3 levels? How many biological replicas were included and how are they? The observed H3K4me3 increase at a\nsubset of TSS of set-24 mutant is modest (<20%, based on Fig 6b), raise the question of whether these TSS sites are the\ndirect or indirect target of the SET-24/HCF-1(COMPASS complex).\n8. Similarly, the mRNA-seq and small RNA-seq analyses lack details about which set-24 allele was used and how many\nbiological replicates were performed.\n9. Since SET-24 is germline-specific, how many of the 757 genes showing SET-24-dependent H3K4me3 are also germline\nexpressed? This analysis could help support a direct role for SET-24 in regulating H3K4me3 via HCF-1. Additionally, do the\ngenes with altered small RNA levels in the set-24 mutant also fall into the category of germline-expressed genes?\nMinor comments:\nLine 178: “transcript sand” should be “transcripts and”.\nFigure 6f: Can not find track labels for sRNA-seq or mRNA-seq.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": ""}, {"round": 2, "reviewer_comments": {"reviewer_1": "I would like to commend the authors on the large amount of extra work that they have performed and included in this revised\nmanuscript. Below are some comments on the additions, in the context of what I wrote in my previous review.\nGiven the increased focus on the opposite effect of HCF-1 and SET-24, is the title still appropriate? It does make it sound as\nthough they act in the same way, when actually they have opposite effects on epigenetic memory.\nI'm also still not convinced that the authors have really nailed the mechanism by which SET-24 acts to regulate TEI.\nMy previous main points\n1. How does SET-24 interact with HCF-1? The authors have added a lot of new data to the manuscript to address this point,\nand have shown that the Kelch domain of HCF-1 interacts with the SET domain (and its immediate flanking regions) of SET-\n24. They furthermore show that loss of one protein does not affect the localization of the other, using fluorescent reporter\nstrains.\n2. Do they see changes in histone acetylation in set-24 mutants? They did not see any global changes to histone acetylation\n(although it’s worth noting that they also didn’t see global changes to H3K4me3 by western blot).\n3. Do the SPK domains of H3K4me3 bind DNA as they speculate? The authors recombinantly express the SPK domain and\ntested them in a band shift assay, but did not see any evidence of DNA binding. I appreciate the effort, and acknowledge that\nabsence of evidence is not evidence of absence, so leaving the comment in the Discussion (lines 445-446) is probably OK. I\nstill do think that answering this question would be informative for the mechanism.\n4. What is the SET domain doing? They showed that the SET domain seems to be required for stability of SET-24, as\nmutations in the SET domain in worms could no longer be visualized with the GFP reporter, and protein could no longer be\ndetected by western blot (although mRNA could). This is a good advance to the paper.\n5. What are the phenotypes of hcf-1::set-24 double mutants? They show that in all cases tested (not just the epigenetic\ninheritance assay), double mutants phenocopy hcf-1 mutants, and propose that this is due to HCF-1 having broader roles\nwith other chromatin remodelling complexes. I think these results really highlight the fact that although SET-24 and HCF-1\nseem to be interacting, it’s really not clear how this fits into the broader context of TEI.\n6. What is going on with the escapees? I suggested various ‘omics analyses could be performed. The authors did some\nsmall RNA seq on one population of escapees and showed dysregulation of small RNAs – not included in the manuscript.\nThey also suggest that other experiments are ongoing and will form the basis of a later manuscript. I’m left a bit unsatisfied,\nbut I guess this is OK on balance, give the amount of other data that they’ve added.\n7. Does SET-24 colocalise with chromatin? The authors have addressed this well by doing colocalization analysis with\nH2B::mCherry and tagRFP::SYP-1, and show that SET-24 only partially localises with chromatin. Worth pointing out is the\napparent expression of SET-24 in granules (overlapping partially with PGL-3) in the P3 or P4 cells. This is non-nuclear\n(although still germline)! The authors should comment on this in the text. It might be meaningful for the action of SET-24 in\nthe context of small RNA regulation.\nOther comments\n1. The recombinant proteins used for the in vitro methyltransferase assays are not at all well purified. There are many\ncontaminants in the Coomassie gel (S1a). Can the authors provide more information to prove that that have indeed\nsuccessfully expressed MBP-CeSET-24 and that it is folded correctly? If it isn't folded correctly (or expressed well) this\nwould explain the negative result.", "reviewer_2": "I am satisfied with the alterations the authors have made to the paper and accept their explanations for the limitations in\ncertain proposed experiments as either technically or otherwise beyond the scope of the paper.\nI appreciate the increased clarity about the characterization of SET-24, its strength of interaction with HCF-1 and analysis of\nthe HCF-1 TEI phenotype.\nI have the following specific additional minor comments:\n1) It seems the proposed model is that SET-24 and HCF-1 are acting antagonistically (and coordinately) in a balance to\nmaintain proper (wild-type) heritable RNAi generational duration. In lines 422-423, for example, it would be both clearer and\nmore accurate to explicitly spell out the molecular-phenotypic description with appropriate directionality rather than just\nsaying “required for heritable RNAi,” which could easily be read as HCF-1’s acting in the same direction as SET-24.\n2) SET-24 and HCF-1 act antagonistically in contributing to the TEI phenotype, and hcf-1 single mutants and hcf-1; set-24\ndouble mutants are equivalent in phenotype, i.e. hcf-1 shows “epistasis” not “dominance” to set-24 (line 335). The authors\nmight make explicit in that context the statement about hcf-1’s being downstream of (or parallel to) set-24 in mediating the\nTEI phenotype (similar to the statement in lines 376-377, “suggesting a role for SET-24 in … regulation through HCF-1 …”),\na conclusion that would be a standard interpretation of epistasis. They might further juxtapose those statements with one\nabout the observation that the two are in the same physical complex, and conclude that part of the discussion with their\nproposed molecular model of how the two could act antagonistically while being in a physical complex. Such clarity would\nhelp contextualize the authors’ findings and make a general statement that would highlight the discovery made.\n3) In lines 535 onwards, could the authors clarify their specific hypothesis about the proposed advantage of a mutant set-24\nallele in a wild isolate? A straightforward explanation would be that the Mrt phenotype is an epi-phenomenon and that there\nis a selective advantage under certain environments to some other consequence of reduced set-24 function. The second\nhypothesis (line 547) seems to be a more complicated and perhaps unnecessary take on this general explanation. Also, the\nfirst hypothesis/explanation (line 537) could explain the Mrt “escapees”/reversibility, but I did not understand why Mrt would\nbe beneficial in the first place? If anything, Mrt has a strong direct negative impact on fertility.\n4) In line 306, the authors should clarify “out-of-frame” mutation. “out-of-frame” is not a standard genetic phrase and might be\ninterpreted as “frameshift,” “deletion or insertion causing a frameshift” or other. ok559 seems to be a deletion mutation that\nresults in an early stop codon (and frameshift?). Whatever the nature of ok559, it should be clearly specified in those terms.", "reviewer_3": "In this revision, the authors experimentally demonstrated that SET-24 lacks detectable HMT activity, and provided additional\nevidence for the interaction between SET-24 and HCF-1, as well as the domains required for this interaction. The\nsequencing analysis has been further strengthened and clarified. Overall, the manuscript’s conclusions are substantially\nstronger, and my previous concerns have been satisfactorily addressed.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "Response to reviewers:\nReviewer #1 (Remarks to the Author):\nOverall thoughts\nThis paper identifies and characterizes a new gene (set-24) involved in transgenerational\nepigenetic inheritance. They start with a bioinformatic analysis of the gene, using a\ncouple of phylogenetic approaches to suggest that its SET domain is most likely non-\nfunctional, and to identify two SPK domains. They next show that two different null\nmutants both display a mortal germline, and are defective in epigentic inheritance –\nalthough the defect appears gradually over generations and is not as strong as their\ncontrol, hrde-1. Using a GFP-fusion protein and qPCR expression analysis they show that\nSET-24 is present in the germline from the mitotic region to the pachytene. They perform\nsome IP-MS experiments which suggest that HCF-1 interacts with SET-24, and go on to\nshow that hcf-1 mutants enhance TEI, rather than having a similar defect to set-24.\nFinally, the perform ChIP for H3K4me3, small RNA and mRNA seq on set-24 mutants, and\nshow a relatively small change in H3K4me3, which is associated with very minimal mRNA\nchanges, and slightly more sRNA changes. They suggest that SET-24 modulates\nH3K4me3 and 22G levels at a small subset of genes.\nThe work is interesting and the claims made are substantiated by the experiments shown\n(for the most part, with some small exceptions outlined in the specific figure notes below),\nand will be of interest to the field. But I find that the research opens up a raft of further\nquestions that must be answered to understand mechanistically how SET-24 functions.\nThank you for your comments. Your suggestions have greatly helped us improve our\nmanuscript.\nHow do you think HCF-1 interacts with SET-24? It doesn’t have any HCF-1 binding motifs\n(Fig 1d), and you didn’t identify SET-26 or SET-9 in your pull downs. It would be interesting\nto extend this analysis – for example: a pull down for SET-24 yielded HCF-1. If you pulled\ndown HCF-1, do you get SET-24? What are the regions of SET-24 that are required to\ninteract with HCF-1? Can you express SET-24 recombinantly and make various\ntruncations to narrow down the region?\nIn the revised manuscript, we address this point with additional experimental evidence\n(in Figs. 5, S6, and S7) further dissecting the SET-24-HCF-1 interaction and textual\nchanges (please see lines 268-270, 285-301, and 464-471).\nHCF-1 and SET-24 interact. Now, we have conducted additional in vitro pull-down assays\n(please see Figs. 5c and S6c) that confirm a direct physical interaction between full-\nlength SET-24 and HCF-1.\nFigs. 5c and S6c\nWe went further and mapped the interactions to specific protein domain, using in vitro\npull-down assays. These approaches revealed that residues 1–378 of HCF-1 (mainly\ncontaining the Kelch domain) directly interact with SET-24 (Figs. 5f, 5h, and S7a). All SET-\n24 truncations containing the N-terminal 1–239 region, which includes the SET domain\nand its flanking sequences, bound to the HCF-1 1-378 fragment (Figs. 5g, 5i, S7b, and\nS7c). Interestingly, the SET domain and some of its flanking sequences seem to be\nnecessary for association with HCF-1 (Figs. 5g, 5j, 5k, S7d, S7f).\nTogether, these data suggest the Kelch domain of HCF-1 directly interacts with the\nSET domain of SET-24, with the flanking sequences of the SET domain also\ncontributing to the interaction.\nHCF-1 modulates HDACS, do you see changes in histone acetylation in SET-24 mutants?\nAlthough HDA-1 was pulled down by HCF-1 in IP-MS reported by Emerson et al.1, our IP-\nMS and Y2H assays did not identify any HDACs as interactors of SET-24. We assessed\nglobal histone acetylation levels through western blotting on wild-type, set-24 mutants,\nand hcf-1 mutants. No significant changes in global histone acetylation levels were\nobserved in the mutants (Fig. S9b). Thus, the SET-24-HCF-1 regulatory nexus may work\nindependently of HCF-1’s interactions with HDA-1. We propose that testing whether\nHDACs participate in the SET-24-HCF-1 regulatory nexus is beyond the scope of this\nmanuscript.\nAlong a similar vein, you speculate that the SPK domains may bind dsDNA binding. It\nwould be nice to test this hypothesis, again perhaps by using recombinantly expressed\ndomains.\nThank you for your comments. To better address the comment, we have generated a\nfigure for the reviewer only (see the Revision Fig. 1 below). To address this, we\nestablished a band shift assay using a DNA-binding protein (the tandem helix-turn-helix\ndomains of the Mos1 transposase) and its known DNA target, as positive control2,3. In this\ncase, a clear DNA band shift is observed (Revision Figs. 1a and 1b). We then expressed\nand purified SPK domains in vitro (Revision Figs. 1c and 1d). As the potential direct DNA\ntargets of the SPK domains remain unknown, we tested the ability of the SPK domains to\nbind to several loci exhibiting H3K4me3 changes in set-24 mutants (as defined in Fig. 7a\nand Supplementary table 4; genomic regions amplified by PCR), and additionally to a\nDNA library containing random sequences of the same size. We did not observe band\nshift (Revision Figs. 1e-1g). This suggests that the SPK domains in SET-24 may not bind\nDNA directly. Alternatively, the DNA sequences tested may not be direct targets.\nDeveloping an experimental system to systematically investigate DNA binding by SPK, an\nuncharacterized protein fold with a yet unknown potential DNA target, falls beyond the\ntimeline of this revision and the scope of the paper.\nMOS1-HTH, the two HTH domains of the transposase Mos1 that have known DNA-binding ability.\nb Electrophoretic mobility shift assay (EMSA) demonstrating high-affinity binding of the isolated\nMos1 transposase double-HTH domain to its cognate terminal inverted repeat DNA sequence.\nc Schematic diagram of the GST-tagged constructs with SPK domains of SET-24. d Coomassie\nblue staining of the purified GST-tagged SPK domains. e EMSA of the SPK domains with a mixture\nof 200 bp DNA fragments from H3K4me3-enriched genes. f Schematic of a double-stranded\nnucleic acid pool containing random sequences of fixed length. The single-stranded DNA library,\ncontaining primer binding regions at the 5′ and 3′ ends, was synthesized by IDT. The double-\nstranded DNA pool was then generated by PCR amplification using primers complementary to\nthe binding regions and using the single-stranded DNA library as template. g EMSA of the SPK\ndomains with the random double-stranded DNA pool. The DNA-binding protein MOS1-HTH did\n4\nnot show a band shift with the double-stranded DNA pool, likely due to the insufficient\nrepresentation of the target sequence in the random-sequence DNA pool.\nWhat do you think that the SET domain is doing, if it isn’t a methyltransferase – do you\nknow if it’s important to the function of SET-24, or are other parts of the protein functional\ninstead. You could make mutants in worms and test them in your assays.\nThis is an important question. To address it, the manuscript now includes additional\nexperimental data and textual changes (Figs. 4e-4g, 5f-5k, S5h-S5i, and S7, please see\nlines 233-253 and 285-301).\nAs described above, in the revised version of the manuscript we mapped the regions of\nSET-24 and HCF-1 mediating their interactions (Figs. 5f-5k and S7). The SET domain of\nSET-24 interacts with Kelch domain of HCF-1 in vitro, which suggests a structural role for\nthe SET domain, by providing a platform for interactions with other proteins.\nThen, as you suggested, We generated SET domain mutants in both set-24::gfp and set-\n24::3xflag strains (Figs. 4e and S5h). Specifically, mj673 and mj677 introduce a five–\namino acid substitution within the conserved region of the ScSET3 (mutating RRSCQNN\nto ASASQNA) in set-24::gfp and set-24::3xflag strains. The mj675 mutation deletes a\nsequence spanning both intronic and exonic regions, but remains in-frame, whereas\nmj674 and mj676 introduce frame-shift deletions in set-24::gfp and set-24::3xflag strains,\nrespectively (Figs. 4e and S5h).\nqPCR analysis revealed that set-24 mRNA levels in the point mutants (mj673 and mj677)\nwere comparable to wild-type, whereas the mj675 deletion allele showed reduced\nabundance, likely due to loss of regulatory sequences in an intron (Fig. S5i). Crucially,\nalthough set-24 mRNA levels remain unchanged in set-24(mj673)::gfp and set-\n24(mj677)::3xflag strains, SET-24 protein was undetectable in all three mutants (Figs. 4f\nand 4g). This finding indicates that the SET domain, including a set of residues highly\nconserved in the ScSET3 family, is required for stability of SET-24 protein. The absence\nof protein in these mutants implies that they would behave similar to set-24(mj617) and\nset-24(syb7014) in Mrt and TEI assays (mj617 is a null allele, and syb7014 phenocopies\nmj617).\nWe conclude that the SET domain of SET-24 has a structural role, stabilising SET-24\nprotein and functioning as a platform for interactions with other proteins.\nGiven that HCF-1 and SET-24 display opposite phenotypes, yet you have evidence for\ninteraction, what phenotypes do you see in a double mutant in your TEI and mrt assays?\nIn the revised manuscript, we provide additional experimental data addressing this\n(please see Figs 6a, 6e-6g, and S8c-S8f, and lines 319-333).\nBoth hcf-1 mutants reduced brood size of wild-type worms at 20 °C and are nearly sterile\nat 25 °C within one or two generations, without producing “escapees” (Fig. 6a). This\nphenotype contrasts with that of set-24 single mutants at both 20 °C and 25 °C (Fig. 6a).\nTo answer the reviewer’s comment, we examined the brood size of set-24; hcf-1 double\nmutants and found that their progeny numbers were comparable to those of the hcf-1\nsingle mutants (Fig. 6a).\nFig. 6a\nIn addition, we quantified the inheritance of RNAi silencing of a GFP reporter in set-\n24; hcf-1 double mutants. We silenced heterozygous +/set-24; +/hcf-1 worms\ncarrying the GFP::H2B transgene by feeding gfp dsRNA and monitored silencing\ninheritance in their progeny (including a range of genotypes: wild-type, set-24 or hcf-\n6\n1 single mutants, and set-24; hcf-1 double mutants; see Fig. 6e). Consistent with\nprior observations, silencing was lost more quickly in set-24 single mutants than in\nwild-type animals, whereas it was maintained for more generations in hcf-1 single\nmutants (Figs. 6f and 6g). Importantly, set-24; hcf-1 double mutants also maintained\nsilencing longer than wild-type worms, similar to the hcf-1 single mutants (Figs. 6f\nand 6g). This phenocopying was observed when experiments were repeated using a\ndifferent genetic experimental design (Figs. S8c-S8f).\nFigs. 6e-6g\nWe conclude that set-24; hcf-1 double mutants phenocopy hcf-1 single mutants in terms\nof fertility defects and RNAi inheritance. We propose that the opposite phenotypes of set-\n24 and hcf-1 mutants, and the dominance of the hcf-1 mutant phenotype are due to the\nbroader regulatory roles of HCF-1 in concert with multiple chromatin remodelling\ncomplexes.\nThe escapees in the mrt assay are fascinating and I was glad to see that you mentioned\nthem in your discussion, and I enjoy your provocative alternative hypothesis. Have you\nconsidered characterising the escaped populations further? For example, if you take\nworms from the escaped population, or simply take the entire G10 cohort, and perform\nvarious omics analyses to compare them to the P0 population, what do you see?\nChanges in chromatin state, for example? Or small RNA populations?\nPerforming these experiments would give a clearer idea of the mechanism by which SET-24 acts.\nassay is very intriguing and worth studying. We believe the occurrence of “escapees” is\nan epigenetic effect. Investigating this phenomenon will not only help reveal the\nmechanism by which SET-24 functions, but also provide broader insights into how\nworms can escape environmental stress (high temperature) through epigenetic\nregulation.\nAs you suggested, we have profiled small RNAs in P0 and escaped populations. We\nsequenced 22G-RNAs in wild-type and set-24(syb7014) mutant worms at 25 °C at both\nP0 and G12 generations (the latter expanded from a single G10 “escapee”; four\nreplicates each condition). The 22G-RNA population at G12 (set-24 vs. wild type) differs\nfrom that at P0 under 25 °C conditions (Revision Figs. 2a-2c), suggesting that 22G-RNA\nderegulation plays a role. The genes with deregulated 22G-RNA levels overlap partially\nbetween P0 and G12, in some cases even changing regulation (i.e. from down- to\nupregulated, or vice-versa; see Revision Fig. 2c). Thus, the small RNA deregulation\nassociated with escape of Mrt phenotype is complex.\nRevision Fig. 2 (for the reviewer only) a Plots showing the proportion of small RNAs length\ndistribution profiles, along with information on the first nucleotides in wild-type and set-\n8\n24(syb7014) samples at 25oC P0 or G12 (“escapees” for set-24 mutants), which were treated with\nRppH. b Venn diagrams showing overlap of targets of differentially expressed 22G-RNAs in set-\n24(syb7014) at 25oC P0 and G12 (fold change > 2 and 5% FDR), G12 worms were collected from\nthe “escapees” lines. c Upset plot showing overlap of targets of upregulated- and downregulated\n22G-RNAs in set-24(syb7014) at 25oC P0 and G12.\nBecause of the apparent complexity of the deregulation and stochasticity of the\nphenotype, additional comprehensive analyses are warranted, for example sequencing\nsmall RNAs on a substantially larger number of biological replicates of escapee\npopulations. However, we believe these could be more effectively tackled in a dedicated\nstudy. Indeed, we are planning future studies to investigate how “escapees” arise in set-\n24 mutants growing in high temperature conditions. Given the experimental caveats\nstated above, we plan to perturb the expression of a series of epigenetic factors involved\nin chromatin remodelling and small RNA pathways during a Mrt experiment. This\napproach may help identify which pathways, when disrupted, can block the occurrence\nof “escapees”.\nSpecific notes on figures\nFigure 1d It’s a bit confusing to have ChrII written next to the gene structure, like the allele\nnames are written next to the protein cartoons. Could that be moved elsewhere for clarity?\nAlso, it’s a minor point, but on my version the coloured boxes representing the protein\ndomains in the gene locus are tiny and very hard to see. Perhaps this needs to be made\na little bigger.\nThank you for your comments. We have removed the “ChrII” label and enlarged the\ncoloured boxes in Fig. S3a.\nFigure S2C – this is interesting! Do you think that these can bind dsDNA? It would be good\nto express them recombinantly and test in some binding assays/gel shift experiments.\nAlternatively, could you use alphafold multimer to get some computational prediction of\nwhether they may bind dsDNA?\nAs mentioned earlier, we tested this hypothesis using the available materials and\ntechniques but did not detect direct DNA binding (see Revision Fig. 1). We also used\nAlphaFold3 to model potential interactions between the SPK domains of SET-24 and\ntelomeric repeats, which are typically recognized by related telomere-binding MYB\ndomains. However, no reliable interactions were observed, possibly due to the DNA-\nbinding sequence of MYB domains is not an appropriate proxy for the SPK domains.\nFigure 2a/b It is hard to tell from the methods section and figure legend, whether these\nexperiments were performed with biological replicates (the experiment repeated\nindependently on different days) or whether all the replicates were performed on the\n9\nsame day. As a small point, it might be worth pointing out in the legend or y axis of 1b that\nthe offspring over only 3 days were counted, which is probably (hopefully) why there are\nless than expected in the wildtype control.\nFigure 2a/b were generated from independent experiments performed on different days.\nWe are now clearly specifying this in the figure legend (please see the figure legend of\nFig. 2)\nThe y-axis shows the total number of offspring at 25 °C, and the brood size is consistent\nwith other results (e.g., brood size in Fig. 6a). To make this clearer, we have labelled the\naxis with “25 °C.” Offspring counting began once the progeny reached the L4 stage, and\ncounted offspring were removed using a vacuum pump. Over three consecutive days, all\noffspring from a single worm were counted. We included this information in the methods\nsection (please see lines 634-635).\nFig 2c The images of the worms are lovely and clear and really make the point quite\nnicely… when they are enlarged. I wonder if you could shrink the quantification graphs\nand enlarge your representative images? Or otherwise rejig the figure, so that they can\nclearly be seen when printed.\nThat is a good point. We have enlarged the representative images in Fig.2c.\nFigure 3b In the set-24 strains, you have around ~90-100% GFP silenced worms in the G1\nand in the G3 around ~50% of silenced worm. In the G3, you also had ~50% worms with\na germline defect (Fig 2c). Can you confirm that the worms that had no GFP expression\ndid actually have a germline, and that they aren’t just GFP negative because they have no\ngermline? I couldn’t see this mentioned anywhere.\nThe silencing assay was performed at 20 °C, whereas the Mrt assay was conducted\nat 25 °C. At 20 °C, the brood sizes of set-24 mutants were comparable to those of wild\ntype (Fig. 6a), and the germline appeared generally normal. Consequently, the silenced\nworms in generation 3 (G3, 20 °C) retained a germline.\nFigure 3c This is an interesting way to try and quantify the GFP expression. What were the\nRNA samples tested? Were the populations mentioned in the figure legend an entire\nplate at each generation, or a subset of a plate?\nFor wild-type and set-24 worms, we picked one repressed worm at each generation\n(when available) and extracted RNA from its progeny (entire plate), after setting aside one\nGFP-silenced worm to propagate the next generation. As indicated in the figure legend,\nfive populations (from five plates) were used at each generation as biological replicates\n10\nfor each genotype. For the hrde-1 mutant, we picked derepressed worms starting from\nG1. This information can be found in the methods section (see lines 657-660).\nFig 3d Nice! And interesting... At G1 neither set-24 allele is particularly defective in you\nvisual GFP readout in 3b, nor different at the mRNA from WT in 3c, yet for set-24(mf123)\nat least, the 22G tested is almost at hrde-1 levels. At G4, set-24(mj617) appears quite\ndefective at this 22G, but not particularly defective (yet) at the GFP level. There’s a bit of\na disconnect here, between 22Gs supposed roles in heritable RNAi and these results,\nsuggesting it’s not quite so clear cut. I don’t dispute the summary of the findings in lines\n173-175, but perhaps the implications of them aren’t so clear cut.\nThat’s a very good point. We propose this is likely related to our observations showing\nthat SET-24 affects both chromatin modifications and small RNA biogenesis (Figs 7 and\nS11). Our data suggests that SET-24 contributes to the maintenance of RNAi-induced\nsilencing through regulation of 22G-RNAs, but the slight disconnection between 22G-\nRNA and GFP expression is likely due to the balance of 22G-RNAs plus the chromatin\nlandscape at the GFP reporter locus. We note that the variability between the set-24\nalleles may also reflect slight stochastic differences in levels of 22G-RNAs targeting gfp\nand chromatin landscape deregulation at the GFP reporter locus. We think this\nstochastic variability may have implications in the emergence of escapees at higher\ntemperatures. As discussed above, a deep comprehensive drive into the basis of\nescapee emergence falls beyond the scope of this paper.\nFigure 4 Lovely imaging. Given the creation of the GFP tagged strains, are the qRTPCRs in\na&b really necessary to include in the main figure? Perhaps instead, you could look more\nclosely at the overlap between SET-24::GFP and chromatin? It looks like the DAPI signal\nand GFP signal overlaps well, but not completely. Could you do some analysis to\ndetermine the amount of overlap/chromatin occupation? What about overlap with the X\nchromosome, is it consistently excluded (for example)? You also show quite convincingly\nin the qPCR experiments that the expression of SET-24 is mostly germline specific, but\nnonetheless, you do see some expression in the glp-4 mutants. It could be useful to look\nat imaging of the whole worm to look at potential other expression of SET-24 (i.e. is it\nexpressed in neurons?)\nThank you for your comments. We have moved the qRT-PCR data to the supplementary\nfigures (Fig. S5a and S5b). We agree that examining the overlap between SET-24::GFP\nand H2B is an excellent idea. Using confocal microscopy, we analysed the colocalization\nof SET-24::GFP and H2B::mCherry in the live worms by calculating Pearson’s\ncolocalization coefficient in ImageJ. This analysis showed that SET-24::GFP partially\ncolocalizes with H2B::mCherry in the nucleus (Fig. 4b and 4d). Conversely, the\ncolocalization between SET-24::GFP and tagRFP::SYP-1, a marker of the synaptonemal\n11\ncomplex, is weaker (Fig. 4c and 4d). With this resolution and by imaging live worms, we\ndetected SET-24::GFP signal dispersed throughout germline nuclei, but also within\npuncta. The SET-24 puncta did not colocalize well with H2B::mCherry and tagRFP::SYP-\n1, suggesting that they are not associated with chromosomes (Figs. 4b and 4c). This\nsuggests that there are two pools of SET-24 protein in germline nuclei: one more closely\nassociated with chromatin, and another forming distinct puncta, which do not overlap\nchromosomes. We included this data in the revised manuscript (please see Figs. 4b-4d)\nand adjusted text accordingly (please see lines 223-231).\nFollowing the reviewer’s comment, we also revisited SET-24 expression beyond the\ngermline. Although a small fraction of SET-24 mRNA is detected in germlineless mutants,\nexamination of SET-24::GFP expression throughout the whole worm with an increased\nresolution confirmed that SET-24 is specifically expressed in the germline (Please see Fig.\nS5f and line 216). Specifically, SET-24::GFP is not expressed in neurons.\nRelated to Figure 5 – around Line 250-252 you should probably also include a reference\nto the Lee lab’s recent paper on SET-26 and HCF-1 (already cited elsewhere as ref 61)\nbecause this paper has pretty good evidence suggesting a direct interaction between\nSET-26 and HCF-1.\nThank you for your comment. We have cited this paper accordingly.\nFigure 6 Here you’ve focused on protein coding genes, but do you see any changes\nglobally? For example, if you call peaks in your WT and set-24 experiments, do they\nmostly overlap? Given the subtle increase in H3K4me3 signal in set-24 mutants,\nperhaps you see an increase in peaks at non-protein coding regions of the genome too?\nThank you for your comments. The H3K4me3 peaks identified in WT and set-24 largely\noverlap (Fig. S10a). We observed that approximately 10% of H3K4me3 peaks are\nincreased in the set-24 mutant, indicating that these changes are not global (Fig. S10b).\nAlthough the increased H3K4me3 peaks in set-24 mutants can occur in non-protein-\ncoding regions, such as ncRNAs, the majority (over 60%) are associated with protein-\ncoding genes (Fig. S10c). Therefore, we focused our subsequent analyses on protein-\ncoding genes. (see lines 350-353)\nIt is difficult to understand how the analysis for determining H3K4me3 enriched genes\nhas been carried out. From reading the methods (lines 685-686) and figure legend, it\nseems that the H3K4me3 enriched genes have been determined based on enrichment\nover input in WT (i.e. the genes that are targeted by this mark in WT), and then this subset\nis shown to be further enriched in H3K4me3 in set-24 mutants. However, the text in lines\n12\n267-269 suggests that the H3K4 enriched genes (note typo in fig 6a top panel)\nenrichment was determined in set-24 mutants. Can this please be clarified?\nWe apologize for the confusion. In wild-type worms, H3K4me3 accumulates at the TSS\nof genes. When set-24 is mutated, a subset of these genes, those already marked with\nH3K4me3, show further increases in H3K4me3 levels. We refer to this subset as the\nH3K4me3-enriched genes. Accordingly, we revised lines 267–269 (in the previous version)\nto read: “Importantly, the increase in H3K4me3 was not genome-wide but was\nrestricted to genes with TSSs already marked by H3K4me3 in the wild-types (Fig. 7b).\nWe identified a subset of genes with significantly elevated H3K4me3 levels in set-\n24(syb7014) mutants, hereafter referred to as H3K4me3-enriched genes (Figs. 7a-c).”\nThe revised sentences are now in the lines 355-359.\nThank you for pointing out the typo, we have also corrected it in the Fig. 7a.\nThe ChIP/mRNAseq/sRNA is performed in whole worms, while SET-24 is expressed in the\ngermline, thus presumably diluting/obscuring the signal. Could you perform these\nexperiments on dissected germlines instead? Or could you take an alternative approach\nand look for changes in H3K4me3 in the germline by IF?\nWe agree with the reviewer that the ideal experiments would involve dissected germlines,\nas using whole worms may dilute the signal, particularly for H3K4me3 ChIP. However,\nperforming these sequencing experiments on dissected germlines was not feasible due\nto insufficient material. In any case, by using whole-worm material, we are likely\nunderestimating the potentially greater differences present in the germline.\nTo further validate SET-24’s role in regulating H3K4me3, we measured total H3 levels\nboth globally and at SET-24–regulated H3K4me3-enriched genes in the ChIP-seq. H3\nlevels were unchanged between strains, indicating that the increase in H3K4me3 in set-\n24 mutants represents a genuine modification change rather than altered H3 abundance\n(Figs. S10b and S10e). Comparison with a published germline expression dataset\nrevealed that approximately 90% of the 757 set-24–dependent, H3K4me3-enriched\ngenes are expressed in the germline4 (Fig. S10f), further supporting a role for SET-24 in\nregulating H3K4me3 in the germline, and suggesting that the majority of the differences\nemerge from germline signal. (please see lines 359-367)\nTypo in 6f – I think the middle panel should read CPM (mRNA) and the bottom panel\nshould be CPM (22G-RNA)\nThank you for this point. We have corrected the Fig. 7g accordingly.\nIn this manuscript the authors describe a function for SET-24 in the maintenance of\ntransgenerational epigenetic inheritance (TEI) through the balance of DNA methylation\nand small RNA production. They emphasize two major findings that distinguish SET-24\nfrom previously described TEI factors: 1) SET-24 is a methyltransferase that lacks both\nthe canonical catalytic motif and the canonical DNA-binding PHD motif and 2) SET-24 is\nspecifically required for maintenance but not for establishment of TEI responses. Major\nrevisions are needed, specifically to strengthen the link between SET-24 and its actions\non chromatin/DNA and to clarify how SET-24’s impacts on chromatin/small RNA\ncontribute to the Mrt TEI phenotype.\nThank you for your comments, and we apologize for not clearly highlighting our findings.\nSET-24 contributes to the maintenance of RNAi-induced transgenerational inheritance\nand regulates small RNA (22G-RNA) population and the histone mark H3K4me3, rather\nthan DNA methylation, which is generally thought to be absent in C. elegans5. Unlike\nmembers of the scSET3 subfamily (e.g., HsMLL5, UpSET, CeSET-9/SET-26, ScSET3), SET-\n24 lacks the PHD domain. To our knowledge, the PHD domains in this subfamily\ninteract with histone modifications, particularly H3K4me3, rather than DNA6-9.\nMajor points:\nUnfortunately, how SET-24 interacts with DNA seems murky at this point, a major missing\nlink. Not only would an understanding of this interaction bridge the TEI phenotype to the\ndownstream H3K4me3 and small RNAs mechanisms, it also would provide a new\nperspective concerning how a catalytically inactive methyltransferase can act to\ninfluence chromatin state. The authors themselves propose a likely scenario –the SPK\n(MYB-like) domains participate in ds-telomeric DNA binding. The authors should (1)\ndelete/mutate the SPK domains site-specifically and assay TEI; (2) delete/mutate the SPK\ndomains site-specifically and check for SET-24 mislocalization from DNA regions using\ntheir fluorescently-tagged SET-24 strain; and/or (3) add to their AlphaFold data and look\nat potential DNA-binding conformations of SET-24.\nThank you for your comments. TEBP-1 and TEBP-2 each contain three MYB domains, but\nonly one directly interacts with DNA despite their structural similarity10,11. The SPK\ndomains of SET-24 share high structural similarity with these MYB domains, suggesting\nthey might also bind DNA (Fig. S2c). To address this, we established a band shift assay\nusing a DNA-binding protein (the tandem helix-turn-helix domains of the Mos1\ntransposase) and its known DNA target, as positive control 2,3. In this case, a clear DNA\nband shift is observed (Revision Figs. 1a and 1b). We then expressed and purified SPK\ndomains in vitro (Revision Figs. 1c and 1d). As the potential direct DNA targets of the\nSPK domains remain unknown, we tested the ability of the SPK domains to bind to several\nregions amplified by PCR), or to a DNA library containing random sequences of the same\nsize, but no band shift was observed (Revision Figs. 1e-1g). This suggests that the SPK\ndomains in SET-24 may not bind DNA directly. Alternatively, the DNA sequences tested\nmay not be direct targets.\nRevision Fig. 1 (for the reviewer only) a Coomassie blue staining of purified GST and GST-\nMOS1-HTH, the two HTH domains of the transposase Mos1 that have known DNA-binding ability.\nb Electrophoretic mobility shift assay (EMSA) demonstrating high-affinity binding of the isolated\nMos1 transposase double-HTH domain to its cognate terminal inverted repeat DNA sequence.\nc Schematic diagram of the GST-tagged constructs with SPK domains of SET-24. d Coomassie\n15\nblue staining of the purified GST-tagged SPK domains. e EMSA of the SPK domains with a mixture\nof 200 bp DNA fragments from H3K4me3-enriched genes. f Schematic of a double-stranded\nnucleic acid pool containing random sequences of fixed length. The single-stranded DNA library,\ncontaining primer binding regions at the 5′ and 3′ ends, was synthesized by IDT. The double-\nstranded DNA pool was then generated by PCR amplification using primers complementary to\nthe binding regions and using the single-stranded DNA library as template. g EMSA of the SPK\ndomains with the random double-stranded DNA pool. The DNA-binding protein MOS1-HTH did\nnot show a band shift with the double-stranded DNA pool, likely due to the insufficient\nrepresentation of the target sequence in the random-sequence DNA pool.\nWe also used AlphaFold3 to model potential interactions between the SPK domains of\nSET-24 and telomeric repeats, which are typically recognized by related telomere-\nbinding MYB domains. However, no reliable interactions were observed, possibly due to\nthe DNA-binding sequence of MYB domains is not a good proxy for the SPK domains.\nIn conclusion, given the lack of clear evidence for a potential DNA-binding motif in SET-\n24, we are currently unable to confirm the hypothesis that SPK domains bind DNA in a\nMYB-like manner. Developing an experimental system to systematically investigate DNA\nbinding by SPK, an uncharacterized protein fold with a yet unknown potential DNA target,\nfalls beyond the timeline of this revision and the scope of the paper.\nWe agree that deleting or mutating the SPK domains and examining the resulting Mrt/TEI\nphenotypes and SET-24 localization would be an effective approach. Unfortunately, due\nto time and material constraints, our attempts to generate these mutants have so far\nbeen unsuccessful. As we can’t predict the time required to generate these strains, we\nplan to pursue this line of investigation in future research.\nRelated to the above issue, SET-24 might be associating with HCF-1 to bind DNA (even\nthough they are functional opposites phenotypically for TEI). Clarity about how SET-24\nand HCF-1 affect each other besides being binding partners should be addressed.\nHuman MLL5 and HCFC1 have previously been shown to be interacting partners, and this\nfact should be stated explicitly. The relevant citation, #78 is in the References but seems\nto be describing something else in the text. set-24 (lf) and hcf-1 (lf) do not affect each\nother’s localization as visualized. We recognize that the current reagents for localizing\nboth SET-24 and HCF-1 are both GFP-based, but the 5th paragraph of the main text is\nsubtitled “The SET-24 interactor, HCF-1 …” and it is important to bolster this claim by one\nor more of the following experiments: (1) Imaging both SET-24 and HCF-1 at higher\nresolution to check for co-localization, which should be easily done, perhaps by imaging\nthe HCF-1::GFP strain with an antibody label (using a separate non-GFP green color)\nagainst the FLAG on the SET-24::3xFLAG and with DAPI to visualize the DNA.(2) SET-24\nand HCF-1 are proposed to be interacting partners, yet they are shown to act in\nopposing directions for the TEI phenotype. To clarify how this interaction is regulated, a double\n16\nmutant should be constructed and tested for TEI or signs of epistasis in the pathway. (3)\nThe authors might also check for the previously identified (in human) HCF-1-binding motif\n(HBM) site in SET-24 as mentioned in reference #78 and perhaps give more insight into\nhow that motif fits in their AlphaFold models and implications for how the potential HCF-\n1 binding site interacts structurally with the SET-24 SPK domains that supposedly bind\nDNA (e.g.,. do they occlude each other sterically, does the structural orientation of the\ndomains inform how the SET-24-HCF-1-DNA complex might work etc.). (4) An in vitro\ninteraction assay, e.g., if purified SET-24 (using the FLAG IP) were found to bind HCF-\n1::GFP (GFP Ab IP) together with purified DNA that would provide evidence for a SET-24-\nHCF-1-DNA interaction.\nThank you for your comments. These comments help us a lot to improve our manuscript.\nTo address this comment, the revised version of the manuscript includes additional data\n(Figs. 4b-4d, 5c-5i, 6a, 6e-6g, S6f, S6h, S7, and S8c-S8f), which we will describe in detail\nbelow, and textual changes.\n(1) Using confocal microscopy, we analysed the colocalization of SET-24::GFP and\nH2B::mCherry in live worms by calculating Pearson’s colocalization coefficient in\nImageJ. This analysis showed that SET-24::GFP partially colocalizes with\nH2B::mCherry in the nucleus (Fig. 4b and 4d). Conversely, the colocalization\nbetween SET-24::GFP and tagRFP::SYP-1, a marker of the synaptonemal complex, is\nweaker (Fig. 4c and 4d). With this resolution and by imaging live worms, we detected\nSET-24::GFP signal dispersed throughout germline nuclei, but also within puncta. The\nSET-24 puncta did not colocalize well with H2B::mCherry and tagRFP::SYP-1,\nsuggesting that they are not associated with chromosomes (Figs. 4b and 4c).\nOur original HCF-1::GFP strain from Siu Sylvia Lee’s lab carried a 3×FLAG tag1, making\nit impossible to perform IF staining for SET-24::3xFLAG, HCF-1::GFP::3xFLAG, and\nDAPI simultaneously. Instead, we generated a transgene expressing mKate2-tagged\nHCF-1 in the germline along with a BFP::H2B transgene to label the histone. We then\nexamined colocalization of SET-24::GFP, HCF-1::mKate2, and BFP::H2B in the\ngermline of live worms. As shown in Figs. 5d and 5e, SET-24 and HCF-1 colocalize\nstrongly and both proteins are partially colocalized with H2B.\nWe next examined whether SET-24 and HCF-1 influence each other’s localization\nusing confocal microscopy and found that neither affected each other’s localization\n(Fig. S6h).\nPlease see lines 223-231 and 277-283.\n(2) Both hcf-1 mutants exhibited reduced brood size at 20 °C and are nearly sterile at\n25 °C within one or two generations, without producing “escapees”. We next\nexamined the brood size of set-24; hcf-1 double mutants and found that their progeny\nnumbers were comparable to those of the hcf-1 single mutants. (Fig. 6a)\nIn addition, we quantified the inheritance of RNAi silencing of a GFP reporter in set-\n24; hcf-1 double mutants. We silenced heterozygous +/set-24; +/hcf-1 worms\ncarrying the GFP::H2B transgene by feeding gfp dsRNA and monitored silencing\ninheritance in their progeny (including a range of genotypes: wild-type, set-24 or hcf-\n1 single mutants, and set-24;hcf-1 double mutants; see Fig. 6e). Consistent with prior\nobservations, silencing was lost more quickly in set-24 single mutants than in wild-\ntype animals, whereas it was maintained for more generations in hcf-1 single mutants\n(Figs. 6f and 6g). Importantly, set-24; hcf-1 double mutants also maintained\nsilencing longer than wild-type worms, similar to the hcf-1 single mutants (Figs. 6f\nand 6g). This phenocopying was observed when experiments were repeated using a\ndifferent genetic experimental design (Figs. S8c-S8f).\nWe conclude that set-24; hcf-1 double mutants phenocopy hcf-1 single mutants in\nterms of fertility defects and RNAi inheritance. We propose that the opposite\nphenotypes of set-24 and hcf-1 mutants, and the dominance of the hcf-1 mutant\nphenotype are due to the broader regulatory roles of HCF-1 in concert with multiple\nchromatin remodelling complexes. (Please see lines 321-335)\n(3) SET-24 protein does not encode a sequence identical to HCF-1 binding motif (HBM)\nin human. Now the interaction between human HCF1 and MLL5 is mentioned in the\nrevised manuscript with the relevant reference. (Please see Fig. S2a and lines 285-\n287 and 464-467)\n(4) We used an in vitro pull-down assay to show that SET-24 and HCF-1 physically\ninteract (Figs. 5c and S6c). We went further and mapped the interactions to specific\nprotein domain, using in vitro pull-down assays. These approaches revealed that\nresidues 1–378 of HCF-1 (mainly containing the Kelch domain) directly interact with\nSET-24 (Figs. 5f, 5h, and S7a). All SET-24 truncations containing the N-terminal 1–\n239 region, which includes the SET domain and its flanking sequences, bound to the\nHCF-1 1-378 fragment (Figs. 5g, 5i, S7b, and S7c). Interestingly, the SET domain and\nsome of its flanking sequences seem to be necessary for association with HCF-1\n(Figs. 5g, 5j, 5k, S7d, S7f). Together, these data suggest the Kelch domain of HCF-1\n19\ndirectly interacts with the SET domain of SET-24, with the flanking sequences of the\nSET domain also contributing to the interaction. (Please see lines 268-270 and 285-\n301)\nFigs. 5c\nIn conclusion, we have provided additional microscopy, genetic, and biochemical\nevidence that further solidifies our claim that SET-24 and HCF-1 are bona fide interactors.\nThe H3K4me3 enrichment and any resultant effects on transcription in set-24(lf) mutants\ncompared to wild-type worms appear mild. To support their claims that altered H3K4me3\nlevels and thus chromatin state is what SET-24 is affecting to regulate TEI , the authors\nshould compare the levels of H3K4me3 and 22-G RNAs in the G3 set-24(lf) affected lines\nwith those in the “escapee” wild-type-looking lines at G4 to see if H3K4me3 and 22-G\nRNA levels return to normal. This experiment might link proposed downstream molecular\nmechanistic effectors of 22G-RNA levels to the organismal Mrt phenotype with good\n(generational) temporal specificity. Such a finding would be of considerable interest\ngiven the proposed adaptive biological functions of SET-24 discussed in the last\nparagraph of the paper.\nIn set-24 mutants, we identified a subset of genes with elevated H3K4me3 levels,\nhereafter referred to as H3K4me3-enriched genes. H3 ChIP analyses in wild-type and\nset-24 mutants revealed no global changes in H3 levels, and H3 occupancy at these\nenriched loci was not increased in set-24 (Figs. S10b and S10e). Thus, although the\nelevation of H3K4me3 in set-24 mutants is modest, the increased H3K4me3 signal likely\nreflects the regulatory effects of SET-24 rather than changes in histone abundance.\nApologies for the confusion. We did not claim that the altered H3K4me3 levels and\nchromatin state in set-24 mutants are underlying the TEI defects. SET-24 regulates\nH3K4me3 and thereby modulates chromatin state at a subset of genes, and it also\ninfluences RNAi-induced TEI. However, we agree that our current data are insufficient to\nconclude that H3K4me3 regulation by SET-24 underlies TEI maintenance.\ncould be key to uncover the dynamics of the deregulation in set-24 mutants. We do note\nthat the nature of the Mrt phenotype, with progressive decrease in fertility, makes it hard\nto collect biomass for experiments such as ChIP-sequencing, which require a\nsubstantial amount of biomass, simply not possible to obtain in a Mrt mutant. Likewise,\nit would be challenging to collect enough biomass for ChIP-sequencing experiments in\nthe context of a TEI assay. This intrinsic limitation of the experimental design of these\nassays makes it intractable to profile small RNAs and chromatin in intermediate stages\nof the Mrt experiment where fertility is still in decline and populations dwindle. Even if\nsuch assays were possible in Mrt worms, another confounding factor would be the\ngermline/somatic signal in whole worms. This is because Mrt worms display atrophied or\nseverely reduced germlines, while P0/escaped worms have healthy germlines (see Fig.\n2c). Therefore, the viable option we embarked on for the time being was to profile small\nRNAs in P0 and escaped populations.\nWe sequenced 22G-RNAs in wild-type and set-24(syb7014) mutant worms at 25 °C at\nboth P0 and G12 generations (the latter expanded from a single G10 “escapee”; four\nreplicates each condition). The 22G-RNA population at G12 (set-24 vs. wild type) differs\nfrom that at P0 under 25 °C conditions (Revision Figs. 2a-2c), suggesting that 22G-RNA\nderegulation plays a role. The genes with deregulated 22G-RNA levels overlap partially\nbetween P0 and G12, in some cases even changing regulation (i.e. from down- to\nupregulated, or vice-versa; see Revision Fig. 2c). Thus, the small RNA deregulation\nassociated with escape of Mrt phenotype is complex.\nBecause of the apparent complexity of the deregulation and stochasticity of the\nphenotype, additional comprehensive analyses are warranted, for example sequencing\nsmall RNAs on a substantially larger number of biological replicates of escapee\npopulations. However, we believe these could be more effectively tackled in a dedicated\nstudy. Indeed, we are planning future studies to investigate how “escapees” arise in set-\n24 mutants growing in high temperature conditions. Given the experimental caveats\nstated above, we plan to perturb the expression of a series of epigenetic factors involved\nin chromatin remodelling and small RNA pathways during a Mrt experiment. This\napproach may help identify which pathways, when disrupted, can block the occurrence\nof “escapees”.\ndistribution profiles, along with information on the first nucleotides in wild-type and set-\n24(syb7014) samples at 25oC P0 or G12 (“escapees” for set-24 mutants), which were treated with\nRppH. b Venn diagrams showing overlap of targets of differentially expressed 22G-RNAs in set-\n24(syb7014) at 25oC P0 and G12 (fold change > 2 and 5% FDR), G12 worms were collected from\nthe “escapees” lines. c Upset plot showing overlap of targets of upregulated- and downregulated\n22G-RNAs in set-24(syb7014) at 25oC P0 and G12.\nRelatedly, such an experiment could also be done with HCF-1 mutants, which show\nopposing TEI effects, to see if the H3K4me3 and 22G-RNA changes identified in set-24(lf)\nmutants are corresponding opposed in hcf-1(lf) mutants thus demonstrating\nmechanistic bidirectionality in tying the phenotypic observations of TEI to the molecular\nplayers.\nhcf-1 mutants exhibit reduced brood size at 20 °C and become nearly sterile at 25 °C\nwithin one or two generations, without producing “escapees” (Fig. 6a). Consequently,\nanalysing small RNAs or histone modifications at 25 °C is not feasible. HCF-1 interacts\n22\nnot only with SET-24 but also with multiple chromatin remodelling complexes, including\nthe COMPASS complex and the H3K4me3 methyltransferase SET-2. Therefore, while\nalterations in H3K4me3 levels are expected in hcf-1 mutants, the function of HCF-1 is\nlikely broader and not limited to its interaction with SET-24. Therefore, while\nalterations in H3K4me3 levels are expected in hcf-1 mutants, the function of HCF-1 is\nlikely broader and not limited to its interaction with SET-24.\nAs suggested, we sequenced 22G-RNAs in hcf-1 mutants at 20 °C (Figs. S11b, S11f, and\nS11g). In both set-24(syb7014) and hcf-1(pk924) mutants, 22G-RNA populations were\naltered, with more 22G-RNAs upregulated than downregulated (Fig. S11b). A subset of\n22G-RNAs was regulated by both hcf-1 and set-24; however, most were regulated by only\none gene, particularly hcf-1, despite the direct interaction between HCF-1 and SET-24\nand their shared contribution to TEI (Fig. S11f). This likely reflects HCF-1’s broader\ninteraction network with multiple chromatin remodelling complexes, which may also\naffect small RNA regulation. Within the subgroup of 22G-RNAs regulated by both hcf-1\nand set-24, some (94/269) were affected in opposite directions, but the majority\n(175/269) were not (Fig. S11g). These findings suggest that the opposing phenotypes of\nhcf-1 and set-24 cannot be explained solely by shared 22G-RNA targets, but instead may\ninvolve additional mechanisms, such as interactions between HCF-1 and other factors.\nWe plan to further investigate how HCF-1 inhibits the maintenance of silencing in future\nstudies. (please see lines 396-403)\nFig. S11b\nFigs. S11f and S11g\nThe authors should explain why the wild-type responses for depressed GFP-RNAi differ\nquite dramatically between Fig 3b (<10-20% at G7) and Fig 5d (close to 100% at G7)?\nThank you for your comments. We apologize for not making it clear.\nFor Fig. 3b, germline nuclear GFP brightness was scored by visual inspection as 1\n(“bright”) or 0 (“dark”), with dim GFP expression also classified as 0. For all other figures\ncontaining GFP RNAi inheritance assays, including Fig. 5d from the previous submission\n(now Figs. 6c, 6d, 6f, 6g, S8a, and S8c–S8f), nuclear GFP brightness was assessed\nvisually by a different team member, with “bright” scored as 1, “dark” scored as 0, and\n“dim” scored as 0.5. This scoring of “dim” may contribute to differences observed in\nwild-type samples across figures. This clarification has been added to the Methods\nsection, see lines 647-652. We note that the phenotype of the mutants relative to wild-\ntype controls is consistent across experiments, despite distinct scoring strategies,\nhighlighting the robustness of our results.\nIn addition, the duration of inheritance is influenced by factors such as the strength of\nthe initial RNAi trigger, the bacterial strain used for feeding, and other unknown\nenvironmental variables. The GFP RNAi inheritance assays for wild-type animals shown\nin different figures were conducted at different times. Although we attempted to maintain\nconsistent experimental conditions, the baseline of the RNAi response often differs.\nHowever, the wild-type controls we include in each experiment allow for adequate, direct,\nand internal comparison with the mutant strains in the same experiment. While the\nbaseline differs between experiments, the mutant effects versus wild-type controls are\nconsistent across all the experiments.\nAltogether, we are confident that our conclusions remain robust.\nThe authors have presented a comprehensive characterization of the phenotypic TEI\nconsequences of the loss of SET-24. The authors make a case of the striking G3 vs G4 Mrt\ndifference, attributing it to “escapee” takeover of the population. There should be a more\ndetailed population breakdown or description of this rather sharp transition reversal. If\none were to pick Mrt-displaying adult worms with degenerated germlines in G3 and assay\ntheir G4 progeny what would be the outcome? Would all G4 progeny be sterile/non-viable?\nAs it stands the increase in animals having normal germlines past G4 might be due to\nreversion or compensation mechanism being activated rather than “escapee” takeover\nand these scenarios could be distinguished.\nincluded a schematic (Fig. S3b) illustrating how defective germlines were scored. For\neach generation, more than 30 worms were examined, sampled evenly from\nindependent lines rather than from chunked plates. In Fig. 2c, by G3, most plates were\nnearly sterile or displayed sterility tendency, and consequently, the majority of worms\nsampled exhibited defective germlines. From G4 onward, however, many plates\ncontained escapee lines, and most worms sampled displayed normal germlines.\nImportantly, our observations indicate that Mrt-phenotype worms (such as those\nwith defective or absent germlines) from G3 retained their phenotype when\npropagated to G4 and beyond, ultimately becoming sterile.\nFig. S3b\nSET-24’s germline-specific expression was previously established (albeit only for L1\nstages) by Engert et al. (2018) (doi:10.1371/journal.pgen.1007295). Given the emphasis\non SET-24 expression in this submitted manuscript, this fact should be explicitly stated\nand this earlier paper should be cited.\nThank you for your comments. We have cited the paper accordingly in lines 202-203.\nAre any of the identified WAGO and Mutator genes identified in this paper possible\neffectors of the Mrt phenotype? Have they appeared in screens / sequencing from studies\ninvolving the Mrt phenotype?\nThank you for your comments. From our small RNA sequencing data (Figs. 7e and S11d),\nwe found that set-24 regulates the population of 22G-RNAs, and the 22G-RNAs regulated\n25\nby set-24 largely overlap with WAGO- and Mutator-class target genes, which have\npreviously been reported to be regulated by WAGOs and Mutator factors12-16. To be clear,\nthese target genes are not WAGO or Mutator genes themselves.\nWe generated lists of overlapping genes between set-24-regulated 22G-RNA targets and\nWAGO- or Mutator-class 22G-RNA targets (Supplementary Table 7). We then manually\nexamined the observed RNAi and allele phenotypes associated with these genes using\nWormbase Simplemine (https://wormbase.org/tools/mine/simplemine.cgi), but we did\nnot identify any factors involved in Mrt or TEI regulation. In conclusion, while we cannot\nfully exclude that SET-24 regulates a Mrt effector, our data does not provide any\nsupporting evidence for this.\nIn this manuscript from Zeng et al, the authors examined a SET-domain containing\nprotein (SET-24) that plays roles in germline immortality and TEI in C. elegans according\nto their previous published work. The SET domain is typically the catalytic domain of\nhistone methyltransferase. However, the authors showed that SET-24 shares sequence\nsimilarity with the scSET3 superfamily members that are catalytic inactive. Therefore,\nwhether SET-24 can methylate histone is unclear. Interestingly, SET-24 is expressed in\ngermline lineage of the C.elegans, and is required for germline immortality and\nheritable RNAi, suggesting it plays important roles in epigenetic inheritance. Using IP-Mass Spec\nand yeast two-hybrid assay, the authors show that SET-24 interact with HCF-1, a key\ncomponent of the COMPASS chromatin remodeling complex that regulate H3K4me3.\nThe author then examine the role of SET-24 in regulating H3K4me3, mRNA and small\nRNA expression. In set-24 mutant, a mild increase of H3K4me3 is observed at a subset of\ntranscription start sites(TSS), but few corresponding mRNA changes were observed. In\ncontrast, more small RNA changes are seen at these TSS, and these small RNAs belong\nto the WAGO and Mutator regulated genes.\nOverall, the manuscript provides strong evidence that SET-24 is required for germline\nimmortality and TEI, offering valuable insight into the field of epigenetic inheritance.\nHowever, the modest H3K4me3 changes at a subset of TSS in the set-24 mutant also\nraise the questions about whether these loci are direct targets of SET-24/HCF-\n1(COMPASS complex). The genome-wide analysis (ChIP-seq, mRNA-seq, small RNA-esq)\nlacks information regarding biological replicates and the allele used and requires major\nrevision.\nThank you for your comments. We added all the information about biological replicates\nand the allele information we are using.\nSpecific comments:\n1. The structure-based phylogenetic analysis supports that key residues involving in\ncatalytic activity in the SET domain are missing in SET-24, SET-9, and SET-26. However,\nSET-26 has also been reported to have H3K9 HMT activity in vitro (PMID: 24685137). It\nremains possible that these SET domains utilize alternative residues for catalytic\nfunction.\nThank you for your comments. To experimentally examine whether SET-24 is catalytically\nactive, we tested the methyltransferase activity of SET-24 on histones in vitro using a\nwell-established non-radioactive methyltransferase assay (Fig. 1d). We purified MBP-\ntagged full-length C. elegans SET-24 (CeSET-24) and S. cerevisiae SET2 (ScSET2), an\nactive H3K36me3 methyltransferase, as a positive control17,18 (Fig. S1a). While the assay\n27\nconfirmed a robust methyltransferase activity of ScSET2, CeSET-24 did not exhibit\nactivity on any of the four core histones in our assay (Fig. 1e). We conclude that SET-24\nlacks detectable histone methyltransferase activity. (please see lines 114-120).\nFigs. 1d and 1e\nFor the other SET factors that lack the canonical residues required for the\nmethyltransferase activity, as mentioned in the manuscript, we describe them as “likely\ncatalytically inactive”. (Please see lines 120-123)\n2. The SET-domain of SET-24 appears to end before the 144 a.a. (Fig. 1C, Fig. S1). The set-\n24 mf123/mj617 allele is truncated after the 188 a.a. . (Fig. 1D). It is not clear if the SET-\ndomain remained in this mutant.\nThank you for pointing this out, we apologize for this lapse.\nIndeed, the mf123/syb7014 allele carries a premature stop codon located after the SET\ndomain. We have updated the schematic in Fig. S3a accordingly. Although the SET\ndomain is still present, we note that it is very likely that it is not expressed, as set-\n24(mf123) and set-24(syb7014) phenocopy the null allele set-24(mj617).\n3. Fig. 4C: SET-24 form puncta in the embryo P-linage. Some SET-24 puncta appear to be\ncytoplasmic and is enriched in PGL-3 foci.\nThat is a good point. We have updated the text accordingly in lines 220-221, “In embryos,\nSET-24::GFP was solely expressed in germline-lineage cells (Fig. 4a).”\n4. Line 217-222, Fig. S6: ChIP might still work even without clear DNA enrichment. This\ncould be due to higher background (since SET-24 only expressed in a subset of germline\nline cells) or fewer binding sites. Sequencing these samples might still reveal the binding\nsites.\nto identify SET-24's binding sites. We had sequenced the SET-24 ChIP products,\nnevertheless none or extremely low throughputs were obtained. We conclude that either\nunknown technical aspects affected the pulldown or SET-24 does not stably associate\nwith chromatin.\n5. The detection of HCF-1 in both the IP-MS and Y2H supports an interaction between\nSET-24 and HCF-1. How many biological replicas were performed for these experiments?\nWere other COMPASS complex components identified in the IP-MS? Including a co-IP\nvalidation of SET-24 and HCF-1 would further strengthen the conclusion.\nThank you for your comments. The revised manuscript includes additional GST-pulldown\nassay data strengthening our conclusion (Figs. 5c, 5f-5k, S6c, and S7, please see lines\n268-270 and 285-301).\nPlease note that HCF-1 was identified in both approaches, which significantly\nstrengthens the credibility of the result. The Y2H experiment was performed by\nHYBRiGENiCS SERVICES (https://www.hybrigenics-services.com) under their standard\nquality controls. The IP-MS was done through label-free quantification, using IPs from\nfour biological replicates of wild-type and SET-24::3xFLAG strains. This approach was\nused extensively in similar IPs of FLAG-tagged proteins from C. elegans samples, yielding\nreproducible results10,12,19. The relevant information has been included in the\ncorresponding methods (Please see the lines 753 and 761-774). In both IP-MS and Y2H\nscreenings, we did not detect other COMPASS components.\nWe further performed in vitro pull-down assays and confirmed that SET-24 directly\ninteracts with HCF-1 in vitro (Figs. 5c and S6c). In addition, we identified specific regions\nof SET-24 and HCF-1 that mediate their interaction (Figs. 5f-5k and S7). Altogether, the\nIP-MS, Y2H, and in vitro pull-down data clearly indicate that SET-24 and HCF-1\ninteract directly.\nFig. 5c\n29\n6. Line 238, Fig5: Is the hcf-1(ok559) mutant a null mutant? More information on this\nallele is necessary to interpret HCF-1’s role in the fertility assay and heritable RNAi assay.\nThank you for your comment. hcf-1(ok559) is not a null mutant but carries an in-frame\ndeletion in the Kelch domain and the hcf-1(ok559) mutants could still express truncated\nHCF-1 in vivo20. We have included the allele information of hcf-1 in Fig. S6g. (Also see the\nlines 305-307)\nTo further validate the phenotypes observed in hcf-1(ok559), we used an alternative hcf-\n1 allele, hcf-1(pk924), to perform the Mrt and TEI assays. As shown in Figs. 6a-d and S8b,\nboth hcf-1 alleles exhibit very similar phenotypes, indicating that the Kelch domain of\nHCF-1 plays an essential role in viability and TEI maintenance. In fact, the revised\nmanuscript includes new data with the identification of the Kelch domain as the domain\nresponsible for interaction with SET-24 (Figs. 5h and S7a). Thus, the in-frame deletion of\nthe Kelch domain is a relevant model to study the roles of HCF-1 in relation to SET-24\nregulation.\n7. Which of the two set-24 mutants were used for the H3K4me3 ChIP-seq? Do both set-\n24 alleles exhibit the same changes in H3K4me3 levels? How many biological replicas\nwere included and how are they? The observed H3K4me3 increase at a subset of TSS of\nset-24 mutant is modest (<20%, based on Fig 6b), raise the question of whether these\nTSS sites are the direct or indirect target of the SET-24/HCF-1(COMPASS complex).\nThank you for your comments! We used set-24(syb7014) for the H3K4me3 ChIP-seq and\nprepared three replicates each for wild type and set-24(syb7014) for sequencing.\nHowever, one of the H3K4me3 ChIP fails in the library preparation. Therefore, in Fig. 7,\nthere are two replicates for set-24(syb7014) and wild-type. This information has been\nadded to the corresponding figures (Please see the figure legend of Figs. 7a and S10b).\nWe did not perform H3K4me3 ChIP-seq for both set-24 alleles, as they exhibit very similar\nphenotypes.\nSince the direct or indirect DNA targets of SET-24, as well as the DNA targets of germline\nHCF-1, remain unknown, we were unable to compare the H3K4me3-enriched genes with\nSET-24 or germline HCF-1 targets. We acknowledge this as a limitation of our study and\nhope to address it in future research.\n8. Similarly, the mRNA-seq small RNA-seq analyses lack details about which set-24\nallele was used and how many biological replicates were performed.\nlegends. (Please see the figure legend of Figs. 7d, 7e, S11a, and S11c)\nFor the mRNA-seq, we used the set-24(syb7014) allele with four replicates for each\nstrain. For the small RNA-seq, we used both set-24(syb7014) and set-24(mj617) alleles,\nwith four replicates for each strain. Each mutant had its own corresponding wild-type\ncontrols, collected at the same time. For set-24(syb7014) and its wild-type controls, the\nsamples were the same as those used for mRNA-seq. Although the syb7014 allele\nshowed stronger deregulation of 22G-RNAs, the profiles of the two alleles correlated well\n(Figs. S11c) and showed similar overlaps with WAGO and Mutator targets (Figs. 7e and\nS11d).\nIn our first submission, we used set-24(mj617) for the small RNA analysis. To maintain\nconsistency across the H3K4me3 ChIP-seq, mRNA-seq, and small RNA-seq datasets, in\nthe revised manuscript we placed the mj617 small RNA data in the supplement Figs\nS11d, and the syb7014 allele data in Figs. 7f and 7g. (Also see the lines 387-389)\n9. Since SET-24 is germline-specific, how many of the 757 genes showing SET-24-\ndependent H3K4me3 are also germline expressed? This analysis could help support a\ndirect role for SET-24 in regulating H3K4me3 via HCF-1. Additionally, do the genes with\naltered small RNA levels in the set-24 mutant also fall into the category of germline-\nexpressed genes?\nThank you for your comments. To assess the germline expression of the 757 set-24-\ndependent H3K4me3-enriched genes, we intersected them with a published dataset of\ngermline-expressed genes4. Our analysis revealed about 90% of set-24(syb7014)-\ndependent H3K4me3-enriched genes and approximately 60% of set-24(syb7014)-\nregulated 22G-RNA targets are expressed in the germline (Figs. S10f and S11e). This\nindicates that the deregulation of H3K4me3 and 22G-RNAs in set-24 mutants has a\nstrong germline signal. (please see the lines 364-367 and 396-399)\nMinor comments:\nLine 178: “transcript sand” should be “transcripts and”.\nFigure 6f: Can not find track labels for sRNA-seq or mRNA-seq.\nThank you for pointing these out. We updated the texts and figures accordingly. (Please\nsee the line 185).\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nThank you!\nReference\n1. Emerson, F.J. et al. The chromatin factors SET-26 and HCF-1 oppose the histone\ndeacetylase HDA-1 in longevity and gene regulation in C. elegans. Nat Commun\n15, 2320 (2024).\n2. Almeida, M.V. et al. Transposable Elements Drive Regulatory and Functional\nInnovation of F-box Genes. Mol Biol Evol 42(2025).\n3. Richardson, J.M., Colloms, S.D., Finnegan, D.J. & Walkinshaw, M.D. Molecular\narchitecture of the Mos1 paired-end complex: the structural basis of DNA\ntransposition in a eukaryote. Cell 138, 1096-108 (2009).\n4. Ortiz, M.A., Noble, D., Sorokin, E.P. & Kimble, J. 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Amplification of siRNA in Caenorhabditis elegans generates a\ntransgenerational sequence-targeted histone H3 lysine 9 methylation footprint.\nNat Genet 44, 157-64 (2012).\n17. Du, H.-N., Fingerman, I.M. & Briggs, S.D. Histone H3 K36 methylation is mediated\nby a trans-histone methylation pathway involving an interaction between Set2\nand histone H4. Genes & Development 22, 2786-2798 (2008).\n18. Strahl, B.D. et al. Set2 Is a Nucleosomal Histone H3-Selective Methyltransferase\nThat Mediates Transcriptional Repression. Molecular and Cellular Biology 22,\n1298-1306 (2023).\n19. Marnik, E.A. et al. The Caenorhabditis elegans TDRD5/7-like protein, LOTR-1,\ninteracts with the helicase ZNFX-1 to balance epigenetic signals in the germline.\nPLOS Genetics 18(2022).\n20. Lee, S. et al. Epigenetic regulation of histone H3 serine 10 phosphorylation\nstatus by HCF-1 proteins in C. elegans and mammalian cells. PLoS One 2, e1213\n(2007).\n34"}]

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