Avalilação PREreview de A novel class of tiny box C/D-like RNAs reveals hidden complexity in the mouse box C/D RNA repertoire

Peer review report:

Caetano et al., investigate the diversity of mammalian box C/D small nucleolar RNAs (SNORDs) by combining Fibrillarin- and Snu13-associated RNA sequencing with extensive analysis of publicly available datasets. They identify 21,732 candidate loci, including a large population of unusually short single-stranded RNAs (20-50 nt), termed tiSNORDs. This work is important because it challenges the current annotation of the mammalian snoRNAs and raises fundamental questions about snoRNP biogenesis and the emergence of regulatory RNAs. Particularly convincing are the enrichment of characteristic box C/D sequence signatures, the association of selected candidates with Fibrillarin, and the demonstration that a 36-nt tiSNORD can guide RNA methylation. The observations concerning terminal stem structures, RNA stability and host-gene expression provide further support for the biological relevance of at least a subset of these RNAs.

Therefore, the study is interesting and potentially significant. Addressing several methodological and interpretative concerns , particularly regarding library-preparation biases, statistical validation of candidate identification, and the distinction between mature RNAs and RNA fragments would strengthen claims and introduce reproducibility.

Major points:

1. RNA library preparation and size-selection bias. Approximately ~70 % of tiSNORDs are 20-50 nt long, yet the size-selection used with the TruSeq small RNA library preparation kit is not specified. Size-dependent recovery and sequence-dependent ligation biases could substantially influence this distribution. The authors acknowledge such biases for SNORD50 and substantial technical variability between datasets. Clarification of the selected insert range and, ideally, independent analysis of RNAs across a broader size range would strengthen this central conclusion. One would be to use splint-ligation library preparation to get ‘unbiased’ small RNA library for sequencing (e.g. Maguire et al., 2020; PMID: 32496547).

2. Statistical validation of sequence signatures. The identification of tiSNORDs relies heavily on canonical C/D-box motifs, their terminal positions and uridine enrichment (Figures 1C to 1G). However, no explicit null model accounts for the search criteria, meaning that some positional enrichment is expected by construction. Small RNA-seq ligation biases may also influence nucleotide frequencies (Kim et al., 2019; PMID: 30605524). Permutation analyses using length- and composition-matched intronic sequences processed through the same pipeline would help ensure statistical significance and estimate false-positive rates. Potential spike ins would be of use as well.

3. Distinguishing mature tiSNORDs from RNA fragments. Although the authors demonstrate stable endogenous expression of tiSNORD candidate and successful processing of selected ectopically expressed candidates, these findings cannot necessarily be extrapolated to thousands of low-abundance sequences. Examining coverage across candidate loci, overlapping fragments, flanking regions and potential longer precursors would help distinguish independently matured tiSNORDs from RNA processing or degradation/fragmentation products.

4. Confidence in the proposed repertoire. 12% of candidates exceed one count per million, and substantial discrepancies are observed between independent datasets (Supplementary Figure 3). The authors appropriately acknowledge these limitations further in the text, but the claim that more than 20,000 loci substantially expand the snoRNA repertoire is a potential since it does not have biochemical validation and mentioning that they are ”putative” in the abstract would help the reader to understand the scope of this article. Stratification by abundance, reproducibility and independent experimental evidence would provide a more reliable high-confidence catalogue.

5. Novelty relative to previously characterized snoRNA fragments. Short functional box C/D RNAs have previously been demonstrated (Deryusheva and Gall, 2019; PMID: 30301832), while snoRNA-derived fragments have been extensively described (Taft et al., 2009; PMID: 19474147). Although the authors acknowledge earlier studies of truncated snoRNAs and mini box C/D-like RNAs, a more systematic discussion with previously characterized fragments would help establish whether tiSNORDs represent a distinct endogenous RNA class or an expanded population of processing products.

Minor points:

1. Reporting the proportion of complete RNA inserts and adapter-trimmed reads in the Methods would be of great interest to see gene/transcript coverage from both read directions and also to see rat conservation for 10 % of the 100 most abundant tiSNORDs, this would be of interest to see if these elements have similar biogenesis route.

2. Figure 4 demonstrates methylation of an engineered Polymerase I substrate. This is an important proof of principle, but endogenous methylation activity remains to be established. The authors could mention this early in their manuscript and clearly mention the limitations of tiSNORD being a functional RNA class, with their future directions that will validate their biological effects.

3. 3 termini of ectopically expressed tiSNORDs could be characterized alongside the 5-termini mapping shown in Figure 4B, to show overall coverage for tiSNORDs and see biases.

I am one of two participants from the same research lab that reviewed this preprint as part of the Transparent and Accountable Peer Review training program. This report was written with the support of my research mentor.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.