Skip to main content
NCBI home page

This is a preprint.

It has not yet been peer reviewed by a journal.

The National Library of Medicine is running a pilot to include preprints that result from research funded by NIH in PMC and PubMed.

medRxiv logoLink to medRxiv
[Preprint]. 2025 Jan 6:2025.01.06.24317169. [Version 1] doi: 10.1101/2025.01.06.24317169

De novo and inherited dominant variants in U4 and U6 snRNAs cause retinitis pigmentosa

Mathieu Quinodoz 1,2,3,*, Kim Rodenburg 4,*, Zuzana Cvackova 5, Karolina Kaminska 1,2, Suzanne E de Bruijn 4,6, Ana Belén Iglesias-Romero 1,2, Erica G M Boonen 4,7, Mukhtar Ullah 1, Nick Zomer 4, Marc Folcher 1,2, Jacques Bijon 8,9, Lara K Holtes 4, Stephen H Tsang 10,11, Zelia Corradi 4, K Bailey Freund 8,12, Stefanida Shliaga 4, Daan M Panneman 4, Rebekkah J Hitti-Malin 4, Manir Ali 13,14, Ala’a AlTalbishi 15, Sten Andréasson 16, Georg Ansari 2, Gavin Arno 17,18,19, Galuh D N Astuti 4, Carmen Ayuso 20,21, Radha Ayyagari 22, Sandro Banfi 23,24, Eyal Banin 25, Mirella T S Barboni 26, Miriam Bauwens 27, Tamar Ben-Yosef 28, David G Birch 29, Pooja Biswas 22, Fiona Blanco-Kelly 20,21, Beatrice Bocquet 30,31, Camiel J F Boon 32,33, Kari Branham 34, Alexis Ceecee Britten-Jones 35, Kinga M Bujakowska 36, Elizabeth L Cadena 37, Giacomo Calzetti 38,39, Francesca Cancellieri 1,2, Luca Cattaneo 40, Peter Charbel Issa 41,42, Naomi Chadderton 43, Luísa Coutinho-Santos 44, Stephen P Daiger 37, Elfride De Baere 27, Berta de la Cerda 45, John N De Roach 46, Julie De Zaeytijd 47,48, Ronny Derks 4, Claire-Marie Dhaenens 49, Lubica Dudakova 50, Jacque L Duncan 51, G Jane Farrar 43, Nicolas Feltgen 2, Lidia Fernández-Caballero 20,21, Juliana M Ferraz Sallum 52, Simone Gana 40, Alejandro Garanto 53,4, Jessica C Gardner 18, Christian Gilissen 4, Kensuke Goto 54, Roser Gonzàlez-Duarte 55, Sam Griffiths-Jones 56, Tobias B Haack 57,58,59, Lonneke Haer-Wigman 4, Alison J Hardcastle 18, Takaaki Hayashi 60, Elise Héon 61, Alexander Hoischen 4,62, Josephine P Holtan 63, Carel B Hoyng 64, Manuel Benjamin B Ibanez IV 65,66, Chris F Inglehearn 14, Takeshi Iwata 67, Kaylie Jones 29, Vasiliki Kalatzis 30,31, Smaragda Kamakari 68, Marianthi Karali 23,69, Ulrich Kellner 70, Krisztina Knézy 26, Caroline C W Klaver 64,71, Robert K Koenekoop 72, Susanne Kohl 73, Taro Kominami 54, Laura Kühlewein 73, Tina M Lamey 46, Bart P Leroy 74,48,47, María Pilar Martín-Gutiérrez 75, Nelson Martins 27, Laura Mauring 76,77,78, Rina Leibu 79, Siying Lin 80,81,19, Petra Liskova 82,50, Irma Lopez 72, Victor R de J López-Rodríguez 83,84, Omar A Mahroo 18,19,85,86, Gaël Manes 87, Martin McKibbin 14,88, Terri L McLaren 46, Isabelle Meunier 30,31, Michel Michaelides 18,19, José M Millán 89, Kei Mizobuchi 60, Rajarshi Mukherjee 88, Zoltán Zsolt Nagy 26, Kornelia Neveling 4, Monika Ołdak 90, Michiel Oorsprong 4, Yang Pan 67, Anastasia Papachristou 91, Antonio Percesepe 92, Maximilian Pfau 2, Eric A Pierce 93, Emily Place 93, Raj Ramesar 94, Florence Andrée Rasquin 95, Gillian I Rice 56, Lisa Roberts 94, María Rodríguez-Hidalgo 96,97, Javier Ruiz-Eddera 96,98, Ataf H Sabir 99,100, Ai Fujita Sajiki 54, Ana Isabel Sánchez-Barbero 20,21, Asodu Sandeep Sarma 25, Riccardo Sangermano 93, Cristina M Santos 44,101, Margherita Scarpato 23, Hendrik P N Scholl 102,103,104, Dror Sharon 25, Sabrina Giovanna Signorini 105, Francesca Simonelli 69, Ana Berta Sousa 106,107, Maria Stefaniotou 108, Katarina Stingl 73, Akiko Suga 67, Lori S Sullivan 37, Viktória Szabó 26, Jacek P Szaflik 109,110, Gita Taurina 111, Carmel Toomes 14, Viet H Tran 112,113, Miltiadis K Tsilimbaris 91, Pavlina Tsoka 91, Veronika Vaclavik 112, Marie Vajter 82,50, Sandra Valeina 114, Enza Maria Valente 115,40, Casey Valentine 94, Rebeca Valero 55, Joseph van Aerschot 116, L Ingeborgh van den Born 7, Andrew R Webster 18,19, Laura Whelan 43,117,118, Bernd Wissinger 119, Georgia G Yioti 108, Kazutoshi Yoshitake 67, Juan C Zenteno 83,84, Roberta Zeuli 23, Theresia Zuleger 57, Chaim Landau 120, Allan I Jacob 121, Frans P M Cremers 4, Winston Lee 122, Jamie M Ellingford 56,123, David Stanek 5, Carlo Rivolta 1,2,3,#,$, Susanne Roosing 4,#
PMCID: PMC11741465  PMID: 39830270

Abstract

The U4 small nuclear RNA (snRNA) forms a duplex with the U6 snRNA and, together with U5 and ~30 proteins, is part of the U4/U6.U5 tri-snRNP complex, located at the core of the major spliceosome. Recently, recurrent de novo variants in the U4 RNA, transcribed from the RNU4-2 gene, and in at least two other RNU genes were discovered to cause neurodevelopmental disorder. We detected inherited and de novo heterozygous variants in RNU4-2 (n.18_19insA and n.56T>C) and in four out of the five RNU6 paralogues (n.55_56insG and n.56_57insG) in 135 individuals from 62 families with non-syndromic retinitis pigmentosa (RP), a rare form of hereditary blindness. We show that these variants are recurrent among RP families and invariably cluster in close proximity within the three-way junction (between stem-I, the 5’ stem-loop and stem-II) of the U4/U6 duplex, affecting its natural conformation. Interestingly, this region binds to numerous splicing factors of the tri-snRNP complex including PRPF3, PRPF8 and PRPF31, previously associated with RP as well. The U4 and U6 variants identified seem to affect snRNP biogenesis, namely the U4/U6 di-snRNP, which is an assembly intermediate of the tri-snRNP. Based on the number of positive cases observed, deleterious variants in RNU4-2 and in RNU6 paralogues could be a significant cause of isolated or dominant RP, accounting for up to 1.2% of all undiagnosed RP cases. This study highlights the role of non-coding genes in rare Mendelian disorders and uncovers pleiotropy in RNU4-2, where different variants underlie neurodevelopmental disorder and RP.

Keywords: snRNA, splicing, spliceosome, non-coding, retinitis pigmentosa, hereditary disease

MAIN TEXT

While approximately 2 million individuals are affected by retinitis pigmentosa (RP) worldwide, it is estimated that 30–50% of these individuals remain without a conclusive genetic diagnosis, even when exome and/or genome sequencing is performed1–4. This is due, in part, to the high genetic heterogeneity of the disease, limited opportunities for genetic testing, and the existence of yet-to-be-identified causal genes. Moreover, the identification of novel disease-associated genes is hindered because RP variants are exceedingly rare in the population, with 97% and 81% occurring at allele frequencies below 0.1% and 0.01%, respectively, in any control subpopulations5,6.

Non-coding RNAs are essential to many regulatory cellular processes, such as the regulation of gene expression and pre-mRNA gene splicing7. In particular, five small nuclear RNAs (snRNAs), U1, U2, U4, U5, and U6, are constituents of the major spliceosome, a large and dynamic macromolecular complex involved in pre-mRNA splicing, a critical intermediate step between transcription and translation for the vast majority of genes in the human genome. Recently, recurrent de novo variants in RNU4-2, one of the two paralogues encoding the human U4 snRNA, have been associated with a frequent neurodevelopmental disorder (NDD), ReNU syndrome (OMIM: 620851). Pathogenic variants in this gene have been shown to cause systematic bias in the recognition of the donor splice site by the spliceosome and to account for as much as 0.4% of all individuals with NDD8,9. Likewise, other snRNA genes, RNU2-2P and RNU5B-1, have also been recently described to be linked to the same condiiton10–12.

Several spliceosomal proteins are also known to be involved in a wide range of hereditary diseases, including RP. Specifically, out of the 114 genes (https://retnet.org/) that are currently associated with non-syndromic RP, the tri-snRNP splicing factors genes PRPF3, PRPF4, PRPF6, PRPF8, PRPF31, and SNRNP200 underly the autosomal dominant form of the condition (adRP), with variants in PRPF31 accounting for 10–20% of all such cases3,13.

Here, we identified both inherited and de novo variants in RNU4-2 and four paralogues of RNU6, encoding the U6 snRNA, as the molecular cause of adRP in 135 individuals across 62 families. We demonstrate that all identified variants cluster in close proximity, within the U4/U6 duplex, and specifically in a region that binds directly to PRPF31 and PRPF3, and indirectly to PRPF6 and PRPF814,15. Finally, we show that the RP-associated variants increase the association of U4 and U6 snRNAs with di-snRNP-specific proteins SART3 and PRPF31.

RNU4-2 variants underlie adRP

We initially examined a non-consanguineous family with adRP spanning two generations. Seven of eight siblings (II:1-II:7) and their father (I:1) were affected, each experiencing a symptomatic onset of night-blindness and progressive loss of peripheral vision beginning in late adolescence to early adulthood. Fundus examination and electrophysiological testing of all affected individuals revealed classical RP features (Supplementary Fig. 1, Supplementary data 1). Genome sequencing was performed for all ten individuals of the family and selective DNA variant filtering and shared haplotype analysis revealed the presence of a variant in RNU4-2 (NR_003137.2:n.18_19insA, Supplementary Table 1) as the possible cause of disease. Among other features, this variant was absent from genomic databases of controls and was present in a highly conserved region of the genome6,16–18.

We then extended our analysis to 1,893 individuals with RP without prior genetic diagnosis and identified three additional families, consisting of 15 affected individuals segregating the same pathogenic variant. In addition, we detected another DNA variant, n.56T>C, that recurred in seven individuals from four families (Supplementary Table 1 and 2, Fig. 1A,C). Similar to n.18_19insA, the n.56T>C variant was absent from genomic databases of control populations. Additional screening of patient cohorts from our respective institutions, as well as the analysis of the UK National Genomic Research Library, hosting data from the Genomics England 100,000 Genomes Project (GEL)19, and from the NHS Genomic Medicine Service (GMS), comprising a total of ~3,000 cases, uncovered an additional patient harboring n.18_19insA and four families (five affected individuals) carrying the n.56T>C variant. Altogether, recurrent variants in RNU4-2 were identified in 36 affected individuals from 13 families (Supplementary Fig. 2). Twenty-seven additional affected individuals from these families could not be assessed genetically as no DNA was available. Of note, incomplete penetrance was observed for nine obligate carriers (of which four were deceased) in 38% of families (five out of 13), who would bear pathogenic variants but have no visual symptoms (Supplementary Fig. 1). One of these individuals was shown to be subclinically affected, one showed no clinical signs of disease upon clinical examination, and three were not clinically evaluated to confirm their unaffected status.

Figure 1: U4-U6 structure and rare variants found in RP cases and controls (gnomAD).

Figure 1:

Open in a new tab

(A) 2D structure of U4-U6 duplex with recurrent variants identified in RP cases (in red for U4 and in green for U6), which cluster in the same region of the complex, the three-way junction. Nucleotides affected by variants previously observed in neurodevelopmental disorder cases are underlined. (B) Rare variants affecting RNU4-1, defined as AF<0.1% in gnomAD v.4.1, identified in RP cases and in controls. (C) same as (B) for RNU4-2 with recurrent variants displayed in red. (D) same as (B) for all five RNU6 paralogues combined, with recurrent variants displayed in green.

Since the only U4 paralogue, RNU4-1, differs from RNU4-2 only at four positions (n.37, n.88, n.99, and n.113), we also assessed this gene (Supplementary Table 3). We did not identify any potentially pathogenic variants, including variants at the sites corresponding to n.18_19 and n.56 of RNU4-2 (Fig. 1B). Conversely, 63 likely benign variants were detected (Supplementary Table 4). NR_003925.1:n.56T>C was observed in two individuals from the “All of Us” database18 but we were unable to assess their phenotype. Notably, RNU4-1 appears to be more tolerant to variation compared to RNU4-2, as evidenced by the many and frequent variants that are present in genomes from the general population (cumulative allele frequency of 20.4% in RNU4-1 vs 1.2% in RNU4-2, gnomAD v4.1) (Fig. 1B,C, Supplementary Fig. 3), although these seem to be reduced in the region corresponding to where pathogenic NDD variants were described in RNU4-2 (Supplementary Fig. 3), indicating that RNU4-1-derived U4 could be partly functional.

In addition to n.18_19insA and n.56T>C, we identified 10 other unique rare variants in RNU4-2 in 10 RP families, which were classified as variants of uncertain significance (VUS), as well as 17 benign changes (Supplementary Table 4).

Variants in U6 paralogues also cause RP

In the U4/U6.U5 tri-snRNP complex, U4 binds to U6, to form the U4/U6 RNA duplex. Since the pathogenic variants observed in U4 were predicted to affect this RNA-RNA structure, we reasoned that variants in U6 could also be associated with adRP and extended our analysis to all five identical paralogous genes producing U6 RNA, scattered across the genome (RNU6-1, RNU6-2, RNU6-7, RNU6-8 and RNU6-9; Supplementary Table 3). In the same international cohorts of patients that were previously analyzed, we identified variants at two specific sites in U6 (n.55_56insG and n.56_57insG) in all RNU6 paralogues, except RNU6-7. Importantly, these variants were either absent or extremely rare in controls and were identified only in individuals with RP (Fig. 1A,D, Supplementary Fig. 2).

In total, pathogenic and likely pathogenic U6 variants were detected in 99 affected individuals from 49 families; 112 additional affected individuals from the same pedigrees could not be tested, but are likely to carry the same pathological genotypes. Variant n.55_56insG was present in the majority of the cases (89 individuals from 43 families), occurring in four out of the five RNU6 paralogues: RNU6-1, RNU6-2, RNU6-8, and RNU6-9 (Supplementary Table 1 and 2, Supplementary Fig. 2). Notably, this variant was confirmed to be a de novo event in seven individuals, clinically identified as sporadic cases. In 12 additional pedigrees, n.55_56insG was observed in individuals born to unaffected parents, for which de novo-ness was suspected but could not be proven, due to lack of parental DNA.

The nearby U6 variant, n.56_57insG, was identified in RNU6-1, RNU6-2, and RNU6-9, in six families with adRP (10 individuals, Fig. 1A,D, Supplementary Fig. 2). This variant is observed once in RNU6-2 in gnomAD v4.1, in a non-Finnish European individual in the age range of 50–55 with an unknown health-status.

Similar to the screening of the RNU4 paralogues, our analysis of RNU6 paralogues revealed 20 VUSs and 70 benign variants, validated by Sanger sequencing (Supplementary Table 4).

In summary, we identified variants in RNU4-2 or RNU6 paralogues to underlie de novo or inherited dominant RP in 62 families. The overall phenotype in all cases in the study cohort was consistent with classical RP on examination and electrophysiological testing with symptomatic onset beginning predominantly in adolescence (Supplementary Table 5). In addition, other concurrent ocular disease features were noted across individuals in the cohort: cystoid macular edema (CME) (55.9%), non-age-related lens opacities (23.6%), and various vitreomacular complications (30.6%) (Supplementary Table 5). Based on our data from ~5,000 RP cases (most lacking a genetic diagnosis) and taking into consideration that on average ~40% of people with RP remain genetically undiagnosed, we can estimate that RNU4 and RNU6-associated RP could be responsible for 1.2% of all undiagnosed cases with this disease. Furthermore, considering that ~30% of RP cases are adRP20,21 and 40 adRP families had recurrent variants in RNU4-2 or RNU6 paralogues, we can further infer that those variants can account for ~2.7% of adRP families.

Predicted effects of variants on the U4/U6 duplex

Analysis of the position of the detected variants in the three-dimensional space of the tri-snRNP complex showed that all variants clustered in close proximity to each other, and in particular within the three-way junction between stem-I and stem-II of the U4/U6 duplex and the 5’ stem-loop of U4 (Fig. 1A). The duplex is stabilized by intramolecular motifs and through base-pairing between U4 and U6 within stem-I (n.56–61), stem-II (n.1–16), stem-III (n.73–79) and the U4 quasi-pseudoknot (n.62 and n.64).

The U4 and U6 variants associated with RP cluster in a different region compared to those underlying NDD (Fig. 1A). In silico modeling predicts that the RNU4-2 variant n.18_19insA inserts a nucleotide between stem-II and the U4 5’ stem-loop affecting the normal base-pairing (Fig. 2A,B), while n.56T>C disrupts the base-pairing between stem-I of the U4/U6 duplex (Fig. 2A,C). Both alterations lead to the extension of the internal loop, an event that was predicted to impact the overall stability of the duplex. In addition, n.18_19insA also modifies the orientation of the 5’ stem-loop relative to stem I and stem II (Fig. 2B).

Figure 2: 2D modeling of the U4-U6 three-way junction.

Figure 2:

Open in a new tab

Wild-type (WT) structure of the U4/U6 duplex surrounding the internal loop (A, D) and structures including pathogenic variants affecting U4 (B, C), U6 (E, F). The gray circle gauges the normal size of the three-way junction, while the dashed lines show the normal orientations of the stems originating from the junction.

In contrast, variants n.55_56insG and n.56_57insG in the RNU6 paralogs are predicted to introduce an additional wobble base-pairing (G-U) with n.56T of U4 and three additional pairings in stem-I of the U4/U6 duplex. These changes alter the duplex’s secondary structure by extending the length of stem-I, reducing the size of the internal loop, and drastically changing the orientation of the 5’ stem-loop (Fig. 2D–F). Interestingly, we observed that a benign insertion at the same position, n.55_56insT, was present in gnomAD v4.1 in all five RNU6 paralogues with a cumulative frequency of 0.12% (n=181). Similarly, a nearby variant, n.57T>G was observed in multiple paralogues, in genotypes from the unaffected population (n=21, gnomAD v4.1).

The recurring variants cluster in the three-way junction close to the 5’ stem-loop (Fig. 1A, 3A), which is known to be critical for the binding of the U4/U6 duplex with the splicing factors PRPF31, PRPF3, PRPF6, and PRPF8, all previously associated with adRP (Fig. 3B)14,15. Specifically, this structure first binds either PRPF31 or PRPF3/4, and is then stabilized to its original orientation when all factors are bound22. The mutated and neighboring U4 and U6 nucleotides in RP cases detected in our study directly participate in the binding of PRPF31 and PRPF3 (Fig. 3C,D), via hydrogen bonds with eight and three residues of these proteins, respectively. Notably, by querying the ClinVar database23, we identified a missense variant affecting one of these residues, p.(Arg449Gly) of PRPF3, that was described in a three-generation family of seven affected individuals with an adRP phenotype similar to most of the affected cases in our study cohort24.

Figure 3: 3D structure of the U4/U6 duplex and its interactions with the neighboring splicing factors PRPF3, PRPF6, PRPF8 and PRPF31.

Figure 3:

Open in a new tab

(A) Naked U4/U6 pairing, showing the close proximity of the pathogenic variants identified (red and green). (B) Same as in (A), with interacting PRPF proteins. (C) Direct interactions of nucleotides of the U4/U6 duplex with PRPF31, by direct hydrogen bonds. (D) Same as (C) but for PRPF3.

RNU4 and RNU6 genes and their expression

Since the human genome contains several RNU4 and RNU6 pseudogenes25, we investigated whether any of these might be incorrectly annotated and could instead produce functional RNA, potentially contributing to the disease. In addition, we sought to understand why the various U4 and U6 paralogues appear to be differentially mutated, with RNU4-1 and RNU6-7 displaying none of the recurrent pathogenic variants in RP cases. We used RNA-seq data from neurosensory retina (NSR), retinal pigment epithelium (RPE), and human choroid, that had been enriched for small RNA, with bioinformatics analysis performed in a strict manner to mitigate complexities associated with reads aligning against multiple paralogues and/or pseudogenes (see Material and Methods). This analysis showed that RNU4-2 has a higher expression compared to RNU4-1 in all tissues analyzed, with an average ratio of 1.65 (Fig. 4A). Conversely, for RNU6 genes and pseudogenes, individual expression in the retina could not be reliably quantified by RNA-seq, since their sequences are identical, except for the last nucleotide. Therefore, we compared total expression of RNU4 and RNU6, regardless of their respective paralogues and pseudogenes. RNU6 expression was on average 2.89x higher across the three tissues, compared to RNU4 (Fig. 4B). Of note, NSR and RPE had higher expression of RNU4 (2.45x) and of RNU6 (6.24x) with respect to the choroid, an ocular tissue that is not directly involved in vision and was therefore used as a control (Fig. 4B). This observation is in agreement with previous data, showing that snRNA expression in the retina is approximately 6-fold higher compared to muscle, testis, heart, and brain26, indicating a high demand for snRNAs in these two retinal layers.

Figure 4: Expression and markers of transcriptional activity for RNU4 and RNU6 genes.

Figure 4:

Open in a new tab

(A) Expression of RNU4-1 and RNU4-2 from RNA-seq of human donor choroid (n=13), neurosensory retina (NSR, n=4) and retinal pigmented epithelium (RPE, n=16). Data are represented in boxplots and the median value is written in the box. (B) Same for RNU4 genes (RNU4-1, RNU4-2 and their pseudogenes (in black)) and for all RNU6 genes (RNU6-1, RNU6-2, RNU6-7, RNU6-8, RNU6-9 and their pseudogenes (in black)). (C) ATAC-seq and H3K27ac signals for three RNU4 genes and 105 pseudogenes (D) ATAC-seq and H3K27ac signals for six RNU6 genes and 1,312 pseudogenes. ATAC-seq data is from Wang et al.54 and H3K27ac data is from Cherry et al.55

In addition, we analyzed ATAC-seq and H3K27ac ChIP-seq data from retinal tissues27 in genomic regions spanning all RNU4 and RNU6 sequences. ATAC-seq assesses chromatin accessibility across the genome, while H3K27ac ChIP-seq reveals the presence of active enhancers. Combined, they provide indirect evidence of active transcription, even in the absence of reliable RNAseq data. Our analysis showed clear marks of active transcription in all paralogous genes (RNU4-1, RNU4-2, RNU6-1, RNU6-2, RNU6-7, RNU6-8, and RNU6-9) in the retina (Fig. 4C,D). Conversely, these signatures were absent from the 105 U4 pseudogenes and the 1,312 U6 pseudogenes, except for RNU4–8P, which displayed strong signals, but probably by virtue of its close proximity to the ACTR1B promoter. Of note, RNU6-92P and RNU6-656P had a high ATAC-seq signals but very low H3K27ac signals (Fig. 4C,D).

Likewise, we performed the same analysis for other snRNA genes present in the human genome, which revealed a similar trend: all RNU genes, with the exception of RNU5F-1, had marks of active transcription and only four (RNU2-2P, RNU1–27P, RNU1–28P, and RNU5E-6P) among the thousands of RNU pseudogenes displayed signals compatible with potential expression, therefore representing plausible candidate genes for retinal disease (Supplementary Fig. 4). Of note, RNU2-2P was recently associated with an NDD phenotype without a description of ocular features12. Interestingly, the same type of analysis, based on conservation and expression data from GTEx, was recently performed by others, showing similar results28.

For RNU6-7, both ATAC-seq and H3K27ac values were within the same range as those observed for other RNU6 genes (Fig. 4D), and, therefore, the absence of pathogenic variants could not be explained by a potential differential expression. We thus analyzed the genetic landscape of variations in healthy individuals in all the five U6 paralogues, and observed that RNU6-7 displayed a lower number of variants, compared to the others (Supplementary Fig. 5). In addition, we identified the recurrent variant n.55_56insG in RNU6-7 in six control individuals of African / African American ancestry in gnomAD v4.1 (AF=0.014%) and in 14 individuals of African origin in the “All of Us” database (AF=0.013%). Considering these results, we propose that RNU6-7-derived U6 is either not part of the spliceosome or is present in only a small number of tri-snRNP complexes, a possibility that warrants investigation in future studies.

Effect of RP variants on snRNP assembly

We immunopurified ectopically expressed U4 and U6 snRNAs containing the RP variants and analyzed their association with specific markers for U4/U6 di-snRNP (SART3 and PRPF31) and U5 snRNP (SNRNP200). All recurrent RP variants in U4 and U6 snRNAs increased the interaction between these snRNAs and di-snRNP markers (Fig. 5), while the U4 n.64_65insT change, which causes NDD, did not.

Figure 5: RP variants in RNU4-2 and RNU6 inhibit snRNP maturation.

Figure 5:

Open in a new tab

(A) Immunoprecipitation of U4-MS2 (WT and variants) and (B) U6-MS2 (WT and variants). snRNPs were immunoprecipitated via MS2-YFP by anti-GFP antibodies and co-precipitated proteins were detected by Western blotting. The position of the MS2 loop (green) in snRNAs is indicated. Three independent experiments were quantified. Immunoprecipitated proteins are normalized to input and U4 or U6 wild-type controls. Statistical significance was analyzed by the two-tailed unpaired t-test. * indicates P-value ≤0.05, ** ≤0.01, and *** ≤0.001

Similarly, U6 RNA bearing the n.55_56insT and n.57T>G variants, observed in healthy control individuals, did not affect the assembly process, and the low amount of protein associated with them indicates that they did enter the assembly process only minimally (Fig. 5B). Taken together, the results indicate that RP pathogenic variants have a specific dominant effect on snRNP biogenesis and slow down the assembly process at the di-snRNP stage.

Discussion

The numerous genes associated with RP and allied diseases belong to very diverse functional classes, ranging from retina-restricted biochemical pathways to ubiquitous cellular processes. Although the molecular deficit resulting from specific RP variants can be modeled for many genes, the general mechanism of pathogenesis, linking thousands of DNA variants in dozens of genes to a common pathological phenotype, remains unknown, despite 40 years of intensive research. The correlation between pathogenic variants in splicing factors belonging to the tri-snRNP, essential for survival in all eukaryotes, and RP, a phenotype restricted to the eye, constitutes perhaps the most intriguing and complex of such molecular enigmas. Variants in these spliceosomal proteins (RP-PRPFs) are associated with the dominant form of the condition, the least prevalent one, at times with reduced penetrance3,13.

In this study, we have identified recurrent variants in RNU4-2, encoding U4 RNA, and in multiple paralogues of the U6 RNA, scattered across the whole human genome, as a cause of RP. Interestingly, these snRNAs are also an integral part of the di- and tri-snRNP and directly interact with some RP-PRPF proteins. In addition, like RP-PRPFs, they are also associated with the same specific phenotype: de novo or inherited adRP, with reduced penetrance for RNU4-2 variants. The clinical presentation of patients with RNU4-2 and RNU6 variants from this study exhibit as well overlap with the other known forms of spliceosome-related adRP, particularly in terms of earlier disease onset (contrasting the generally milder prognosis of most other forms of adRP29,30) and the relatively high co-occurrence of features such as cataracts and CME found in PRPF3131,32, PRPF833 and SNRNP20034. Prevalence estimations indicate that these snRNA pathogenic changes may account for an elevated number of undiagnosed cases, and it is therefore surprising that the RNU4 and RNU6 genes have escaped disease association until now. A partial explanation for this phenomenon is that mainstream sequencing approaches, both in research and diagnostics, are biased towards DNA-capturing procedures that do not include snRNA genes. Nevertheless, genome sequencing is being implemented in routine diagnostics, and these variants may have eluded detection so far because they affect non-coding transcripts and are therefore more difficult to score in terms of potential pathogenicity by analytical pipelines.

An intriguing feature of pathogenic changes in RNU4-2 is their pleiotropy with respect to NDD (ReNU) and RP. Although the exact mechanism for this phenotypic selectivity is unknown, it highlights the presence of a new allelic series involving non-coding RNA genes. A potential explanation for such divergent phenotypes could reside in the position that ReNU and RP variants have with respect to the U4/U6 duplex. ReNU pathogenic variants are included within the stem III of the duplex, whereas RP variants cluster, in close spatial proximity, to the three-way junction, in regions to which several of the RP-associated splicing factors bind. Our ectopic expression experiments showed in fact that snRNAs bearing RP variants display enhanced interaction with di-snRNP protein markers, suggesting that pathogenesis could result from a gain-of-function / dominant-negative mechanism, rather than from haploinsufficiency. This hypothesis was strengthened by the evidence that molecularly similar but benign variants, commonly observed in the general population, seemed not to efficiently bind to di-snRNP markers, supporting the idea that spliceosomal functions could be haplosufficient with respect to heterozygous and snRNA-depleting variants. Moreover, the pathogenic variants identified in this study are located precisely in regions of the U4/U6 duplex that interact directly with PRPF3 and PRPF31 proteins, two splicing factors previously associated with adRP. These proteins, when mutated, destabilize the spliceosome complex formation, leading to delayed and abnormal splicing events, particularly in the retina26,35,36. Therefore, it is plausible that all RP variants identified in RNU4-2 and RNU6 paralogues could lead to photoreceptor death and subsequent visual loss via similar early events of pathogenesis, while having no influence on the development of the brain. The fact that RP variants in RNU4-2 are not located in the variant-depleted region of the gene that defines the NDD hotspot also suggests that such variants may be milder with respect to those giving rise to ReNU, leading to delays in complex assembly rather than to defects in pre-mRNA processing.

Although variants associating RNU4-2 to ReNU syndrome have been primarily reported as de novo events8,12, in our study most individuals with RP (67%) bear RNU4-2 and RNU6 changes as inherited variants. In part, this difference can be explained by the reduced reproductive fitness associated with NDD. Unlike ReNU syndrome, symptomatic onset (night-blindness and peripheral vision loss) in non-syndromic adRP begins later in life, with severe central vision loss occurring significantly beyond reproductive age. Another difference involves the inheritance of dominant variants, which in ReNU seems to be almost exclusively of maternal origin8. We did not observe the same trend for RP, with variants being inherited from fathers and mothers in numerous cases, indicating the absence of any sex-specific negative selection during gametogenesis or at the embryonic stage.

The human genome contains two RNU4 paralogues and five RNU6 paralogues. This indicates that, assuming equal expression within paralogues, the presence of only ~25% of mutant U4 (heterozygous genotype, over two copies) or ~10% of mutant U6 (heterozygous genotype, over five copies) is sufficient to lead to a disease phenotype, again in support of a gain-of-function / dominant-negative molecular mechanism. This could be a crucial consideration for the development of potential gene-based therapies, as gene-augmentation strategies may be suboptimal compared to gene correction or antisense oligonucleotide approaches. Our data also highlight the existence of mutational hotspots outside the coding regions of the human genome, emphasizing the need for further research into these parts of our genetic material, and show that the clustering of de novo pathogenic variants is not restricted to severe diseases with childhood onset37, but may extend to milder pathologies, such as RP.

In conclusion, we identified four recurrent pathogenic variants in RNU4-2 and four out of the five paralogues of the U6 snRNA as a frequent cause of de novo or inherited adRP. The immediate impact of these findings involves improved diagnosis and genetic counselling for patients with hereditary visual loss, especially for isolated cases who could potentially bear heterozygous de novo events. More fundamentally, this work significantly broadens our understanding of the genetic landscape of human disease, paving the way for the development of new molecular therapeutic approaches.

Supplementary Material

Supplement 1
media-1.pdf (1.8MB, pdf)
Supplement 2
media-2.pdf (290KB, pdf)
Supplement 3
media-3.pdf (377.4KB, pdf)
Supplement 4
media-4.pdf (415.1KB, pdf)
Supplement 5
media-5.pdf (436.5KB, pdf)
Supplement 6
media-6.xlsx (72.7KB, xlsx)
Supplement 7
media-7.xlsx (12.3KB, xlsx)
Supplement 8
media-8.xlsx (9.2KB, xlsx)
Supplement 9
media-9.xlsx (81KB, xlsx)
Supplement 10
media-10.xlsx (73.7KB, xlsx)
Supplement 11
media-11.xlsx (9.5KB, xlsx)
Supplement 12
media-12.docx (18.8KB, docx)
Supplement 13

Acknowledgements and funding sources

The authors of the article would like to thank the patients and their family members for their help and participation in this study. We are very grateful to Sitta Föhr for technical and administrative support, to Saskia van de Velde-Visser, Ellen Blokland and Marlie Jacobs-Camps for sample registration and administration, to Mattias Van Heetvelde, Toon Rosseel (computational), Quinten Mahieu (technical), Marieke Debruyne, Stijn Van de Sompele (clinical reporting) for their support.

C.R. was supported by the Swiss National Science Foundation (SNSF) Grant No. 310030_204285 entitled “Genomics of inherited retinal diseases”. S.R. was supported by the Foundation Fighting Blindness Career Development Award (CD-GE-0621-0809-RAD), Radboudumc Starter grant (OZI-23.009) and NWO Aspasia (015.021.028). S.R., C.R., E.D.B., M.B., S.B., D.St., were supported by HORIZON-MSCA-2022-DN (No.101120562, ProgRET). E.D.B., S.R., C.R. were supported by the EJPRD19-234 Solve-RET. This work has been funded by a Foundation Fighting Blindness Program Project Award (PPA-0622-0841-UCL) (to A.J.H, S.R. and S.E.dB.). S.R. and F.P.M.C. were supported by the Gelderse Blindenstichting, the Algemene Nederlandse Vereniging ter voorkoming van Blindheid, Oogfonds, Landelijke Stichting voor Blinden en Slechtzienden, Rotterdamse Stichting Blindenbelangen, Stichting Blindenhulp, Stichting tot Verbetering van het Lot der Blinden, and Stichting Blinden-Penning. M.Q. was supported by the RetinAward 2021. S.H.T. - Jonas Children’s Vision Care (JCVC) is supported by the National Institute of Health U01EY030580, U01EY034590 R24EY028758, R24EY027285, 5P30EY019007, R01EY033770, R01EY018213, R01EY024698, the Foundation Fighting Blindness TA-GT-0321-0802-COLU-TRAP, Richard Jaffe, NYEE Foundation, the Rosenbaum Family Foundation, the Gebroe Family Foundation, Piyada Phanaphat Fund, the Research to Prevent Blindness (RPB) Physician-Scientist Award, unrestricted funds from RPB, New York, NY, USA. C.A. was supported by Instituto de Salud Carlos III (ISCIII) of the Ministerio de Ciencia e Innovación and Unión Europea – European Regional Development Fund (FEDER) (PI22/00321 and IMP/00009), Centro de Investigación Biomédica en Red Enfermedades Raras (CIBERER, 06/07/0036), IIS-FJD BioBank (PT13/0010/0012), the Organización Nacional de Ciegos Españoles (ONCE), European Regional Development Fund (FEDER), the University Chair UAM-IIS-FJD of Genomic Medicine. This work was performed by using the data contained in the “Programa Infraestructura de Medicina de Precisión asociada a la Ciencia y la Tecnología en Medicina Genómica (IMPaCT-GENóMICA)”, coordinated by the CIBERER and founded by ISCIII. L.F.C. was supported by Centro de Investigación Biomédica en Red (CIBER). R.A. was supported by the National Eye Institute (NEI) (RO1 EY030591, RO1 EY031663, T32 EY026590, and P30 EY22589). C.C.W.K was supported by the Combined Ophthalmic Research Rotterdam) grant 8.2.0. S.B. was supported by the Italian Telethon Foundation. G.J.F. and N.C. were supported by Fighting Blindness Ireland (FB22FAR, FB16FAR), Fighting Blindness Ireland - Health Research Charities Ireland (MRCG-2016-14) and Science Foundation Ireland (16/IA/4452 and 22/FFP-A/10544). J.E. was supported by the Macular Society (United Kingdom), and the University of Manchester Core Genomics Technology Facility. T.B.Y. was supported by the Israel Science Foundation (331/24). A.C.B.J. is supported by the University of Melbourne Research Fellowship. K.M.B. was supported by the National Eye Institute (NEI) (RO1 EY035717 and P30 EY014104 [MEE core support]), the Iraty Award 2023, the Lions Foundation, and the Research to Prevent Blindness (Unrestricted Grant). L.S.S., E.L.C. and S.P.D. were supported by grants from the Foundation Fighting Blindness (EGI-GE1218-0753-UCSD) and the Brett & Jane Eberle Foundation. E.D.B. and B.P.L were supported by Ghent University Special Research Fund (BOF20/GOA/023) and E.D.B. (1802220N) and B.P.L. (1803816N) are Senior Clinical Investigators of the Research Foundation-Flanders (FWO). N.M. and S.S. are Ph.D. fellows of HORIZON-MSCA-2022-DN ProgRET (No.101120562). R.A. was supported by the Foundation Fighting Blindness. J.D was supported by the UCSF Vision Core shared resource of the NIH/NEI P30 EY002162, the Foundation Fighting Blindness, and an unrestricted grant from Research to Prevent Blindness. T.I. was supported by research grant from the Japan Agency for Medical Research and Development (AMED) (20ek0109493h0001, 21ek0109493h0002, 22ek0109493h0003, 23ek0109617h0002, 24ek0109617h0003). R.K.K. was supported by The Montreal Children’s Hospital Foundation, The Vision Sciences Research Network (VSRN), The National Institutes of Health (NIH)(R01 EY030499-01, Dr. Lentz), The Canadian Institutes for Health Research (CIHR), Fighting Blindness Canada (FBC), and Fonds de Recherche du Québec - Santé (FRQS). R.K.K. participates in the NAC Attack clinical trial, which is funded by the National Institutes of Health via grants UG1EY033286, UG1EY033293, UG1EY033286, and UG1EY033292. T.M.L., T.L.M and J.N.D.R. were supported by Retina Australia (awarded to the Australian Inherited Retinal Disease Registry and DNA Bank). O.M. was supported by the Wellcome Trust (grant no: 206619/Z/17/Z). T.L.M. was supported by Retina Australia. Awarded to the Australian Inherited Retinal Disease Registry and DNA Bank. M.P. was supported by the BrightFocus Foundation (M2024009N). E.A.P. was supported by the National Eye Institute (NEI) (R01 EY012910). R.R. was supported by Retina South Africa and the South African Medical Research Council (MRC). S.G.S. and E.M.V. were supported by the Italian Ministry of Health (RF-2019-12369368). D.St. was supported by the Ministry of Education, Youth and Sports of the Czech Republic grant for RNA therapy (CZ.02.01.01/00/22_008/0004575). T.B.H. was supported by the European Commission (Recon4IMD - GAP-101080997) and the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG, grant numbers 418081722 and 433158657 to T.B.H.). P.L. and L.D. were supported by a research grant (NW24-06-00083) from the Ministry of Health of the Czech Republic and UNCE/24/MED/022. V.R.dJ.L.R. and J.C.Z. were supported by the Velux Stiftung Grant 1860. M.A., M.M., C.F.I. J.C.G, A.J.H, and C.T. are supported by Retina UK and Fight for Sight UK (RP Genome Project Grant GR586). A.J.H, J.C.G, M.M, O.A.M, A.W, G.A and S.L were supported by the National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology. S.L. was funded by an MRC Clinician Scientist Fellowship. J.M.S. was supported by Instituto de Salud Carlos III (ISCIII) of the Spanish Ministry of Health (PI22/00213), Centro de Investigación Biomédica en Red Enfermedades Raras (CIBERER, 06/07/1030, CIPROM/2023/26 from the Generalitat Valenciana and IMPaCT-GENOMICA (IMP/00009) co-funded by ISCIII and FEDER. S.R., C.C.W.K, C.J.F.B., A.G. were supported by the Dutch ministry of Education, Culture and Sciences, Gravitation grant: 024.006.034 Lifelong VISION. W.L. was supported by the National Institute of Health/National Eye Institute (1K99EY036930-01).

This work is supported by partners of the European Reference Network for Rare Eye Diseases ERN-EYE (Grant Agreement No 101085439, C.J.F.B., E.D.B., C.B.H, S.K, B.P.L, P.L., L.H-W., K.S, L.I.v.d.B.). Novartis contributed funding for the preceding RP-LCA smMIPs panel design and subsequent sequencing (to F.P.M.C., S.R. and D.M.P). Novartis was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

This research was made possible through access to data in the National Genomic Research Library, which is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The National Genomic Research Library holds data provided by patients and collected by the NHS as part of their care, and data collected as part of their participation in research. The National Genomic Research Library is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK, and the Medical Research Council have also funded research infrastructure.

Data availability

Research on the de-identified patient data used in this publication from the Genomics England 100,000 Genomes Project and the NHS GMS dataset can be carried out in the Genomics England Research Environment subject to a collaborative agreement that adheres to patient-led governance. All interested readers will be able to access the data in the same manner that the authors accessed the data. For more information about accessing the data, interested readers may contact research-network@genomicsengland.co.uk or access the relevant information on the Genomics England website: https://www.genomicsengland.co.uk/research. The data generated during this study (pathogenic variants and VUSs identified) are submitted to the Leiden Open (source) Variation Database (LOVD) (http://www.lovd.nl) and ClinVar.

References

  • 1.Verbakel S. K. et al. Non-syndromic retinitis pigmentosa. Prog Retin Eye Res 66, 157–186 (2018). 10.1016/j.preteyeres.2018.03.005 [DOI] [PubMed] [Google Scholar]
  • 2.Peter V. G. et al. The first genetic landscape of inherited retinal dystrophies in Portuguese patients identifies recurrent homozygous mutations as a frequent cause of pathogenesis. PNAS Nexus 2, pgad043 (2023). 10.1093/pnasnexus/pgad043 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Perea-Romero I. et al. Genetic landscape of 6089 inherited retinal dystrophies affected cases in Spain and their therapeutic and extended epidemiological implications. Sci Rep 11, 1526 (2021). 10.1038/s41598-021-81093-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Conti G. M. et al. Genetics of Retinitis Pigmentosa and Other Hereditary Retinal Disorders in Western Switzerland. Ophthalmic Res 67, 172–182 (2024). 10.1159/000536036 [DOI] [PubMed] [Google Scholar]
  • 5.Hanany M., Rivolta C. & Sharon D. Worldwide carrier frequency and genetic prevalence of autosomal recessive inherited retinal diseases. Proc Natl Acad Sci U S A 117, 2710–2716 (2020). 10.1073/pnas.1913179117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Karczewski K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020). 10.1038/s41586-020-2308-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Fu X. D. Non-coding RNA: a new frontier in regulatory biology. Natl Sci Rev 1, 190–204 (2014). 10.1093/nsr/nwu008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Chen Y. et al. De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome. Nature 632, 832–840 (2024). 10.1038/s41586-024-07773-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Greene D. et al. Mutations in the U4 snRNA gene RNU4-2 cause one of the most prevalent monogenic neurodevelopmental disorders. Nat Med 30, 2165–2169 (2024). 10.1038/s41591-024-03085-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Jackson A., Thaker N., Blakes A. & Banka S. Analysis of R-loop forming regions identifies RNU2-2P and RNU5B-1 as neurodevelopmental disorder genes. medRxiv, 2024.2010.2004.24314692 (2024). 10.1101/2024.10.04.24314692 [DOI] [Google Scholar]
  • 11.Nava C. et al. Dominant variants in major spliceosome U4 and U5 small nuclear RNA genes cause neurodevelopmental disorders through splicing disruption. medRxiv, 2024.2010.2007.24314689 (2024). 10.1101/2024.10.07.24314689 [DOI] [Google Scholar]
  • 12.Greene D. et al. Mutations in the U2 snRNA gene RNU2-2P cause a severe neurodevelopmental disorder with prominent epilepsy. medRxiv, 2024.2009.2003.24312863 (2024). 10.1101/2024.09.03.24312863 [DOI] [Google Scholar]
  • 13.Weisschuh N. et al. Genetic architecture of inherited retinal degeneration in Germany: A large cohort study from a single diagnostic center over a 9-year period. Hum Mutat 41, 1514–1527 (2020). 10.1002/humu.24064 [DOI] [PubMed] [Google Scholar]
  • 14.Mozaffari-Jovin S. et al. The Prp8 RNase H-like domain inhibits Brr2-mediated U4/U6 snRNA unwinding by blocking Brr2 loading onto the U4 snRNA. Genes Dev 26, 2422–2434 (2012). 10.1101/gad.200949.112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Liu S. et al. Binding of the human Prp31 Nop domain to a composite RNA-protein platform in U4 snRNP. Science 316, 115–120 (2007). 10.1126/science.1137924 [DOI] [PubMed] [Google Scholar]
  • 16.Chen S. et al. A genomic mutational constraint map using variation in 76,156 human genomes. Nature 625, 92–100 (2024). 10.1038/s41586-023-06045-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Sudlow C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 12, e1001779 (2015). 10.1371/journal.pmed.1001779 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Denny J. C. et al. The “All of Us” Research Program. N Engl J Med 381, 668–676 (2019). 10.1056/NEJMsr1809937 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Caulfield M. National Genomic Research Library (2017). 10.6084/m9.figshare.4530893.v7 [DOI]
  • 20.Daiger S. P., Bowne S. J. & Sullivan L. S. Genes and Mutations Causing Autosomal Dominant Retinitis Pigmentosa. Cold Spring Harb Perspect Med 5 (2014). 10.1101/cshperspect.a017129 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Sullivan L. S. et al. Prevalence of disease-causing mutations in families with autosomal dominant retinitis pigmentosa: a screen of known genes in 200 families. Invest Ophthalmol Vis Sci 47, 3052–3064 (2006). 10.1167/iovs.05-1443 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Hardin J. W., Warnasooriya C., Kondo Y., Nagai K. & Rueda D. Assembly and dynamics of the U4/U6 di-snRNP by single-molecule FRET. Nucleic Acids Res 43, 10963–10974 (2015). 10.1093/nar/gkv1011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Landrum M. J. et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 42, D980–985 (2014). 10.1093/nar/gkt1113 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Zhong Z. et al. Two novel mutations in PRPF3 causing autosomal dominant retinitis pigmentosa. Sci Rep 6, 37840 (2016). 10.1038/srep37840 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Denison R. A., Van Arsdell S. W., Bernstein L. B. & Weiner A. M. Abundant pseudogenes for small nuclear RNAs are dispersed in the human genome. Proc Natl Acad Sci U S A 78, 810–814 (1981). 10.1073/pnas.78.2.810 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Tanackovic G. et al. PRPF mutations are associated with generalized defects in spliceosome formation and pre-mRNA splicing in patients with retinitis pigmentosa. Hum Mol Genet 20, 2116–2130 (2011). 10.1093/hmg/ddr094 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.D’Haene E. et al. Comparative 3D genome analysis between neural retina and retinal pigment epithelium reveals differential cis-regulatory interactions at retinal disease loci. Genome Biol 25, 123 (2024). 10.1186/s13059-024-03250-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Prasetyo N. K. & Gardner P. P. Assessing the robustness of human ncRNA notation at HGNC. bioRxiv, 2024.2012.2008.627405 (2024). 10.1101/2024.12.08.627405 [DOI] [Google Scholar]
  • 29.Hamel C. Retinitis pigmentosa. Orphanet J Rare Dis 1, 40 (2006). 10.1186/1750-1172-1-40 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Grover S. et al. Visual acuity impairment in patients with retinitis pigmentosa at age 45 years or older. Ophthalmology 106, 1780–1785 (1999). 10.1016/s0161-6420(99)90342-1 [DOI] [PubMed] [Google Scholar]
  • 31.Bodenbender J. P. et al. Clinical and Genetic Findings in a Cohort of Patients with PRPF31-Associated Retinal Dystrophy. Am J Ophthalmol 267, 213–229 (2024). 10.1016/j.ajo.2024.06.020 [DOI] [PubMed] [Google Scholar]
  • 32.Waseem N. H. et al. Mutations in the gene coding for the pre-mRNA splicing factor, PRPF31, in patients with autosomal dominant retinitis pigmentosa. Invest Ophthalmol Vis Sci 48, 1330–1334 (2007). 10.1167/iovs.06-0963 [DOI] [PubMed] [Google Scholar]
  • 33.Maubaret C. G. et al. Autosomal dominant retinitis pigmentosa with intrafamilial variability and incomplete penetrance in two families carrying mutations in PRPF8. Invest Ophthalmol Vis Sci 52, 9304–9309 (2011). 10.1167/iovs.11-8372 [DOI] [PubMed] [Google Scholar]
  • 34.Yusuf I. H. et al. Clinical Characterization of Retinitis Pigmentosa Associated With Variants in SNRNP200. JAMA Ophthalmol 137, 1295–1300 (2019). 10.1001/jamaophthalmol.2019.3298 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Buskin A. et al. Disrupted alternative splicing for genes implicated in splicing and ciliogenesis causes PRPF31 retinitis pigmentosa. Nat Commun 9, 4234 (2018). 10.1038/s41467-018-06448-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Azizzadeh Pormehr L., Ahmadian S., Daftarian N., Mousavi S. A. & Shafiezadeh M. PRPF31 reduction causes mis-splicing of the phototransduction genes in human organotypic retinal culture. Eur J Hum Genet 28, 491–498 (2020). 10.1038/s41431-019-0531-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Veltman J. A. & Brunner H. G. De novo mutations in human genetic disease. Nat Rev Genet 13, 565–575 (2012). 10.1038/nrg3241 [DOI] [PubMed] [Google Scholar]
  • 38.Petersen-Jones S. M. et al. Patients and animal models of CNGβ1-deficient retinitis pigmentosa support gene augmentation approach. J Clin Invest 128, 190–206 (2018). 10.1172/jci95161 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Lee W. et al. Cis-acting modifiers in the ABCA4 locus contribute to the penetrance of the major disease-causing variant in Stargardt disease. Hum Mol Genet 30, 1293–1304 (2021). 10.1093/hmg/ddab122 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Robson A. G. et al. ISCEV Standard for full-field clinical electroretinography (2022 update). Doc Ophthalmol 144, 165–177 (2022). 10.1007/s10633-022-09872-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Li H. & Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009). 10.1093/bioinformatics/btp324 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.DePristo M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43, 491–498 (2011). 10.1038/ng.806 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Wang K., Li M. & Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38, e164 (2010). 10.1093/nar/gkq603 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Yeo G. & Burge C. B. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol 11, 377–394 (2004). 10.1089/1066527041410418 [DOI] [PubMed] [Google Scholar]
  • 45.Jaganathan K. et al. Predicting Splicing from Primary Sequence with Deep Learning. Cell 176, 535–548.e524 (2019). 10.1016/j.cell.2018.12.015 [DOI] [PubMed] [Google Scholar]
  • 46.Freeman P. J., Hart R. K., Gretton L. J., Brookes A. J. & Dalgleish R. VariantValidator: Accurate validation, mapping, and formatting of sequence variation descriptions. Hum Mutat 39, 61–68 (2018). 10.1002/humu.23348 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Richards S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17, 405–424 (2015). 10.1038/gim.2015.30 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Ellard S. et al. ACGS best practice guidelines for variant classification 2019. Assoc. Clin. Genet. Sci, 1–32 (2019). [Google Scholar]
  • 49.Gruber A. R., Lorenz R., Bernhart S. H., Neuböck R. & Hofacker I. L. The Vienna RNA websuite. Nucleic Acids Res 36, W70–74 (2008). 10.1093/nar/gkn188 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Johnson P. Z. & Simon A. E. RNAcanvas: interactive drawing and exploration of nucleic acid structures. Nucleic Acids Res 51, W501–w508 (2023). 10.1093/nar/gkad302 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.McHarg S. et al. Mast cell infiltration of the choroid and protease release are early events in age-related macular degeneration associated with genetic risk at both chromosomes 1q32 and 10q26. Proc Natl Acad Sci U S A 119, e2118510119 (2022). 10.1073/pnas.2118510119 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Langmead B. & Salzberg S. L. Fast gapped-read alignment with Bowtie 2. Nat Methods 9, 357–359 (2012). 10.1038/nmeth.1923 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Li H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009). 10.1093/bioinformatics/btp352 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Wang J. et al. ATAC-Seq analysis reveals a widespread decrease of chromatin accessibility in age-related macular degeneration. Nat Commun 9, 1364 (2018). 10.1038/s41467-018-03856-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Cherry T. J. et al. Mapping the cis-regulatory architecture of the human retina reveals noncoding genetic variation in disease. Proc Natl Acad Sci U S A 117, 9001–9012 (2020). 10.1073/pnas.1922501117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Van de Sompele S. et al. Multi-omics approach dissects cis-regulatory mechanisms underlying North Carolina macular dystrophy, a retinal enhanceropathy. Am J Hum Genet 109, 2029–2048 (2022). 10.1016/j.ajhg.2022.09.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Roithová A. et al. The Sm-core mediates the retention of partially-assembled spliceosomal snRNPs in Cajal bodies until their full maturation. Nucleic Acids Res 46, 3774–3790 (2018). 10.1093/nar/gky070 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1
media-1.pdf (1.8MB, pdf)
Supplement 2
media-2.pdf (290KB, pdf)
Supplement 3
media-3.pdf (377.4KB, pdf)
Supplement 4
media-4.pdf (415.1KB, pdf)
Supplement 5
media-5.pdf (436.5KB, pdf)
Supplement 6
media-6.xlsx (72.7KB, xlsx)
Supplement 7
media-7.xlsx (12.3KB, xlsx)
Supplement 8
media-8.xlsx (9.2KB, xlsx)
Supplement 9
media-9.xlsx (81KB, xlsx)
Supplement 10
media-10.xlsx (73.7KB, xlsx)
Supplement 11
media-11.xlsx (9.5KB, xlsx)
Supplement 12
media-12.docx (18.8KB, docx)
Supplement 13
NIHPP2025.01.06.24317169v1-supplement-13.pdf (198.7KB, pdf)

Data Availability Statement

Research on the de-identified patient data used in this publication from the Genomics England 100,000 Genomes Project and the NHS GMS dataset can be carried out in the Genomics England Research Environment subject to a collaborative agreement that adheres to patient-led governance. All interested readers will be able to access the data in the same manner that the authors accessed the data. For more information about accessing the data, interested readers may contact research-network@genomicsengland.co.uk or access the relevant information on the Genomics England website: https://www.genomicsengland.co.uk/research. The data generated during this study (pathogenic variants and VUSs identified) are submitted to the Leiden Open (source) Variation Database (LOVD) (http://www.lovd.nl) and ClinVar.

Articles from medRxiv are provided here courtesy of Cold Spring Harbor Laboratory Preprints

RESOURCES