De novo variants in the splicing factor gene SF3B1 are associated with neurodevelopmental disorders

Domain: neuroscience
Published: 2026-01-23
Editorial outcome: minor_revision

Abstract
SF3B1 is an essential and ubiquitous splicing factor that plays a pivotal role in the early steps of pre-mRNA splicing. Recurrent somatic missense mutations in SF3B1 are frequent in cancers, but no constitutional variant has been reported so far. We describe here a cohort of 26 individuals with neurodevelopmental disorders, harbouring SF3B1 constitutional heterozygous variants that appeared mostly de novo. Patients present with a global developmental delay, associated with variable neurological and facial dysmorphic traits. A dichotomy may emerge between patients harbouring predicted loss of function (n=9) and missense variants (n=17), the latter being associated with a more severe and syndromic phenotype, including heart and gastrointestinal anomalies. We focused on de novo SF3B1 missense variants, which were largely distinct from those reported in cancer. Functional complementation assays show that de novo SF3B1 missense variants did not cause a loss of function of the protein. Targeted and genome-wide analysis of RNA splicing reveal that they affect canonical and alternative splicing more moderately than somatic variants, and subtly modify the splicing of many transcripts. These findings place SF3B1 among the rare U2 snRNP components implicated in both cancer and neurodevelopmental disorders, highlighting its critical and multifaceted role in human disease.

Introduction
RNA splicing is a crucial process in eukaryotes where introns are excised from a nascent pre-messenger RNA (pre-mRNA), and adjacent exons are joined to form a mature mRNA. Alternative RNA splicing is a complex and highly regulated mechanism that widely diversifies the proteome by creating multiple proteins from a single gene1. In humans, most introns are recognized and excised by the major spliceosome, which consists of a large and dynamic ribonucleoprotein (RNP) complex including small nuclear RNAs (U1, U2, U4/U6 and U5), in interaction with auxiliary proteins. The spliceosome assembly relies on sequential and dynamic RNA-RNA interactions between U2 and U6 small nuclear RNA (snRNA), and between snRNAs and intronic splice sites2. Disruption in spliceosome components due to genetic variants lead to disorders referred to as spliceosomopathies3.

SF3B1 (Splicing factor 3b, subunit 1) is an essential, ubiquitously abundant protein, which plays a pivotal role in the early steps of pre-mRNA splicing, by stabilising the U2 snRNP complex at branch point (BP) sequences. SF3B1 is the largest subunit of SF3b, a heptameric protein complex of U2 snRNP. SF3B1 comprises an unstructured N-terminal domain and a conserved highly structured C-terminal domain called HEAT (Huntington Elongation Factor 3 protein, phosphatase 2A and the yeast PI3-kinase TOR1), composed of 20 repeats4. SF3B1 is the most frequently mutated RNA splicing factor across cancers, notably in haematological malignancies5 including myelodysplastic neoplasms6 and chronic lymphocytic leukaemia, as well as in solid tumours, such as uveal melanoma7, breast and pancreatic cancers. Until now, only somatic cancer-associated variants of SF3B1 have been reported. They are essentially missense heterozygous variants resulting in recurrent amino acid substitutions in the H4-H8 repeats of the HEAT domain, with K700E hotspot being the most frequent4.

RNA seq studies conducted in various cancers have shown that SF3B1 somatic variants are change-of-function variants that alter canonical and alternative splicing through the recognition of cryptic BP and the use of cryptic or alternative 3’ splice sites7–9, leading to a remodelling of approximately 1% of the transcriptome. As a result, novel transcripts involved in a diversity of cellular pathways are generated, which may be recognized by nonsense mediated mRNA decay (NMD) or may lead to novel protein isoforms8,10. Although all somatic SF3B1 variants alter the proper recognition of BP sequences, the missplicing pattern can partly vary with the variant nature, and some variants of SF3B1 have been associated with distinct clinical outcomes, highlighting differential functional impact of cancer-associated SF3B1 variants11,12.

Defects in spliceosome genes, including components of U2 snRNP, have been described in various syndromes, notably neurodevelopmental disorders (NDD)13,14. NDD of genetic origin are a heterogeneous group of condition that manifest during childhood, including intellectual disability (ID) and autism spectrum disorder (ASD), collectively affecting 3% of the population15–18. Exome or genome sequencing has become a standard procedure for the aetiological diagnosis of these disorders19. More than 1500 genes are known to be involved in NDD15, some of them encode components or regulators of the spliceosome20,21. The latter includes genes encoding core or auxiliary components of the U2 snRNP complex to which SF3B1 belongs, such as U2AF220, the U2 snRNA RNU2-222 or PUF6023. Deleterious variants in PUF60 are responsible for Verheij syndrome (MIM:#615583) in which ID is accompanied by microcephaly and various skeletal malformations13,20,23,24.

Here, we report a cohort of 26 individuals with NDD, harbouring SF3B1 variants, which appeared mostly de novo and are largely distinct from those commonly found in cancer. Given the prevalence of de novo variants in developmental disorders25 and the essential function of SF3B1 in pre-mRNA splicing, we postulated that pathogenic de novo variants affecting the function of SF3B1 could be implicated in NDD. To decipher the molecular and cellular consequences of these de novo SF3B1 variants, we conducted targeted analysis and RNA sequencing (RNAseq) in dedicated cellular models expressing the SF3B1 variants of interest. Our findings provide compelling evidence supporting an association between de novo SF3B1 variants and NDD.

Results
Patients carrying predicted loss-of-function and missense variants of SF3B1 present with a neurodevelopmental syndrome
The 26 individuals participating in the study were included based on the identification of a heterozygous SF3B1 variant identified by exome or genome sequencing, suspected to be pathogenic according to in silico predictions, frequency in population databases and/or inheritance and segregation in the family. In total, we identified 25 distinct SF3B1 variants that mostly occurred de novo, in 26 unrelated individuals, with one of the variants being recurrent. Our cohort comprised 10 female and 16 male patients with an age range of 1–24 years at the time of inclusion in the cohort. Clinical data are presented in Fig. 1, Table 1 and Supplementary Data 1. We did not find any other genetic variant that may explain the phenotype of the patients (Supplementary Data 1), except for patient 1, who carries a variant of uncertain significance in the LARP1 gene, for patient 19, who is heterozygous for an inherited variant in CACNA1A, and for patient 22, who carries an inherited variant of uncertain significance in RORA.

The series encompasses 16 missense variants and 9 putative loss-of-function (pLoF) variants, including three splicing variants, three nonsense, one frameshift insertion and two frameshift deletions (Fig. 2A). All variants were absent from the general population databases (gnomAD V4.1.0-NonUKB), except for p.R397H found in one individual, arguing against simple polymorphism. All variants were private, except for the p.R939C missense variant, found in two unrelated individuals. The use of several splicing prediction tools (MaxEntScan26, SpiP27, dbscSNV28, SpliceAI29) does not provide strong evidence that missense variants may disrupt an ESE or favour usage of a novel splice site (Supplementary Table 1). We investigated the 16 missense variants using in silico pathogenicity predictors (SIFT, PolyPhen2, Mutation Taster, CADD, REVEL, Alphamissense) and found that most were predicted to be pathogenic (Supplementary Table 2). These variants often affect highly conserved amino acids in constrained SF3B1 regions, as indicated by the missense tolerance ratio (MTR) and CADD scores (Fig. 2C). Based on ACMG (American College of Medical Genetics and Genomics) guidelines and presuming a gene-disease association, most variants were classified as Likely Pathogenic or Pathogenic, except four of them (classified as of uncertain significance), namely p.N829S, p.A1229G, p.R736C and p.R397H (Supplementary Table 3).

Almost all (23/26) affected individuals exhibited at least one neurodevelopmental abnormality, the most frequent being language delay (21/26). Motor delay was found in 18/24 individuals. Intellectual disability (ID) was present in 9/15 individuals, some cases being too young (8/26) to assess. The severity of ID was mainly mild to moderate, only two individuals presenting with severe ID (12 and 21). Individuals 9 and 10, although not presenting with neurodevelopmental delay, suffered from spastic quadriplegia. Seizures were reported in 13 individuals, with variable ages of onset and types, but infantile spasms were recurrent (3/13). Other notable neurological features included hypotonia, which was present in eleven patients. When performed, brain MRI did not identify recurrent abnormalities, except a corpus callosum anomaly in two individuals (3 and 22), and posterior fossa anomaly in two other cases (2 and 8).

Dysmorphic features were found in 20/26 individuals, although we could not identify a typical facial gestalt (Fig. 1B). Some non-specific signs, such as low-set ears, were recurrent, as well as cupid’s bow lips, found in two patients. The most notable feature was palatal abnormality, as 12 patients exhibited cleft palate or a high-arched palate. Ophthalmologic findings were not specific.

Heart anomalies were found in 8/25 individuals, mostly atrial and ventricular septal defects (patients 15, 16, 17, 20). The individual presenting the most severe cardiac condition was case 6, who was diagnosed with tetralogy of Fallot.

Intrauterine growth retardation was present in five individuals, and six individuals exhibited postnatal short stature. Head circumference, when available, was normal in 15 individuals, whereas seven presented with microcephaly. The most recurrent and notable findings were feeding challenges. Eight patients suffered from feeding difficulties, with the need for a gastrointestinal tube during infancy for six of them, resulting in growth delay or low weight.

Almost all variants arose de novo, except in three cases (P21, P22, P23) that were all pLoF variants. In two of these cases, the parent carrying the variant was symptomatic. In individual 21, the variant p.E809Dfs*7 was inherited from the mother, who had learning difficulties. His sister, also carrying the variant, presented with developmental delay, autism spectrum disorder and learning difficulties. One maternal uncle had adaptive schooling and was followed in psychiatry. Two maternal aunts stopped school early, and one first cousin, deceased, presented with seizures and development delay. In individual 22, the father carrying the variant p.V695Wfs*34 presents with development delay and discontinued formal education at the age of 14. In only one case (individual 23), the variant p.R166* was inherited from an asymptomatic father; however, segregation analysis revealed that the variant had arisen de novo in the father. Finally, in individual 24, the segregation was incomplete due to the absence of paternal DNA.

To investigate a putative genotype-phenotype correlation, we first performed an unsupervised clustering of clinical features. This clustering suggested the presence of three patient groups, which appear to differ in terms of phenotype severity and variant type (Fig. 1A). The left cluster comprised three patients presenting only with abnormal muscle tone, two of whom carried a pLoF variant. In the right cluster, where most patients harboured a missense variant, we observed a trend toward more severe phenotypes and a higher frequency of congenital anomalies, suggesting a possible correlation between the type of variation (missense or pLoF) and the clinical outcome. To mitigate potential bias arising from missing data, we performed unsupervised clustering after excluding clinical variables with missing information in more than 30% of patients. This analysis yielded comparable results, with missense variants consistently clustering together (Supplementary Fig. 1). More specifically, short stature was mostly found in individuals with missense variants (7/13 vs 1/7), as well as gastrointestinal abnormalities (mainly feeding difficulties, with the need of gastrostomy, 9/14 vs 2/9) (Table 1). Microcephaly was present in 6/14 individuals with missense variants, and in only one individual with a pLoF variant. Congenital anomalies, especially cardiac malformations, were also more frequent in patients with missense variants (7/16 vs 1/9), as well as palatal defects (11/17 vs 1/9). The only variants that were inherited were pLoF, also suggesting that they could be associated with a less severe phenotype or a variable expressivity. Overall, these findings suggest that missense variants could have a functional effect different from pLoF variants.

SF3B1 variants associated with neurodevelopmental disorders are distinct from cancer-associated SF3B1 variants
The missense variants affect highly conserved amino acid positions, which are distributed along the HEAT domain except for R397 and P370 (Supplementary Fig. 2 and Fig. 2D). Six missense variants impact amino acids that are clustered into H4 to H8 repeats, like the most frequent somatic variants (including p.R625H, p.K666N and p.K700E).

To better understand the consequences of the missense variants on SF3B1 function, we mapped the position of the residues on the SF3B1 structure from a human activated spliceosome (mature Bact complex) (PDB: 5Z56) (Fig. 2D). SF3B1 is required to stabilise the U2 snRNA-pre-mRNA duplex at the BP region, making this step of the splicing cycle relevant to study. Remarkably, the substituted residues are mainly located on the same side of the HEAT domain, facing the pre-mRNA. Only three residues (R736, E722 and R939) face outward. Notably, the residues T703, R736, K741 and P780 are in a pocket (namely the RNA path) that faces the three most affected residues in cancer, i.e. R625, K666 and K700 (Fig. 2D). We aimed to predict possible consequences of the substitutions on SF3B1 intramolecular and intermolecular interactions using Pymol. For the most part, the substituted residues are predicted to affect interactions within a HEAT repeat helix, between different HEAT repeat helices or with SF3B1 partners (Fig. 2E and Supplementary Fig. 3). Some substitutions, such as T703P, are predicted to increase intramolecular interactions, rigidifying the structure locally, while others may disrupt local interactions (such as N829S, R939C). Glutamic acids at positions 906 and 1029 are close to the pre-mRNA, and the change of charge induced by the substitution by a lysine may affect the positioning of the pre-mRNA. The proline at position 780 is in a close proximity with the pre-mRNA and the protein RBMX2 and its substitution by a leucine may affect these interactions. Remarkably, half the missense variants lead to substitution of residues located close to residues directly involved in the interaction with DDX42 and DDX4630,31 helicases, which act in the early steps of spliceosome assembly. In particular, K741 has been shown to directly interact with DDX42 and DDX46. Since the spliceosome undergoes intense compositional and structural changes during the splicing cycle, some of the substituted residues may be involved in other important interactions, beyond the Bact complex.

Notably, out of the 15 missense variants, 8 were not reported at all in the Catalogue of Somatic Mutations in cancer database (COSMIC), while 7 of them were reported in only a few cases of tumour samples or cell lines (range of 1 to 4 reported cases) (Supplementary Table 4), including p.T703P, p.E722K, p.R736C and p.K741Q. This suggests that the SF3B1 variants associated with NDD are predominantly distinct from common cancer-associated SF3B1 variants.

SF3B1 missense variants associated with a neurodevelopmental disorder do not cause a loss-of-function
We aimed to determine the functional consequences of de novo SF3B1 missense variants, the most frequent variants in our series. To investigate both change-of-function (as for cancer-associated variants) and loss-of-function hypotheses, we followed the same targeted approach previously used by our group for other SF3B1 variants32. Importantly, somatic SF3B1 variants are neomorphic variants that lead to splicing alterations distinct from those observed upon SF3B1 silencing (siSF3B1/shSF3B1)33,34. The principle of the analysis was to express the SF3B1 variants of interest in a same cellular model in which the expression of endogenous SF3B1 was silenced, in order to study the ability of each SF3B1 variant to suppress the splicing and cell proliferation defects caused by endogenous SF3B1 silencing. Considering the high occurrence of SF3B1 somatic mutations in haematological neoplasms, we decided to use erythroleukemia K562 cells as a cellular model to study all de novo SF3B1 missense variants, in comparison to well established controls developed in this cell model. Indeed, several RNAseq and functional studies have been performed in K562 cells harbouring cancer-associated SF3B1 mutations, both by our group32 and by others35–37.

Four additional missense variants were identified in patients after experimental work was near completion, for this reason we studied a total of 11 (out of 15) SF3B1 missense variants. The steady-state levels of each variant protein, tagged with a FLAG epitope on N-terminus, were similar to the wild type counterpart, indicating that each variant preserves the stability of the protein (Supplementary Fig. 4). We then investigated specific exon skipping events known to be altered upon SF3B1 silencing, in particular in DUSP11 (exon 6) and RBM5 (exon 16)32. As a control, we included a condition in which an inactive isoform of SF3B1 was expressed, namely SF3B1ins, which we previously characterized as an aberrant transcript produced upon expression of K700E32. Moreover, should the E980* variant escape the NMD pathway, thereby leading to the translation of a truncated protein, we sought to investigate the functionality of the resulting polypeptide. As expected, expressing the truncated E980* protein did not suppress the splicing defects caused by SF3B1 silencing, confirming the essential nature of the last third of the HEAT domain. In contrast, expressing each missense variant restored splicing proficiency, indicating that none of the eleven missense variants led to a loss-of-function phenotype (Fig. 3A, B and Supplementary Fig. 4). To confirm these results, we used the same readouts in an alternative cell model, HEK293T, in which we expressed eight missense variants (Supplementary Fig. 5) and obtained similar findings.

We then studied the ability of selected SF3B1 variants to suppress the proliferation defect caused by SF3B1 silencing. Four SF3B1 variants (E722K, P780L, N829S and E980*) were expressed under the control of a doxycycline-inducible promoter in K562 cells in which endogenous SF3B1 was silenced. While expressing the E980* truncated protein was unable to restore cell proliferation, as observed for the inactive splicing isoform used as a control (SF3B1ins), expressing each of the three missense variants E722K, P780L and N829S restored the cell proliferation at a level similar to the wild type counterpart (Fig. 3C, D), as previously reported for K700E32. These results confirm that E722K, P780L and N829S variants do not abolish the function of the SF3B1 protein.

To investigate whether the missense variants would share similarities with cancer-associated SF3B1 variants, we studied specific splicing events in TMEM14C, ENOSF1, SEPT6, SF3B1(ins), MAP3K7, ZDHCC16 and DLST, which are known to be mis-spliced upon expression of the K700E variant. Using this splicing assay, we showed that only P780L, and, to a lesser extent, T703P, shared some similarities with the cancer-associated K700E variant, with lower inclusion levels (Fig. 3E).

Overall, none of the eleven NDD-associated SF3B1 missense variants that have been studied caused a loss-of-function of the protein, suggesting a molecular mechanism different from that observed with disruptive variants (pLoF). Furthermore, two missense variants shared partial similarities with K700E, suggesting a reduced fidelity in the recognition of BP sequences.

Denovo SF3B1 missense variants E722K, P780L and N829S alter RNA splicing more moderately than K700E
To investigate whether the missense variants would affect canonical and alternative splicing at the transcriptome level, we performed RNA sequencing in K562 cells stably expressing selected missense variants (E722K, P780L and N829S), in comparison to wild type SF3B1 (Fig. 4A). We also included the most studied cancer-associated variant, K700E, as a comparison. Given that none of these variants led to a loss-of-function, we decided to induce the expression of the variants in a background in which endogenous SF3B1 was not silenced, so that we could maintain equivalent levels of endogenous and recombinant SF3B1 protein, mimicking a heterozygous state, which was verified by western-blotting (Supplementary Fig. 6A). Moreover, at both RNA and protein levels, the three recombinant NDD-associated SF3B1 variants and the wild type (recombinant) counterpart were expressed at a similar level (Supplementary Fig. 6B).

The alternative splicing analysis consisted of the detection and the quantification of the five classical splicing events (SE= skipped exons, A5'SS= alternative 5′ splice sites, A3'SS= alternative 3′ splice sites, RI= retained introns, MXE= mutually exclusive exon usage) using the software rMATS (turbo v4.1.2). We selected splicing events with a minimum percent spliced In (PSI) of 0.1, i.e. alternative or aberrant transcripts representing at least 10% of total transcripts at a specific junction. We analysed differentially spliced junctions associated with each variant in comparison to the wild type condition, focusing on the events with an absolute value of delta PSI (PSISF3B1var — PSISF3B1wt) set to a minimum of 0.1. The proportion of splicing types affected by K700E was similar to that reported in the literature36 with an edited K562-K700E cell line, validating our inducible cellular model. Overall, differential analysis of splice junctions showed an impact of each variant on global alternative splicing, affecting both known and, mainly, novel junctions (i.e. not annotated) (Fig. 4B). The effect of NDD-associated variants was quantitatively less important than for the K700E variant. The number of genes with significantly differentially spliced transcripts was between 1374 and 1715, compared to 2022 for K700E. However, many significant differentially spliced junctions had a delta PSI between 0.1 and 0.2 (Supplementary Fig. 6), which requires to nuance the interpretation of the functional impact of such events. Of note, with a delta PSI cut-off at 0.25, the number of genes with significantly differentially spliced transcripts was 448 for E722K, 532 for P780L, 417 for N829S and 715 for K700E. When considering novel junctions, NDD-associated SF3B1 missense variants modulate all classes of alternative splicing (Fig. 4C, Supplementary Fig. 7 and 8), but mainly SE, which is the most prevalent type of alternative splicing in human cells38, and A3’SS events. Pairwise comparisons of proportions indicate that P780L impacted (known and novel) splicing events in a similar proportion to K700E, except for MXE (p=0,0024) that was more represented in P780L. While the proportions of A5’SS and RI were unchanged by the SF3B1 mutational status, the proportion of SE in E722K and N829S was higher than that observed in K700E, at the expense of A3’SS events. Nevertheless, the proportion of novel splicing events was overall similar whatever the variant (Fig. 4D and Supplementary Fig. 6).

To further support these findings in a more clinically relevant model, we examined alternative splicing profiles (using rMATS) in short-term cultured lymphocytes derived from two NDD patients (carrying variants p.N829S and p.P370L) in comparison to 14 controls. Remarkably, principal component analysis (PCA) showed that the two patient samples clustered together and separately from the controls, which strongly suggests a distinct splicing signature associated with N829S and P370L variants (Fig. 4G and Supplementary Fig. 9).

To investigate whether some pathways would be predominantly affected by SF3B1 variants, we performed a Gene set enrichment analysis (GSEA) on the list of significant genes showing aberrant splicing events identified by rMATS. When considering all splicing events, the most significant terms associated with each variant included cytoplasmic translation, ribosome biogenesis, RNA splicing and RNA processing, Nonsense Mediated Decay, DNA repair as well as axon guidance and nervous system development (Table 2, Fig. 4F and Supplementary Fig. 10). The latter term covered 59 differentially spliced genes for E722K, 60 for N829S and 70 for P780L (98 for K700E), among which 19 to 27 were A3’SS events. Moreover, the term « Disorders of nervous system development » was enriched for P780L, with missplicing of SIN3A, TBL1XR1, HDAC3, NCOR2 and TBL1X, some of which in common with N829S and E722K. When performing GSEA with KEGG pathways, the terms Ribosome, Ubiquitin mediated proteolysis and Nucleocytoplasmic transport were shared between two or three NDD-associated variants.

To further investigate the impact of each variant on the transcriptome, we performed a differential gene expression analysis (Supplementary Data 2). The number of Differentially Expressed Genes (DEG) was low in comparison to that reported for K700E (n=104), especially for N829S (n=4) and E722K (n=5), suggesting a more moderate overall impact on gene expression for the latter. In contrast, P780L presented with 23 DEG. Interestingly, the gene encoding the ribosomal protein RPS15A, a component of the 40S subunit which has been associated with Diamond-Blackfan anaemia39 and several cancers, was underexpressed in both N829S and P780L expression conditions. MTRNR2L12, encoding a little-studied humanin-like peptide which might have a neuroprotective role40, was underexpressed in both E722K and N829S expressing cells. The number of DE transcripts was higher (n=131 for E722K, n=236 for N829S, n=382 for P780L and n=329 for K700E) and some of them were also misspliced (Supplementary Fig. 11). GSEA shows enrichment in genes involved in several pathways, including the regulation of transcription by RNA polymerase II, DNA metabolic process, chromosome organisation and RNA splicing, as well as in translation (initiation, regulation) (Supplementary Data 3). Given that more than 1500 NDD-associated genes have been reported so far, it is not surprising that DE transcripts and/or differentially spliced genes in our study include many genes that are known to be associated with NDD (Supplementary Fig. 12). Considering RNA splicing is tightly regulated in a cell-type-specific manner, and that splicing outcomes observed in one cellular context may not fully recapitulate those in other tissues, further validation in additional cell models would be necessary to characterize the tissue-specific effects of the variants.

Impact of de novo SF3B1 missense variants on the selection of cryptic 3’ splice sites
To further characterize the impact of each variant on RNA splicing, we investigated whether the different variants affected the same junctions, focusing on SE and A3’SS events (Fig. 4E and Supplementary Fig. 8). For each variant, 25–32% of SE events were found in common with K700E, suggesting limited common mechanisms between somatic and germline variants. Among those, 50 SE events were shared by all four variants, while NDD-associated SF3B1 variants shared 84 SE events (Fig. 4E). Remarkably, approximately one third of differentially spliced SE events (31% to 37.5%) was shared with at least another SF3B1 NDD-associated variant. Nevertheless, most differentially SE were actually unique or shared with another variant.

Regarding A3’SS events, between 61% and 74% of events were variant specific. Nevertheless, 164 A3’SS events were found in common between 2 or 3 NDD-associated SF3B1 variants (Fig. 5A and Supplementary Fig. 8). In particular, the P780L variant shared the most A3’SS events with the K700E cancer variant, with a total of n=158, compared to n=89 for E722K and n=93 for N829S. As illustrated in the Sashimi plots (Supplementary Fig. 13), P780L altered the splicing of SEPT6 less drastically than K700E, as observed by end-point RT-PCR (Fig. 3E). Other interesting examples of transcripts showing A3’SS events exclusively within both P780L and K700E variants include ENOX2, HSPBP1 and the oncogenic long non-coding RNA CRNDE, as confirmed by an alternative method (Fig. 5B). Among the A3’SS events that were found in common (38 events, including 24 shared with K700E), we noticed a low and variable PSI, suggesting that each variant affects splicing differently in a subtle way (Supplementary Fig. 8). Importantly, when we extended the study of CRNDE, ENOX2 and HSPBP1 missplicing to the other variants, we found that L536I and T703P led to similar missplicing (Fig. 5D and Supplementary Fig. 5E).

Given the known function of SF3B1, we specifically analysed the sequence of the A3’SS junctions that were differentially used by SF3B1 variants. Remarkably, the distance between alternative AG’ and canonical AG was different (Fig. 5E). For K700E, the cryptic site was on average located at a distance of 17 nucleotides from the canonical AG, as previously reported in the literature41. Similar results were obtained with the somatic R625H variant, validating the inducible model used in this study for splicing analysis. In contrast, the NDD-associated SF3B1 variants preferentially selected cryptic AG’ that were mainly located closer to the canonical AG, with a peak centred to 7 nucleotides for both P780L and E722K (Fig. 5E), suggesting different sequence requirements. Moreover, we found that each of the NDD-associated SF3B1 variants mostly leads to the selection of cryptic AG’ that are located downstream of the canonical AG, in contrast to K700E and R625H (Fig. 5F). Notably, a second peak was visible for P780L, which mapped to the main peak observed for K700E/R625H, reflecting A3’SS events with cryptic AG’ located upstream of canonical AG. Analysing the motif frequency plots for aberrant AG’ and canonical AG allowed us to define sequence motifs that appeared to be relatively distinct from the one observed upon K700E expression (Fig. 5G). Nevertheless, differences between density plots were modest, suggesting that small differences in polypyrimidine tract composition rather than major branch point changes are likely responsible for the observed splicing differences.

Alternative splicing choices are determined by interactions between RNA-binding proteins (RBP) and cis-regulatory binding motifs located in introns and exons. We performed motif analyses of RBP in the vicinity of the junctions that were mis-spliced upon expression of NDD-associated SF3B1 variants, using rMAPS242 (Supplementary Table 5). Regarding A3’SS events, we report an enrichment in SRSF1 binding motifs and a depletion of motifs for SRSF9, RBM47, SRp40, SRp20 and PCBP2. Sequences in the vicinity of alternative SE events are enriched with motifs for the following RBP: HuR, RBM42, HNRNPA1, PCBP1 and PTBP1 (5’ of exons), as well as SRSF1, PABPC3 and A1CF (3’ of exons), and are depleted of motifs for RBMS3 and CNOT4 (5’ of exons), as well as for HNRNPA1L2 and RBMS3 (5’ of exons). This analysis suggests that SF3B1 variants may favour usage of cryptic splice sites in cooperation with specific RBP.

Methods
Patient recruitment and clinical data analysis
A total of 26 individuals were included in our study. Individual 1’s variant was identified by whole exome sequencing in the framework of the HUGODIMS consortium, whose goal was to investigate the molecular basis of developmental disorders in a research setting. The 25 remaining affected individuals were enroled after submitting the SF3B1 variant found in individual 1 to the GeneMatcher platform51. The variants in these 26 individuals were identified either by trio or solo exome sequencing (ES) conducted primarily in a diagnostic setting, or within various research cohorts. All data included in this study were collected and shared in compliance with institutional policies and applicable regulations. This study was approved by the ethics committee of Nantes CHU Hospital (comité consultatif sur le traitement de l’information en matière de recherche no. 14.556). All families gave written informed consent for inclusion in the study and for publication according to their respective institutional IRB approved protocols. All patients or their guardians have seen the data within the context of the publication. The authors affirm that human research participants (P1, P6, P7, P12, P16, P18, P21, P23, P25 and P26) provided written informed consent for publication of the images in Fig. 1. The individuals or their guardians have seen the photographs within the context of the publication. Clinical data were collected from the referring physician using an anonymized Excel sheet. Categorical data for 15 clinical features from all patients were converted to 0 (absent), 0.5 (present, mild), or 1 (present). Hierarchical clustering was performed using pheatmap R package, using ward.D2 clustering method keeping missing values. In this manuscript, the term predicted loss-of-function (pLOF) is restricted to nonsense, frameshift and canonical splice-site variants. Missense variants are gathered in a unique category, regardless of their functional impact.

Prediction software and variant classification
The prediction of missense variants’ pathogenicity was assessed using common in silico predictors, such as SIFT52, PolyPhen253, Mutation Taster54, MetaSVM55, CADD56, REVEL57 and Alphamissense58. CADD scores were compared with scores of rare variants (i.e. allele frequency <10–5) in gnomAD V4.1. The mean scores were compared using independent t tests. Protein missense tolerance ratio (MTR) was visualised using MTR-Viewer59. We adopted the 31-codon sliding window and used exome-sequencing standing-variation data in the gnomAD database, version 2.0. MTR data were downloaded from Missense Tolerance Ratio (MTR) Gene Viewer (http://mtr-viewer.mdhs.unimelb.edu.au/mtr-viewer/). A simulation of variant classification according to the American College of Medical Genetics and ClinGen recommendations60–62 was made, with the assumption of a definitive gene-disease association. The Pymol Software (The PyMOL Molecular Graphics System, Version 2.5 Schrödinger, LLC) was used to visualise and explore structures containing SF3B1 (PDB: 5Z56). Pymol’s mutagenesis tool was used to produce the 2E panel.

Cloning and directed mutagenesis
Plasmids encoding P370S, P370L, L536I, T703P, E722K, P780L, N829S, E906K, R939C, E980*, E1029K and A1229G variants of SF3B1 were produced by site directed mutagenesis (QuikChange II XL Site-Directed Mutagenesis Kit, Agilent) using pCMV-3tag-SF3B1 plasmid as a template, which contains an optimised version of SF3B17,32. The correct introduction of mutations was confirmed by Sanger sequencing. Four SF3B1 variants (E722K, P780L, N829S, E980*) were introduced in the lentiviral plasmid pCW57.1 using In-Fusion® HD Cloning Plus kit (Takara), according to the manufacturer’s instructions. Primers used for cloning and directed mutagenesis are listed in Supplementary Data 4. shSF3B1 and siSF3B1 targeting endogenous SF3B1 mRNA (3’UTR) were designed as described previously32.

Generation of SF3B1 inducible K562 cell lines
Lentiviral particles (pCW57.1) were produced by the Vect’UB vectorology core facility (Bordeaux, France). K562 cells were transduced with a multiplicity of infection of 2. Selection of stable positive cells was done with puromycin (Sigma) for SF3B1 inducible cell lines or G418 (Sigma) for shSF3B1 inducible cell lines (pLKO-Tet-on plasmid). Transduction with the shSF3B1 construct was done in K562 stable cell lines expressing SF3B1wt, SF3B1K700E, SF3B1ins, SF3B1E722K, SF3B1P780L, SF3B1N829S and SF3B1E980* to obtain co-transduced stable cell lines. Expression of recombinant SF3B1 and/or shSF3B1 was induced by treating cells with 2 microg/mL of doxycycline (Sigma).

Cell culture
The K562 and HEK293T cell lines were obtained from ATCC. K562 and K562-derived cell lines were cultured in RPMI 1640 medium (Gibco), supplemented with 10% foetal bovine serum (Gibco) and 2 mM of L-glutamine (Gibco), at 37°C and 5% of CO2. K562 cells were transfected by electroporation using Cell Line NucleofectorTM Kit V (Amaxa, Lonza) according to the manufacturer’s instructions. Transfections were done with 2×106 cells and 4 μg of plasmid and/or 30 pmol of SF3B1 siRNAs designed to specifically target the 3’UTR sequence, as described previously32. HEK293T cells were cultured in EMEM medium (Gibco) supplemented with 10% foetal bovine serum (Gibco) and were transfected with lipofectamine 2000 (Invitrogen) according to the manufacturer’s instructions. Cellular proliferation curves represent the rate of cell growth, defined as the number of living cells at a time relative to the initial number of cells.

RNA extraction and RT-PCR
RNA was extracted from K562 and HEK293T cells using the Nucleospin RNA kit (Macherey-Nagel). Reverse transcription was performed with High Capacity cDNA reverse transcription kit (Applied Biosystems). PCR was performed using GoTaq® G2 DNA Polymerase kit (Promega). Primers used are listed in Supplementary Data 4. PCR products were analysed on 2% or 3% agarose gels or on 6% acrylamide gels. Quantification of DNA bands was performed with Image studio lite software.

Western-blot
Proteins were extracted with a lysis buffer containing NP40 1% — SDS 0,1% and were quantified with the Dc protein kit (Biorad). 30 μg of total proteins were separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto nitrocellulose membranes. We used the following antibodies: anti-SF3B1 (1:4000, A300-996A, Bethyl), anti-FLAG (1:5000, #F3165, Sigma), anti‑actin (1:10000, #ab8226, Abcam), Donkey anti‑mouse (1:5000, #926-32222, LICOR) and goat anti-rabbit (1:5000, #926-2211, LICOR). Immunofluorescence was detected using the Odyssey Infrared Imaging system (LICOR).

RNA sequencing and Bioinformatic analysis
The expression of wild type or variant SF3B1 in K562 was induced for 7 days with 2 microg/mL of doxycycline (in RPMI, 10% FBS, 2 mM Gln 2 μg/mL) before RNA was extracted using Nucleospin RNA kit (Macherey-Nagel). Biological independent replicates (n=3), which refer to independent cultures from the same inducible cell line pool, were realised for each condition. RNA integrity was monitored by Bioanalyser (Agilent), with RNA Integrity Numbers ranging from 9.1 to 9.8. Directional library preparation (rRNA removal) was chosen, and RNA sequencing was performed by Novogene on an Illumina NovaSeq platform, using a 150-bp paired-end sequencing strategy.

After sequencing, raw data were obtained in the fastq format. The software FastQC63 was used for validating the quality of the data and Trimmomatic64 was used for trimming of the adapter content and overrepresented sequences. The alignment of the trimmed sequences to the human transcriptome was performed with the Kallisto tool65. Final normalisation was performed using the Relative Log Expression (RLE) method66 and only transcripts coding for proteins were kept. Differentially expressed transcripts were identified using an adjusted p value cutoff (FDR) <0.05 and absolute values of Fold Change >1.5 with R-package DESeq267. The R package gprofiler268 was used to perform pathway enrichment analysis (DB: GO:BP, KEGG, REAC and WP) with gene symbols as input. The following options were selected: correction_method=fdr, user_threshold=0.05.

Differential splicing analysis
The alternative splicing analysis consisted of the detection of splicing events (SE= skipped exons, A5'SS= alternative 5′ splice sites, A3'SS= alternative 3′ splice sites, RI= retained introns, MXE= mutually exclusive exon usage), the statistical comparison and the effect prediction using rMATS turbo v4.1.2 with the option –novelSS to enable detection of novel splice sites and Homo_sapiens.GRCh38.92.exon as annotation file. rMATS (replicate Multivariate Analysis of Transcript Splicing) is a statistical method for robust and flexible detection of differential AS from replicate RNA-Seq data. Only splicing events with PSI (Percent Spliced In) greater than 10% and adjusted p-value lower than 0.05 have been selected. Novel splice sites were included. The average number of reads covering the splice event was at least 10. UpSet was used to visualise the intersecting sets between 4 or more conditions.

Lymphocyte cultures and RNA sequencing
RNAseq experiments were performed following a protocol similar as previously described for RNU4-269. Briefly, Peripheral Blood Mononuclear Cells were isolated from EDTA blood and cultured in lymphocyte-stimulating medium for 48–72h. Stranded RNA-Seq libraries were prepared from 100 ng total RNA using the SureSelect XT-HS2 kit (Human All Exon V8 capture probes; Ref: G9774C), followed by sequencing on an Illumina NextSeq 550 to obtain ~25–30 million paired-end reads per sample. Reads were aligned to GRCh38 with STAR v2.7.11a. For splicing analysis, we focused on 16 individuals sequenced in the same run: 2 SF3B1 patients carrying N829S and P370L, and 14 probands with NDD without rare variants in SF3B1. rMATS-turbo v4.3.0 was used with 2 cases Vs 14 controls to detect alternative splicing events with the following parameters: -t paired –anchorLength 1 –libType fr-firststrand –novelSS –variable-read-length –allow-clipping. For each splicing category, rMATS outputs were filtered for mean coverage >10, ΔPSI >0.05 and FDR <0.1. We kept only one event by gene, the most significant. To visualize results, we performed principal component analysis using sklearn (v1.7.1) in python (v.3.12.2).

Statistics
The statistical analysis was performed using R version 4.3.1. Furthermore, the prop.test function was used to test proportions of different types of events between groups.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Uguen, Bernot and colleagues report a detailed analysis of the molecular effects of mutations in the splicing factor SF3B1 that they have identified in a cohort of 26 patients displaying neurodevelopmental disorders. The mutations are scattered through most of the primary amino acid sequence of the protein, are distinct from those that appear as somatic mutations in various cancers and can be classified in two main groups, those predicted to cause loss of functon(e.g. in splice sites or causing stop codons) and that they turn out to be inherited, and those harboring missense mutations of less clear predicted significance. Remarkably, the latter group is associated with stronger pathological phenotypes, including beyond neurodevelopmental disorders. Functional characterization in a depletion/complementation system using cell lines shows that the novel mutations do not compromise the general activity of SF3B1 (sustaining cell proliferation) nor induce activation of cryptic 3’ splice sites characteristic of cancer mutations in SF3B1. RNA-seq analyses upon ectopic expression of the mutant proteins, however, show substantial splicing changes associated with the novel missense mutations, most frequently private to individual mutants. Genes important for nervous system development are enriched among the common targets, opening the possibility that their alteration in cells expressing the mutant proteins may eventually explain at least part of the associated phenotypes.\nThese are very relevant observations documenting for the first time the association between neurodevelopmental disorders and mutations in SF3B1, a key core splicing factor frequently mutated in cancer and target of anti-tumor drugs. The detailed molecular characterization of the splicing activities associated with a substantial number of mutants sheds light both on common principles of SF3B1 alterations as well as on the distinct properties conferred by the different mutations and their correlation with the severity of symptoms, highlighting the variety of regulatory functions of a core component of the spliceosome in charge of the fundamental role of recognizing the branch point in pre-mRNAs.\nIn my opinion the following revisions could help to improve the manuscript:\n1. Figure 2E: it is not easy to understand from the figure which interactions (with which residues and the predicted consequences) are affected by the indicated mutations. Additional discussions in the main text and/or Figure legend would be helpful.\n2. Figure 3D, E: “SF3B1ins” is referred to in the text or in panel 3D as a LoF control, but in panel 3E is presented as a transcript species produced under expression of K700E variant. This needs to be clarified.\n3. Figure 5E: it is unclear from the text or Figure legend what is the difference between the left and right panel. Nor what is the purpose of the inset “for reviewers only”.\n4. Figure 5G: the significance of the differences between density plots is unclear because the differences are small and affect the composition of polypyrimidine tracts, which are in general quite degenerate and unstructured. The analyses that would make a difference would be the mapping or prediction of the positions of branch points used in the absence or presence of mutations.\n5. Discussion: the sentence in lines 472-474 may be confusing for some readers, because on one hand states that germline mutations display milder phenotypes and on the other points out to the wider, presumably deleterious effects of mutations in SF3B1 that would occur during development. More generally, it may be worth explaining more clearly that, given the heterozygous nature of SF3B1 mutants, LoF mutations may “simply” reduce the total levels of the protein, while missense mutations likely compete with the wild type protein for incorporation into U2 snRNP particles and induce changes in splice site recognition that may function in a dominant negative fashion to induce phenotypes.\nJuan Valcárcel", "reviewer_2": "Kevin Uguen and colleagues report de novo variants in SF3B1 as the genetic cause of a new, clinically variable neurodevelopmental syndrome. SF3B1 encodes the splicing factor 3b, subunit 1, a component of the U2 snRNP complex of the spliceosome, which mediates the recognition of the branch point. This patient cohort has mainly been assembled through Genematcher. Somatic recurrent missense variants of SF3B1 have been previously reported in multiple cancer types but this is the first report of constitutional variants in this gene underlying a genetic NDD. The authors then performed functional studies for 9 out of the 13 missense variants identified in a cell model that has previously been used to assess the impact of somatic variants identified in cancer. They show evidence that the variants associated with NDD have a different and overall milder impact on splicing than that previously reported for the most recurrent variant (K700E) found in cancers. The identifications of variants in SF3B1 in NDD and the comparison of their functional impact with that of variants previously identified in cancer is both original and compelling. The methods and designed experiments are sound, and the results convincingly support the conclusions. The study is particularly timely, given the growing interest in splicing-related genes in NDD.\nMy main critique is linked to the description of the results and the order in which they appear in the manuscript, which makes the text sometimes difficult to follow.\nTo improve the clarity and readability of the manuscript, I listed specific points below:\n1. Instead of “Novel”, the title could explicitly include the mode of inheritance of the variants\nIntroduction\n2. The introduction is lengthy and currently gives the (false) impression of covering the entire field of genes involved in splicing with NDD whereas many genes are missing (to cite just a few: HNRNPU, HNRNPK; HNRNPC, HNRNPR, HNRPA2B1, SNRNP200, NOVA2, …). I recommend streamlining the introduction to focus on concepts essential for understanding the study while avoiding broad generalities on NDDs and genes not directly related to this manuscript. For example, details on the nature and impact of SF3B1 variants in cancer would be more relevant to give some background on the findings obtained in this manuscript.\n3. Page 3 line 113 and page 6, lines 255 and 258: the terms “change-of-function” and “modification-of-function” are unclear. Do the authors mean “gain-of-function”?\n4. Page 3, line 122: we usually consider that NDD of genetic origin affect 3-4% of the population maximum. 10% probably includes very mild\" forms and non-genetic forms of NDD.\n5. Page 3, line 130: please correct “RNU-2P” to “RNU2-2P”\nResults\n6. page 4, lines 148-154: The authors should briefly specify how the variants were identified and, if possible, provide some context on the nature and size of the cohorts used for variant discovery.\n7. Could the authors indicate for each of the 26 patients if other variants have been identified by exome or genome analysis that could account for the patients’ phenotype?\n8. The clinical part lacks details about the nature of the variants associated with each feature. The authors may want to consider having the paragraph detailing the variants (lines 212-250)) before the clinical paragraphs so they can relate phenotypic features to specific variants. For instance, when discussing the three inherited cases, the exact variant details could be specified. This restructuring would also improve the clarity of genotype-phenotype correlations (Page 5, Lines 196–208).\n9. It is unclear if dividing clinical features into multiple subheadings (head and neck, cardiac, etc.) is necessary. Removing the subheadings and linking these sections might improve readability and flow.\n10. The abbreviation \"pLoF\" appears before it is defined (putative loss-of-function, Line 212). Consider defining it earlier.\n11. How do the authors classify variants as putative loss-of-functon(pLoF) in their genotype-phenotype correlations? Are they referring only to nonsense, canonical splice site variants (i.e., variants introducing premature termination codons) or do they also incorporate functional evidence? Additionally, please consider that missense variants can also result in loss of functon(LoF), and LoF and gain of functon(GoF) are not always mutually exclusive-; a single variant may exhibit both effects.\n12. Page 5, Line 218: The authors should be more specific when referring to pathogenicity criteria. For example, rather than stating \"pathogenicity predictors\", they should explicitly list the predictive tools used (the reader only finds this out two sentences later).\n13. Page 5, lines 227-233: It is difficult to distinguish which variants are associated with cancer and which ones were identified in this study. Including an introductory paragraph earlier about somatic variants in SF3B1 found in cancer and their impact may improve clarity (see previous comment regarding the introduction).\n14. Page 6, line 271: A similar issue with the skipping of exon 6 in DUSP11 and exon 11 in RBM5. Without prior context on these splicing events, the rationale is difficult to follow.\n15. Page 6, line 272: Could the authors clarify whether they overexpress the SF3B1 p.Glu980* protein? If so, did they first verify, at least theoretically, that this variant escapes nonsense-mediated decay? Otherwise, the most likely consequence of this variant (and other pLoF variants) would be haploinsufficiency (without truncated protein produced).\n16. Similarly, have the authors investigated whether any of the missense variants identified in patients could impact SF3B1 splicing, such as by disrupting an ESE or creating/enhancing a novel splice site before overexpressing them?\n17. Page 6, lines 272-276: The same variant is referred to using different nomenclatures (p.Glu980*/p.Glu980Ter). Please homogenize.\n18. Page 6, lines 278-279: The authors suddenly shift to the one-letter amino acid code (e.g., E980*). For clarity, the variant nomenclature should be consistent throughout the text.\n19. Page 12, line 566: Could the authors clarify what is meant by 'biological replicates' in the RNAseq experiments? Does this refer to independent cultures from the same immortalized cell clone (inducible cell lines) or were three different clones used? If the same clone was used, could variant-specific splicing be due to clonal effects? Please provide additional information in the methods section.\n20. Could the authors provide further discussion on how variant-specific splicing might explain the phenotypic differences observed in patients?\n21. While the rationale for using a cell model previously used to study splicing in cancer-specific variants is clear, could the authors discuss how the RNAseq results may be influenced by cell-type specificity?\nFigures\n22. Figure 1A: The heatmap is an effective way to visualize clinical features, but the meaning of the three clusters is unclear. It also seems that a significant portion of the clustering may be driven by missing data, rather than meaningful differences.", "reviewer_3": "In the manuscript by Uguen et al., the authors report several SF3B1 mutations found in a cohort of 26 patients with neurodevelopmental diseases (NDDs). Those mutations, mainly missense variants, are different from the hotspot mutations seen in cancer. Among the SF3B1 mutations seen in NDD patients, the authors focused on SF3B1 E722K, P780L, N829S to perform RNAseq analysis in K562 cells stably expressing these variants. The authors showed that SF3B1 E722K, P780L, N829S expression induces splicing changes compared to SF3B1 WT, to a lesser extent than the cancer associated K700E variant.\nMajor comments:\n-The authors used K562 and HEK293T cells to study the splicing changes due to the described SF3B1 variants. These cancer cell lines are not an ideal model in this study due to the high mutational burden in these cancer cell lines and the non-physiologic SF3B1 expression. It would be ideal for the authors to use patient-derived fibroblasts, lymphoblastoid cell lines, or even primary human blood (or other cells) for the splicing analysis.\n-The authors claim that SF3B1 variants described in this manuscript are associated with NDDs, but they do not include in their analysis a comparison with healthy controls, or NDD patients with SF3B1 WT. What is the frequency of the reported SF3B1 mutations in healthy controls, or NDD patients from HUGODIMS consortium?\n-The three variants that the authors focused on for the RNAseq analysis are single, De Novo variants. However, in the cohort described in this study there was three inherited SF3B1 variants, namely p.(Glu809AspfsTer7), p.(Val695TrpfsTer34) and p.(Arg166Ter) and two recurrent variants, namely P370S/L and R939C. Analysis of the splicing changes due to these inherited or recurrent SF3B1 variants could have been a stronger argument that SF3B1 is involved in NDDs.\n-The authors only mention in line #444 that patient 1 also harbors LARP1 mutation. A systematic description of all the genetic mutations, or absence of it, in the 26-patient cohort is important to associate SF3B1 with NDDs in this cohort.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Point-by-point response to the reviewers’ comments\nReviewer #1 (Remarks to the Author):\nUguen, Bernot and colleagues report a detailed analysis of the molecular effects of mutations in\nthe splicing factor SF3B1 that they have identified in a cohort of 26 patients displaying\nneurodevelopmental disorders. The mutations are scattered through most of the primary amino\nacid sequence of the protein, are distinct from those that appear as somatic mutations in various\ncancers and can be classified in two main groups, those predicted to cause loss of functon(e.g. in\nsplice sites or causing stop codons) and that they turn out to be inherited, and those harboring\nmissense mutations of less clear predicted significance. Remarkably, the latter group is associated\nwith stronger pathological phenotypes, including beyond neurodevelopmental disorders.\nFunctional characterization in a depletion/complementation system using cell lines shows that the\nnovel mutations do not compromise the general activity of SF3B1 (sustaining cell proliferation) nor\ninduce activation of cryptic 3’ splice sites characteristic of cancer mutations in SF3B1. RNA-seq\nanalyses upon ectopic expression of the mutant proteins, however, show substantial splicing\nchanges associated with the novel missense mutations, most frequently private to individual\nmutants. Genes important for nervous system development are enriched among the common\ntargets, opening the possibility that their alteration in cells expressing the mutant proteins may\neventually explain at least part of the associated phenotypes.\nThese are very relevant observations documenting for the first time the association between\nneurodevelopmental disorders and mutations in SF3B1, a key core splicing factor frequently\nmutated in cancer and target of anti-tumor drugs. The detailed molecular characterization of the\nsplicing activities associated with a substantial number of mutants sheds light both on common\nprinciples of SF3B1 alterations as well as on the distinct properties conferred by the different\nmutations and their correlation with the severity of symptoms, highlighting the variety of regulatory\nfunctions of a core component of the spliceosome in charge of the fundamental role of recognizing\nthe branch point in pre-mRNAs.\nIn my opinion the following revisions could help to improve the manuscript:\n1. Figure 2E: it is not easy to understand from the figure which interactions (with which residues\nand the predicted consequences) are affected by the indicated mutations. Additional discussions\nin the main text and/or Figure legend would be helpful.\nWe thank the reviewer for this comment. To facilitate the reading of Figure 2E, we extended the\ncorresponding legend and detailed the amino acids likely to be involved in the modified\ninteractions.\n2. Figure 3D, E: “SF3B1ins” is referred to in the text or in panel 3D as a LoF control, but in panel\n3E is presented as a transcript species produced under expression of K700E variant. This needs\nto be clarified.\nWe thank the reviewer for pointing out this lack of clarity regarding SF3B1ins. We clarified this\npoint both in the main text and in the legend of Figure 3.\nMain text : “As a control, we included a condition in which an inactive isoform of SF3B1 was\nexpressed, namely SF3B1ins, which we previously characterized as an aberrant transcript\nproduced upon expression of K700E”.\ndeficient, was used as a control.” (panel 3A); “...K562 cells expressing the inactive SF3B1ins\nsplicing isoform” (panel 3D).\nTo increase readability, we also replaced the term “WT ins” by “ins” in Figure 3.\n3. Figure 5E: it is unclear from the text or Figure legend what is the difference between the left\nand right panel. Nor what is the purpose of the inset “for reviewers only”.\nWe thank the reviewer for this comment. The right panel of Figure 5E included an additional\ncondition (cancer-associated R625H variant) that perfectly matches the K700E condition. To avoid\nredundancy, we deleted the left panel, as the right panel is the most comprehensive.\nInserting the panel from Liu et al (Cancer Discovery 10, 806–821 2020) was meant to underline\nthe consistency between their results and ours, regarding the distance between cryptic and\ncanonical AG site for the cancer-associated SF3B1 variants. If the policy of Nature\nCommunications allows such insert from another article, we would be inclined to keep it.\n4. Figure 5G: the significance of the differences between density plots is unclear because the\ndifferences are small and affect the composition of polypyrimidine tracts, which are in general\nquite degenerate and unstructured. The analyses that would make a difference would be the\nmapping or prediction of the positions of branch points used in the absence or presence of\nmutations.\nWe thank the reviewer for this comment. Following your suggestion, we performed branch-point\n(BP) analyses using the R package branchpointer. For A3SS events showing significant\ndifferences between the variants and WT, a 100-nucleotide region upstream of the 3′ splice site\n(AG and AG’) was extracted and analyzed for each of the four variants using the\npredictBranchpoints function. Only the branchpoints with a highest prediction probability were\nretained for further analysis. We compared the predicted distances of branchpoints to the 3′ splice\nsites, either canonical (AG) or cryptic (AG’). The distance differences between the predicted\nbranchpoint and corresponding 3’ splice site (canonical vs cryptic) overlay the density plot reported\nin Figure 5E (see figure below, for reviewers).\nDistribution of Distance Differences Between the Predicted Branchpoint and 3′ Sites (Canonical vs. Cryptic).\nDensity plot showing the absolute difference in predicted branchpoint-to-3′ splice site distance between cryptic and\ncanonical splice sites across the different variants.\nWT, the predicted branchpoint usage and positions remain largely conserved, suggesting that\nsmall differences in polypyrimidine tract composition rather than major branchpoint changes are\nlikely responsible for the observed splicing differences. Nonetheless, this interpretation should be\ntempered by the fact that BP predictions are not straightforward.\nWe propose to modify the main text to balance the interpretation of the motif frequency plots :\n“Nevertheless, differences between density plots were modest, suggesting that small differences\nin polypyrimidine tract composition rather than major branchpoint changes are likely responsible\nfor the observed splicing differences.”\n5. Discussion: the sentence in lines 472-474 may be confusing for some readers, because on one\nhand states that germline mutations display milder phenotypes and on the other points out to the\nwider, presumably deleterious effects of mutations in SF3B1 that would occur during development.\nMore generally, it may be worth explaining more clearly that, given the heterozygous nature of\nSF3B1 mutants, LoF mutations may “simply” reduce the total levels of the protein, while missense\nmutations likely compete with the wild type protein for incorporation into U2 snRNP particles and\ninduce changes in splice site recognition that may function in a dominant negative fashion to\ninduce phenotypes.\nWe thank the reviewer for this suggestion. The sentence in lines 472-474 may indeed be\nconfusing. We rephrased it. We also added a sentence in the paragraph related to the molecular\nmechanisms.\nJuan Valcárcel\nReviewer #2 (Remarks to the Author):\nKevin Uguen and colleagues report de novo variants in SF3B1 as the genetic cause of a new,\nclinically variable neurodevelopmental syndrome. SF3B1 encodes the splicing factor 3b, subunit\n1, a component of the U2 snRNP complex of the spliceosome, which mediates the recognition of\nthe branch point. This patient cohort has mainly been assembled through Genematcher. Somatic\nrecurrent missense variants of SF3B1 have been previously reported in multiple cancer types but\nthis is the first report of constitutional variants in this gene underlying a genetic NDD. The authors\nthen performed functional studies for 9 out of the 13 missense variants identified in a cell model\nthat has previously been used to assess the impact of somatic variants identified in cancer. They\nshow evidence that the variants associated with NDD have a different and overall milder impact\non splicing than that previously reported for the most recurrent variant (K700E) found in cancers.\nThe identifications of variants in SF3B1 in NDD and the comparison of their functional impact with\nthat of variants previously identified in cancer is both original and compelling. The methods and\ndesigned experiments are sound, and the results convincingly support the conclusions. The study\nis particularly timely, given the growing interest in splicing-related genes in NDD.\nMy main critique is linked to the description of the results and the order in which they appear in\nthe manuscript, which makes the text sometimes difficult to follow.\n1. Instead of “Novel”, the title could explicitly include the mode of inheritance of the variants\nWe replaced “Novel” by “de novo”, as (i) most variants appeared de novo and (ii) our study focuses\nessentially on de novo variants.\nIntroduction\n2. The introduction is lengthy and currently gives the (false) impression of covering the entire field\nof genes involved in splicing with NDD whereas many genes are missing (to cite just a few:\nHNRNPU, HNRNPK; HNRNPC, HNRNPR, HNRPA2B1, SNRNP200, NOVA2, …). I recommend\nstreamlining the introduction to focus on concepts essential for understanding the study while\navoiding broad generalities on NDDs and genes not directly related to this manuscript. For\nexample, details on the nature and impact of SF3B1 variants in cancer would be more relevant to\ngive some background on the findings obtained in this manuscript.\nWe thank the reviewer for this recommendation. We shortened the paragraph related to NDD and\nfocused on the core and auxiliary components of the U2 snRNP complex to which SF3B1 belongs.\nWe also slightly extended the paragraph on somatic SF3B1 variants.\n3. Page 3 line 113 and page 6, lines 255 and 258: the terms “change-of-function” and\n“modification-of-function” are unclear. Do the authors mean “gain-of-function”?\nCancer-associated mutations of SF3B1 are considered as neomorphic mutations that redirect\nsplicing to novel splice sites or shift the ratio of alternative transcripts. Thus they do not formally\ncorrespond to “gain-of-function” mutations. To homogenize the manuscript, we replaced the term\n“Modification-of-function” (page 6 line 269) by change-of-function.\n4. Page 3, line 122: we usually consider that NDD of genetic origin affect 3-4% of the population\nmaximum. 10% probably includes very mild\" forms and non-genetic forms of NDD.\nWe thank the reviewer for this remark. We modified the manuscript accordingly.\n5. Page 3, line 130: please correct “RNU-2P” to “RNU2-2P”\nWe thank the reviewer for highlighting this mistake. We corrected the manuscript (RNU2-2).\nResults\n6. page 4, lines 148-154: The authors should briefly specify how the variants were identified and,\nif possible, provide some context on the nature and size of the cohorts used for variant discovery.\nWe thank the reviewer for this comment. Patients’ DNA were sequenced primarily in a diagnostic\nsetting or within various research cohorts at each center. We recruited the patients through the\nGeneMatcher platform. We modified the main text in the Methods section accordingly.\n7. Could the authors indicate for each of the 26 patients if other variants have been identified by\nexome or genome analysis that could account for the patients’ phenotype?\nentitled “Other hits”. We also modify the main text to add this precision (lines 158-160). Since the\noriginal submission, we were informed that P22 also carries a missense variant in RORA, that is\ninherited from his mother and considered as a variant of uncertain significance.\n8. The clinical part lacks details about the nature of the variants associated with each feature.\nThe authors may want to consider having the paragraph detailing the variants (lines 212-250)) before\nthe clinical paragraphs so they can relate phenotypic features to specific variants. For instance,\nwhen discussing the three inherited cases, the exact variant details could be specified. This\nrestructuring would also improve the clarity of genotype-phenotype correlations (Page 5, Lines\n196–208).\nWe thank the reviewer for this comment. We modified the manuscript accordingly, which improves\nthe clarity of the text. Based on the current sample size and the available clinical data, it is not yet\npossible to delineate a clear association between the molecular nature of the variant and the\nclinical features. Nevertheless, we proposed the hypothesis that missense variants could be\nassociated with a more severe phenotype, compared to pLoF variants, as exemplified by more\nfrequent congenital anomalies (i.e. microcephaly, heart malformation…). Concerning the inherited\ncases, we modified the text accordingly (lines 202-212).\n9. It is unclear if dividing clinical features into multiple subheadings (head and neck, cardiac, etc.)\nis necessary. Removing the subheadings and linking these sections might improve readability and\nflow.\nWe modified the manuscript to remove the subheadings.\n10. The abbreviation \"pLoF\" appears before it is defined (putative loss-of-function, Line 212).\nConsider defining it earlier.\nWe modified the main text accordingly.\n11. How do the authors classify variants as putative loss-of-functon(pLoF) in their genotype-\nphenotype correlations? Are they referring only to nonsense, canonical splice site variants (i.e.,\nvariants introducing premature termination codons) or do they also incorporate functional\nevidence? Additionally, please consider that missense variants can also result in loss of\nfuncton(LoF), and LoF and gain of functon(GoF) are not always mutually exclusive-; a single\nvariant may exhibit both effects.\nWe thank the reviewer for this comment. We chose to gather nonsense, canonical splice site and\nframeshift variants in the pLOF category. We are aware that missense variants can be responsible\nfor loss, gain of function or both, but we showed that, for the variants described, they are not\nresponsible for a loss of SF3B1 protein function. We added a sentence to precise the meaning of\npLOF in the manuscript (lines 540-541).\n12. Page 5, Line 218: The authors should be more specific when referring to pathogenicity criteria.\ntools used (the reader only finds this out two sentences later).\nWe thank the reviewer for pointing out this issue. We added the pathogenicity predictors in the\nmain text (line 168), which can also be found in Sup Table S2.\n13. Page 5, lines 227-233: It is difficult to distinguish which variants are associated with cancer\nand which ones were identified in this study. Including an introductory paragraph earlier about\nsomatic variants in SF3B1 found in cancer and their impact may improve clarity (see previous\ncomment regarding the introduction).\nWe thank the reviewer for this comment. We modified the text accordingly, being more specific\nwhen citing cancer-associated variants.\n14. Page 6, line 271: A similar issue with the skipping of exon 6 in DUSP11 and exon 11 in RBM5.\nWithout prior context on these splicing events, the rationale is difficult to follow.\nWe thank the reviewer for this remark. We changed the text accordingly : “We then investigated\nspecific exon skipping events known to be altered upon SF3B1 silencing, in particular in DUSP11\n(exon 6) and RBM5 (exon 11).”\n15. Page 6, line 272: Could the authors clarify whether they overexpress the SF3B1 p.Glu980*\nprotein? If so, did they first verify, at least theoretically, that this variant escapes nonsense-\nmediated decay? Otherwise, the most likely consequence of this variant (and other pLoF variants)\nwould be haploinsufficiency (without truncated protein produced).\nWe thank the reviewer for highlighting this point. We modified the text to clarify that we\noverexpressed the truncated protein. Due to the localization of the PTC, the p.Glu980* variant\nshould produce transcripts that undergo NMD, leading to haploinsufficiency. This is why we\nconsidered this variant as a pLoF variant (cf paragraph on the proportion of variants).\nNevertheless, we overexpressed the truncated p.Glu980 variant to evaluate whether, should the\ntranscript escape NMD, the resulting truncated protein would retain any functional activity. Our\nresults confirm the essential nature of the C-term part of the HEAT domain of SF3B1.\n16. Similarly, have the authors investigated whether any of the missense variants identified in\npatients could impact SF3B1 splicing, such as by disrupting an ESE or creating/enhancing a novel\nsplice site before overexpressing them?\nWe thank the reviewer for this pertinent comment. We used several splicing prediction tools\n(MaxEntScan, SpiP, dbscSNV, SpliceAI) to test whether any of the missense variants could\ndisrupt an ESE or enhance a novel splice site, and included the results in Sup table 2. Among the\n16 missense variants analyzed, 10 were not predicted to have any effect by any of the\ncomputational tools employed. Three variants (E1029K, Y587N, and R397H) exhibited only a\nweak prediction of a potential ESE alteration and by SpiP only. The remaining three variants\n(E722K, M613V, and E906K) also yielded weak predictions, each supported by only one tool. We\nthus added the following sentence in the main text: “The use of several splicing prediction tools\n(MaxEntScan34, SpiP35, dbscSNV36, SpliceAI37) does not provide strong evidence that missense\nvariants may disrupt an ESE or favor usage of a novel splice site.”\n6\n17. Page 6, lines 272-276: The same variant is referred to using different nomenclatures\n(p.Glu980*/p.Glu980Ter). Please homogenize.\nWe thank the reviewer for noticing this mistake. We homogenized using p.Glu980*.\n18. Page 6, lines 278-279: The authors suddenly shift to the one-letter amino acid code (e.g.,\nE980*). For clarity, the variant nomenclature should be consistent throughout the text.\nWe thank the reviewer for this comment. We decided to use the one-letter amino acid code\nthroughout the text.\n19. Page 12, line 566: Could the authors clarify what is meant by 'biological replicates' in the\nRNAseq experiments? Does this refer to independent cultures from the same immortalized cell\nclone (inducible cell lines) or were three different clones used? If the same clone was used,\ncould variant-specific splicing be due to clonal effects? Please provide additional information in the\nmethods section.\nWe thank the reviewer for this remark. In this study, biological replicates in the RNAseq\nexperiments refer to independent cultures from the same inducible cell line pools. The cells were\nnot cloned after transfection in order to avoid analysing clone-specific particularities. We specified\nit in the methods section: “Biological independent replicates (n=3), which refer to independent\ncultures from the same inducible cell line pool, were realised for each condition”.\n20. Could the authors provide further discussion on how variant-specific splicing might explain the\nphenotypic differences observed in patients?\nWe thank the reviewer for this suggestion. We added the following sentence in the discussion\nsection, following the paragraph about somatic variants : ”This suggests that each mutation may\nconfer a unique splicing signature that influences disease phenotype. A similar scenario may occur\nfor the NDD-associated SF3B1 variants, which might explain the phenotypic differences observed\nin patients.”\n21. While the rationale for using a cell model previously used to study splicing in cancer-specific\nvariants is clear, could the authors discuss how the RNAseq results may be influenced by cell-\ntype specificity?\nWe thank the reviewer for this pertinent comment. RNA splicing is highly regulated in a cell-type-\nspecific manner, and splicing outcomes observed in one cellular context may not fully reflect those\nin other tissues or physiological states. Our choice of K562 model was guided by both its proven\ncapacity to reveal splicing alterations linked to specific variants, as exemplified by cancer-\nassociated SF3B1 variants, and the practical constraints associated with accessing disease-\nrelevant tissues.\nvaluable to comprehensively characterize the tissue-specific splicing effects of the variants, and\nwe are currently exploring such approaches in ongoing work.\nWe added the following sentence in the results section “Considering RNA splicing is tightly\nregulated in a cell-type-specific manner, and that splicing outcomes observed in one cellular\ncontext may not fully recapitulate those in other tissues, further validation in additional cell models\nwould be necessary to characterize the tissue-specific effects of the variants.” (lines 385-388)\nFigures\n22. Figure 1A: The heatmap is an effective way to visualize clinical features, but the meaning of\nthe three clusters is unclear. It also seems that a significant portion of the clustering may be driven\nby missing data, rather than meaningful differences.\nWe thank the reviewer for this important comment. The first aim of the heatmap was to provide a\ndescriptive overview of clinical similarities across patients, and the results led us to highlight an\nhypothetical difference between missense and pLoF variants. We are aware that missing data\ncould influence the clustering, so we used the ward.D2 method to handle missing data. We also\nreanalysed the dataset after excluding features with >30% of missing values and we can see that\nthe overall structure of the heatmap remained consistent. We modified the manuscript and Figure\n1A accordingly, and included the second version of the heatmap in a supplementary Figure (S1)\nmissing data in >30% of patients were excluded.\nReviewer #3 (Remarks to the Author):\nIn the manuscript by Uguen et al., the authors report several SF3B1 mutations found in a cohort\nof 26 patients with neurodevelopmental diseases (NDDs). Those mutations, mainly missense\nvariants, are different from the hotspot mutations seen in cancer. Among the SF3B1 mutations\nseen in NDD patients, the authors focused on SF3B1 E722K, P780L, N829S to perform RNAseq\nanalysis in K562 cells stably expressing these variants. The authors showed that SF3B1 E722K,\nP780L, N829S expression induces splicing changes compared to SF3B1 WT, to a lesser extent\nthan the cancer associated K700E variant.\nMajor comments:\n9\n-The authors used K562 and HEK293T cells to study the splicing changes due to the described\nSF3B1 variants. These cancer cell lines are not an ideal model in this study due to the high\nmutational burden in these cancer cell lines and the non-physiologic SF3B1 expression. It would\nbe ideal for the authors to use patient-derived fibroblasts, lymphoblastoid cell lines, or even\nprimary human blood (or other cells) for the splicing analysis.\nWe thank the reviewer for this insightful comment. In this study, we chose to investigate the\nmolecular effects of missense variants within a consistent genetic background, employing two\ndistinct cell lines. This strategy was intended to minimize background-driven variability.\nWe agree that incorporating data from patient samples would be a major improvement. Despite\nthe inherent challenges of obtaining patient-derived primary cells, we successfully collected\nperipheral blood samples from patients P1 (p.N829S) and P26 (p.P370L). Peripheral blood\nmononuclear cells (PBMC) were isolated and lymphocytes cultured for three days using the same\nstandardized protocol as for controls (n = 14, NDD without any SF3B1 variant), prior to RNA\nextraction and sequencing. All samples were processed and cultured independently. Splicing\nanalysis was subsequently performed using rMATS on both SF3B1 patient-derived and control\nsamples. Notably, principal component analysis (PCA) revealed that the two patient samples\nclustered together, distinctly separate from the control group, suggesting a specific alternative\nsplicing signature.\nFor the revised version, we included these results in Supplementary Figure 9, and modified the\nmain text by adding the following paragraph: “To further support these findings, we examined\nalternative splicing profiles (using rMATS) in short-term cultured lymphocytes derived from two\nNDD patients (carrying variants p.N829S and p.P370L) in comparison to 14 controls. Remarkably,\nprincipal component analysis (PCA) showed that the two patient samples clustered together and\nseparately from the controls, which strongly suggests a distinct splicing signature associated with\np.N829S and p.P370L variants (Figure 4F and Sup Figure 9)”.\n-The authors claim that SF3B1 variants described in this manuscript are associated with NDDs,\nbut they do not include in their analysis a comparison with healthy controls, or NDD patients with\nSF3B1 WT. What is the frequency of the reported SF3B1 mutations in healthy controls, or NDD\npatients from HUGODIMS consortium?\nWe thank the reviewer for this remark. This information can be found in line 163 where we indicate\nthat all variants were absent from general population databases, namely gnomAd. Regarding the\nfrequency in patients from the HUGODIMS consortium; except for patient 1, no other variant in\nSF3B1 was identified.\n-The three variants that the authors focused on for the RNAseq analysis are single, De Novo\nvariants. However, in the cohort described in this study there was three inherited SF3B1 variants,\nnamely p.(Glu809AspfsTer7), p.(Val695TrpfsTer34) and p.(Arg166Ter) and two recurrent\nvariants, namely P370S/L and R939C. Analysis of the splicing changes due to these inherited or\nrecurrent SF3B1 variants could have been a stronger argument that SF3B1 is involved in NDDs.\nWe thank the reviewer for these constructive comments. As the majority of patients (two-thirds)\ncarry missense variants, we chose to focus specifically on this subset within the scope of the\npresent study.\nthe RNA sequencing analyses conducted on K562 cells. Still, following RNA sequencing, we were\nable to extend the identification of missplicing events (CRNDE, PQBP1, ENOX2) to more\nmissense variants, including T703P and L536I.\nThe recurrent variant p.R939C was incorporated within the splicing-targeted study; however, it\nwas not selected for the RNA-seq analysis, as its recurrent status had not been established at the\ntime the experiments were conducted. The next phase of this research will certainly include a\ncomprehensive analysis of this recurrent variant.\nRegarding the second recurrent variant position : for the revised version of the manuscript, we\nperformed splicing assays for both P370S and P370L, and showed that these two variants do not\ninactivate SF3B1 function (please see Sup Figure 4). Moreover, we show that none of the\nsubstitutions (P370S and P370L) leads to missplicing typical of K700E (new figure 3E). Finally,\nperipheral blood samples were successfully obtained from patient P26 (p.P370L). Remarkably, as\ndescribed above, RNA sequencing of cultured lymphocytes derived from this patient substantiated\nthat this SF3B1 variant does induce alterations in the alternative splicing profile relative to controls\nwithout SF3B1 mutation.\nFor the revised version, we added the splicing data for P370S/L (DUSP11 and RBM5 splicing\nassay) in Supplementary Figure 4 and in Figure 3E for the cancer-associated splicing events. We\nalso incorporated the PCA performed on PSI values of significant alternative splicing events from\nshort-term cultured lymphocytes (Figure 4G and sup Figure 9)\n-The authors only mention in line #444 that patient 1 also harbors LARP1 mutation. A systematic\ndescription of all the genetic mutations, or absence of it, in the 26-patient cohort is important to\nassociate SF3B1 with NDDs in this cohort.\nWe thank the reviewer for this remark. This information is given in Table S1, in the line entitled\n“Other hits”. We modified the main text to add this information (first section of Results).\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nIn addition to the modifications suggested by the reviewers, we added the validation of HSPBP1\nsplicing event (A3’SS) and corrected a few typos.\nWe also added more information about the P22 individual in the subheading entitled\n“inheritance”.\nPlease find here the list of modifications made to the figures:\n- Figure 1A: modification of the map\n- Figure 2A: correction of a typo\n- Figure 2E: replacement of the E722(K) zoom-in by the R939(C) zoom-in.\n- Figure 3E: incorporation of the results for P370S and P370L\n- Figure 4: inclusion of panel G (PCA on splicing events from patients lymphocytes)\n- Figure 5B and 5D: inclusion of the validation of HSPBP1 splicing event (A3’SS)\n- Addition of a Supplementary Figure (S1) entitled “Hierarchical clustering of clinical\nfeatures (rows) of the cohort’s patients (columns). Features with missing data in >30% of\npatients were excluded.”\n- Extension of the Supplementary Figure S4 (previously S3), with data on the molecular\nimpact of SF3B1 missense variants P370S and P370L.\n- Addition of a Supplementary Figure (S9) entitled “Principal component analysis\nperformed on PSI values of significant alternative splicing events from short-term\ncultured lymphocytes.”\n12"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed all the points raised in my previous report and I am happy to recommend publication of the manuscript in Nature Communications.", "reviewer_2": "The authors have adequately addressed all points raised in the first round of review. I have no further comments.", "reviewer_3": "The authors have addressed my initial comments and questions. I have no further issues with the manuscript.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter