Skip to main content
FEBS Open Bio logoLink to FEBS Open Bio
. 2022 Jun 6;12(7):1419–1434. doi: 10.1002/2211-5463.13444

Mutations in RPS19 may affect ribosome function and biogenesis in Diamond Blackfan anemia

Disha‐Gajanan Hiregange 1, Andre Rivalta 1, Ada Yonath 1, Ella Zimmerman 1, Anat Bashan 1, Hagith Yonath 2,3,
PMCID: PMC9249338  PMID: 35583751

Abstract

Ribosomes, the cellular organelles translating the genetic code to proteins, are assemblies of RNA chains and many proteins (RPs) arranged in precise fine‐tuned interwoven structures. Mutated ribosomal genes cause ribosomopathies, including Diamond Blackfan anemia (DBA, a rare heterogeneous red‐cell aplasia connected to ribosome malfunction) or failed biogenesis. Combined bioinformatical, structural, and predictive analyses of potential consequences of possibly expressed mutations in eS19, the protein product of the highly mutated RPS19, suggest that mutations in its exposed surface could alter its positioning during assembly and consequently prevent biogenesis, implying a natural selective strategy to avoid malfunctions in ribosome assembly. A search for RPS19 pseudogenes indicated > 90% sequence identity with the wild‐type, hinting at its expression in cases of absent or truncated gene products.

Keywords: DBA, eS19, genetic mutations, ribosomes, ribosomopathies, RPS19


Diamond Blackfan anemia (DBA) is a rare congenital intrinsic erythroid hypoplasia, associated with mutated ribosomal genes. Combined bioinformatical, structural, and predictive analyses of potential consequences of expressed mutations in eS19, the protein product of the highest mutated RPS19, suggest that its surface‐exposed mutations could alter its positioning and consequently interfere with ribosome biogenesis, implying a natural selective strategy to avoid malfunctioning ribosomes.

graphic file with name FEB4-12-1419-g005.jpg


Abbreviations

RP

ribosomal proteins

rRNA

ribosomal RNA

DBA

Diamond Blackfan anemia

NMD

nonsense‐mediated mRNA decay

Ribosomes are extremely efficient molecular machines that accurately translate the genetic code into proteins in all living cells. In eukaryotes, the functional ribosomes are comprised of long rRNA chains containing ~ 6880 nucleotides and ~ 80 different RPs, which are arranged precisely [1, 2, 3] in two interacting unequal subunits (called 40S and 60S, according to their sedimentation coefficients). Ribosomes' performance is accomplished by a highly correlated intricate mechanism, enabled by cooperative contributions of their various components and interactions with non‐ribosomal cellular entities.

Typically, ribosome's biogenesis proceeds smoothly and efficiently [4, 5, 6, 7], although it requires substantial intracellular molecular trafficking, delicate cooperation between the ribosomal components, and specific interactions with cellular assembly, activation, and finalization factors [8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]. The RPs play a significant role in coordinating the maturation of the ribosome [21, 22] and, together with natural or modified rRNA bases (e.g., the modified rRNA base 1248 pseudouridine, m1acp3Ψ), they are collectively implicated in maintaining ribosome biogenesis and in regulating its function [5, 23, 24, 25, 26, 27, 28].

Ribosomopathies, a collection of genetic diseases, are predisposition syndromes associated mainly with either impaired ribosome biogenesis or ribosome dysfunction [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]. Mutations in genes coding for ribosomal proteins have been implicated in several congenital syndromes belonging to a heterogeneous group of disorders [40, 41, 42, 43] that share malfunctioning bone marrow, linked to blood impediments directly or via issues concerning heme export [44]. Among them, some have been associated with various physical abnormalities, such as cleft lip and/or palate and cardiac defects [45, 46, 47]. Sequencing exomes of affected individuals identified mutations in different genes linked to impaired ribosome biogenesis and decreased translational efficiency [48, 49, 50, 51] or defective mRNA translation [52].

Diamond Blackfan anemia (DBA), a rare congenital intrinsic erythroid hypoplasia, was discovered in 1936 [53] in infants and children and categorized in 1937 as congenital hyperplastic anemia [54]. Its clinical aspects were described in the 1960s [55] and the 1970s [56]. In the post human genome era, DBA was identified as the first human ribosomopathy [57], and in 2006, it was considered as a paradigm for a ribosome‐based disease [58]. In 2008, a database for DBA mutated ribosomal genes was constructed [46], further updated in 2010 [59]. Similar to several other ribosomopathies, DBA is connected to the tumor suppressor gene TP53, which plays a central role in controlling ribosome function under stress [30, 60, 61, 62] and provides a surveillance mechanism for ribosomal function. The classical DBA presentation is a significant red cell aplasia in young infants, with congenital malformations in about 50% of the patients [47, 55, 63, 64]. In recent years, milder ‘non‐classical’ cases with less distinct phenotypes have been identified. Currently, bone marrow transplantation extends patients' survival [65, 66].

Molecular pathogenesis studies showed that approximately half of all known DBA cases are attributed to mutations in the pre‐rRNA‐processing protein TSR2 [67, 68, 69, 70, 71, 72, 73, 74, 75, 76] and RP genes, primarily, but not exclusively, those of the small ribosomal 40S subunit. Impressively, despite the wealth of DBA‐associated mutated genes, DBA is linked mainly to mutations in RPS19, the first DBA ribosomal mutated gene to be discovered [69, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86]. These mutations, which result in hematopoietic and developmental abnormalities [40, 59, 87, 88, 89, 90, 91, 92, 93, 94], account for 25% of all DBA patients [10, 79, 82] and illustrate the significance of eS19, the protein coded by the RPS19 gene. In addition to eS19 involvement in ribosome biogenesis [95, 96], it plays a role in cellular regulation in humans. Some of these mutations may have a dominant negative effect (as was shown in mice [97]) by binding to its own mRNA [98], presumably by a similar mechanism that is exploited by other ribosomal proteins [99, 100, 101, 102, 103].

The remarkable similarity between the 3D structures of eS19 within the functionally active human ribosome, and that of isolated Pyrococcus abyssi, which shares only 36% sequence identity and 57% sequence similarity [104], hints at the significance of its 3D structure.

Sixty‐four different mutations in RPS19 have been clinically identified in DBA patients despite the relatively short length of its coded protein eS19 (∼ 145 amino acids, depending on the species). These are spread throughout the protein and were shown to be connected to several pathologies [105]. Commonly, mutated RPS19 is linked to dysregulation of deltaNp63 and p53 [40], defects in 18S ribosomal RNA synthesis, assembly of the small ribosomal subunit, ribosome maturation [106, 107, 108], and increased proteasome activity [109, 110].

Here, we describe our studies on the highly mutated gene RPS19 and its coded protein, eS19. We performed structural, biophysical, mutational, and genomic comparative analyses of the potential outcomes of eS19 mutations by examining its structural and interactions patterns, as observed within the 3D structure of the human ribosome. Our results shed light on the natural response to the type of the mutation and the consequent expected implications on ribosome biogenesis or ribosome function. Furthermore, our analyses indicate the existence of an ingenious natural selection mechanism to avoid the disturbance of a ribosome malfunction by hindering the biogenesis of ribosomes with a mutated functional site, despite the risk that it may lead to a significant reduction in the ribosome level. In parallel, nonsense‐mediated mRNA degradation (NMD) analysis [111] indicated that a small number of predicted mutations in RPS19 could diminish eS19 transcription and translation. Subsequently, we identified a pseudogene that highly resembles the natural RPS19 gene, thus may replace it under specific circumstances, such as heavily truncated or entirely deleted protein.

Materials and methods

Information about the mutations was extracted from published reports [46, 59, 88, 89, 90, 91, 92, 93]. The PDB files with IDs 4UG0 [2], 6G4W [15], and 6G53 [14] were the sources for the structural details of the fully and partially assembled human ribosome that were used for the various analyses. Coordinates of the different maturation states of the partially assembled large ribosomal subunit were taken from Ameismeier et al. [15]. The distances reported in Table S2 were calculated using chimerax [112, 113]. The PDB IDs of the various assembly states are shown in each sheet; in PDB 6G4W, the side of eS19 facing the assembly factor RRP12, and RRP12 itself is less well resolved; hence, the distances were calculated by substituting the original eS19 chain with the one from 4UG0.

COOT [114] and ucsf chimera [115] were used for generating the atomic models. The mutations were mapped on the models by using ucsf chimera.

RPS19 genes, pseudogenes, and mRNA sequences for the mutation analysis were extracted from NCBI (gene ID 6223, transcript ID NM_001022.4).

Pseudogene sequences were taken from the NCBI RefSeq track [116] in the UCSC Genome Browser (Human Genome version hg38) [117] and translated to amino acids using Expasy Translate (https://web.expasy.org/translate/) [118].

The predictions of the amino acid sequences of the mutated proteins were performed using Expasy Translate (https://web.expasy.org/translate/). Nonsense‐mediated mRNA degradation prediction tool [119] was used to predict which mutated transcript variants escaped NMD. The NMD for point mutations (missense/nonsense) were predicted using the 50–55 nucleotide rule. EMBOSS NEEDLE [120] was used to calculate the percentage identity, similarity, and gaps between each pseudogene and RPS19 wild‐type. Sequence alignments were performed with clustalw [121] and visualized in jalview [122]. SWISS‐MODEL [123, 124, 125, 126, 127] was used to predict mutated eS19 with 4UG0 chosen as a template. ucsf chimerax was used to superimpose the wild‐type eS19 and mutated eS19 models that SWISS‐MODEL generated. Potential H‐bonds were calculated using the built‐in tool in uscf chimerax.

Results

Distribution of RPs mutations in DBA

To seek insights into how the mutations that cause DBA may influence ribosomal biogenesis and/or functionality, we imposed all of the predictable mutations in the RPs on the human ribosome structure [1, 2, 3]. We noticed that the predictable mutations are distributed throughout the ribosome, mostly on or in proximity to the ribosome surface (Fig. 1). By placing the DBA mutation sites on the human ribosome structure, we gained insights into how such modifications may influence ribosome functionality and thus may reveal some aspects of cellular malfunctioning. We pursued comparative structural and genomic analyses related to the expected mutations at the RP level and their expected implications in the contexts of (a) ribosomal biogenesis and (b) the functionality of the ribosome. We studied the anticipated locations of each previously described DBA mutation within the RPs, based on the positions of the related features in the human ribosome structure (PDBID 4UG0) [2]. Then, we examined the distribution of viable DBA mutated ribosomal proteins within the human ribosome for selecting those suitable for predictive evaluation of the expected interactions with their rRNA surroundings.

Fig. 1.

Fig. 1

(A) Surface representations of the human ribosome (PDB ID 4UG0), showing all ribosomal proteins whose genes were found mutated, in variable colors. The rRNA and the unaffected proteins are shown as light brown ribbons. The two images are 180° rotated with respect to each other. (B) Surface representations of the human ribosome (PDB ID 4UG0), showing that all mutations in the ribosomal proteins are exposed at the surface, and many of them around the 60S central protuberance and the 40S head. [Colour figure can be viewed at wileyonlinelibrary.com]

Specifically, we focused on RPS19, and its encoded small ribosomal subunit protein, eS19, owing to the vast number of mutations identified in it in the DBA patients [10, 79, 82]. We expected that some of these mutations would be involved in the ribosome assembly as, in all states of the pre‐assembled ribosome, it is located in close proximity to the surface of the pre‐small subunit [14, 15, 128].

Structural implications of RPS19 mutations in DBA

To assess the various consequences of the RPS19 mutations on its protein product, eS19, we mapped the positions of all known mutations on the eS19 3D structure within the human ribosome. We marked them according to their types, namely missense, nonsense, insertion, and deletions mutations (Fig. 2). As seen, the missense and nonsense mutations tend to cluster in the helical regions, whereas the insertions and deletions are located in loops or the less structured termini, which are less expected to cause substantial structural alterations but may be needed for interactions with the proximate rRNA.

Fig. 2.

Fig. 2

Expected Diamond Blackfan anemia (DBA) mutations in eS19 mapped on its 3D structure within the human ribosome. (A) The structure of the human eS19. (B) Zoomed view of the region of 18S rRNA that is interacting or located in close proximity to mutated amino acids of eS19. The 18S rRNA is shown in light brown. The rRNA bases interacting or located close to eS19 (1365–1595, i.e., h37–h41) are shown using atoms representation. eS19 residues affected by insertion/deletion mutations, nonsense mutations, and missense mutations are shown in red, blue, and purple, respectively. The mutation sites were taken from previous reports [46, 59, 88, 89, 90, 91, 92, 93] of DBA patients' data. [Colour figure can be viewed at wileyonlinelibrary.com]

In addition, we examined the regions of the rRNA that interact with, or are located in close proximity to, eS19 (i.e., nucleotides 1365–1595, comprising helices h37‐h41). These rRNA residues may be affected by structural changes in eS19 upon mutations and consequently, should modify the ribosome structure and either affect ribosome biogenesis or intervene with ribosome functional activity. Our analysis was based on (a) the notion that several RPS19 mutations could lead to impaired ribosome assembly and (b) the high conservation of eS19 structure (Fig. 3). Practically, this analysis was an attempt to structurally analyze the fate of the various mutations, namely to predict which mutations can be connected to failed biogenesis and which could be incorporated into assembled ribosomes and then be involved in ribosome malfunctioning.

Fig. 3.

Fig. 3

Structural similarity of human and the archaeal Pyrococcus abyssi protein eS19 [104], showing the cleft and main helix that seem to be involved in mRNA binding. (A) Left: The structures of human eS19 (PDBID 4UG0), in gray and colored mutations as in Fig. 2; middle: The structure of P. abyssi eS19 [104] (PDBID 2V7F). Note the partial lack of the observation of the flexible regions, or their modified structure, in the isolated protein vs. the ribosome‐incorporated protein; right: Overlay of both structures of eS19, of P. abyssi in green, and in gray within the human ribosome, on which residues W52 and R62 that are interacting with eS19 own mRNA [98] are marked. (B) Assumed mutated amino acids are marked as class I (pink) and class II (blue) on the structure of the human eS19, according to [104]. (C) Space‐filling surface representation of eS19 (gray). Amino acids W52 and R62 are marked in pink. The arrow points at the mRNA binding cleft. [Colour figure can be viewed at wileyonlinelibrary.com]

Furthermore, based on the accumulated knowledge of ribosomal structure/function relationships, we assumed that RP mutations are likely to trigger structural modifications in their surroundings, which may generate additional structural modification in the rRNA or the RPs of the second or third shells around the mutations, and these may even propagate further and trigger additional modifications. For this analysis, we (a) classified the distribution of RPS19 mutations according to their structural motifs (Table S1) (b) calculated the distances of all eS19 atoms to their neighborhood in the mature 40S, as well as in its various known assembly intermediate states of the creation of pre‐40S [14, 15] (c) identified interatomic ‘contacts’ by selecting all of the eS19 atoms whose distances to their neighbors are ≤ 4 Å (Table S2). We assumed that mutations of these atoms have a higher chance to influence the profile of the protein's interactions, which consequently may obstruct incorporation into the assembling ribosome and hamper the entire ribosome maturation. To assess whether the DBA mutations in eS19 affect or disrupt the rRNA environment during the small subunit (pre‐40S) maturation, we compared the different pre‐40S stages of wild‐type eS19 [14] and of the predicted mutated eS19 (Fig. S2). Following this, we inspected the potential H‐bonds that may be formed between eS19 and the surrounding environment. We analyzed the five states (A–E) that have been identified [14] and noticed that State D and State E had virtually identical H‐bonds. Hence, we considered only states A–D. For each state, to predict the H‐bonds of the mutated eS19, we replaced the existing eS19 chain with the mutated eS19 models that were generated by SWISS‐MODEL [123, 124, 125, 126, 127] and found that, as for these regions in native eS19, its expected mutants were not involved in any direct interaction with the non‐ribosomal factors, during the maturation process. As the natural H‐bonds are mostly between eS19 and the surrounding rRNA, the missense mutation should disrupt them, hence supporting the notion that some RP mutations in DBA patients might affect the ribosome maturation and assembly. Thus, by analyzing the interactions of eS19 with its rRNA vicinity in the assembly of 40S particle (Table S2), we added a new dimension to the evaluation of possible contributions of eS19 mutants to DBA. As the termini and internal loops are supposed to be relatively flexible and less structured (Fig. 3), intuitively, we expected that these should create a variety of positive and negative contacts with their surroundings during assembly. Indeed, we found that a few amino acids of these regions do interact with their neighboring rRNA or other RPs throughout the maturation process, but many of them do not (e.g., among the loop of residues 114–116, only residue 115 reaches their neighbors in a few stages). Similarly, in contrast to our initial thought, not even a single contact between eS19 and any assembly factors was found (Fig. 4).

Fig. 4.

Fig. 4

eS19 does not interact with any structurally studied assembly factors [14, 15]. [Colour figure can be viewed at wileyonlinelibrary.com]

It was shown that eS19 binds to its own mRNA in a fashion likely connected to a regulation strategy [98]. The highly conserved region involved in this regulation mechanism includes an α‐helix composed of residues 52–67, located at a rather exposed central part of the protein, on its polar face. In the DBA mutation database, the respective genomic region was shown to contain a large number of missense mutations in the exposed residues W52, R56, S59, and R62, and hence, it is called the ‘eS19 mutation hot spot’ [104]. Importantly, we found that residue R62, a part of this α‐helix, which is exposed on the surface of the mature ribosomes, is heavily involved in contacts with the neighboring rRNA during all assembly states [14, 15] (e.g., up to 45 contacts 2.9–4 Å with nucleotides C1542 and U1543, in a single assembly state). This unexpected finding seems to show that owing to the location of R62, almost all of its mutations should modify, disturb, or eliminate its contacts with its neighboring rRNA. These disturbances and the consequent non‐native contacts should harm the correct incorporation of the mutated eS19 into the pre‐40S particle, which should interfere with the creation of the 40S particle, thus perturbing the delicate biogenesis process and resulting in partially assembled ribosomal small subunits. In this way, we revealed a natural procedure to prevent the formation of functionally failing ribosomes as, if incorporated, its mutations are bound to interfere with proper ribosomal function.

Mutation analysis of the links between ribosome biogenesis and maturation

We carried out an extensive structural and comparative analysis of the expected consequence of the genomic modifications and their diverse phenotypic implications. Prediction of the structure of the mutated eS19 using SWISS‐MODEL and its comparison with the structure of the wild‐type eS19 raised the possibility that the missense mutations might disrupt the neighboring rRNA environment (Fig. 2 and Fig. S1). In addition, our predicted structure of the eS19 with insertion and deletion mutations revealed that most of these DBA mutations would alter the length of the C terminus or its conformation (Fig. 5B,C). This might affect the protein localization in the nucleolus and/or hinder its role in ribosome biogenesis (Fig. 5).

Fig. 5.

Fig. 5

RPS19 insertion and deletion mutations affect eS19 length in Diamond Blackfan anemia. (A) Amino acid sequence of eS19 with nucleolar localization signal marked in a red box. (B) Structural comparison of predicted mutated eS19 with c.25_42del mutation (cyan) and wild‐type eS19 (gray). (C) Structural comparison of predicted mutated eS19 with c.331delC mutation (purple) and wild‐type eS19 (gray). [Colour figure can be viewed at wileyonlinelibrary.com]

Genomic analysis of eS19 mutations in DBA and its transcripts

We mapped the detailed distribution of the known mutations on the exons of RPS19 [88, 94] (Fig. S3) and calculated their expected influence on the lengths of the expressed proteins (Fig. S3). We also classified the RPS19 mutations as per the distribution on the structural motifs of its protein product eS19 (Table S1). Our calculations and predictions revealed that mutations of the RPS19 gene, including frameshift and nonsense, could result in a shorter eS19 (Fig. S4). These shorter proteins may still be incorporated into the ribosome and allow its function. An example is the C‐terminal tail, which extends into the rRNA environment.

Based on the extent of RP‐ribosome possible interactions, we assumed that although the C‐terminal tail is an integral part of the protein, its truncation might be less harmful. Conversely, these mutations may result in a devastating event for the ribosome's maturation and/or function. These cases may result in a reduced number of ribosomes in the cells, in agreement with the results of genomic studies performed elsewhere [129]. In addition, a nonsense‐mediated mRNA decay (NMD) analysis [111] revealed that almost half of the mutated transcript variants (47%) might escape NMD (NMD−; Table S3 highlighted in green), whereas 29% undergo NMD (NMD+), possibly leading to protein depletion (Fig. 6). Notably, potential mRNA with DBA missense mutations escaped NMD, thus increasing the possibility of incorporating mutated protein in ribosome (Fig. 6B).

Fig. 6.

Fig. 6

Mutation distribution and nonsense‐mediated mRNA degradation (NMD) analysis for RPS19 in Diamond Blackfan anemia (DBA). (A) distribution of mutation types reported in DBA patients. (B) NMD analysis of potential mRNA with DBA mutation. [Colour figure can be viewed at wileyonlinelibrary.com]

eS19 pseudogene in DBA

Several ribosomal proteins are known to have pseudogenes [130, 131], and we analyzed the properties of seven of them [132]. An earlier report showed that pseudogenes RPS19P1 and RPS19P2, which share 57% and 45% similarity with the wild‐type eS19, respectively, are not expressed [132], and a substantially higher similarity was obtained when the comparison was based on eS19 cDNA and pseudogene sequence [132]. In addition, a recent study has described an exciting suggestion of paralog‐switching in which canonical RPs are replaced by paralog RPs in Drosophila testis and ovary, expecting to alter the ribosome surface and regulate the process of translation. This study hints at the possibility of the incorporation of RP‐like proteins in the ribosome [133].

There are no reported paralogs for RPS19; however, our prediction of potential protein sequences of the pseudogene revealed that one of them, RPS19P3, shares 90.4% identity and 93.2% similarity with the wild‐type eS19 (Fig. 7 and Table 1). In addition, the mutations that escape NMD share some homology with RPS19P3 pseudogene (Fig. 7B). Notably, the amino acid differences between eS19 and RPS19P3 coincide with DBA reported mutation, predicted structure of RPS19P3 is similar to eS19 (Fig. 7C).

Fig. 7.

Fig. 7

eS19 pseudogenes in Diamond Blackfan anemia. (A) Sequence alignment of eS19 with pseudogenes. The sequence of the wild‐type eS19 was aligned with its seven pseudogenes (RPS19P1, RPS19P2, RPS19P3, RPS19P4, RPS19P5, RPS19P6, RPS19P7) with clustalw [121] and visualized using jalview [122]. (B) Sequence alignment of RPS19P3 with predicted mutated protein eS19. Sequences of RPS19P3 were aligned with predicted mutated protein of c.53_54insAGA, (C)187_189insCAC RPS19 mutations with clustalw and visualized using jalview. (C) Pairwise alignment of eS19 wild‐type and the expected protein product of RPS19P3, left‐ the predicted structure of the protein product of RPS19P3 (pink) overlapped onto wild‐type eS19 (gray). Right‐ the differences in amino acid sequences are mapped onto the 3D structure of eS19, in red. [Colour figure can be viewed at wileyonlinelibrary.com]

Table 1.

Homology between RPS19P3 pseudogenes and the expected mutated protein.

Pseudogenes Identity (%) Similarity (%) Gaps (%)
RPS19P1 51.0 57.2 24.8
RPS19P2 41.5 45.3 45.9
RPS19P3 90.4 93.2 0.7
RPS19P4 31.4 35.8 50.9
RPS19P5 24.7 27.4 67.8
RPS19P6 20.6 26.3 65.1
RPS19P7 11.7 11.7 86.9

Discussion and conclusions

In this study, we focused on the structure, location, and spatial positioning of protein eS19, the product of the ribosomal gene RPS19, which was suggested to participate in a regulatory process by binding its own mRNA in isolation [98], similar to a few other ribosomal proteins [99, 100, 101, 102, 103]. As this protein maintains the same overall specific 3D structure within the active ribosome and in isolation (Fig. 3), the preservation of this inherent 3D structure may indicate its importance and hints at functional conservation alongside comparable tasks.

Our detailed predictive analysis indicates various outcomes for the different eS19 mutations. Thus, we expect that although many eS19 mutations may not hamper ribosome biogenesis, those connected to functional relevance, for example, R62, may obstruct ribosomes assembly. Hence, our analyses led to the identification of nature's ingenious selective strategy to avoid ribosome function loss by impeding the biogenesis of ribosomes with a mutated member of its functional site. This new understanding of the relative functional and structural contributions sheds some light on the so far unexplained mechanism of RPS19 involvement in impaired ribosome biogenesis. Moreover, the results of our analysis indicate the rather unanticipated finding that mutations, which are implicated mainly in dysregulation of ribosome biogenesis, may result from nature's attempts to avoid future ribosome malfunction. On the other hand, this distinctive procedure may allow the incorporation of eS19 with mutations located in positions away from the functional region, a point that has not yet been explored.

Owing to the assumption that some of the mutations that were identified in RPS19 are expressed in eS19, we identified common denominators among the expected structural‐functional outcome of the various known RPS19 DBA mutations. Importantly, these findings are supported by additional observations, mainly (a) the existence of functional ribosomes with truncated rRNA [134] and (b) the rRNA modification patterns that supersede temperature variations [135]. Thus, we revealed a natural mechanism for controlling ribosome biogenesis. We will not be surprised if similar associations will be detected in other cases related to ribosomopathies.

In principle, it seems that the studies reported here illuminate a fundamental aspect of natural mechanism to minimize or eliminate the incorporation of ribosomal proteins with mutated functional sites by hampering ribosome maturation. However, although this mechanism seems to avoid the creation of malfunctioning ribosomes as it is based on disrupting ribosome biogenesis, it can lead to a reduction in the number of ribosomes or ribosome insufficiency.

Our structural approach was accompanied by a genomic analysis, based on recent studies showing that some pseudogenes maintain or might have regained protein‐coding capacity [136], thus suggesting that pseudogenes may also contribute to the transcriptome and proteome of various species. Some pseudogenes are evolutionarily conserved [137], a property that may be a key to understanding unique disease subtypes [138] and tissue‐specificity [139]. This raises questions about the expression of pseudogenes of RPs in ribosomopathies. Spatiotemporal expression pattern and unique functions ascribed to pseudogenes of a few proteins, including PTEN, HTR7, and SUMO1 [140, 141, 142, 143, 144], may open a new direction for further investigations of ribosomopathies.

About a decade ago, DBA was identified as a ribosomal puzzle [145]. Since then, the understanding of the molecular basis of this disease underwent significant progress, yet many unanswered questions remain. We hope that our combined structural, bioinformatical, and genetic approach to elucidate phenotype–genotype correlations of genetic diseases creates an opening for subsequent consequent evaluation of additional questions relating to the connection between genetic modifications of components of human ribosomes and their expression in various ribosomopathies.

Conflict of interest

The authors declare no conflict of interest.

Author contributions

D‐GH, AR, and EZ performed the analyses, AY and AB designed the studies, HY conceived, initiated, and supervised the project, D‐GH, AB, AY, and HY wrote the manuscript with contributions and approval from all other authors.

Supporting information

Table S1. Distribution of RPS19 mutations on its structural motifs.

Table S2. The Predicted interatomic contacts of eS19 atoms whose distances to their neighbors are less than or equal to 4 Å.

Table S3. Predicted eS19_NMD results (NM_001022.4).

Fig. S1. RPS19 missense mutation affecting rRNA environment in DBA.

Fig. S2. 40S intermediates & eS19. The figure is grouped based on the “State”, i.e., the actual 40S maturation stage, comparing the effects of mutations on the H bonds. The predicted H‐bonds are represented as blue dotted lines in both WT‐eS19 (red) and the mutated eS19 (pink with mutated residues in blue) at different stages of 40S maturation (called “states”, from A to D).

Fig. S3. RPS19 mutation map in DBA.

Fig. S4. RPS19 mutation effects the length of eS19 protein. Sequences of wild‐type eS19 were aligned with predicted mutated protein eS19 on different type of mutations using jalview [133] (a) Frameshift mutations and Nonsense mutations (b‐c) Insertion and Deletion mutations (d) Stop gained mutations and Missense mutations (e) Missense mutations.

Acknowledgements

We thank Dr Shifra Ben‐Dor, Dr Elena Ainbinder, Sarit Samiya, Shoshana Tel‐Or, and Dr Maggie Kessler for experimental support. Funding was provided by European Research Council Grants POC for 322581 (NOVRIB) and the Kimmelman Center for Macromolecular Assemblies. AY holds the Martin S. and Helen Kimmel Professorial Chair at the Weizmann Institute of Science.

Data accessibility

The data that support the findings of this study are available in the Supporting Information of this article.

References

  • 1. Ben‐Shem A, Garreau de Loubresse N, Melnikov S, Jenner L, Yusupova G, Yusupov M. The structure of the eukaryotic ribosome at 3.0 a resolution. Science. 2011;334:1524–9. [DOI] [PubMed] [Google Scholar]
  • 2. Khatter H, Myasnikov AG, Natchiar SK, Klaholz BP. Structure of the human 80S ribosome. Nature. 2015;520:640–5. [DOI] [PubMed] [Google Scholar]
  • 3. Anger AM, Armache J‐P, Berninghausen O, Habeck M, Subklewe M, Wilson DN, et al. Structures of the human and Drosophila 80S ribosome. Nature. 2013;497:80–5. [DOI] [PubMed] [Google Scholar]
  • 4. Sharma S, Lafontaine DLJ. ‘View from a bridge’: a new perspective on eukaryotic rRNA base modification. Trends Biochem Sci. 2015;40:560–75. [DOI] [PubMed] [Google Scholar]
  • 5. Babaian A, Rothe K, Girodat D, Minia I, Djondovic S, Milek M, et al. Loss of m1acp3Ψ ribosomal RNA modification is a major feature of cancer. Cell Rep. 2020;31:107611. [DOI] [PubMed] [Google Scholar]
  • 6. Natchiar SK, Myasnikov AG, Kratzat H, Hazemann I, Klaholz BP. Visualization of chemical modifications in the human 80S ribosome structure. Nature. 2017;551:472–7. [DOI] [PubMed] [Google Scholar]
  • 7. Li W, Ward FR, McClure KF, Chang ST‐L, Montabana E, Liras S, et al. Structural basis for selective stalling of human ribosome nascent chain complexes by a drug‐like molecule. Nat Struct Mol Biol. 2019;26:501–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Bohnsack KE, Bohnsack MT. Uncovering the assembly pathway of human ribosomes and its emerging links to disease. EMBO J. 2019;38:e100278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Schilling V, Peifer C, Buchhaupt M, Lamberth S, Lioutikov A, Rietschel B, et al. Genetic interactions of yeast NEP1 (EMG1), encoding an essential factor in ribosome biogenesis: genetic interactions of the essential ribosome biogenesis factor Nep1. Yeast. 2012;29:167–83. [DOI] [PubMed] [Google Scholar]
  • 10. Buchhaupt M, Meyer B, Kötter P, Entian K‐D. Genetic evidence for 18S rRNA binding and an Rps19p assembly function of yeast nucleolar protein Nep1p. Mol Genet Genomics. 2006;276:273–84. [DOI] [PubMed] [Google Scholar]
  • 11. Angermayr M, Roidl A, Bandlow W. Yeast Rio1p is the founding member of a novel subfamily of protein serine kinases involved in the control of cell cycle progression: novel class of protein kinases. Mol Microbiol. 2002;44:309–24. [DOI] [PubMed] [Google Scholar]
  • 12. Widmann B, Wandrey F, Badertscher L, Wyler E, Pfannstiel J, Zemp I, et al. The kinase activity of human Rio1 is required for final steps of cytoplasmic maturation of 40S subunits. Mol Biol Cell. 2012;23:22–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Bowen AM, Musalgaonkar S, Moomau CA, Gulay SP, Mirvis M, Dinman JD. Ribosomal protein uS19 mutants reveal its role in coordinating ribosome structure and function. Translation. 2015;3:e1117703. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Ameismeier M, Cheng J, Berninghausen O, Beckmann R. Visualizing late states of human 40S ribosomal subunit maturation. Nature. 2018;558:249–53. [DOI] [PubMed] [Google Scholar]
  • 15. Ameismeier M, Zemp I, van den Heuvel J, Thoms M, Berninghausen O, Kutay U, et al. Structural basis for the final steps of human 40S ribosome maturation. Nature. 2020;587:683–7. [DOI] [PubMed] [Google Scholar]
  • 16. Dez C, Houseley J, Tollervey D. Surveillance of nuclear‐restricted pre‐ribosomes within a subnucleolar region of Saccharomyces cerevisiae . EMBO J. 2006;25:1534–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Ribbeck K. The permeability barrier of nuclear pore complexes appears to operate via hydrophobic exclusion. EMBO J. 2002;21:2664–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Görlich D, Seewald MJ, Ribbeck K. Characterization of ran‐driven cargo transport and the RanGTPase system by kinetic measurements and computer simulation. EMBO J. 2003;22:1088–100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Grandi P, Rybin V, Baßler J, Petfalski E, Strauß D, Marzioch M, et al. 90S pre‐ribosomes include the 35S pre‐rRNA, the U3 snoRNP, and 40S subunit processing factors but predominantly lack 60S synthesis factors. Mol Cell. 2002;10:105–15. [DOI] [PubMed] [Google Scholar]
  • 20. Ho JH‐N, Kallstrom G, Johnson AW. Nmd3p is a Crm1p‐dependent adapter protein for nuclear export of the large ribosomal subunit. J Cell Biol. 2000;151:1057–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Martín‐Marcos P, Hinnebusch AG, Tamame M. Ribosomal protein L33 is required for ribosome biogenesis, subunit joining, and repression of GCN4 translation. Mol Cell Biol. 2007;27:5968–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Robledo S, Idol RA, Crimmins DL, Ladenson JH, Mason PJ, Bessler M. The role of human ribosomal proteins in the maturation of rRNA and ribosome production. RNA. 2008;14:1918–29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Jack K, Bellodi C, Landry DM, Niederer RO, Meskauskas A, Musalgaonkar S, et al. rRNA Pseudouridylation defects affect ribosomal ligand binding and translational Fidelity from yeast to human cells. Mol Cell. 2011;44:660–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Schosserer M, Minois N, Angerer TB, Amring M, Dellago H, Harreither E, et al. Methylation of ribosomal RNA by NSUN5 is a conserved mechanism modulating organismal lifespan. Nat Commun. 2015;6:6158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Rakauskaite R, Dinman JD. An arc of unpaired “hinge bases” facilitates information exchange among functional centers of the ribosome. Mol Cell Biol. 2006;26:8992–9002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Nakamoto T. The initiation of eukaryotic and prokaryotic protein synthesis: a selective accessibility and multisubstrate enzyme reaction. Gene. 2007;403:1–5. [DOI] [PubMed] [Google Scholar]
  • 27. Passmore LA, Schmeing TM, Maag D, Applefield DJ, Acker MG, Algire MA, et al. The eukaryotic translation initiation factors eIF1 and eIF1A induce an open conformation of the 40S ribosome. Mol Cell. 2007;26:41–50. [DOI] [PubMed] [Google Scholar]
  • 28. Liang X, Liu Q, Fournier MJ. rRNA modifications in an Intersubunit bridge of the ribosome strongly affect both ribosome biogenesis and activity. Mol Cell. 2007;28:965–77. [DOI] [PubMed] [Google Scholar]
  • 29. Narla A, Ebert BL. Ribosomopathies: human disorders of ribosome dysfunction. Blood. 2010;115:3196–205. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Mills EW, Green R. Ribosomopathies: there's strength in numbers. Science. 2017;358:eaan2755. [DOI] [PubMed] [Google Scholar]
  • 31. De Keersmaecker K, Sulima SO, Dinman JD. Ribosomopathies and the paradox of cellular hypo‐ to hyperproliferation. Blood. 2015;125:1377–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Sardana R, Johnson AW. The methyltransferase adaptor protein Trm112 is involved in biogenesis of both ribosomal subunits. Mol Biol Cell. 2012;23:4313–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Sardana R, White JP, Johnson AW. The rRNA methyltransferase Bud23 shows functional interaction with components of the SSU processome and RNase MRP. RNA. 2013;19:828–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Bellemer C, Chabosseau P, Gallardo F, Gleizes P‐E, Stahl G. Genetic interactions show the importance of rRNA modification machinery for the role of Rps15p during ribosome biogenesis in S. cerevisiæ . PLoS ONE. 2010;5:e10472. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Yang L, Song T, Chen L, Kabra N, Zheng H, Koomen J, et al. Regulation of SirT1‐Nucleomethylin binding by rRNA coordinates ribosome biogenesis with nutrient availability. Mol Cell Biol. 2013;33:3835–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Thomas SR, Keller CA, Szyk A, Cannon JR, LaRonde‐LeBlanc NA. Structural insight into the functional mechanism of Nep1/Emg1 N1‐specific pseudouridine methyltransferase in ribosome biogenesis. Nucleic Acids Res. 2011;39:2445–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Meyer B, Wurm JP, Kötter P, Leisegang MS, Schilling V, Buchhaupt M, et al. The Bowen–Conradi syndrome protein Nep1 (Emg1) has a dual role in eukaryotic ribosome biogenesis, as an essential assembly factor and in the methylation of Ψ1191 in yeast 18S rRNA. Nucleic Acids Res. 2011;39:1526–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Montellese C, Montel‐Lehry N, Henras AK, Kutay U, Gleizes P‐E, O'Donohue M‐F. Poly(a)‐specific ribonuclease is a nuclear ribosome biogenesis factor involved in human 18S rRNA maturation. Nucleic Acids Res. 2017;45:6822–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Freed EF, Bleichert F, Dutca LM, Baserga SJ. When ribosomes go bad: diseases of ribosome biogenesis. Mol Biosyst. 2010;6:481–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Danilova N, Sakamoto KM, Lin S. Ribosomal protein S19 deficiency in zebrafish leads to developmental abnormalities and defective erythropoiesis through activation of p53 protein family. Blood. 2008;112:5228–37. [DOI] [PubMed] [Google Scholar]
  • 41. Mason PJ, Perdigones N, Bessler M. Using induced human pluripotent stem cells to study Diamond–Blackfan anemia: an outlook on the clinical possibilities. Expert Rev Hematol. 2013;6:627–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Garçon L, Ge J, Manjunath SH, Mills JA, Apicella M, Parikh S, et al. Ribosomal and hematopoietic defects in induced pluripotent stem cells derived from Diamond Blackfan anemia patients. Blood. 2013;122:912–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Babaylova ES, Gopanenko AV, Bulygin KN, Tupikin AE, Kabilov MR, Malygin AA, et al. mRNA regions where 80S ribosomes pause during translation elongation in vivo interact with protein uS19, a component of the decoding site. Nucleic Acids Res. 2020;48:912–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Keel SB, Doty RT, Yang Z, Quigley JG, Chen J, Knoblaugh S, et al. A heme export protein is required for red blood cell differentiation and iron homeostasis. Science. 2008;319:825–8. [DOI] [PubMed] [Google Scholar]
  • 45. Gazda HT, Sheen MR, Vlachos A, Choesmel V, O'Donohue M‐F, Schneider H, et al. Ribosomal protein L5 and L11 mutations are associated with cleft palate and abnormal thumbs in Diamond‐Blackfan anemia patients. Am J Hum Genet. 2008;83:769–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Boria I, Quarello P, Avondo F, Garelli E, Aspesi A, Carando A, et al. A new database for ribosomal protein genes which are mutated in Diamond‐Blackfan anemia. Hum Mutat. 2008;29:E263–70. [DOI] [PubMed] [Google Scholar]
  • 47. Engidaye G, Melku M, Enawgaw B. Diamond Blackfan anemia: genetics, pathogenesis, diagnosis and treatment. EJIFCC. 2019;30:67–81. [PMC free article] [PubMed] [Google Scholar]
  • 48. De Keersmaecker K, Atak ZK, Li N, Vicente C, Patchett S, Girardi T, et al. Exome sequencing identifies mutation in CNOT3 and ribosomal genes RPL5 and RPL10 in T‐cell acute lymphoblastic leukemia. Nat Genet. 2013;45:186–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Girardi T, De Keersmaecker K. T‐ALL: ALL a matter of translation? Haematologica. 2015;100:293–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Van Vlierberghe P, Ferrando A. The molecular basis of T cell acute lymphoblastic leukemia. J Clin Invest. 2012;122:3398–406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Chiaretti S, Foa R. T‐cell acute lymphoblastic leukemia. Haematologica. 2009;94:160–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Thiadens KAMH, de Klerk E, Fokkema IFAC, t Hoen PAC, von Lindern M. Ribosome profiling uncovers the role of uORFs in translational control of gene expression during erythroblast differentiation. Blood. 2014;124:2658–8. [Google Scholar]
  • 53. Josephs HW. Anaemia of infancy and early childhood. Medicine (Baltimore). 1936;15:307–451. [Google Scholar]
  • 54. Diamond LK, Blackfan KD. Hypoplastic anemia. Am J Dis Child. 1938;56:464–7. [Google Scholar]
  • 55. Diamond LK, Allen DM, Magill FB. Congenital (erythroid) hypoplastic anemia: a 25‐year study. Am J Dis Child. 1961;102:403–15. [DOI] [PubMed] [Google Scholar]
  • 56. Diamond LK. Congenital hypoplastic anemia: Diamond‐Blackfan syndrome. Historical and clinical aspects. Blood Cells. 1978;4:209–13. [PubMed] [Google Scholar]
  • 57. Da Costa L, Moniz H, Simansour M, Tchernia G, Mohandas N, Leblanc T. Diamond‐Blackfan anemia, ribosome and erythropoiesis. Transfus Clin Biol. 2010;17:112–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Ellis SR, Massey AT. Diamond Blackfan anemia: a paradigm for a ribosome‐based disease. Med Hypotheses. 2006;66:643–8. [DOI] [PubMed] [Google Scholar]
  • 59. Boria I, Garelli E, Gazda HT, Aspesi A, Quarello P, Pavesi E, et al. The ribosomal basis of diamond‐blackfan anemia: mutation and database update. Hum Mutat. 2010;31:1269–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Chakraborty A, Uechi T, Nakajima Y, Gazda HT, O'Donohue M‐F, Gleizes P‐E, et al. Cross talk between TP53 and c‐Myc in the pathophysiology of Diamond‐Blackfan anemia: evidence from RPL11‐deficient in vivo and in vitro models. Biochem Biophys Res Commun. 2018;495:1839–45. [DOI] [PubMed] [Google Scholar]
  • 61. Gazda HT, Preti M, Sheen MR, O'Donohue M‐F, Vlachos A, Davies SM, et al. Frameshift mutation in p53 regulator RPL26 is associated with multiple physical abnormalities and a specific pre‐ribosomal RNA processing defect in diamond‐blackfan anemia. Hum Mutat. 2012;33:1037–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. McGowan KA, Li JZ, Park CY, Beaudry V, Tabor HK, Sabnis AJ, et al. Ribosomal mutations cause p53‐mediated dark skin and pleiotropic effects. Nat Genet. 2008;40:963–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. Sultana S, Ferdous S, Hossain N, Shah M, Das M, Ferdous A. Diamond Blackfan anemia a rare anemia of infancy. Bangladesh J child Health. 2007;31:40–2. [Google Scholar]
  • 64. Nathan DG, Oski FA. Hematology of infancy and childhood. 3rd ed. Philadelphia, PA: W.B. Saunders Co.; 1987. [Google Scholar]
  • 65. Mugishima H, Gale RP, Rowlings PA, Horowitz MM, Marmont AM, McCann SR, et al. Bone marrow transplantation for Diamond‐Blackfan anemia. Bone Marrow Transplant. 1995;15:55–8. [PubMed] [Google Scholar]
  • 66. Roy V, Pérez WS, Eapen M, Marsh JCW, Pasquini M, Pasquini R, et al. Bone marrow transplantation for Diamond‐Blackfan anemia. Biol Blood Marrow Transplant. 2005;11:600–8. [DOI] [PubMed] [Google Scholar]
  • 67. Vlachos A, Federman N, Reyes‐Haley C, Abramson J, Lipton J. Hematopoietic stem cell transplantation for Diamond Blackfan anemia: a report from the Diamond Blackfan anemia registry. Bone Marrow Transplant. 2001;27:381–6. [DOI] [PubMed] [Google Scholar]
  • 68. Da Costa L, Tchernia G, Gascard P, Lo A, Meerpohl J, Niemeyer C, et al. Nucleolar localization of RPS19 protein in normal cells and mislocalization due to mutations in the nucleolar localization signals in 2 Diamond‐Blackfan anemia patients: potential insights into pathophysiology. Blood. 2003;101:5039–45. [DOI] [PubMed] [Google Scholar]
  • 69. Gazda HT, Grabowska A, Merida‐Long LB, Latawiec E, Schneider HE, Lipton JM, et al. Ribosomal protein S24 gene is mutated in Diamond‐Blackfan anemia. Am J Hum Genet. 2006;79:1110–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70. Gripp KW, Curry C, Olney AH, Sandoval C, Fisher J, Chong JX‐L, et al. Diamond‐Blackfan anemia with mandibulofacial dystostosis is heterogeneous, including the novel DBA genes TSR2 and RPS28 . Am J Med Genet A. 2014;164:2240–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71. Farrar JE, Vlachos A, Atsidaftos E, Carlson‐Donohoe H, Markello TC, Arceci RJ, et al. Ribosomal protein gene deletions in Diamond‐Blackfan anemia. Blood. 2011;118:6943–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72. Lipton JM, Ellis SR. Diamond‐Blackfan anemia: diagnosis, treatment, and molecular pathogenesis. Hematol Oncol Clin North Am. 2009;23:261–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73. Ito E, Konno Y, Toki T, Terui K. Molecular pathogenesis in Diamond–Blackfan anemia. Int J Hematol. 2010;92:413–8. [DOI] [PubMed] [Google Scholar]
  • 74. Sakamoto KM, Narla A. Perspective on Diamond–Blackfan anemia: lessons from a rare congenital bone marrow failure syndrome. Leukemia. 2018;32:249–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75. Wlodarski MW, Da Costa L, O'Donohue M‐F, Gastou M, Karboul N, Montel‐Lehry N, et al. Recurring mutations in RPL15 are linked to hydrops fetalis and treatment independence in Diamond‐Blackfan anemia. Haematologica. 2018;103:949–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76. Mirabello L, Khincha PP, Ellis SR, Giri N, Brodie S, Chandrasekharappa SC, et al. Novel and known ribosomal causes of Diamond‐Blackfan anaemia identified through comprehensive genomic characterisation. J Med Genet. 2017;54:417–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77. Ikeda F, Yoshida K, Toki T, Uechi T, Ishida S, Nakajima Y, et al. Exome sequencing identified RPS15A as a novel causative gene for Diamond‐Blackfan anemia. Haematologica. 2017;102:e93–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78. Sankaran VG, Ghazvinian R, Do R, Thiru P, Vergilio J‐A, Beggs AH, et al. Exome sequencing identifies GATA1 mutations resulting in Diamond‐Blackfan anemia. J Clin Invest. 2012;122:2439–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79. Miyake K, Utsugisawa T, Flygare J, Kiefer T, Hamaguchi I, Richter J, et al. Ribosomal protein S19 deficiency leads to reduced proliferation and increased apoptosis but does not affect terminal erythroid differentiation in a cell line model of Diamond‐Blackfan anemia. Stem Cells. 2008;26:323–9. [DOI] [PubMed] [Google Scholar]
  • 80. Cmejla R, Cmejlova J, Handrkova H, Petrak J, Petrtylova K, Mihal V, et al. Identification of mutations in the ribosomal protein L5 (RPL5) and ribosomal protein L11 (RPL11) genes in Czech patients with Diamond‐Blackfan anemia. Hum Mutat. 2009;30:321–7. [DOI] [PubMed] [Google Scholar]
  • 81. Farrar JE, Nater M, Caywood E, McDevitt MA, Kowalski J, Takemoto CM, et al. Abnormalities of the large ribosomal subunit protein, Rpl35a, in Diamond‐Blackfan anemia. Blood. 2008;112:1582–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82. Campagnoli MF, Ramenghi U, Armiraglio M, Quarello P, Garelli E, Carando A, et al. RPS19 mutations in patients with Diamond‐Blackfan anemia. Hum Mutat. 2008;29:911–20. [DOI] [PubMed] [Google Scholar]
  • 83. Draptchinskaia N, Gustavsson P, Andersson B, Pettersson M, Willig T‐N, Dianzani I, et al. The gene encoding ribosomal protein S19 is mutated in Diamond‐Blackfan anaemia. Nat Genet. 1999;21:169–75. [DOI] [PubMed] [Google Scholar]
  • 84. Willig TN, Draptchinskaia N, Dianzani I, Ball S, Niemeyer C, Ramenghi U, et al. Mutations in ribosomal protein S19 gene and diamond blackfan anemia: wide variations in phenotypic expression. Blood. 1999;94:4294–306. [PubMed] [Google Scholar]
  • 85. Caterino M, Aspesi A, Pavesi E, Imperlini E, Pagnozzi D, Ingenito L, et al. Analysis of the interactome of ribosomal protein S19 mutants. Proteomics. 2014;14:2286–96. [DOI] [PubMed] [Google Scholar]
  • 86. Kampen KR, Sulima SO, Vereecke S, De Keersmaecker K. Hallmarks of ribosomopathies. Nucleic Acids Res. 2020;48:1013–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87. Uechi T, Nakajima Y, Chakraborty A, Torihara H, Higa S, Kenmochi N. Deficiency of ribosomal protein S19 during early embryogenesis leads to reduction of erythrocytes in a zebrafish model of Diamond‐Blackfan anemia. Hum Mol Genet. 2008;17:3204–11. [DOI] [PubMed] [Google Scholar]
  • 88. Ulirsch JC, Verboon JM, Kazerounian S, Guo MH, Yuan D, Ludwig LS, et al. The genetic landscape of Diamond‐Blackfan anemia. Am J Hum Genet. 2018;103:930–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 89. Campagnoli MF, Garelli E, Quarello P, Carando A, Varotto S, Nobili B, et al. Molecular basis of Diamond‐Blackfan anemia: new findings from the Italian registry and a review of the literature. Haematologica. 2004;89:480–9. [PubMed] [Google Scholar]
  • 90. Orfali KA, Ohene‐Abuakwa Y, Ball SE. Diamond Blackfan anaemia in the UK: clinical and genetic heterogeneity: DBA genetic study. Br J Haematol. 2004;125:243–52. [DOI] [PubMed] [Google Scholar]
  • 91. Tsangaris E, Klaassen R, Fernandez CV, Yanofsky R, Shereck E, Champagne J, et al. Genetic analysis of inherited bone marrow failure syndromes from one prospective, comprehensive and population‐based cohort and identification of novel mutations. J Med Genet. 2011;48:618–28. [DOI] [PubMed] [Google Scholar]
  • 92. Wan Y, Chen X, An W, Ruan M, Zhang J, Chang L, et al. Clinical features, mutations and treatment of 104 patients of Diamond‐Blackfan anemia in China: a single‐center retrospective study. Int J Hematol. 2016;104:430–9. [DOI] [PubMed] [Google Scholar]
  • 93. Smetanina NS, Mersiyanova IV, Kurnikova MA, Ovsyannikova GS, Hachatryan LA, Bobrynina VO, et al. Clinical and genomic heterogeneity of Diamond Blackfan anemia in The Russian Federation: Diamond Blackfan anemia in The Russian Federation. Pediatr Blood Cancer. 2015;62:1597–600. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94. Ichimura T, Yoshida K, Okuno Y, Yujiri T, Nagai K, Nishi M, et al. Diagnostic challenge of Diamond–Blackfan anemia in mothers and children by whole‐exome sequencing. Int J Hematol. 2017;105:515–20. [DOI] [PubMed] [Google Scholar]
  • 95. Choesmel V, Bacqueville D, Rouquette J, Noaillac‐Depeyre J, Fribourg S, Crétien A, et al. Impaired ribosome biogenesis in Diamond‐Blackfan anemia. Blood. 2007;109:1275–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96. Flygare J, Aspesi A, Bailey JC, Miyake K, Caffrey JM, Karlsson S, et al. Human RPS19, the gene mutated in Diamond‐Blackfan anemia, encodes a ribosomal protein required for the maturation of 40S ribosomal subunits. Blood. 2007;109:980–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97. Devlin EE, DaCosta L, Mohandas N, Elliott G, Bodine DM. A transgenic mouse model demonstrates a dominant negative effect of a point mutation in the RPS19 gene associated with Diamond‐Blackfan anemia. Blood. 2010;116:2826–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 98. Schuster J, Fröjmark A‐S, Nilsson P, Badhai J, Virtanen A, Dahl N. Ribosomal protein S19 binds to its own mRNA with reduced affinity in Diamond‐Blackfan anemia. Blood Cells Mol Dis. 2010;45:23–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99. Badhai J, Fröjmark A‐S, Razzaghian HR, Davey E, Schuster J, Dahl N. Posttranscriptional down‐regulation of small ribosomal subunit proteins correlates with reduction of 18S rRNA in RPS19 deficiency. FEBS Lett. 2009;583:2049–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100. Ivanov AV, Malygin AA, Karpova GG. Human ribosomal protein S26 suppresses the splicing of its pre‐mRNA. Biochim Biophys Acta. 2005;1727:134–40. [DOI] [PubMed] [Google Scholar]
  • 101. Malygin AA, Parakhnevitch NM, Ivanov AV, Eperon IC, Karpova GG. Human ribosomal protein S13 regulates expression of its own gene at the splicing step by a feedback mechanism. Nucleic Acids Res. 2007;35:6414–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102. Macías S, Bragulat M, Tardiff DF, Vilardell J. L30 binds the nascent RPL30 transcript to repress U2 snRNP recruitment. Mol Cell. 2008;30:732–42. [DOI] [PubMed] [Google Scholar]
  • 103. Moore KS, von Lindern M. RNA binding proteins and regulation of mRNA translation in erythropoiesis. Front Physiol. 2018;9:910. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104. Gregory LA, Aguissa‐Toure A‐H, Pinaud N, Legrand P, Gleizes P‐E, Fribourg S. Molecular basis of Diamond Blackfan anemia: structure and function analysis of RPS19. Nucleic Acids Res. 2007;35:5913–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 105. Ellis SR, Gleizes P‐E. Diamond Blackfan anemia: ribosomal proteins going rogue. Semin Hematol. 2011;48:89–96. [DOI] [PubMed] [Google Scholar]
  • 106. Léger‐Silvestre I, Caffrey JM, Dawaliby R, Alvarez‐Arias DA, Gas N, Bertolone SJ, et al. Specific role for yeast homologs of the Diamond Blackfan anemia‐associated Rps19 protein in ribosome synthesis. J Biol Chem. 2005;280:38177–85. [DOI] [PubMed] [Google Scholar]
  • 107. Idol RA, Robledo S, Du H‐Y, Crimmins DL, Wilson DB, Ladenson JH, et al. Cells depleted for RPS19, a protein associated with Diamond Blackfan anemia, show defects in 18S ribosomal RNA synthesis and small ribosomal subunit production. Blood Cells Mol Dis. 2007;39:35–43. [DOI] [PubMed] [Google Scholar]
  • 108. Juli G, Gismondi A, Monteleone V, Caldarola S, Iadevaia V, Aspesi A, et al. Depletion of ribosomal protein S19 causes a reduction of rRNA synthesis. Sci Rep. 2016;6:35026. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 109. Angelini M, Cannata S, Mercaldo V, Gibello L, Santoro C, Dianzani I, et al. Missense mutations associated with Diamond–Blackfan anemia affect the assembly of ribosomal protein S19 into the ribosome. Hum Mol Genet. 2007;16:1720–7. [DOI] [PubMed] [Google Scholar]
  • 110. Cretien A, Hurtaud C, Moniz H, Proust A, Marie I, Wagner‐Ballon O, et al. Study of the effects of proteasome inhibitors on ribosomal protein S19 (RPS19) mutants, identified in patients with Diamond‐Blackfan anemia. Haematologica. 2008;93:1627–34. [DOI] [PubMed] [Google Scholar]
  • 111. Hsu M‐K, Lin H‐Y, Chen F‐C. NMD classifier: a reliable and systematic classification tool for nonsense‐mediated decay events. PLoS ONE. 2017;12:e0174798. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 112. Goddard TD, Huang CC, Meng EC, Pettersen EF, Couch GS, Morris JH, et al. UCSF ChimeraX: meeting modern challenges in visualization and analysis. Protein Sci. 2018;27:14–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 113. Pettersen EF, Goddard TD, Huang CC, Meng EC, Couch GS, Croll TI, et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 2021;30:70–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 114. Emsley P, Lohkamp B, Scott WG, Cowtan K. Features and development of Coot . Acta Crystallogr D Biol Crystallogr. 2010;66:486–501. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 115. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem. 2004;25:1605–12. [DOI] [PubMed] [Google Scholar]
  • 116. Pruitt KD, Brown GR, Hiatt SM, Thibaud‐Nissen F, Astashyn A, Ermolaeva O, et al. RefSeq: an update on mammalian reference sequences. Nucleic Acids Res. 2014;42:D756–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 117. Navarro Gonzalez J, Zweig AS, Speir ML, Schmelter D, Rosenbloom KR, Raney BJ, et al. The UCSC genome browser database: 2021 update. Nucleic Acids Res. 2021;49:D1046–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 118. Duvaud S, Gabella C, Lisacek F, Stockinger H, Ioannidis V, Durinx C. Expasy, the Swiss bioinformatics resource portal, as designed by its users. Nucleic Acids Res. 2021;49:W216–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 119. Coban‐Akdemir Z, White JJ, Song X, Jhangiani SN, Fatih JM, Gambin T, et al. Identifying genes whose mutant transcripts cause dominant disease traits by potential gain‐of‐function alleles. Am J Hum Genet. 2018;103:171–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 120. Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, et al. The EMBL‐EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019;47:W636–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 121. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23:2947–8. [DOI] [PubMed] [Google Scholar]
  • 122. Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 123. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS‐MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46:W296–303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 124. Bienert S, Waterhouse A, de Beer TAP, Tauriello G, Studer G, Bordoli L, et al. The SWISS‐MODEL repository—new features and functionality. Nucleic Acids Res. 2017;45:D313–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 125. Guex N, Peitsch MC, Schwede T. Automated comparative protein structure modeling with SWISS‐MODEL and Swiss‐PdbViewer: a historical perspective. Electrophoresis. 2009;30:S162–73. [DOI] [PubMed] [Google Scholar]
  • 126. Studer G, Rempfer C, Waterhouse AM, Gumienny R, Haas J, Schwede T. QMEANDisCo—distance constraints applied on model quality estimation. Bioinformatics. 2020;36:1765–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 127. Bertoni M, Kiefer F, Biasini M, Bordoli L, Schwede T. Modeling protein quaternary structure of homo‐ and hetero‐oligomers beyond binary interactions by homology. Sci Rep. 2017;7:10480. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 128. Cerezo E, Plisson‐Chastang C, Henras AK, Lebaron S, Gleizes P, O'Donohue M, et al. Maturation of pre‐40S particles in yeast and humans. Wiley Interdiscip Rev RNA. 2019;10:e1516. [DOI] [PubMed] [Google Scholar]
  • 129. Da Costa L, Willig T‐N, Fixler J, Mohandas N, Tchernia G. Diamond‐Blackfan anemia. Curr Opin Pediatr. 2001;13:10–5. [DOI] [PubMed] [Google Scholar]
  • 130. Zhang Z. Identification and analysis of over 2000 ribosomal protein pseudogenes in the human genome. Genome Res. 2002;12:1466–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 131. Balasubramanian S, Zheng D, Liu Y‐J, Fang G, Frankish A, Carriero N, et al. Comparative analysis of processed ribosomal protein pseudogenes in four mammalian genomes. Genome Biol. 2009;10:R2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 132. Cmejla R, Blafkova J, Stopka T, Zavadil J, Pospisilova D, Mihal V, et al. Ribosomal protein S19 gene mutations in patients with Diamond‐Blackfan anemia and identification of ribosomal protein S19 pseudogenes. Blood Cells Mol Dis. 2000;26:124–32. [DOI] [PubMed] [Google Scholar]
  • 133. Hopes T, Norris K, Agapiou M, McCarthy CGP, Lewis PA, O'Connell MJ, et al. Ribosome heterogeneity in Drosophila melanogaster gonads through paralog‐switching. Nucleic Acids Res. 2021;50:2240–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 134. Matzov D, Taoka M, Nobe Y, Yamauchi Y, Halfon Y, Asis N, et al. Cryo‐EM structure of the highly atypical cytoplasmic ribosome of Euglena gracilis . Nucleic Acids Res. 2020;48:11750–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 135. Sas‐Chen A, Thomas JM, Matzov D, Taoka M, Nance KD, Nir R, et al. Dynamic RNA acetylation revealed by quantitative cross‐evolutionary mapping. Nature. 2020;583:638–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 136. Chen X, Wan L, Wang W, Xi W‐J, Yang A‐G, Wang T. Re‐recognition of pseudogenes: from molecular to clinical applications. Theranostics. 2020;10:1479–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 137. Pink RC, Wicks K, Caley DP, Punch EK, Jacobs L, Francisco Carter DR. Pseudogenes: pseudo‐functional or key regulators in health and disease? RNA. 2011;17:792–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 138. Gasi Tandefelt D, Boormans J, Hermans K, Trapman J. ETS fusion genes in prostate cancer. Endocr Relat Cancer. 2014;21:R143–52. [DOI] [PubMed] [Google Scholar]
  • 139. Mei D, Song H, Wang K, Lou Y, Sun W, Liu Z, et al. Up‐regulation of SUMO1 pseudogene 3 (SUMO1P3) in gastric cancer and its clinical association. Med Oncol. 2013;30:709. [DOI] [PubMed] [Google Scholar]
  • 140. Tay Y, Kats L, Salmena L, Weiss D, Tan SM, Ala U, et al. Coding‐independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs. Cell. 2011;147:344–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 141. Poliseno L, Salmena L, Zhang J, Carver B, Haveman WJ, Pandolfi PP. A coding‐independent function of gene and pseudogene mRNAs regulates tumour biology. Nature. 2010;465:1033–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 142. Koda Y, Soejima M, Wang B, Kimura H. Structure and expression of the gene encoding secretor‐type Galactoside 2‐alpha‐l‐fucosyltransferase (FUT2). Eur J Biochem. 1997;246:750–5. [DOI] [PubMed] [Google Scholar]
  • 143. Lui KY, Peng H, Lin J, Qiu C, Chen H, Fu R, et al. Pseudogene integrator complex subunit 6 pseudogene 1 (INTS6P1) as a novel plasma‐based biomarker for hepatocellular carcinoma screening. Tumor Biol. 2016;37:1253–60. [DOI] [PubMed] [Google Scholar]
  • 144. Kalyana‐Sundaram S, Shankar S, DeRoo S, Iyer MK, Palanisamy N, Chinnaiyan AM, et al. Gene fusions associated with recurrent amplicons represent a class of passenger aberrations in breast cancer. Neoplasia. 2012;14:702–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 145. Dianzani I, Loreni F. Diamond‐Blackfan anemia: a ribosomal puzzle. Haematologica. 2008;93:1601–4. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Table S1. Distribution of RPS19 mutations on its structural motifs.

Table S2. The Predicted interatomic contacts of eS19 atoms whose distances to their neighbors are less than or equal to 4 Å.

Table S3. Predicted eS19_NMD results (NM_001022.4).

Fig. S1. RPS19 missense mutation affecting rRNA environment in DBA.

Fig. S2. 40S intermediates & eS19. The figure is grouped based on the “State”, i.e., the actual 40S maturation stage, comparing the effects of mutations on the H bonds. The predicted H‐bonds are represented as blue dotted lines in both WT‐eS19 (red) and the mutated eS19 (pink with mutated residues in blue) at different stages of 40S maturation (called “states”, from A to D).

Fig. S3. RPS19 mutation map in DBA.

Fig. S4. RPS19 mutation effects the length of eS19 protein. Sequences of wild‐type eS19 were aligned with predicted mutated protein eS19 on different type of mutations using jalview [133] (a) Frameshift mutations and Nonsense mutations (b‐c) Insertion and Deletion mutations (d) Stop gained mutations and Missense mutations (e) Missense mutations.

Data Availability Statement

The data that support the findings of this study are available in the Supporting Information of this article.


Articles from FEBS Open Bio are provided here courtesy of Wiley

RESOURCES