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Identification of RPS14 as a 5q- syndrome gene by RNA interference screen

Abstract

Somatic chromosomal deletions in cancer are thought to indicate the location of tumour suppressor genes, by which a complete loss of gene function occurs through biallelic deletion, point mutation or epigenetic silencing, thus fulfilling Knudson’s two-hit hypothesis1. In many recurrent deletions, however, such biallelic inactivation has not been found. One prominent example is the 5q- syndrome, a subtype of myelodysplastic syndrome characterized by a defect in erythroid differentiation2. Here we describe an RNA-mediated interference (RNAi)-based approach to discovery of the 5q- disease gene. We found that partial loss of function of the ribosomal subunit protein RPS14 phenocopies the disease in normal haematopoietic progenitor cells, and also that forced expression of RPS14 rescues the disease phenotype in patient-derived bone marrow cells. In addition, we identified a block in the processing of pre-ribosomal RNA in RPS14-deficient cells that is functionally equivalent to the defect in Diamond–Blackfan anaemia, linking the molecular pathophysiology of the 5q- syndrome to a congenital syndrome causing bone marrow failure. These results indicate that the 5q- syndrome is caused by a defect in ribosomal protein function and suggest that RNAi screening is an effective strategy for identifying causal haploinsufficiency disease genes.

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Figure 1: Screen of the common deleted region for the 5q - syndrome.
Figure 2: Multiple shRNAs targeting RPS14 recapitulate the 5q- syndrome in vitro.
Figure 3: RPS14 is required for 18S pre-rRNA processing and 40S ribosomal subunit formation.
Figure 4: RPS14 overexpression rescues erythroid differentiation in samples from patients with 5q deletions.

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References

  1. Knudson, A. G. Mutation and cancer: statistical study of retinoblastoma. Proc. Natl Acad. Sci. USA 68, 820–823 (1971)

    ADS  Article  Google Scholar 

  2. Van den Berghe, H. et al. Distinct haematological disorder with deletion of long arm of no. 5 chromosome. Nature 251, 437–438 (1974)

    CAS  ADS  Article  Google Scholar 

  3. Heaney, M. L. & Golde, D. W. Myelodysplasia. N. Engl. J. Med. 340, 1649–1660 (1999)

    CAS  Article  Google Scholar 

  4. Giagounidis, A. A., Germing, U. & Aul, C. Biological and prognostic significance of chromosome 5q deletions in myeloid malignancies. Clin. Cancer Res. 12, 5–10 (2006)

    CAS  Article  Google Scholar 

  5. List, A. et al. Lenalidomide in the myelodysplastic syndrome with chromosome 5q deletion. N. Engl. J. Med. 355, 1456–1465 (2006)

    CAS  Article  Google Scholar 

  6. Boultwood, J. et al. Narrowing and genomic annotation of the commonly deleted region of the 5q- syndrome. Blood 99, 4638–4641 (2002)

    CAS  Article  Google Scholar 

  7. Raza, A. et al. Apoptosis in bone marrow biopsy samples involving stromal and hematopoietic cells in 50 patients with myelodysplastic syndromes. Blood 86, 268–276 (1995)

    CAS  PubMed  Google Scholar 

  8. Zender, L. et al. Identification and validation of oncogenes in liver cancer using an integrative oncogenomic approach. Cell 125, 1253–1267 (2006)

    CAS  Article  Google Scholar 

  9. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)

    CAS  ADS  Article  Google Scholar 

  10. Ferreira-Cerca, S. et al. Roles of eukaryotic ribosomal proteins in maturation and transport of pre-18S rRNA and ribosome function. Mol. Cell 20, 263–275 (2005)

    CAS  Article  Google Scholar 

  11. Draptchinskaia, N. et al. The gene encoding ribosomal protein S19 is mutated in Diamond–Blackfan anaemia. Nature Genet. 21, 169–175 (1999)

    CAS  Article  Google Scholar 

  12. Gazda, H. T. et al. Ribosomal protein S24 gene is mutated in Diamond–Blackfan anemia. Am. J. Hum. Genet. 79, 1110–1118 (2006)

    CAS  Article  Google Scholar 

  13. Flygare, J. et al. Human RPS19, the gene mutated in Diamond–Blackfan anemia, encodes a ribosomal protein required for the maturation of 40S ribosomal subunits. Blood 109, 980–986 (2007)

    CAS  Article  Google Scholar 

  14. Liu, J. M. & Ellis, S. R. Ribosomes and marrow failure: coincidental association or molecular paradigm? Blood 107, 4583–4588 (2006)

    CAS  Article  Google Scholar 

  15. Quesenberry, P. J. & Colvin, G. A. in Williams Hematology 153 (McGraw-Hill, New York, 2005)

    Google Scholar 

  16. Quigley, J. G. et al. Identification of a human heme exporter that is essential for erythropoiesis. Cell 118, 757–766 (2004)

    CAS  Article  Google Scholar 

  17. Amsterdam, A. et al. Many ribosomal protein genes are cancer genes in zebrafish. PLoS Biol. 2, E139 (2004)

    Article  Google Scholar 

  18. Horrigan, S. K. et al. Delineation of a minimal interval and identification of 9 candidates for a tumor suppressor gene in malignant myeloid disorders on 5q31. Blood 95, 2372–2377 (2000)

    CAS  PubMed  Google Scholar 

  19. Liu, T. X. et al. Chromosome 5q deletion and epigenetic suppression of the gene encoding α-catenin (CTNNA1) in myeloid cell transformation. Nature Med. 13, 78–83 (2007)

    Article  Google Scholar 

  20. Joslin, J. M. et al. Haploinsufficiency of EGR1, a candidate gene in the del(5q), leads to the development of myeloid disorders. Blood 110, 719–726 (2007)

    CAS  Article  Google Scholar 

  21. Fodde, R. & Smits, R. Cancer biology. A matter of dosage. Science 298, 761–763 (2002)

    CAS  Article  Google Scholar 

  22. Mullighan, C. G. et al. Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia. Nature 446, 758–764 (2007)

    CAS  ADS  Article  Google Scholar 

  23. Ebert, B. L. et al. An RNA interference model of RPS19 deficiency in Diamond–Blackfan anemia recapitulates defective hematopoiesis and rescue by dexamethasone: identification of dexamethasone-responsive genes by microarray. Blood 105, 4620–4626 (2005)

    CAS  Article  Google Scholar 

  24. Moffat, J. et al. A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell 124, 1283–1298 (2006)

    CAS  Article  Google Scholar 

  25. Golub, T. R. et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999)

    CAS  Article  Google Scholar 

  26. Ebert, B. L. et al. An erythroid differentiation signature predicts response to lenalidomide in myelodysplastic syndrome. PLoS Med. (in the press)

  27. Stegmaier, K. et al. Gene expression-based high-throughput screening (GE-HTS) and application to leukemia differentiation. Nature Genet. 36, 257–263 (2004)

    CAS  Article  Google Scholar 

  28. Gnatenko, D. V. et al. Transcript profiling of human platelets using microarray and serial analysis of gene expression. Blood 101, 2285–2293 (2003)

    CAS  Article  Google Scholar 

  29. Bolstad, B. M., Irizarry, R. A., Astrand, M. & Speed, T. P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185–193 (2003)

    CAS  Article  Google Scholar 

  30. Tang, H. et al. Amino acid-induced translation of TOP mRNAs is fully dependent on phosphatidylinositol 3-kinase-mediated signaling, is partially inhibited by rapamycin, and is independent of S6K1 and rpS6 phosphorylation. Mol. Cell. Biol. 21, 8671–8683 (2001)

    CAS  Article  Google Scholar 

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Acknowledgements

We thank Broad Institute RNAi and Genetic analysis platforms for advice, single-nucleotide polymorphism analysis and reagents. This work was supported by grants from the National Heart Lung and Blood Institute to T.R.G., B.L.E. and S.R.E. T.R.G. is an investigator of the Howard Hughes Medical Institute.

Author Contributions B.L.E., J.P., J.B., C.Y.C., P.T. and S.R.E. performed experiments and analysed data. D.E.R. provided essential reagents. N.G., A.R. and E.A. provided samples from patients. B.L.E. and T.R.G. wrote the manuscript.

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Correspondence to Todd R. Golub.

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Ebert, B., Pretz, J., Bosco, J. et al. Identification of RPS14 as a 5q- syndrome gene by RNA interference screen. Nature 451, 335–339 (2008). https://doi.org/10.1038/nature06494

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