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Record W2536296768 · doi:10.1182/blood.v124.21.244.244

An Unexpected Role for Ribonuclease Inhibitor (RNH1) in Erythropoiesis

2014· article· en· W2536296768 on OpenAlexaff
Ramanjaneyulu Allam, Vijaykumar Chennupati, Diogo F. T. Veiga, Kendle M. Maslowski, Aubry Tardivel, Manfredo Quadroni, Michel A. Duchosal, H. Robson MacDonald, Nicolás Fasel, Anne Angelillo‐Scherrer, Pascal Schneider, Trang Hoang

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsGATA1BiologyErythropoiesisGATA2HaematopoiesisCell biologyTranscription factorMolecular biologyGene expressionDiamond–Blackfan anemiaGeneStem cellGeneticsRNAInternal medicine

Abstract

fetched live from OpenAlex

Abstract Ribonuclease Inhibitor (RNH1) is a ubiquitously expressed leucine-rich repeat protein. The human RNH1 gene evolved via gene duplication and is conserved among mammalian species. RNH1 binds to and inhibits pancreatic type ribonucleases. Further, RNH1 contains numerous cysteine residues whose sulfhydryl groups might play key structural roles and protect from oxidative damage (Dickson et al Prog. Nucleic Acid Res. Mol. Biol 2005). Despite of all these observations, the precise biological role of RNH1in vivo remains unexplored. Here, we describe an essential role for Rnh1 in the regulation of erythropoiesis by controlling erythroid differentiation. To understand the biological function of Rnh1, Rnh1-deficient (Rnh1-/-) mice were generated. Rnh1-/- embryos die between embryonic days E8.5 to E10 due to severe decrease in erythroid cells. Similar percentages of c-Kit+CD41+ cells (Hematopoietic stem/progenitor cells) were present in Rnh1-/- yolk sacs compared to control genotypes, however differentiation of mature erythroid cells was impaired. Rnh1 is expressed in erythroid cells and its expression coincides with the site of primitive erythropoiesis in the yolk sac. Gene expression studies revealed that levels of hematopoietic transcription factors (TF) in Rnh1-deficient yolk sacs were normal, but their target genes were down-regulated. These results indicate that a post-transcriptional mechanism that affects TF gene function. Supporting this, protein levels of the erythroid transcription factor GATA1 and PPARγ, previously shown to control the proliferation and differentiation of erythroid progenitors, were selectively impaired. Whereas myeloid transcription factors C/EBPa and C/EBPb were not affected in Rnh1-/- embryos, suggesting that Rnh1 deficiency specifically affects the translation of erythroid transcription factors. At the molecular level, using the human erythroid K562 cell line, we show that RNH1 is recruited to the ribosome complex and binds to the ribosomal proteins. RNH1-deficiency decreased polysome formation and conversely its overexpression increased polysome formation. Increased expression of RNH1 also increased globin gene expression in K562 cells. These results suggest that RNH1 associates with ribosomes and regulates the translation of erythroid-specific genes, which are necessary for erythroid differentiation. Furthermore, Rnh1 haploinsufficiency leads to decreased erythropoiesis in the spleen of adult mice. Ribosomal haploinsufficiency in several ribosomal genes is known to impair ribosome function and cause macrocytic anemia in Diamond–Blackfan anemia (DBA), a congenital bone marrow failure syndrome, and the 5q- syndrome, a subtype of myelodysplastic syndrome (Narla et al Int. J. Hematol 2011). Recently it has been shown that ribosomal haploinsufficiency can specifically cause a decrease in GATA1 mRNA translation (Ludwig et al Nature Med 2014). Similar to these ribosomal genes, we demonstrate that Rnh1 associates with ribosomes and its deficiency impairs the translation of Gata1 and other erythroid-specific transcription factors, which leads to arrest in erythroid maturation. Collectively our results unravel the important biological function of Rnh1 in the regulation of erythropoiesis, and point to novel therapeutic targets for disorders of erythropoiesis involving ribosomal defects. Summary Figure: RNH1 is recruited to ribosomal complex and is involved in translation of erythroid specific transcription factors (TF) e.g.GATA1. These TFs are necessary for differentiation of progenitor cells in to erythroid cells. RNH1 deficiency impairs the translation of GATA1 and other erythroid-specific transcription factors, which leads to arrest in erythroid maturation. Summary Figure:. RNH1 is recruited to ribosomal complex and is involved in translation of erythroid specific transcription factors (TF) e.g.GATA1. These TFs are necessary for differentiation of progenitor cells in to erythroid cells. RNH1 deficiency impairs the translation of GATA1 and other erythroid-specific transcription factors, which leads to arrest in erythroid maturation. Summary Figure: RNH1 is recruited to ribosomal complex and is involved in translation of erythroid specific transcription factors (TF) e.g.GATA1. These TFs are necessary for differentiation of progenitor cells in to erythroid cells. RNH1 deficiency impairs the translation of GATA1 and other erythroid-specific transcription factors, which leads to arrest in erythroid maturation. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.258
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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