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Record W2988739382 · doi:10.1182/blood-2019-130147

Characterizing Dyskeratosis Congenita Caused By Parn Mutations in the Zebrafish

2019· article· en· W2988739382 on OpenAlexaff
Anna Cordeiro, Adam P Deveau, Santhosh Dhanraj, Yigal Dror, Jason N. Berman

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsDyskeratosis congenitaZebrafishBiologyGeneticsGeneDanioCancer researchTelomere

Abstract

fetched live from OpenAlex

Inherited bone marrow failure syndromes (IBMFs) are a group of rare genetic disorders characterized by deficient hematopoiesis and extra-hematologic traits. Most known entities are related to a specific gene or group of genes, but others still remain unclassified. In many cases, the involved proteins are required for critical processes involved in cell survival, such as ribosome biogenesis, maintenance of telomere length, and DNA repair. Importantly, patients with IBMFs have higher risks of developing a variety of cancers from leukemia to solid tumours of the head and neck. In 2015, we published four patients from three different families with mutations in the Poly(A)-specific ribonuclease (PARN) gene. This gene encodes a ribonuclease which is involved in degradation of the poly(A) tails, which regulate mRNA turnover, and thus gene expression. Three of the patients presented with several degrees of mental illness and/or developmental delay. The fourth patient, harbored both a monoallelic deletion and a point mutation at the catalytic domain of the protein, and presented with bone marrow failure and hypomyelination, similar to a severe form of dyskeratosis congenital (DC) known as Hoyeraal-Hreidarsson syndrome. In the last two decades, zebrafish (Danio rerio) has emerged as an excellent animal model for human disease, and is especially relevant in hematology, since many of the transcription factors and cell types are highly conserved. Zebrafish have a single PARN ortholog,with 64% sequence identity to the human gene. Using CRISPR-Cas9 genome editing and a combination of six sgRNAs, we generated a 1.2 kb deletion in the zebrafish parn ortholog extending from exon 5 to 13, causing a premature stop codon. Homozygous fish were generated by incrossing to replicate the complete loss-of-function observed in the patient with the DC-like phenotype. Using whole-mount in situ hybridization (WISH) at 48 hours post-fertilization (hpf), we observed a decrease in the number of several mature myeloid cell lineages including neutrophils (labeled with mpx; p<0.0001), macrophages (lcp1; p=0.0005) and mast cells (cpa5; p=0.0005). We also observed a decrease in the amount of hemoglobin (o-dianisidine staining; p<0.0001). However, the number of hematopoietic stem cells (HSCs) was unchanged in parn mutants. This data parallels similar findings using parn directed splice site and translation start site morpholinos. PARN is described as a protein involved in RNA processing, but has also been associated with telomere maintenance. This latter process is crucial for cell senescence and genome integrity, and is a known cause of several IBMFSs. The telomerase ribonucleoprotein complex is highly active in hematopoietic stem and progenitor cells (HSPCs) and plays a role in cell differentiation. This complex is composed of a reverse transcriptase (TERT), RNA template (TERC), and the dyskerin protein complex (DKC1), mutations of which represent a common cause of DC. qPCR analysis in zebrafish parn mutants revealed a 2.98-fold reduction in tert expression compared with the wild type fish. Combined, these findings suggest that PARN plays an important role in HSC differentiation into myeloid and erythroid lineages, resulting in a bone marrow failure phenotype. Our model provides a unique in vivo platform to study the role of PARN in hematopoiesis and for identifying compounds that restore normal blood cell ratios, which may have the potential to prevent future leukemic transformation. 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.261
Teacher spread0.252 · 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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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