Sequence and transcriptional study of<i>HNRPK</i>pseudogenes, and expression and molecular modeling analysis of hnRNP K isoforms
Bibliographic record
Abstract
The heterogeneous nuclear ribonucleoproteins (hnRNPs) comprise a large family of proteins that play important roles in telomere biogenesis, DNA repair, cellular signaling, and the regulation of expression at both the transcriptional and translational levels. One of the most extensively studied hnRNP family members, hnRNP K, has been implicated in a variety of processes, including chromatin remodeling, transcription, splicing, and translation events. In this study, we analyzed processed HNRPK pseudogenes (HNRPK psi1-psi4) and coding sequences. HNRPK pseudogenes are apparently nonfunctional, and psi1 might correspond to transcripts from an ancestral gene. Phylogenetic and sequence analyses suggest that HNRP genes arose by duplication, and that new structural and sequence features expanded the functions of hnRNPs. The expression analysis of hnRNP K isoforms showed that isoform a is expressed in normal testis and in non-small cell lung cancer (NCI-H1155 NSCLC cell line), although the shorter isoform (isoform b) is expressed in different tumor cell lines (IM9 B-lymphoblastoid, Hs578T human breast cancer epithelial, T98G human glioma cell lines). Using molecular modeling, we obtained KH1 and KH3 models, which pointed to important residues for DNA-protein binding and no structural differences between isoforms a and b. To our knowledge, this is the first phylogenetic study including vertebrate HNRP genes and HNRPK pseudogenes, and the first report comparing the KH1 and KH3 domains of isoforms a and b of the hnRNP K protein. New investigations in tumor samples must be done to validate the differential expression observed here. The results shown are important because the hnRNP K protein might represent a new target for pharmacologic intervention in virus replication and cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".