Systems biology surveillance decrypts pathological transcriptome remodeling
Bibliographic record
Abstract
BACKGROUND: Pathological cardiac development is precipitated by dysregulation of calreticulin, an endoplasmic reticulum (ER)-resident calcium binding chaperone and critical contributor to cardiogenesis and embryonic viability. However, pleiotropic phenotype derangements induced by calreticulin deficiency challenge the identification of specific downstream transcriptome elements that direct proper cardiac formation. Here, differential transcriptome navigation was used to diagnose high priority calreticulin domain-specific gene expression changes and decrypt complex cardiac-specific molecular responses elicited by discrete functional regions of calreticulin. METHODS: Wild type (WT), calreticulin-deficient (CALR(-/-)), and calreticulin truncation variant (CALR(-/-)-NP and CALR(-/-)-PC) pluripotent stem cells were used to investigate molecular remodeling underlying a model of cardiopathology. Bioinformatic deconvolution of isolated transcriptomes was performed to identify predominant expression trends, gene ontology prioritizations, and molecular network features characteristic of discrete cell types. RESULTS: Stem cell lines with wild type (WT), calreticulin-deficient (CALR(-/-)) genomes, as well as calreticulin truncation variants exclusively expressing either the chaperoning (CALR(-/-)-NP) or the calcium binding (CALR(-/-)-PC) domain exhibited characteristic molecular signatures determined by unsupervised agglomerative clustering. Kohonen mapping of RNA expression changes identified transcriptome dynamics that segregated into 12 discrete gene expression meta-profiles which were enriched for regulation of Eukaryotic Initiation Factor 2 (EIF2) signaling. Focused examination of domain-specific gene ontology remodeling revealed a general enrichment of Cardiovascular Development in the truncation variants, with unique prioritization of "Cardiovascular Disease" exclusive to the cohort of down regulated genes of the PC truncation variant. Molecular cartography of genes that comprised this cardiopathological category revealed uncharacterized and novel gene relationships, with identification of Pitx2 as a critical hub within the topology of a CALR(-/-) compromised network. CONCLUSIONS: Diagnostic surveillance, through an algorithm that integrates pluripotent stem cell transcriptomes with advanced high throughput assays and computational bioinformatics, revealed collective gene expression network changes that underlie differential phenotype development. Stem cell transcriptomes provide a deep collective molecular index that reflects ad hoc robustness of the pluripotent gene network. Remodeling events such as monogenic lesions provide a background by which high priority candidate disease effectors and regulators can be identified, demonstrated here by a molecular profiling algorithm that decrypts pluripotent wild type versus disrupted genomes.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".