Gene Expression Profile of the Human Trabecular Meshwork: NEIBank Sequence Tag Analysis
Bibliographic record
Abstract
PURPOSE: To characterize the gene expression pattern in the human trabecular meshwork (TM) and identify candidate genes for glaucoma by expressed sequence tag (EST) analysis as part of the NEIBank project. METHODS: RNA was extracted from dissected human TM and used to construct unamplified, un-normalized cDNA libraries in the pSPORT1 vector. More than 4000 clones were sequenced from the 5' end. Clones were clustered and identified using GRIST software. In addition, the expression patterns of genes encoding olfactomedin-domain proteins were analyzed by RT-PCR. RESULTS: After non-mRNA contaminants were removed, 3459 independent TM-expressed clones were obtained. These were grouped in 1888 clusters, potentially representing individual expressed genes. Transcripts for the myocilin gene, a locus for inherited glaucoma, formed the third most abundant cluster in the TM collection, and several other genes implicated in glaucoma (PITX2, CYP1B1, and optineurin) were also represented. One abundant TM transcript was from the gene for the angiopoietin-like factor CTD6, which is located at on the long arm of chromosome 1, area 36.2-36.1 in the region of the glaucoma locus GLC3B, whereas other transcripts were from genes close to known glaucoma loci. The TM collection contains cDNAs for genes that are preferentially expressed in the lymphatic endothelium (matrix Gla protein, apolipoprotein D precursor, and selenoprotein P precursor). In addition to EST profiling, RT- PCR was used to detect transcripts of the olfactomedin-domain proteins latrotoxin receptor Lec3 and optimedin in the TM. CONCLUSIONS: The TM libraries are a good source of molecular markers for TM and candidate genes for glaucoma. The abundance of myocilin cDNAs corresponds to the critical role of this gene in glaucoma and contrasts with libraries derived from cultured tissue. The expression profile raises the possibility that cells of the TM and Schlemm's canal may be more similar to lymphatic, rather than blood vascular endothelium.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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".