Over-Expression of Either MECP2_e1 or MECP2_e2 in Neuronally Differentiated Cells Results in Different Patterns of Gene Expression
Bibliographic record
Abstract
Mutations in MECP2 are responsible for the majority of Rett syndrome cases. MECP2 is a regulator of transcription, and has two isoforms, MECP2_e1 and MECP2_e2. There is accumulating evidence that MECP2_e1 is the etiologically relevant variant for Rett. In this study we aim to detect genes that are differentially transcribed in neuronal cells over-expressing either of these two MECP2 isoforms. The human neuroblastoma cell line SK-N-SH was stably infected by lentiviral vectors over-expressing MECP2_e1, MECP2_e2, or eGFP, and were then differentiated into neurons. The same lentiviral constructs were also used to infect mouse Mecp2 knockout (Mecp2(tm1.1Bird)) fibroblasts. RNA from these cells was used for microarray gene expression analysis. For the human neuronal cells, ∼ 800 genes showed >three-fold change in expression level with the MECP2_e1 construct, and ∼ 230 with MECP2_e2 (unpaired t-test, uncorrected p value <0.05). We used quantitative RT-PCR to verify microarray results for 41 of these genes. We found significant up-regulation of several genes resulting from over-expression of MECP2_e1 including SRPX2, NAV3, NPY1R, SYN3, and SEMA3D. DOCK8 was shown via microarray and qRT-PCR to be upregulated in both SK-N-SH cells and mouse fibroblasts. Both isoforms up-regulated GABRA2, KCNA1, FOXG1 and FOXP2. Down-regulation of expression in the presence of MECP2_e1 was seen with UNC5C and RPH3A. Understanding the biology of these differentially transcribed genes and their role in neurodevelopment may help us to understand the relative functions of the two MECP2 isoforms, and ultimately develop a better understanding of RTT etiology and determine the clinical relevance of isoform-specific mutations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".