Differential aggregation and functional impairment induced by polyalanine expansions in FOXL2, a transcription factor involved in cranio-facial and ovarian development
Bibliographic record
Abstract
Polyalanine (polyAla) tract expansions have been associated with an increasing number of human diseases. Here, we have undertaken a functional study of the effects of polyAla expansions in the context of the transcription factor FOXL2, involved in cranio-facial and ovarian development. Using two cellular models, we show that FOXL2 polyAla expansions lead to protein mislocalization and aggregation in a length-dependent manner. The fraction of cells containing cytoplasmic staining displays a sigmoidal relationship with respect to the length of the polyAla tract, suggesting the existence of a threshold length above which protein mislocalization occurs. The existence of such a threshold might be rationalized if we consider that the longer the polyAla tract is, the higher its tendency to misfolding or to inducing spurious interactions with cytoplasmic components. To study the intranuclear dynamics of polyAla-expanded FOXL2, we performed fluorescence recovery after photobleaching experiments. The most unexpected result concerned the pathogenic protein containing 19 Ala residues in the run, which was virtually immobile, although this variant does not present a classical aggregation pattern. Luciferase assays and real time RT-PCR of many potential target genes showed that polyAla expansions induce different losses of activity according to the target promoters tested. We provide molecular explanations for these findings. Although our main focus is the mechanisms of pathogenesis of polyAla-expanded proteins, we discuss the potential relevance of polyAla length variation in micro- and macroevolution because polyAla-containing proteins tend to be transcription factors.
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 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) | 0.001 | 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".