Loss-of-Function Analysis Reveals Distinct Requirements of the Translation Initiation Factors eIF4E, eIF4E-3, eIF4G and eIF4G2 in Drosophila Spermatogenesis
Bibliographic record
Abstract
In eukaryotes, post-transcriptional regulation of gene expression has a key role in many cellular and developmental processes. Spermatogenesis involves a complex developmental program that includes changes in cell cycle dynamics and dramatic cellular remodeling. Translational control is critical for spermatogenesis in Drosophila as many mRNAs synthesized in the spermatocytes are translated only much later during spermatid differentiation. Testes-specific translation initiation factors eIF4E-3 and eIF4G2 are essential specifically for male fertility. However, details of their roles during different stages of spermatogenesis are unknown, and the role of canonical translation initiation factors in spermatogenesis remains unexplored. In this study, we addressed the functional role of eIF4E-1, eIF4E-3, eIF4G and eIF4G2 in testes development and formation of mature sperm. Using the UAS-Gal4 system and RNA interference, we systematically knocked down these four genes in different stages of germ cell development, and in the somatic cells. Our results show that eIF4E-1 function in early germ cells and the surrounding somatic cells is critical for spermatogenesis. Both eIF4E-1 and eIF4E-3 are required in spermatocytes for chromosome condensation and cytokinesis during the meiotic stages. Interestingly, we find that eIF4G knockdown did not affect male fertility while eIF4G2 has distinct functions during spermatogenesis; it is required in early germ cells for proper meiotic divisions and spermatid elongation while its abrogation in spermatocytes caused meiotic arrest. Double knockdown of eIF4G and eIF4G2 shows that these proteins act redundantly during the early stages of spermatogenesis. Taken together, our analysis reveals spatio-temporal roles of the canonical and testes-specific translation initiation factors in coordinating developmental programs during spermatogenesis.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".