Transcriptome analysis and RNA interference of cockroach phototransduction indicate three opsins and suggest a major role for TRPL channels
Bibliographic record
Abstract
Our current understanding of insect phototransduction is based on a small number of species, but insects occupy many different visual environments. We created the retinal transcriptome of a nocturnal insect, the cockroach, Periplaneta americana to identify proteins involved in the earliest stages of compound eye phototransduction, and test the hypothesis that different visual environments are reflected in different molecular contributions to function. We assembled five novel mRNAs: two green opsins, one UV opsin, and one each TRP and TRPL ion channel homologs. One green opsin mRNA (pGO1) was 100-1000 times more abundant than the other opsins (pGO2 and pUVO), while pTRPL mRNA was 10 times more abundant than pTRP, estimated by transcriptome analysis or quantitative PCR (qPCR). Electroretinograms were used to record photoreceptor responses. Gene-specific in vivo RNA interference (RNAi) was achieved by injecting long (596-708 bp) double-stranded RNA into head hemolymph, and verified by qPCR. RNAi of the most abundant green opsin reduced both green opsins by more than 97% without affecting UV opsin, and gave a maximal reduction of 75% in ERG amplitude 7 days after injection that persisted for at least 19 days. RNAi of pTRP and pTRPL genes each specifically reduced the corresponding mRNA by 90%. Electroretinogram (ERG) reduction by pTRPL RNAi was slower than for opsin, reaching 75% attenuation by 21 days, without recovery at 29 days. pTRP RNAi attenuated ERG much less; only 30% after 21 days. Combined pTRP plus pTRPL RNAi gave only weak evidence of any cooperative interactions. We conclude that silencing retinal genes by in vivo RNAi using long dsRNA is effective, that visible light transduction in Periplaneta is dominated by pGO1, and that pTRPL plays a major role in cockroach phototransduction.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".