Transcriptome analysis of adult Caenorhabditis elegans cells reveals tissue-specific gene and isoform expression
Bibliographic record
Abstract
The biology and behavior of adults differ substantially from those of developing animals, and cell-specific information is critical for deciphering the biology of multicellular animals.Thus, adult tissue-specific transcriptomic data are critical for understanding molecular mechanisms that control their phenotypes.We used adult cell-specific isolation to identify the transcriptomes of C. elegans' four major tissues (or "tissue-ome"), identifying ubiquitously expressed and tissue-specific "enriched" genes.These data newly reveal the hypodermis' metabolic character, suggest potential worm-human tissue orthologies, and identify tissuespecific changes in the Insulin/IGF-1 signaling pathway.Tissue-specific alternative splicing analysis identified a large set of collagen isoforms.Finally, we developed a machine learning-based prediction tool for 76 sub-tissue cell types, which we used to predict cellular expression differences in IIS/FOXO signaling, stage-specific TGF-β activity, and basal vs. memory-induced CREB transcription.Together, these data provide a rich resource for understanding the biology governing multicellular adult animals. Author summaryC. elegans is the simplest multi-cellular model system, with only 959 somatic cells in the fully-developed adult.This work describes the isolation and RNA-seq analysis of the worm's major adult tissues.Previously, the isolation of adult tissues has been hampered by the worm's tough outer cuticle, but identification of the transcriptomes of adult tissues is necessary to understand the biology of adults, which differs substantially from that of embryonic and larval cells.We recently developed a method to isolate and RNA-sequence adult tissues, and applied it here to characterize the muscle, neuron, intestine, and epidermis adult transcriptomes and isoform profiles.The data reveal interesting new characteristics for adult tissues, particularly the hypodermis' metabolic function, which we have functionally tested.The tissue transcriptomes were also used to identify relevant human
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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 | 0.000 | 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 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".