Neuropeptide precursors and neuropeptides in the sea cucumber Apostichopus japonicus: a genomic, transcriptomic and proteomic analysis
Bibliographic record
Abstract
The sea cucumber Apostichopus japonicus is a foodstuff with very high economic value in China, Japan and other countries in south-east Asia. It is at the heart of a multibillion-dollar industry and to meet demand for this product, aquaculture methods and facilities have been established. However, there are challenges associated with optimization of reproduction, feeding and growth in non-natural environments. Therefore, we need to learn more about the biology of A. japonicus, including processes such as aestivation, evisceration, regeneration and albinism. One of the major classes of molecules that regulate physiology and behaviour in animals are neuropeptides, and a few bioactive peptides have already been identified in A. japonicus. To facilitate more comprehensive investigations of neuropeptide function in A. japonicus, here we have analysed genomic and transcriptomic sequence data and proteomic data to identify neuropeptide precursors and neuropeptides in this species. We identified 44 transcripts encoding neuropeptide precursors or putative neuropeptide precursors, and in some instances neuropeptides derived from these precursors were confirmed by mass spectrometry. Furthermore, analysis of genomic sequence data enabled identification of the location of neuropeptide precursor genes on genomic scaffolds and linkage groups (chromosomes) and determination of gene structure. Many of the precursors identified contain homologs of neuropeptides that have been identified in other bilaterian animals. Precursors of neuropeptides that have thus far only been identified in echinoderms were identified, including L- and F-type SALMFamides, AN peptides and others. Precursors of several peptides that act as modulators of neuromuscular activity in A. japonicus were also identified. The discovery of a large repertoire of neuropeptide precursors and neuropeptides provides a basis for experimental studies that investigate the physiological roles of neuropeptide signaling systems in A. japonicus. Looking ahead, some of these neuropeptides may have effects that could be harnessed to enable improvements in the aquaculture of this economically important species.
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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 | 0.001 | 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".