Structure and evolution of the sea star egg receptor for sperm bindin
Bibliographic record
Abstract
Selection on coevolving sperm- and egg-recognition molecules is a potent engine of population divergence leading to reproductive isolation and speciation. The study of receptor-ligand pairs can reveal co-evolution of male- and female-expressed genes or differences between their evolution in response to selective factors such as sperm competition and sexual conflict. Phylogeographical studies of these patterns have been limited by targeted gene methods that favour short protein-coding sequences amplifiable by PCR. Here, I use high-throughput transcriptomic methods to characterize the structure and divergence of full-length coding sequences for the gene encoding the protein component of a large complex egg surface glycopeptide receptor for the sperm acrosomal protein bindin from the sea star Patiria miniata. I used a simple but effective method for resolving nucleotide polymorphisms into haplotypes for phylogeny-based analyses of selection. The protein domain organization of sea star egg bindin receptor (EBR1) was similar to sea urchins and included a pair of protein-recognition domains plus a series of tandem repeat domains of two types. Two populations separated by a well-characterized phylogeographical break included lineages of EBR1 alleles under positive selection at several codons (similar to selection on sperm bindin in the same populations). However, these populations shared the same alleles that were under selection for amino acid differences at multiple codons (unlike the pattern of selection for population divergence in sperm bindin). The significance of positively selected EBR1 domains and alleles could be tested in functional analyses of fertilization rates associated with EBR1 (and bindin) polymorphisms.
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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".