New methods to identify conserved microsatellite loci and develop primer sets of high cross‐species utility – as demonstrated for birds
Bibliographic record
Abstract
We have developed a new approach to create microsatellite primer sets that have high utility across a wide range of species. The success of this method was demonstrated using birds. We selected 35 avian EST microsatellite loci that had a high degree of sequence homology between the zebra finch Taeniopygia guttata and the chicken Gallus gallus and designed primer sets in which the primer bind sites were identical in both species. For 33 conserved primer sets, on average, 100% of loci amplified in each of 17 passerine species and 99% of loci in five non-passerine species. The genotyping of four individuals per species revealed that 24-76% (mean 48%) of loci were polymorphic in the passerines and 18-26% (mean 21%) in the non-passerines. When at least 17 individuals were genotyped per species for four Fringillidae finch species, 71-85% of loci were polymorphic, observed heterozygosity was above 0.50 for most loci and no locus deviated significantly from Hardy-Weinberg proportions. This new set of microsatellite markers is of higher cross-species utility than any set previously designed. The loci described are suitable for a range of applications that require polymorphic avian markers, including paternity and population studies. They will facilitate comparisons of bird genome organization, including genome mapping and studies of recombination, and allow comparisons of genetic variability between species whilst avoiding ascertainment bias. The costs and time to develop new loci can now be avoided for many applications in numerous species. Furthermore, our method can be readily used to develop microsatellite markers of high utility across other taxa.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".