Development of unigene-derived SSR markers in cowpea (<i>Vigna unguiculata</i>) and their transferability to other<i>Vigna</i>species
Bibliographic record
Abstract
Unigene sequences available in public databases provide a cost-effective and valuable source for the development of molecular markers. In this study, the identification and development of unigene-based SSR markers in cowpea (Vigna unguiculata (L.) Walp.) is presented. A total of 1071 SSRs were identified in 15 740 cowpea unigene sequences downloaded from the National Center for Biotechnology Information. The most frequent SSR motifs present in the unigenes were trinucleotides (59.7%), followed by dinucleotides (34.8%), pentanucleotides (4%), and tetranucleotides (1.5%). The copy number varied from 6 to 33 for dinucleotide, 5 to 29 for trinucleotide, 5 to 7 for tetranucleotide, and 4 to 6 for pentanucleotide repeats. Primer pairs were successfully designed for 803 SSR motifs and 102 SSR markers were finally characterized and validated. Putative function was assigned to 64.7% of the unigene SSR markers based on significant homology to reported proteins. About 31.7% of the SSRs were present in coding sequences and 68.3% in untranslated regions of the genes. About 87% of the SSRs located in the coding sequences were trinucleotide repeats. Allelic variation at 32 SSR loci produced 98 alleles in 20 cowpea genotypes. The polymorphic information content for the SSR markers varied from 0.10 to 0.83 with an average of 0.53. These unigene SSR markers showed a high rate of transferability (88%) across other Vigna species, thereby expanding their utility. Alignment of unigene sequences with soybean genomic sequences revealed the presence of introns in amplified products of some of the SSR markers. This study presents the distribution of SSRs in the expressed portion of the cowpea genome and is the first report of the development of functional unigene-based SSR markers in cowpea. These SSR markers would play an important role in molecular mapping, comparative genomics, and marker-assisted selection strategies in cowpea and other Vigna 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".