Rapid Identification of Alleles at the Soybean Maturity Gene E3 using genotyping by Sequencing and a Haplotype‐Based Approach
Why this work is in the frame
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Bibliographic record
Abstract
In eastern Canada, earliness is an important trait for soybean given the short growing season. The aim of this work was to develop tools for breeders to rapidly identify alleles present in their germplasm at the recently cloned maturity locus E3 ( GmPhyA3 ). The tremendous throughput of modern DNA sequencing technology has allowed the use of genotyping by sequencing (GBS) approaches to identify and genotype thousands of single nucleotide polymorphisms (SNPs) across the entire genome. We have used a GBS protocol and SNP‐calling pipeline optimized for soybean to characterize 53 near‐isogenic lines (NILs) contrasting for maturity loci. Results obtained clearly showed the suitability of GBS to provide a dense SNP coverage and very accurate information on the location and size of introgressed regions. We then developed a GBS haplotype method to characterize 91 plant introductions (PIs) as well as a set of 305 lines representative of the Eastern Canadian germplasm for their allelic status at the GmPhyA3 gene. Six distinct haplotypes in and around the E3 locus were observed. Subsequent tests on two genotypes per haplotype (PCR test for a previously reported allele, sequencing entire gene), and validation on a subset of lines, allowed to determine that each of these corresponded to a different allele of this gene. We found that the functional allele E3Ha and the loss of function allele e3‐tr were the two most prevalent in the Eastern Canadian germplasm, while the e3‐fs allele was found at low frequency and e3‐ns was absent. These results show that this approach is a powerful method for rapid allelic characterization, and its application to other maturity genes will be useful for breeding purposes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it