Single-nucleotide polymorphisms(SNPs) in a sucrose synthase gene are associated with wood properties in Catalpa fargesii bur
Bibliographic record
Abstract
Association study is a powerful means for identifying molecular markers, such as single-nucleotide polymorphisms (SNPs) associated with important traits in forest trees. Catalpa fargesii Bur is a valuable commercial tree in China and identifying SNPs that associate with wood property would make a foundation of the marker-assisted breeding in the future. However, related work has not been reported yet. We cloned a 2887 bp long sucrose synthase ( SUS ) gene from the genome of C. fargesii , which is a key enzyme in sucrose metabolism and also associated to wood formation in trees, coding 806 amino acids that expressed mainly in young branches, xylem, and leaves according to real-time quantitative PCR. Then we identified allelic variations of CfSUS associated with nine wood quality associated traits in Catalpa fargesii Bur. Totally, 135 SNPs were identified through cloning and sequencing the CfSUS locus from a mapping population (including 93 unrelated individuals) and 47 of which were genotyped as common SNPs (minor allele frequency > 5%) in the association population that comprised of 125 unrelated individuals collected from main distribution area. Nucleotide diversity and linkage disequilibrium (LD) analysis showed CfSUS has a relative low SNP diversity ( π T = 0.0034) and low LD (r 2 dropped below 0.1 within 1600 bp). Using the association analysis, we found 11 common SNPs and 14 haplotypes were significantly associated with the traits (false discovery rate, Q<0.1), explaining 3.21–12.41% of the phenotypic variance. These results provide molecular markers above associated with wood basic density, pore rate, and six other traits of wood, which have potential applications in breeding of Catalpa fargesii Bur. We first cloned a SUS gene in C. fargesii , then identified several SNPs and haplotypes that associated with wood properties within this gene, suggesting CfSUS participates in the wood formation of C. fargesii . Moreover, molecular markers we identified in this study may be applied into marker-assisted breeding of C. fargesii in the future.
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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".