Genome, Transcriptome, and Germplasm Sequencing Uncovers Functional Variation in the Warm-Season Grain Legume Horsegram Macrotyloma uniflorum (Lam.) Verdc.
Bibliographic record
Abstract
Horsegram is a grain legume with excellent nutritional and remedial properties and good climate resilience, able to adapt to harsh environmental conditions. Here, we used a combination of short- and long-read sequencing technologies to generate a genome sequence of 279.12Mb, covering 83.53% of the estimated total size of the horsegram genome, and we annotated 24,521 genes. De novo prediction of DNA repeats showed that approximately 25.04% of the horsegram genome was made up of repetitive sequences, the lowest among the legume genomes sequenced so far. The major transcription factors identified in the horsegram genome were bHLH , ERF , C2H2 , WRKY , NAC , MYB , and bZIP , suggesting that horsegram is resistant to drought. Interestingly, the genome is abundant in Bowman–Birk protease inhibitors (BBIs), which can be used as a functional food ingredient. The results of maximum likelihood phylogenetic and estimated synonymous substitution analyses suggested that horsegram is closely related to the common bean and diverged approximately 10.17 million years ago. The double-digested restriction associated DNA (ddRAD) sequencing of 40 germplasms allowed us to identify 3,942 high-quality SNPs in the horsegram genome. A genome-wide association study with powdery mildew identified 10 significant associations similar to the MLO and RPW8 . 2 genes. The reference genome and other genomic information presented in this study will be of great value to horsegram breeding programs. In addition, keeping the increasing demand for food with nutraceutical values in view, these genomic data provide opportunities to explore the possibility of horsegram for use as a source of food and nutraceuticals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".