The Amaranth Genome: Genome, Transcriptome, and Physical Map Assembly
Bibliographic record
Abstract
Amaranth ( L.) is an emerging pseudocereal native to the New World that has garnered increased attention in recent years because of its nutritional quality, in particular its seed protein and more specifically its high levels of the essential amino acid lysine. It belongs to the Amaranthaceae family, is an ancient paleopolyploid that shows disomic inheritance (2 = 32), and has an estimated genome size of 466 Mb. Here we present a high-quality draft genome sequence of the grain amaranth. The genome assembly consisted of 377 Mb in 3518 scaffolds with an N of 371 kb. Repetitive element analysis predicted that 48% of the genome is comprised of repeat sequences, of which -like elements were the most commonly classified retrotransposon. A de novo transcriptome consisting of 66,370 contigs was assembled from eight different amaranth tissue and abiotic stress libraries. Annotation of the genome identified 23,059 protein-coding genes. Seven grain amaranths (, , and ) and their putative progenitor () were resequenced. A single nucleotide polymorphism (SNP) phylogeny supported the classification of as the progenitor species of the grain amaranths. Lastly, we generated a de novo physical map for using the BioNano Genomics' Genome Mapping platform. The physical map spanned 340 Mb and a hybrid assembly using the BioNano physical maps nearly doubled the N of the assembly to 697 kb. Moreover, we analyzed synteny between amaranth and sugar beet ( L.) and estimated, using analysis, the age of the most recent polyploidization event in amaranth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".