Assembly and comparative analysis of transposable elements from low coverage genomic sequence data in Asparagales
Bibliographic record
Abstract
The research field of comparative genomics is moving from a focus on genes to a more holistic view including the repetitive complement. This study aimed to characterize relative proportions of the repetitive fraction of large, complex genomes in a nonmodel system. The monocotyledonous plant order Asparagales (onion, asparagus, agave) comprises some of the largest angiosperm genomes and represents variation in both genome size and structure (karyotype). Anonymous, low coverage, single-end Illumina data from 11 exemplar Asparagales taxa were assembled using a de novo method. Resulting contigs were annotated using a reference library of available monocot repetitive sequences. Mapping reads to contigs provided rough estimates of relative proportions of each type of transposon in the nuclear genome. The results were parsed into general repeat types and synthesized with genome size estimates and a phylogenetic context to describe the pattern of transposable element evolution among these lineages. The major finding is that although some lineages in Asparagales exhibit conservation in repeat proportions, there is generally wide variation in types and frequency of repeats. This approach is an appropriate first step in characterizing repeats in evolutionary lineages with a paucity of genomic resources.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".