Transposon fingerprinting using low coverage whole genome shotgun sequencing in Cacao (Theobroma cacao L.) and related species
Bibliographic record
Abstract
BACKGROUND: Transposable elements (TEs) and other repetitive elements are a large and dynamically evolving part of eukaryotic genomes, especially in plants where they can account for a significant proportion of genome size. Their dynamic nature gives them the potential for use in identifying and characterizing crop germplasm. However, their repetitive nature makes them challenging to study using conventional methods of molecular biology. Next generation sequencing and new computational tools have greatly facilitated the investigation of TE variation within species and among closely related species. RESULTS: (i) We generated low-coverage Illumina whole genome shotgun sequencing reads for multiple individuals of cacao (Theobroma cacao) and related species. These reads were analysed using both an alignment/mapping approach and a de novo (graph based clustering) approach. (ii) A standard set of ultra-conserved orthologous sequences (UCOS) standardized TE data between samples and provided phylogenetic information on the relatedness of samples. (iii) The mapping approach proved highly effective within the reference species but underestimated TE abundance in interspecific comparisons relative to the de novo methods. (iv) Individual T. cacao accessions have unique patterns of TE abundance indicating that the TE composition of the genome is evolving actively within this species. (v) LTR/Gypsy elements are the most abundant, comprising c.10% of the genome. (vi) Within T. cacao the retroelement families show an order of magnitude greater sequence variability than the DNA transposon families. (vii) Theobroma grandiflorum has a similar TE composition to T. cacao, but the related genus Herrania is rather different, with LTRs making up a lower proportion of the genome, perhaps because of a massive presence (c. 20%) of distinctive low complexity satellite-like repeats in this genome. CONCLUSIONS: (i) Short read alignment/mapping to reference TE contigs provides a simple and effective method of investigating intraspecific differences in TE composition. It is not appropriate for comparing repetitive elements across the species boundaries, for which de novo methods are more appropriate. (ii) Individual T. cacao accessions have unique spectra of TE composition indicating active evolution of TE abundance within this species. TE patterns could potentially be used as a "fingerprint" to identify and characterize cacao accessions.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".