Genome-Wide Analysis of Transposon Insertion Polymorphisms Reveals Intraspecific Variation in Cultivated Rice
Bibliographic record
Abstract
Insertions and precise eliminations of transposable elements generated numerous transposon insertion polymorphisms (TIPs) in rice (Oryza sativa). We observed that TIPs represent more than 50% of large insertions and deletions (>100 bp) in the rice genome. Using a comparative genomic approach, we identified 2,041 TIPs between the genomes of two cultivars, japonica Nipponbare and indica 93-11. We also identified 691 TIPs between Nipponbare and indica Guangluai 4 in the 23-Mb collinear regions of chromosome 4. Among them, retrotransposon-based insertion polymorphisms were used to reveal the evolutionary relationships of these three cultivars. Our conservative estimates suggest that the TIPs generated approximately 14% of the genomic DNA sequence differences between subspecies indica and japonica. It was also found that more than 10% of TIPs were located in expressed gene regions, representing an important source of genetic variation. Transcript evidence implies that these TIPs induced a series of genetic differences between two subspecies, including interrupting host genes, creating different expression forms, drastically changing intron length, and affecting expression levels of adjacent genes. These analyses provide genome-wide insights into evolutionary history and genetic variation of rice.
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 | 0.000 |
| 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 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".