Genomic Environments and Their Influence on Transposable Element Communities
Bibliographic record
Abstract
Abstract Background Despite decades of research the factors that cause differences in transposable element (TE) distribution and abundance within and between genomes are still unclear. Transposon Ecology is a new field of TE research that promises to aid our understanding of this often-large part of the genome by treating TEs as species within their genomic environment, allowing the use of methods from ecology on genomic TE data. Community ecology methods are particularly well suited for application to TEs as they commonly ask questions about how diversity and abundance of a community of species is determined by the local environment of that community. Results Using a redundancy analysis, we found that ~ 50% of the TEs within a diverse set of genomes are distributed in a predictable pattern along the chromosome, and the specific TE superfamilies that show these patterns are relate to the phylogeny of the host taxa. In a more focused analysis, we found that ~60% of the variation in the TE community within the human genome is explained by its location along the chromosome, and of that variation two thirds (~40% total) was explained by the 3D location of that TE community within the genome (i.e. what other strands of DNA physically close in the nucleus). Of the variation explained by 3D location half (20% total) was explained by the type of regulatory environment (sub compartment) that TE community was located in. Using an analysis to find indicator species, we found that some TEs could be used as predictors of the environment (sub compartment type) in which they were found; however, this relationship did not hold across different chromosomes. Conclusions These analyses demonstrated that TEs are non-randomly distributed across many diverse genomes and were able to identify the specific TE superfamilies that were non-randomly distributed in each genome. Furthermore, going beyond the one-dimensional representation of the genome as a linear sequence was important to understand TE patterns within the genome. Additionally, we extended the utility of traditional community ecology methods in analyzing patterns of TE diversity.
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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".