Comparative genomics analysis reveals high levels of differential DNA transposition among primates
Bibliographic record
Abstract
ABSTRACT Mobile elements generated via DNA transposition constitute ∼50% of the primate genomes. As a result of past and ongoing activity, DNA transposition is responsible for generating inter- and intra-species genomic variations, and it plays important roles in shaping genome evolution and impacting gene function. While limited analysis of mobile elements has been performed in many primate genomes, a large-scale comparative genomic analysis examining the impact of DNA transposition on primate evolution is still missing. Using a bioinformatics comparative genomics approach, we performed analysis of species-specific mobile elements (SS-MEs) in eight primate genomes, which include human, chimpanzee, gorilla, orangutan, green monkey, crab-eating macaque, rhesus monkey, and baboon. These species have good representations for the top two primate families, Hominidae (great apes) and the Cercopithecidae (old world monkeys), for which draft genome sequences are available. Our analysis identified a total of 230,855 SS-MEs from the eight primate genomes, which collectively contribute to ∼82 Mbp genome sequences, ranging from 14 to 25 Mbp for individual genomes. Several new interesting observations were made based on these SS-MEs. First, the DNA transposition activity level reflected by the numbers of SS-MEs was shown to be drastically different across species with the highest (baboon genome) being more than 30 times higher than the lowest (crab-eating macaque genome). Second, the compositions of SS-MEs, as well as the top active ME subfamilies, also differ significantly across genomes. By the copy numbers of SS-MEs divided into major ME classes, SINE represents the dominant class in all genomes, but more so in the Cercopithecidae genomes than in the Hominidae genomes in general with the orangutan genome being the outliner of this trend by having LINE as the dominant class. While AluY represents the major SINE groups in the Hominidae genomes, AluYRa1 is the dominant SINE in the Cercopithecidae genomes. For LINEs, each Hominidae genome seems to have a unique most active L1 subfamily, but all Cercopithecidae genomes have L1RS2 as the most active LINEs. While genomes with a high number of SS-MEs all have one or more very active ME subfamilies, the crab-eating macaque genome, being the one with an extremely low level of DNA transposition, has no single ME class being very active, suggesting the existence of a genome-wide mechanism suppressing DNA transposition. Third, DNA transposons, despite being considered dead in primate genomes, were in fact shown to have a certain level of activity in all genomes examined with a total of ∼2,400 entries as SS-MEs. Among these SS-MEs, at least 23% locate to genic regions, including exons and regulatory elements, presenting significant potentials for their impact on gene function. Very interestingly, our data demonstrate that, among the eight primates included in this study, the human genome is shown to be the most actively evolving genome via DNA transposition as having the highest most recent activity of many ME subfamilies, notably the AluYa5/Yb8/Yb9, L1HS, and SVA-D subfamilies. Representing the first of its kind, our large-scale comparative genomics study has shown that mobile elements evolved quite differently among different groups and species of primates, indicating that differential DNA transposition has served as an important mechanism in primate evolution.
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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".