Discovery of Human Inversion Polymorphisms by Comparative Analysis of Human and Chimpanzee DNA Sequence Assemblies
Bibliographic record
Abstract
With a draft genome-sequence assembly for the chimpanzee available, it is now possible to perform genome-wide analyses to identify, at a submicroscopic level, structural rearrangements that have occurred between chimpanzees and humans. The goal of this study was to investigate chromosomal regions that are inverted between the chimpanzee and human genomes. Using the net alignments for the builds of the human and chimpanzee genome assemblies, we identified a total of 1,576 putative regions of inverted orientation, covering more than 154 mega-bases of DNA. The DNA segments are distributed throughout the genome and range from 23 base pairs to 62 mega-bases in length. For the 66 inversions more than 25 kilobases (kb) in length, 75% were flanked on one or both sides by (often unrelated) segmental duplications. Using PCR and fluorescence in situ hybridization we experimentally validated 23 of 27 (85%) semi-randomly chosen regions; the largest novel inversion confirmed was 4.3 mega-bases at human Chromosome 7p14. Gorilla was used as an out-group to assign ancestral status to the variants. All experimentally validated inversion regions were then assayed against a panel of human samples and three of the 23 (13%) regions were found to be polymorphic in the human genome. These polymorphic inversions include 730 kb (at 7p22), 13 kb (at 7q11), and 1 kb (at 16q24) fragments with a 5%, 30%, and 48% minor allele frequency, respectively. Our results suggest that inversions are an important source of variation in primate genome evolution. The finding of at least three novel inversion polymorphisms in humans indicates this type of structural variation may be a more common feature of our genome than previously realized.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".