First nuclear genome assembly of an extinct moa species, the little bush moa ( <i>Anomalopteryx didiformis</i> )
Bibliographic record
Abstract
A bstract High throughput sequencing (HTS) has revolutionized the field of ancient DNA (aDNA) by facilitating recovery of nuclear DNA for greater inference of evolutionary processes in extinct species than is possible from mitochondrial DNA alone. We used HTS to obtain ancient DNA from the little bush moa ( Anomalopteryx didiformis ), one of the iconic species of large, flightless birds that became extinct following human settlement of New Zealand in the 13 th century. In addition to a complete mitochondrial genome at 249.9X depth of coverage, we recover almost 900 Mb of the moa nuclear genome by mapping reads to a high quality reference genome for the emu ( Dromaius novaehollandiae ). This first nuclear genome assembly for moa covers approximately 75% of the 1.2 Gb emu reference with sequence contiguity sufficient to identify more than 85% of bird universal single-copy orthologs. From this assembly, we isolate 40 polymorphic microsatellites to serve as a community resource for future population-level studies in moa. We also compile data for a suite of candidate genes associated with vertebrate limb development and show that the wingless moa phenotype is likely not attributable to gene loss or pseudogenization among this candidate set. We also identify potential function-altering coding sequence variants in moa for future experimental assays.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".