Assembly and <scp>RNA</scp>‐free annotation of highly heterozygous genomes: The case of the thick‐billed murre (<i>Uria lomvia</i>)
Bibliographic record
Abstract
Thanks to a dramatic reduction in sequencing costs followed by a rapid development of bioinformatics tools, genome assembly and annotation have become accessible to many researchers in recent years. Among tetrapods, birds have genomes that display many features that facilitate their assembly and annotation, such as small genome size, low number of repeats and highly conserved genomic structure. However, we found that high genomic heterozygosity could have a great impact on the quality of the genome assembly of the thick-billed murre (Uria lomvia), an arctic colonial seabird. In this study, we tested the performance of three genome assemblers, ray/sscape, soapdenovo2 and platanus, in assembling the highly heterozygous genome of the thick-billed murre. Our results show that platanus, an assembler specifically designed for heterozygous genomes, outperforms the other two approaches and produces a highly contiguous (N50 = 15.8 Mb) and complete genome assembly (93% presence of genes from the Benchmarking Universal Single Copy Ortholog [BUSCO] gene set). Additionally, we annotated the thick-billed murre genome using a homology-based approach that takes advantage of the genomic resources available for birds and other taxa. Our study will be useful for those researchers who are approaching assembly and annotation of highly heterozygous genomes, or genomes of species of conservation concern, and/or who have limited financial resources.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".