It’s okay to be green: Draft genome of the North American bullfrog (Rana [Lithobates] catesbeiana)
Bibliographic record
Abstract
Abstract Frogs play important ecological roles as sentinels, insect control and food sources. Several species are important model organisms for scientific research to study embryogenesis, development, immune function, and endocrine signaling. The globally-distributed Ranidae (true frogs) are the largest frog family, and have substantial evolutionary distance from the model laboratory Xenopus frog species. Consequently, the extensive Xenopus genomic resources are of limited utility for Ranids and related frog species. More widely applicable amphibian genomic data is urgently needed as more than two-thirds of known species are currently threatened or are undergoing population declines. Herein, we report on the first genome sequence of a Ranid species, an adult male North American bullfrog ( Rana [Lithobates] catesbeiana ). We assembled high-depth Illumina reads (66-fold coverage), into a 5.8 Gbp (NG50 = 57.7 kbp) draft genome using ABySS v1.9.0. The assembly was scaffolded with LINKS and RAILS using pseudo-long-reads from targeted denovo assembler Kollector and Illumina Synthetic Long-Reads, as well as reads from long fragment (MPET) libraries. We predicted over 22,000 protein-coding genes using the MAKER2 pipeline and identified the genomic loci of 6,227 candidate long noncoding RNAs (IncRNAs) from a composite reference bullfrog transcriptome. Mitochondrial sequence analysis supported Lithobates as a subgenus of Rana. RNA-Seq experiments identified ~6,000 thyroid hormone– responsive transcripts in the back skin of premetamorphic tadpoles; the majority of which regulate DNA/RNA processing. Moreover, 1/6 th of differentially-expressed transcripts were putative lncRNAs. Our draft bullfrog genome will serve as a useful resource for the amphibian research community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".