Diatom Biodiversity and Speciation Revealed by Comparative Analysis of Mitochondrial Genomes
Bibliographic record
Abstract
Diatoms (Bacillariophyta) constitute one of the most diverse and ecologically significant groups of phytoplankton, comprising 100,000–200,000 species in three classes Bacillariophyceae, Mediophyceae, and Coscinodiscophyceae. However, due to the limited resolution of common molecular markers including 18S rDNA, 28S rDNA, ITS, rbcL, and cox1, diatom biodiversity has not been adequately ascertained. Organelle genomes including mitochondrial genomes (mtDNAs) have been proposed to be “super barcodes” for distinguishing diatom species because of their rich genomic content, and the rapid progress of DNA sequencing technologies that has made it possible to construct mtDNAs with increasing throughout and decreasing cost. Here, we constructed complete mtDNAs of 15 diatom species including five Coscinodiscophyceae species (Guinardia delicatula, Guinardia striata, Stephanopyxis turris, Paralia sulcata, and Actinocyclus sp.), four Mediophyceae species (Hemiaulus sinensis, Odontella aurita var. minima, Lithodesmioides sp., and Helicotheca tamesis), and six Bacillariophyceae species (Nitzschia ovalis, Nitzschia sp., Nitzschia traheaformis, Cylindrotheca closterium, Haslea tsukamotoi, and Pleurosigma sp.) to test the practicality of using mtDNAs as super barcodes. We found that mtDNAs have much higher resolution compared to common molecular markers as expected. Comparative analysis of mtDNAs also suggested that mtDNAs are valuable in evolutionary studies by revealing extensive genome rearrangement events with gene duplications, gene losses, and gains and losses of introns. Synteny analyses of mtDNAs uncovered high conservation among species within an order, but extensive rearrangements including translocations and/or inversions between species of different orders within a class. Duplication of cox1 was discovered for the first time in diatoms in Nitzschia traheaformis and Haslea tsukamotoi. Molecular dating analysis revealed that the three diatom classes split 100 Mya and many diatom species appeared since 50 Mya. In conclusion, more diatom mtDNAs representing different orders will play great dividends to explore biodiversity and speciation of diatoms in different ecological regions.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".