Inferring the shallow phylogeny of true salamanders (Salamandra) by multiple phylogenomic approaches
Bibliographic record
Abstract
The rise of high-throughput sequencing techniques provides the unprecedented opportunity to analyse controversial phylogenetic relationships in great depth, but also introduces a risk of being misinterpreted by high node support values influenced by unevenly distributed missing data or unrealistic model assumptions. Here, we use three largely independent phylogenomic data sets to reconstruct the controversial phylogeny of true salamanders of the genus Salamandra, a group of amphibians providing an intriguing model to study the evolution of aposematism and viviparity. For all six species of the genus Salamandra, and two outgroup species from its sister genus Lyciasalamandra, we used RNA sequencing (RNAseq) and restriction site associated DNA sequencing (RADseq) to obtain data for: (1) 3070 nuclear protein-coding genes from RNAseq; (2) 7440 loci obtained by RADseq; and (3) full mitochondrial genomes. The RNAseq and RADseq data sets retrieved fully congruent topologies when each of them was analyzed in a concatenation approach, with high support for: (1) S. infraimmaculata being sister group to all other Salamandra species; (2) S. algira being sister to S. salamandra; (3) these two species being the sister group to a clade containing S. atra, S. corsica and S. lanzai; and (4) the alpine species S. atra and S. lanzai being sister taxa. The phylogeny inferred from the mitochondrial genome sequences differed from these results, most notably by strongly supporting a clade containing S. atra and S. corsica as sister taxa. A different placement of S. corsica was also retrieved when analysing the RNAseq and RADseq data under species tree approaches. Closer examination of gene trees derived from RNAseq revealed that only a low number of them supported each of the alternative placements of S. atra. Furthermore, gene jackknife support for the S. atra - S. lanzai node stabilized only with very large concatenated data sets. The phylogeny of true salamanders thus provides a compelling example of how classical node support metrics such as bootstrap and Bayesian posterior probability can provide high confidence values in a phylogenomic topology even if the phylogenetic signal for some nodes is spurious, highlighting the importance of complementary approaches such as gene jackknifing. Yet, the general congruence among the topologies recovered from the RNAseq and RADseq data sets increases our confidence in the results, and validates the use of phylotranscriptomic approaches for reconstructing shallow relationships among closely related taxa. We hypothesize that the evolution of Salamandra has been characterized by episodes of introgressive hybridization, which would explain the difficulties of fully reconstructing their evolutionary relationships.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".