Phylogenomics from Whole Genome Sequences Using aTRAM
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Bibliographic record
Abstract
Novel sequencing technologies are rapidly expanding the size of data sets that can be applied to phylogenetic studies. Currently the most commonly used phylogenomic approaches involve some form of genome reduction. While these approaches make assembling phylogenomic data sets more economical for organisms with large genomes, they reduce the genomic coverage and thereby the long-term utility of the data. Currently, for organisms with moderate to small genomes ($<$1000 Mbp) it is feasible to sequence the entire genome at modest coverage ($10-30\times$). Computational challenges for handling these large data sets can be alleviated by assembling targeted reads, rather than assembling the entire genome, to produce a phylogenomic data matrix. Here we demonstrate the use of automated Target Restricted Assembly Method (aTRAM) to assemble 1107 single-copy ortholog genes from whole genome sequencing of sucking lice (Anoplura) and out-groups. We developed a pipeline to extract exon sequences from the aTRAM assemblies by annotating them with respect to the original target protein. We aligned these protein sequences with the inferred amino acids and then performed phylogenetic analyses on both the concatenated matrix of genes and on each gene separately in a coalescent analysis. Finally, we tested the limits of successful assembly in aTRAM by assembling 100 genes from close- to distantly related taxa at high to low levels of coverage.Both the concatenated analysis and the coalescent-based analysis produced the same tree topology, which was consistent with previously published results and resolved weakly supported nodes. These results demonstrate that this approach is successful at developing phylogenomic data sets from raw genome sequencing reads. Further, we found that with coverages above $5-10\times$, aTRAM was successful at assembling 80-90% of the contigs for both close and distantly related taxa. As sequencing costs continue to decline, we expect full genome sequencing will become more feasible for a wider array of organisms, and aTRAM will enable mining of these genomic data sets for an extensive variety of applications, including phylogenomics. [aTRAM; gene assembly; genome sequencing; phylogenomics.].
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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 | 0.000 |
| 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 it