New insights into the blood‐stage transcriptome of <i>Plasmodium falciparum</i> using RNA‐Seq
Why this work is in the frame
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Bibliographic record
Abstract
Recent advances in high-throughput sequencing present a new opportunity to deeply probe an organism's transcriptome. In this study, we used Illumina-based massively parallel sequencing to gain new insight into the transcriptome (RNA-Seq) of the human malaria parasite, Plasmodium falciparum. Using data collected at seven time points during the intraerythrocytic developmental cycle, we (i) detect novel gene transcripts; (ii) correct hundreds of gene models; (iii) propose alternative splicing events; and (iv) predict 5' and 3' untranslated regions. Approximately 70% of the unique sequencing reads map to previously annotated protein-coding genes. The RNA-Seq results greatly improve existing annotation of the P. falciparum genome with over 10% of gene models modified. Our data confirm 75% of predicted splice sites and identify 202 new splice sites, including 84 previously uncharacterized alternative splicing events. We also discovered 107 novel transcripts and expression of 38 pseudogenes, with many demonstrating differential expression across the developmental time series. Our RNA-Seq results correlate well with DNA microarray analysis performed in parallel on the same samples, and provide improved resolution over the microarray-based method. These data reveal new features of the P. falciparum transcriptional landscape and significantly advance our understanding of the parasite's red blood cell-stage transcriptome.
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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 | 0.001 |
| 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