Sequencing and De Novo Analysis of the Hemocytes Transcriptome in Litopenaeus vannamei Response to White Spot Syndrome Virus Infection
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: White spot syndrome virus (WSSV) is a causative pathogen found in most shrimp farming areas of the world and causes large economic losses to the shrimp aquaculture. The mechanism underlying the molecular pathogenesis of the highly virulent WSSV remains unknown. To better understand the virus-host interactions at the molecular level, the transcriptome profiles in hemocytes of unchallenged and WSSV-challenged shrimp (Litopenaeus vannamei) were compared using a short-read deep sequencing method (Illumina). RESULTS: RNA-seq analysis generated more than 25.81 million clean pair end (PE) reads, which were assembled into 52,073 unigenes (mean size = 520 bp). Based on sequence similarity searches, 23,568 (45.3%) genes were identified, among which 6,562 and 7,822 unigenes were assigned to gene ontology (GO) categories and clusters of orthologous groups (COG), respectively. Searches in the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG) mapped 14,941 (63.4%) unigenes to 240 KEGG pathways. Among all the annotated unigenes, 1,179 were associated with immune-related genes. Digital gene expression (DGE) analysis revealed that the host transcriptome profile was slightly changed in the early infection (5 hours post injection) of the virus, while large transcriptional differences were identified in the late infection (48 hpi) of WSSV. The differentially expressed genes mainly involved in pattern recognition genes and some immune response factors. The results indicated that antiviral immune mechanisms were probably involved in the recognition of pathogen-associated molecular patterns. CONCLUSIONS: This study provided a global survey of host gene activities against virus infection in a non-model organism, pacific white shrimp. Results can contribute to the in-depth study of candidate genes in white shrimp, and help to improve the current understanding of host-pathogen interactions.
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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 | 0.001 | 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 it