Pan-Transcriptome Analysis of Pine Wilt Disease in Resistant and Susceptible Pinus Species

Table 1_Pan-transcriptome analysis of pine wilt disease-resistant and susceptible Pinus species and a hybrid.xlsx contains transcriptomic data from a study comparing pine wilt disease progression. The dataset, created by Bae Young Choi and last updated in March 2026, includes results from a deep learning-based phenotyping program and pan-transcriptome analysis of three susceptible and three resistant Pinus species and a hybrid over 14 weeks post-infection.

Use Cases

• Identify gene expression markers for disease resistance based on transcriptomic profiles of susceptible and resistant species.
• Train models for high-throughput disease symptom quantification based on the described deep learning phenotyping program.
• Investigate the role of specific gene families, such as the elongation factor Tu receptor (EFR) and pathogenesis-related (PR) genes, in pine wilt disease response.
• Compare molecular responses, such as leaf abscission and abscisic acid pathway activation, between different Pinus species.

Strengths

• Includes data from six distinct biological entities: three susceptible and three resistant Pinus species and a hybrid.
• Data collection spans a defined 14-week observation period after pine wood nematode infection.
• Analysis integrates a novel deep learning-based phenotyping program for symptom quantification.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (21.9 KB), indicating a limited scope, likely containing summary or processed results rather than raw sequencing data.

Provenance

Source

Bae Young Choi via figshare

Collection Method

Deep learning-based phenotyping and pan-transcriptome analysis of Pinus species infected with pine wood nematode.

Time Range

Observation period of 14 weeks post-infection.

Freshness

Last updated 2026-03-25 22:01:55; freshness should be verified.