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Updated: Jan 10, 2026

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Comparative transcriptomic profiling of field-grown cassava genotypes across season transitions
Mariam Webber-Birungi1, Joseph Enye Iboyi1,2, Erik Alexandersson3,4
1International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
None:
Cassava (Manihot esculenta, Crantz) is a perennial crop cultivated in tropical and subtropical areas. In its cultivation cycle, it encounters environmental stresses related to changes in temperature and water fluctuations during seasonal transitions. We profiled the transcriptomes of four field-grown genotypes to investigate the molecular basis of adaptation to season transitions. 3'mRNA-seq libraries were prepared from samples collected from storage roots to capture gene expression changes associated with shifts from rainy to dry and dry to rainy seasons. Reproducibility and variability within the dataset were evaluated using correlation analysis and principal component analysis, providing confidence in data quality and consistency across samples. The usability of these data was proved by differential expression analysis during the rainy-to-dry and dry-to-rainy transitions, and by functional enrichment analysis. The detailed information of the experimental environmental conditions and of the workflow from planting to final DEGs analysis provided, make this dataset a useful resource for future research on plant responses to environmental fluctuations and to identify candidate genes for crop improvement strategies for climate-resilient varieties.
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