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Updated: Dec 8, 2025
Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Global Transcriptome and Correlation Analysis Reveal Cultivar-Specific Molecular Signatures Associated with Fruit
Shaofeng Peng1,2,3, Jia Lu4, Zhen Zhang2,3
1Beijing Forestry University, Haidian, 100083 Beijing, China.
Background:
Oil-tea Camellia is a very important edible oil plant widely distributed in southern China. Tea oil extracted from the oil-tea Camellia seeds is beneficial to health and is considered as a health edible oil. We attempt to identify genes related to fatty acid biosynthesis in an oil-tea Camellia seed kernel, generated a comprehensive transcriptome analysis of the seed kernel at different developmental stages, and explore optimal picking time of fruit. Material and Methods. A gas chromatography-mass spectrometer was used to detect the content of various fatty acids in samples. Transcriptome analysis was performed to detect gene dynamics and corresponding functions.
Results:
Multiple phenotypic data were counted in detail, including the oil content, oleic acid content, linoleic acid content, linolenic acid content, fruit weight, fruit height, fruit diameter, single seed weight, seed length, and seed width in different developmental stages, which indicate that a majority of indicators increased with the development of oil-tea Camellia. The transcriptomics was conducted to perform a comprehensive and system-level view on dynamic gene expression networks for different developmental stages. Short Time-series Expression Miner (STEM) analysis of XL106 (the 6 time points) and XL210 (8 time points) was performed to screen related fatty acid (FA) gene set, from which 1041 candidate genes related to FA were selected in XL106 and 202 related genes were screened in XL210 based on GO and KEGG enrichment. Then, candidate genes and trait dataset were combined to conduct correlation analysis, and 10 genes were found to be strongly connected with several key traits.
Conclusions:
The multiple phenotypic data revealed the dynamic law of changes during the picking stage. Transcriptomic analysis identified a large number of potential key regulatory factors that can control the oil content of dried kernels, oleic acid, linoleic acid, linolenic acid, fresh seed rate, and kernel-to-seed ratio, thereby providing a new insight into the molecular networks underlying the picking stage of oil-tea Camellia, which provides a theoretical basis for the optimal fruit picking point.
