Dataset Information

Sugar Metabolism and Transcriptome Analysis Reveal Key Sugar Transporters during Camellia oleifera Fruit Development.

ABSTRACT: Camellia oleifera is a widely planted woody oil crop with economic significance because it does not occupy cultivated land. The sugar-derived acetyl-CoA is the basic building block in fatty acid synthesis and oil synthesis in C. oleifera fruit; however, sugar metabolism in this species is uncharacterized. Herein, the changes in sugar content and metabolic enzyme activity and the transcriptomic changes during C. oleifera fruit development were determined in four developmental stages (CR6: young fruit formation; CR7: expansion; CR9: oil transformation; CR10: ripening). CR7 was the key period of sugar metabolism since it had the highest amount of soluble sugar, sucrose, and glucose with a high expression of genes related to sugar transport (four sucrose transporters (SUTs) or and one SWEET-like gene, also known as a sugar, will eventually be exported transporters) and metabolism. The significant positive correlation between their expression and sucrose content suggests that they may be the key genes responsible for sucrose transport and content maintenance. Significantly differentially expressed genes enriched in the starch and sucrose metabolism pathway were observed in the CR6 versus CR10 stages according to KEGG annotation. The 26 enriched candidate genes related to sucrose metabolism provide a molecular basis for further sugar metabolism studies in C. oleifera fruit.

SUBMITTER: He Y

PROVIDER: S-EPMC8775869 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundOil-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.ResultsMultiple 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.ConclusionsThe 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.

Project description:BackgroundRapidly driven by the need for developing sustainable sources of nutritionally important fatty acids and the rising concerns about environmental impacts after using fossil oil, oil-plants have received increasing awareness nowadays. As an important oil-rich plant in China, Camellia oleifera has played a vital role in providing nutritional applications, biofuel productions and chemical feedstocks. However, the lack of C. oleifera genome sequences and little genetic information have largely hampered the urgent needs for efficient utilization of the abundant germplasms towards modern breeding efforts of this woody oil-plant.ResultsHere, using the 454 GS-FLX sequencing platform, we generated approximately 600,000 RNA-Seq reads from four tissues of C. oleifera. These reads were trimmed and assembled into 104,842 non-redundant putative transcripts with a total length of ∼38.9 Mb, representing more than 218-fold of all the C. oleifera sequences currently deposited in the GenBank (as of March 2014). Based on the BLAST similarity searches, nearly 42.6% transcripts could be annotated with known genes, conserved domains, or Gene Ontology (GO) terms. Comparisons with the cultivated tea tree, C. sinensis, identified 3,022 pairs of orthologs, of which 211 exhibited the evidence under positive selection. Pathway analysis detected the majority of genes potentially related to lipid metabolism. Evolutionary analysis of omega-6 fatty acid desaturase (FAD2) genes among 20 oil-plants unexpectedly suggests that a parallel evolution may occur between C. oleifera and Olea oleifera. Additionally, more than 2,300 simple sequence repeats (SSRs) and 20,200 single-nucleotide polymorphisms (SNPs) were detected in the C. oleifera transcriptome.ConclusionsThe generated transcriptome represents a considerable increase in the number of sequences deposited in the public databases, providing an unprecedented opportunity to discover all related-genes associated with lipid metabolic pathway in C. oleifera. It will greatly enhance the generation of new varieties of C. oleifera with increased yields and high quality.

Dataset Information

Sugar Metabolism and Transcriptome Analysis Reveal Key Sugar Transporters during Camellia oleifera Fruit Development.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets