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Identification of MV-generated ROS responsive EST clones in floral buds of Litchi chinensis Sonn
KEY MESSAGE : A suppression subtractive hybridization library was constructed using inflorescence primordia of ‘Nuomici’ litchi to identify EST clones responsive to MV-generated ROS. 93 ESTs could be aligned as unique gene sequences in the inflorescence primordia of litchi. Litchi is an evergreen wo...
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Published in: | Plant cell reports 2013-09, Vol.32 (9), p.1361-1372 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | KEY MESSAGE : A suppression subtractive hybridization library was constructed using inflorescence primordia of ‘Nuomici’ litchi to identify EST clones responsive to MV-generated ROS. 93 ESTs could be aligned as unique gene sequences in the inflorescence primordia of litchi. Litchi is an evergreen woody tree widely cultivated in subtropical and tropical regions. However, defective flowering is a pending problem of litchi production. Our previous study indicated that reactive oxygen species (ROS) induced by methyl viologen dichloride hydrate (MV) promotes flowering in litchi. In the present study, a suppression subtractive hybridization (SSH) library was constructed using inflorescence primordia of ‘Nuomici’ with the aim to find out ROS responsive clones during floral differentiation. 1856 Expressed sequence tag (EST) clones were randomly selected. Clones carrying single exogenous fragments were screened by reverse northern analysis to identify those responsive to MV-generated ROS. A total of 783 differentially expressed EST clones were identified as MV responsive cDNA and were subjected to sequencing. Among them, 26 clones were represented more than three times. 783 clones were aligned to 93 unique gene sequences. The unique genes were classified into 9 categories. 16 % of them were involved in transport facilitation, 11 % in transcription regulation, 4 % in stress response, 9 % in carbohydrate metabolism, 1 % in secondary metabolism, 14 % in intracellular signaling, and 25 % in other metabolism, while 9 % were genes with unknown functions and 11 % were genes with no match in the database. |
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ISSN: | 0721-7714 1432-203X |
DOI: | 10.1007/s00299-013-1448-8 |