Transcriptional start site analysis based on genetic fragment analysis system: from prediction to data evaluation
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    Abstract:

    [Objective] To establish a pipeline for unknown transcriptional start site (TSS) identification without radioactivity, we used genetic fragment analysis system and replenished two steps regarding prediction and evaluation.[Methods] We used unknown TSSs of GroEL genes from M. xanthus as a case. Firstly, we predicted the potential TSSs through bioinformatics databases. According to the prediction, we designed and synthesized fluorescence labeled primers to carry out the reverse transcription reactions. Further, we took advantage of the genetic fragment analysis system to identify TSSs with internal standards. Finally, we applied the normal distribution theory to evaluate the data.[Results] We determined the numbers, abundances and accurate sites of the TSSs:GroEL1 has one promoter and the site is TSS286, whereas GroEL2 has two promoters, and the sites are TSS548 and TSS502. TSS286 is 14.3 times more abundant than TSS548 and TSS548 is 13.8 times more than TSS502.[Conclusion] The bioinformatics analyzing indicates the range for the experimental design. TSS determination through genetic fragment analysis system is safer, more automatic and accurate. Normal distribution theory further refines the reliability of results. Combination of the three techniques establishes a more complete pipeline of primer extension for unknown TSS determination.

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Zhifeng Li, Wenyan Zhang, Yang Liu, Shaofeng Qu, Yan Wang, Liping Zhu, Yuezhong Li. Transcriptional start site analysis based on genetic fragment analysis system: from prediction to data evaluation. [J]. Acta Microbiologica Sinica, 2017, 57(2): 254-263

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History
  • Received:June 28,2016
  • Revised:August 05,2016
  • Adopted:
  • Online: January 19,2017
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