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 TSS(286), whereas GroEL2 has two promoters, and the sites are TSS548 and TSS(502). TSS(286) is 14.3 times more abundant than TSS(548) and TSS(548) is 13.8 times more than TSS(502).
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.