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Bulletin of Botanical Research ›› 2016, Vol. 36 ›› Issue (6): 895-901.doi: 10.7525/j.issn.1673-5102.2016.06.013

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Cloning and Expression Analysis of Two NAC Transcription Factors in Bambusa emeiensis

LI Hui-Ping1,2, LI Bang-Yong1,2, HU Shang-Lian1,2, CAO Ying1,2   

  1. 1. Lab of Plant Cell Engineering Southwest University of Science and Technology, Mianyang 621010;
    2. Engineering Research Center for Biomass Resource Utilization and Modification of Sichuan Province, Mianyang 621010
  • Received:2016-08-30 Online:2016-11-15 Published:2016-11-16
  • Supported by:
    National Natural Science Foundation of China(Nos.31400257,31400333); Breeding Program Fund Project by the 13th Five-Year Plan of Sichuan Province(Nos:16ZS212301); Fund of Engineering Research Center for Biomass Resource Utilizaiton and Modification of Sichuan Province(Nos.12zxsk07,13zxsk01); Graduate innovation fund of Southwest University of Science and Technology(Nos.16ycx069)

Abstract: Based on the transcriptome database of Bambusa emeiensis and genome information of Phyllostachys heterocycla, the two NAC genes were cloned by homology cloning technology from the shoots of B.emeiensis, named as BeNAC1(GenBank:KU550706) and BeNAC2(GenBank:KU821586), encoding 313 and 389 amino acids, respectively. By protein function prediction and conserved domain multiple alignment, both of BeNAC1 and BeNAC2 contained NAM conserved region. By protein structure prediction, the putatived three-dimensional structure of BeNAC1 and BeNAC2 protein was similar to a rice protein with known crystal structure. By subcellular localization prediction analysis, BeNAC1 was mainly concentrated in the cytoplasm, and BeNAC2 was mainly concentrated in the nucleus. Tissue expression pattern analysis showed that BeNAC1 and BeNAC2 displayed similar tissue-specific, both having the highest expression on stems, whereas in addition to the bamboo shoots, the expression of BeNAC1 in each tissue tested was higher than that of BeNAC2.

Key words: Bambusa emeiensis, NAC transcription factors, clone, bioinformatics analysis, tissue expression pattern

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