Login / Signup

Characterization of peanut phytochromes and their possible regulating roles in early peanut pod development.

Ye ZhangJinbo SunHan XiaChuanzhi ZhaoLei HouBaoshan WangAiqin LiMin ChenShuzhen ZhaoXingjun Wang
Published in: PloS one (2018)
Arachis hypogaea L. geocarpy is a unique feature different from other legume plants. Flowering and fertilization occur above ground, while the following processes of pod formation and development proceed in the soil. The zygote divides only few times to develop into pre-embryo and then further embryo developmental process stops when the gynoecium is exposed to light condition or normal day/night period. In this study, eight phytochrome genes were identified in two wild peanuts (four in Arachis duranensis and four in Arachis ipaensis). Using RACE and homologous cloning, the full CDS of AhphyA, AhphyA-like, AhphyB and AhphyE were acquired in cultivated peanut. Protein structure analysis showed that the conservative coding domains of phytochromes from a number of other plant species were found in these proteins. The C-terminal of AhphyA, AhphyA-like and AhphyB could interact with phytochrome-interacting factor 3 in vitro. The expression patterns of these genes in various tissues were analyzed by qRT-PCR, and significant differences were observed. Interestingly, the expression levels of AhphyA-like changed significantly during gynophore growth and early pod development. Furthermore, protein accumulation patterns of AhphyA and AhphyB in gynophore were different during early pod development stages in that AhphyA and AhphyB proteins were not detected in S1 and S2 gynophores, while significant accumulation of AhphyA and AhphyB were detected in S3 gynophore. These results provided evidence that phytochromes mediated light signal transduction may play key roles in peanut geocarpy development.
Keyphrases
  • poor prognosis
  • binding protein
  • machine learning
  • pregnant women
  • deep learning
  • dna damage
  • physical activity
  • transcription factor
  • depressive symptoms
  • quantum dots
  • amino acid
  • data analysis