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Identification of Anthocyanins-Related Glutathione S-Transferase (GST) Genes in the Genome of Cultivated Strawberry (Fragaria × ananassa).

Yuanxiu LinLianxi ZhangJiaHao ZhangYunting ZhangYan WangQing ChenYa LuoYunting ZhangMengyao LiXiao-Rong WangHao-Ru Tang
Published in: International journal of molecular sciences (2020)
Anthocyanins are responsible for the red color of strawberry, they are a subclass of flavonoids synthesized in cytosol and transferred to vacuole to form the visible color. Previous studies in model and ornamental plants indicated members of the glutathione S-transferase (GST) gene family were involved in vacuolar accumulation of anthocyanins. In the present study, a total of 130 FaGST genes were identified in the genome of cultivated strawberry (Fragaria × ananassa), which were unevenly distributed across the 28 chromosomes from the four subgenomes. Evolutionary analysis revealed the expansion of FaGST family was under stable selection and mainly drove by WGD/segmental duplication event. Classification and phylogenetic analysis indicated that all the FaGST genes were clarified into seven subclasses, among which FaGST1, FaGST37, and FaGST97 belonging to Phi class were closely related to FvRAP, an anthocyanin-related GST of wildwood strawberry, and this clade was clustered with other known anthocyanin-related GSTs. RNAseq-based expression analysis at different developmental stages of strawberry revealed that the expression of FaGST1, FaGST37, FaGST39, FaGST73, and FaGST97 was gradually increased during the fruit ripening, consistent with the anthocyanins accumulation. These expression patterns of those five FaGST genes were also significantly correlated with those of other anthocyanin biosynthetic genes such as FaCHI, FaCHS, and FaANS, as well as anthocyanin regulatory gene FaMYB10. These results indicated FaGST1, FaGST37, FaGST39, FaGST73, and FaGST97 may function in vacuolar anthocyanin accumulation in cultivated strawberry.
Keyphrases
  • genome wide
  • genome wide identification
  • bioinformatics analysis
  • dna methylation
  • poor prognosis
  • transcription factor
  • genome wide analysis
  • machine learning
  • copy number
  • gene expression
  • drug induced