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Genome-wide survey and expression analyses of the GRAS gene family in Brassica napus reveals their roles in root development and stress response.

Pengcheng GuoJing WenJin YangYunzhuo KeMangmang WangMingming LiuFeng RanYunwen WuPengfeng LiJiana LiHai Du
Published in: Planta (2019)
Genome-wide identification, classification, expression analyses, and functional characterization of GRAS genes in oil crop, Brassica napus, indicate their importance in root development and stress response. GRAS proteins are a plant-specific transcription factor gene family involved in tissues development and stress response. We classified 87 putative GRAS genes in the Brassica napus genome (BnGRASs) into 13 subfamilies by phylogenetic analysis. The C-terminal GRAS domains of Brassica napus (B. napus) proteins were less conserved among subfamilies, but were conserved within each subfamily. A series of analyses revealed that 89.7% of the BnGRASs did not have intron insertions, and 24 specific-motifs were found at the N-terminal. A highly conserved microRNA 171 (miRNA171) target was observed specifically in the HAM subfamily across land plants. A total of 868 pairs of interaction proteins were predicted, the primary of which were transcription factors involved in transcriptional regulation and signal transduction. Integrated comparative analysis of GRAS genes across 26 species of algae, mosses, ferns, gymnosperms, and angiosperms revealed that this gene family originated in early mosses and was classified into 19 subfamilies, 14 of which may have originated prior to bryophyte evolution. RNA-Seq analysis demonstrated that most BnGRASs were widely expressed in different tissues/organs at different stages in B. napus, and 24 BnGRASs were highly/specifically expressed in roots. Results from a qRT-PCR analysis suggested that two BnGRASs belonging to SCR and LISCL subfamilies potentially have important roles in the stress response of roots.
Keyphrases
  • genome wide identification
  • transcription factor
  • rna seq
  • single cell
  • genome wide
  • dna binding
  • poor prognosis
  • dna methylation
  • climate change
  • gene expression
  • machine learning
  • long non coding rna
  • fatty acid