RESUMO
The NAC family is an important transcription factor which regulate plant growth and developmentï¼ signal transductionï¼ and stress response.In this studyï¼ the protein identificationï¼ subfamily classificationï¼ the determination of physical and chemical propertiesï¼ protein structureï¼ and expression pattern of NAC family were performed using bioinformatic methods based on the RNA-seq data of ginger. The results showed that a total of 72 NAC transcription factors were identified in 271.1 Mb total nucleotidesï¼ and they could be clustered into 13 subfamilies according to the phylogenetic tree.The physical and chemical propertiesï¼ structure analysis revealed that the amino acid number and isoelectric point were different among 13 NAC subfamilies; the secondary structure of NACs transcription factors mainly consist of random coilï¼ and the tertiary structure is similar.In additionï¼the expression patterns of genes under different soil moisture and Ralstonia solanacearum infection showed that 23 NACs were differentially expressedï¼ which were mainly distributed in â §ï¼â ¦ï¼ and â ©â ¤ subfamilies related to plant senescenceï¼ hormone metabolism and cell wall metabolism.The results provide some valuable information for the research and development of NAC transcription factors in ginger.
Assuntos
Proteínas de Plantas/genética , RNA de Plantas/genética , Fatores de Transcrição/genética , Zingiber officinale/genética , Regulação da Expressão Gênica de Plantas , Família Multigênica , Filogenia , Estrutura Terciária de Proteína , Análise de Sequência de RNARESUMO
Sweet potato flowers were collected for a transcriptome analysis to identify the putative floral-specific and flowering regulatory-related genes by using the RNA-sequencing technique. Pair-end short reads were de novo assembled by an integrated strategy, and then the floral transcriptome was carefully compared with several published vegetative transcriptomes. A total of 2595 putative floral-specific and 2928 putative vegetative-specific transcripts were detected. We also identified a large number of transcripts similar to the key genes in the flowering regulation network of Arabidopsis thaliana.