Bacterial canker of kiwifruit, caused by Pseudomonas syringae pv. actinidiae (Psa), has emerged since 2008 and is the most important disease of kiwifruit, threatening its production in the world. Until now, little is known about the molecular interaction between Psa and kiwifruit plants: to elucidate early molecular events of kiwifruits-Psa interaction, Illumina RNA-seq was conducted at 3 h, 24 h and 48 h after Psa inoculation and mock inoculation, both on acibenzolar-S-methyl (ASM)-pretreated and untreated Actinidia chinensis plants. De novo assembly of kiwifruit transcriptome consists of 39,607 transcripts, about 4500 of them were differentially expressed (DE) in the various situations. During infection process, genes modulation caused by Psa in A. chinensis involve about 3000 transcripts modulated that is mainly evident at 3hpi rather than 24hpi or 48hpi. Only few transcripts were common between the three infections time points (1,5%). Moreover, transcripts modulation in infected ASM-untreated plants were higher than in ASM pre-treated infected plants. To investigate transcriptome expression profile during infection process, both in ASM untreated and ASM pre-treated plants, Hierarchical Cluster Analysis (HCA) were performed to reveal the coordinates change of some important gene functional categories. Moreover, MapMan has been shown to be an effective tool to map transcriptome data, to define functional categories and to perform time course analysis in order to identify differentially-represented functional groups. Regulation overview highlight difference in hormonal balance, transcriptional regulation and signaling. For example, seven major families of TF (AP2/ERF, MYB, Myc-bHLH, GATA, NAC, WRKY and GRAS), reported as linked to plant stress responses such as pathogens, were found DE in response to Psa in ASM pretreated plants with respect to the untreated ones. Different TFs were linked also with signaling and hormonal balance and probably involved in the ability of ASM plants to assemble the right defense response against PSA. On the other side, ASM untreated plants try to mount a response at 3 hpi , but not adequate to counteract the infection. Moreover, the RNA-seq technology has permitted to identify novel differentially expressed transcripts of unknown functions but related with infection and ASM treatment. Bacterial canker of kiwifruit, caused by Pseudomonas syringae pv. actinidiae (Psa), has emerged since 2008 and is the most important disease of kiwifruit, threatening its production in the world. Until now, little is known about the molecular interaction between Psa and kiwifruit plants: to elucidate early molecular events of kiwifruits-Psa interaction, Illumina RNA-seq was conducted at 3 h, 24 h and 48 h after Psa inoculation and mock inoculation, both on acibenzolar-S-methyl (ASM)-pretreated and untreated Actinidia chinensis plants. De novo assembly of kiwifruit transcriptome consists of 39,607 transcripts, about 4500 of them were differentially expressed (DE) in the various situations. During infection process, genes modulation caused by Psa in A. chinensis involve about 3000 transcripts modulated that is mainly evident at 3hpi rather than 24hpi or 48hpi. Only few transcripts were common between the three infections time points (1,5%). Moreover, transcripts modulation in infected ASM-untreated plants were higher than in ASM pre-treated infected plants. To investigate transcriptome expression profile during infection process, both in ASM untreated and ASM pre-treated plants, Hierarchical Cluster Analysis (HCA) were performed to reveal the coordinates change of some important gene functional categories. Moreover, MapMan has been shown to be an effective tool to map transcriptome data, to define functional categories and to perform time course analysis in order to identify differentially-represented functional groups. Regulation overview highlight difference in hormonal balance, transcriptional regulation and signaling. For example, seven major families of TF (AP2/ERF, MYB, Myc-bHLH, GATA, NAC, WRKY and GRAS), reported as linked to plant stress responses such as pathogens, were found DE in response to Psa in ASM pretreated plants with respect to the untreated ones. Different TFs were linked also with signaling and hormonal balance and probably involved in the ability of ASM plants to assemble the right defense response against PSA. On the other side, ASM untreated plants try to mount a response at 3 hpi , but not adequate to counteract the infection. Moreover, the RNA-seq technology has permitted to identify novel differentially expressed transcripts of unknown functions but related with infection and ASM treatment.

Deciphering kiwifruit transcriptome during the infection by Pseudomonas syringae pv. actinidiae (Psa)

BURIANI, GIAMPAOLO;CELLINI, ANTONIO;DONATI, IRENE;SPINELLI, FRANCESCO;
2015

Abstract

Bacterial canker of kiwifruit, caused by Pseudomonas syringae pv. actinidiae (Psa), has emerged since 2008 and is the most important disease of kiwifruit, threatening its production in the world. Until now, little is known about the molecular interaction between Psa and kiwifruit plants: to elucidate early molecular events of kiwifruits-Psa interaction, Illumina RNA-seq was conducted at 3 h, 24 h and 48 h after Psa inoculation and mock inoculation, both on acibenzolar-S-methyl (ASM)-pretreated and untreated Actinidia chinensis plants. De novo assembly of kiwifruit transcriptome consists of 39,607 transcripts, about 4500 of them were differentially expressed (DE) in the various situations. During infection process, genes modulation caused by Psa in A. chinensis involve about 3000 transcripts modulated that is mainly evident at 3hpi rather than 24hpi or 48hpi. Only few transcripts were common between the three infections time points (1,5%). Moreover, transcripts modulation in infected ASM-untreated plants were higher than in ASM pre-treated infected plants. To investigate transcriptome expression profile during infection process, both in ASM untreated and ASM pre-treated plants, Hierarchical Cluster Analysis (HCA) were performed to reveal the coordinates change of some important gene functional categories. Moreover, MapMan has been shown to be an effective tool to map transcriptome data, to define functional categories and to perform time course analysis in order to identify differentially-represented functional groups. Regulation overview highlight difference in hormonal balance, transcriptional regulation and signaling. For example, seven major families of TF (AP2/ERF, MYB, Myc-bHLH, GATA, NAC, WRKY and GRAS), reported as linked to plant stress responses such as pathogens, were found DE in response to Psa in ASM pretreated plants with respect to the untreated ones. Different TFs were linked also with signaling and hormonal balance and probably involved in the ability of ASM plants to assemble the right defense response against PSA. On the other side, ASM untreated plants try to mount a response at 3 hpi , but not adequate to counteract the infection. Moreover, the RNA-seq technology has permitted to identify novel differentially expressed transcripts of unknown functions but related with infection and ASM treatment. Bacterial canker of kiwifruit, caused by Pseudomonas syringae pv. actinidiae (Psa), has emerged since 2008 and is the most important disease of kiwifruit, threatening its production in the world. Until now, little is known about the molecular interaction between Psa and kiwifruit plants: to elucidate early molecular events of kiwifruits-Psa interaction, Illumina RNA-seq was conducted at 3 h, 24 h and 48 h after Psa inoculation and mock inoculation, both on acibenzolar-S-methyl (ASM)-pretreated and untreated Actinidia chinensis plants. De novo assembly of kiwifruit transcriptome consists of 39,607 transcripts, about 4500 of them were differentially expressed (DE) in the various situations. During infection process, genes modulation caused by Psa in A. chinensis involve about 3000 transcripts modulated that is mainly evident at 3hpi rather than 24hpi or 48hpi. Only few transcripts were common between the three infections time points (1,5%). Moreover, transcripts modulation in infected ASM-untreated plants were higher than in ASM pre-treated infected plants. To investigate transcriptome expression profile during infection process, both in ASM untreated and ASM pre-treated plants, Hierarchical Cluster Analysis (HCA) were performed to reveal the coordinates change of some important gene functional categories. Moreover, MapMan has been shown to be an effective tool to map transcriptome data, to define functional categories and to perform time course analysis in order to identify differentially-represented functional groups. Regulation overview highlight difference in hormonal balance, transcriptional regulation and signaling. For example, seven major families of TF (AP2/ERF, MYB, Myc-bHLH, GATA, NAC, WRKY and GRAS), reported as linked to plant stress responses such as pathogens, were found DE in response to Psa in ASM pretreated plants with respect to the untreated ones. Different TFs were linked also with signaling and hormonal balance and probably involved in the ability of ASM plants to assemble the right defense response against PSA. On the other side, ASM untreated plants try to mount a response at 3 hpi , but not adequate to counteract the infection. Moreover, the RNA-seq technology has permitted to identify novel differentially expressed transcripts of unknown functions but related with infection and ASM treatment.
2015
2nd International Symposium on Psa - Book of abstracts
21
22
Michelotti, V; Lamontanara, A; Orrù, L; Buriani, G; Cellini, A; Donati, I; Vanneste, J; Cattivelli, L; Spinelli, F; Tacconi, G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/545653
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