ena-STUDY-CURTIN UNIVERSITY-05-10-2018-02:41:53:037-51
Exploration of wheat and pathogen transcriptomes during tan spot infection
Objectives: The fungus Pyrenophora tritici-repentis is the causal agent of tan spot, a major disease of wheat (Triticum aestivum). Here, we used RNA sequencing to generate transcriptional datasets for both the host and pathogen during infection and during in vitro pathogen growth stages. Data description: To capture gene expression during wheat infection with P. tritici-repentis isolate M4, RNA datasets were generated for wheat inoculations with P. tritici-repentis (infection) and a mock (control) 3 and 4 days post-infection. The P. tritici-repentis isolate M4 was also RNA sequenced to capture gene expression in vitro at two different growth stages: 7-day old vegetative mycelia and 9-day old sporulating mycelia. In total 6 RNA datasets are available to aid in the validation of predicted genes of P. tritici-repentis and wheat. The datasets generated offer an insight into the transcriptomic profile of the host-pathogen interaction and can be used to investigate the expression of a subset of transcripts or targeted genes prior to designing cost-intensive RNA sequencing experiments, that would be best further explored with replication and a time series analysis.
Objectives: The fungus Pyrenophora tritici-repentis is the causal agent of tan spot, a major disease of wheat (Triticum aestivum). Here, we used RNA sequencing to generate transcriptional datasets for both the host and pathogen during infection and during in vitro pathogen growth stages. Data description: To capture gene expression during wheat infection with P. tritici-repentis isolate M4, RNA datasets were generated for wheat inoculations with P. tritici-repentis (infection) and a mock (control) 3 and 4 days post-infection. The P. tritici-repentis isolate M4 was also RNA sequenced to capture gene expression in vitro at two different growth stages: 7-day old vegetative mycelia and 9-day old sporulating mycelia. In total 6 RNA datasets are available to aid in the validation of predicted genes of P. tritici-repentis and wheat. The datasets generated offer an insight into the transcriptomic profile of the host-pathogen interaction and can be used to investigate the expression of a subset of transcripts or targeted genes prior to designing cost-intensive RNA sequencing experiments, that would be best further explored with replication and a time series analysis.