IDENTIFICATION OF CANDIDATE GENES INVOLVED IN NITRIC OXIDE SIGNALLING DURING HYPERSENSITIVE-CELL DEATH

Nitric oxide (NO) is a widespread signalling molecule that regulates various aspects of plant growth, development and stress responses. Numerous studies have demonstrated NO accumulation and downstream NO signalling plays an important role in plant defence against pathogens. In particular NO plays a crucial role in mediating the hypersensitive disease resistance response (HR). This resistance mechanism includes the activation of a programmed cell death at the attempted sites of infection, aiming to restrict pathogen infection and spread (Jones and Dangl, 2006). NO was shown to work synergistically with hydrogen peroxide to trigger the HR-cell death. Despite extensive investigation on this signalling pathway, the molecular mechanism through which NO acts is still unclear. To gain further insights specifically into NO signaling network underlying the activation of HR-cell death, a NO fumigation system, which allows treating plants with a precise amount of NO gas concentration in air has been established in our laboratory and previously tested. An optimization of such system was then successfully applied here to establish conditions of NO treatment that activate a uniform and reproducible cell death program in a larger number (320) of 4-week-old Arabidopsis thaliana plants, with the final aim of improve the screening performance. Then by using this facility and newly established NO fumigation conditions we screened further 39225 M2 EMS mutagenized Arabidopsis thaliana. These, together with previously fumigated mutants, complexively allowed to rescue 30 mutants presenting a consistent impaired NO response phenotype. These pre-selected mutants were then infected by pathogen to confirm a possible alteration also in HR-cell death. Among these, 14 mutants were found to be impaired HR-cell death likely because of alterations related to NO-signalling. The candidates were then subjected to additional genetic analysis to test inheritance of the mutant phenotype and to confirm they were suitable for to the identification of the causal mutation through deep sequencing based strategies. The genetic inheritance of the mutant phenotype was determined through analysis in the backcross F1 and F2 progeny. Phenotypic evaluation of the BC1F1 progeny demonstrated that phenotype of one of the candidates is caused by a dominant mutation. Therefore, this candidate was excluded from further studies. So far, BC1F2 populations and segregation analysis in the F2 progeny have been performed for three of the 14 candidate mutants. Furthermore allelism among six selected mutants was checked which revealed two allelic mutants, which were however sharing the same original mutational event, thus strengthening the reliability of our screening procedure. In order to set a strategy for the identification of the causal mutation by the “mapping by sequencing” approach, sequencing pools of resistant BC1F2 recombinants were generated and sequenced by Illumina NGS. However, our first attempt to identify causal mutation based on bulked BC1F2 didn’t provide expected SNP index at putative causal mutation loci because of false positive contamination in the sequencing pool, suggesting that BC1F3 recombinants with a confirmed phenotype should be used, in our case, for the identification of the causal mutation through this approach.