Genetic variation in strigolactone production and tillering in rice and its effect on Striga hermonthica infection

Tillering in cereals is a complex process in the regulation of which also signals from the roots in the form of strigolactones play an important role. The strigolactones are signalling molecules that are secreted into the rhizosphere where they act as germination stimulants for root parasitic plants and hyphal branching factors for arbuscular mycorrhizal fungi. On the other hand, they are also transported from the roots to the shoot where they inhibit tillering or branching. In the present study, the genetic variation in strigolactone production and tillering phenotype was studied in twenty rice varieties collected from all over the world and correlated with S. hermonthica infection. Rice cultivars like IAC 165, IAC 1246, Gangweondo and Kinko produced high amounts of the strigolactones orobanchol, 2′-epi-5-deoxystrigol and three methoxy-5-deoxystrigol isomers and displayed low amounts of tillers. These varieties induced high S. hermonthica germination, attachment, emergence as well as dry biomass. In contrast, rice cultivars such as Super Basmati, TN 1, Anakila and Agee displayed high tillering in combination with low production of the aforementioned strigolactones. These varieties induced only low S. hermonthica germination, attachment, emergence and dry biomass. Statistical analysis across all the varieties confirmed a positive correlation between strigolactone production and S. hermonthica infection and a negative relationship with tillering. These results show that genetic variation in tillering capacity is the result of genetic variation in strigolactone production and hence could be a helpful tool in selecting rice cultivars that are less susceptible to S. hermonthica infection.     

Characterization of the natural variation in Arabidopsis thaliana metabolome by the analysis of metabolic distance

Metabolite fingerprinting is widely used to unravel the chemical characteristics of biological samples. Multivariate data analysis and other statistical tools are subsequently used to analyze and visualize the plasticity of the metabolome and/or the relationship between those samples. However, there are limitations to these approaches for example because of the multi-dimensionality of the data that makes interpretation of the data obtained from untargeted analysis almost impossible for an average human being. These limitations make the biological information that is of prime importance in untargeted studies be partially exploited. Even in the case of full exploitation, current methods for relationship elucidation focus mainly on between groups variation and differences. Therefore, a measure that is capable of exploiting both between- and within-group biological variation would be of great value. Here, we examined the natural variation in the metabolome of nine Arabidopsis thaliana accessions grown under various environmental conditions and established a measure for the metabolic distance between accessions and across environments. This data analysis approach shows that there is just a minor correlation between genetic and metabolic diversity of the nine accessions. On the other hand, it delivers so far in Arabidopsis unexplored chemical information and is shown to be biologically relevant for resistance studies.

     

Characterization of the natural variation in <Emphasis Type="Italic"> Arabidopsis thaliana</Emphasis> metabolome by the analysis of metabolic distance

Metabolite fingerprinting is widely used to unravel the chemical characteristics of biological samples. Multivariate data analysis and other statistical tools are subsequently used to analyze and visualize the plasticity of the metabolome and/or the relationship between those samples. However, there are limitations to these approaches for example because of the multi-dimensionality of the data that makes interpretation of the data obtained from untargeted analysis almost impossible for an average human being. These limitations make the biological information that is of prime importance in untargeted studies be partially exploited. Even in the case of full exploitation, current methods for relationship elucidation focus mainly on between groups variation and differences. Therefore, a measure that is capable of exploiting both between- and within-group biological variation would be of great value. Here, we examined the natural variation in the metabolome of nine Arabidopsis thaliana accessions grown under various environmental conditions and established a measure for the metabolic distance between accessions and across environments. This data analysis approach shows that there is just a minor correlation between genetic and metabolic diversity of the nine accessions. On the other hand, it delivers so far in Arabidopsis unexplored chemical information and is shown to be biologically relevant for resistance studies.