Signalling and genetic networks underlie most biological processes and are often complex, containing many highly connected components. Modelling these networks can provide insight into mechanisms but is challenging given that rate parameters are often not well defined. Boolean modelling, in which components can only take on a binary value with connections encoded by logic equations, is able to circumvent some of these challenges, and has emerged as a viable tool to probe these complex networks. In this review, we will give an overview of Boolean modelling, with a specific emphasis on its use in plant biology. We review how Boolean modelling can be used to describe biological networks and then discuss examples of its applications in plant genetics and plant signalling.

Improving the drought resistance of high yielding rice (Oryza sativa L.) varieties for upland areas is a goal of rice breeders since upland rice relies exclusively on rainfall for water and is generally low yielding. Identifying quantitative trait loci (QTLs) which confer drought resistance promises to speed this goal. We have previously described the use of 82 restriction fragment length polymorphism (RFLP) markers in the genetic mapping of root growth characteristics that are potentially involved in drought resistance in a population of 178 F2 plants derived from a cross of two drought resistant upland varieties, Azucena and Bala. Here we report the characterization and QTL mapping of three other mechanisms of drought resistance, leaf rolling, stomatal behaviour and early flowering, in this population. When the youngest fully expanded leaf was excised from 12 rice varieties, ‘IR20’ and ‘Bala’ were identified as slow at rolling. Although ‘Azucena’ rolled its leaves much faster than ‘Bala’ upon excision, stomatal resistance rose more rapidly in ‘Bala’, resulting in a lower rate of water loss. By assessing leaf rolling and stomatal resistance in the F2 population, it was possible to identify QTLs for these traits. A QTL for slow leaf rolling from ‘Bala’ was found on chromosome 1. Two QTLs associated with resting stomatal conductance were found on chromosomes 3 and 12. QTLs for the rate of stomatal closure were found on chromosomes 3 and 7. In addition, it was possible to map QTLs associated with the days to heading which were found on chromosomes 3, 8 and 10. These results identify markers of potential value to breeders and are discussed in the context of previously reported data for heading date QTLs in rice and for stomatal conductance QTLs in maize.