ABSTRACT
Despite their overwhelming complexity, living cells display a high degree of internal mechanical and functional organization which can largely be attributed to the intracellular biopolymer scaffold, the cytoskeleton. Being a very complex system far from thermodynamic equilibrium, the cytoskeleton's ability to organize is at the same time challenging and fascinating. The extensive amounts of frequently interacting cellular building blocks and their inherent multifunctionality permits highly adaptive behavior and obstructs a purely reductionist approach. Nevertheless (and despite the field's relative novelty), the physics approach has already proved to be extremely successful in revealing very fundamental concepts of cytoskeleton organization and behavior. This review aims at introducing the physics of the cytoskeleton ranging from single biopolymer filaments to multicellular organisms. Throughout this wide range of phenomena, the focus is set on the intertwined nature of the different physical scales (levels of complexity) that give rise to numerous emergent properties by means of self-organization or self-assembly.
ABSTRACT
ABSTRACT A quantitative trait loci (QTL) analysis of resistance to Sclerotinia sclerotiorum was carried out with 283 sunflower (Helianthus annuus) F(2:3) families derived from a cross between a resistant (SWS-B-04) and a highly susceptible sunflower inbred line. For that purpose, a genetic map based on 195 amplified fragment length polymorphism and 20 simple sequence repeat markers was constructed. The map has a size of 2,273.5 centimorgans and comprises 17 linkage groups, 12 of which could be associated to already defined linkage groups. The heads of sunflower F(3) families were artificially inoculated by using sclerotinia mycelium in three field environments. The lesion length was measured in centimeters 1 week postinoculation and head rot was scored according to a 1-to-8 head rot scale 2 weeks postinoculation. Using the composite interval mapping procedure, three QTL for lesion length and two QTL for head rot could be identified. These QTL explain 10.6 to 17.1% of the total phenotypic variance.