Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Changes in morphology and physiology of an East Mediterranean sponge in different habitats

The sponge Tetilla sp. (Tetractinomorpha: Tetillidae) is a common species in the eastern Mediterranean. This sponge inhabits four different habitat types differing in wave impact and irradiance levels. Two of these habitats (a shallow cave and deep water) are characterized by relatively calm water, whereas the other two (shallow exposed site and tide pools) are in turbulent water with high energy flow. The present study examined the influence of physical (depth, illumination and water motion) and biotic factors on morphology, skeletal plasticity and reproductive traits among the four spatially separated populations. Sponges from tidal pools had significantly larger body volume than sponges from deep water and from shallow caves (ANOVA: tidal-deep P< 0.0001; tidal-shallow caves P< 0.05). Sponges from exposed habitats were significantly larger than deep-water sponges (ANOVA: P=0.01). In addition, individuals from tide pools and from the exposed habitat had a significantly higher proportion of structural silica than sponges from the calmer deep water and from the cave sites. Oxea spicules in sponges from the calm habitats were significantly shorter than in those from the tidal pools and the exposed habitats. The percentage of spicules out of a sponge's dry weight in individuals transplanted from deep (calm) to shallow (turbulent) water significantly increased by 21.9&PLUSMN; 12.9%. The new spicule percentage did not differ significantly from that of sponges originally from shallow water. Oocyte diameter differed significantly between habitats. The maximal size of mature eggs was found in deep-water sponges in June (97&PLUSMN; 5 μ m). In the shallow habitats, a smaller maximal oocyte diameter was found in the cave, in May (56.5&PLUSMN; 3 μ m). Furthermore, oocyte density in shallow-water sponges was highest in May and decreased in June (with 88.2&PLUSMN; 9 and 19.3&PLUSMN; 9 oocytes mm(-2), respectively). At the same time (June), oocyte density of deep-water sponges had just reached its maximum (155&PLUSMN; 33.7 oocytes mm(-2)). The difference in oocyte size and density between deep- and shallow-water individuals indicates an earlier gamete release in the shallow sponge population. The results suggest that plasticity in skeletal design of this sponge indicates a trade off between spicule production and investment in reproduction.

Mind and body: Concepts of human cognition, physiology and false belief in children with autism or typical development

This study examined theory of mind (ToM) and concepts of human biology (eyes, heart, brain, lungs and mind) in a sample of 67 children, including 25 high functioning children with autism (age 6-13), plus age-matched and preschool comparison groups. Contrary to Baron-Cohen [1989, Journal of Autism and Developmental Disorders, 19(4), 579-600], most children with autism correctly understood the functions of the brain (84%) and the mind (64%). Their explanations were predominantly mentalistic. They outperformed typically developing preschoolers in understanding inner physiological (heart, lungs) and cognitive (brain, mind) systems, and scored as high as age-matched typical children. Yet, in line with much previous ToM research, most children with autism (60%) failed false belief, and their ToM performance was unrelated to their understanding of. human biology. Results were discussed in relation to neurobiological and social-experiential accounts of the ToM deficit in autism.

Coadaptation: A unifying principle in evolutionary thermal biology

Over the last 50 yr, thermal biology has shifted from a largely physiological science to a more integrated science of behavior, physiology, ecology, and evolution. Today, the mechanisms that underlie responses to environmental temperature are being scrutinized at levels ranging from genes to organisms. From these investigations, a theory of thermal adaptation has emerged that describes the evolution of thermoregulation, thermal sensitivity, and thermal acclimation. We review and integrate current models to form a conceptual model of coadaptation. We argue that major advances will require a quantitative theory of coadaptation that predicts which strategies should evolve in specific thermal environments. Simply combining current models, however, is insufficient to understand the responses of organisms to thermal heterogeneity; a theory of coadaptation must also consider the biotic interactions that influence the net benefits of behavioral and physiological strategies. Such a theory will be challenging to develop because each organism's perception of and response to thermal heterogeneity depends on its size, mobility, and life span. Despite the challenges facing thermal biologists, we have never been more pressed to explain the diversity of strategies that organisms use to cope with thermal heterogeneity and to predict the consequences of thermal change for the diversity of communities.

Trait physiology and crop modelling to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.