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.

Resistance gene analogues in sugarcane and sorghum and their association with quantitative trait loci for rust resistance

Fifty-four different sugarcane resistance gene analogue (RGA) sequences were isolated, characterized, and used to identify molecular markers linked to major disease-resistance loci in sugarcane. Ten RGAs were identified from a sugarcane stem expressed sequence tag (EST) library; the remaining 44 were isolated from sugarcane stem, leaf, and root tissue using primers designed to conserved RGA motifs. The map location of 31 of the RGAs was determined in sugarcane and compared with the location of quantitative trait loci (QTL) for brown rust resistance. After 2 years of phenotyping, 3 RGAs were shown to generate markers that were significantly associated with resistance to this disease. To assist in the understanding of the complex genetic structure of sugarcane, 17 of the 31 RGAs were also mapped in sorghum. Comparative mapping between sugarcane and sorghum revealed syntenic localization of several RGA clusters. The 3 brown rust associated RGAs were shown to map to the same linkage group (LG) in sorghum with 2 mapping to one region and the third to a region previously shown to contain a major rust-resistance QTL in sorghum. These results illustrate the value of using RGAs for the identification of markers linked to disease resistance loci and the value of simultaneous mapping in sugarcane and sorghum.

Parkinson's disease and family history

The study of family history in Parkinson's disease (PD) has resulted in considerable debate over the role of genetic factors in the development of PD. Despite this, family history is consistently identified as an independent risk factor for PD. A multifactorial disease process in which genetic, environmental and lifestyle factors culminate in overall risk seems most likely. This article reviews existing studies of familial aggregation in PD. Recent insights into rare genetic causes of PD have affirmed the importance of ongoing family history research. Future efforts should emphasise well-designed family studies with extensive, non-exclusive phenotyping and ideally long-term follow-up. © 2006 Elsevier Ltd. All rights reserved.

Swimming behaviour and post-swimming activity in Vitamin D receptor knockout mice

Animal experiments have shown that Vitamin D plays a role in both brain development and adult brain function. The adult Vitamin D receptor null mutant mouse (VDR -/-) is reported to be less active and more anxious than wild-type litter mate controls and to have poor swimming ability. However, an anxious behavioural phenotype is inferred from differences in locomotor behaviour. This is a general problem in behavioural phenotyping where a neurological phenotype is inferred from changes in locomotion which will be affected by non-neurological factors, such as muscle fatigue. In this study of VDR -/-, we conducted a detailed examination of one form of motor behaviour, swimming, compared to wildtype littermate controls. Swimming was assessed using a forced swim test, a laneway swimming test and a watermaze test using a visible platform. Post-swimming activity was assessed by comparing grooming and rearing behaviour before, and 5 min after, the forced swimming test. We replicated previous findings in which VDR -/- mice demonstrate more sinking episodes than wildtype controls in the forced swim test but they were similar to controls in the time taken to swim a 1 m laneway, and in the time taken to reach a visible platform in the watermaze. Thus, the VDR -/- mice were able to swim but were not able to float. Grooming and rearing behaviour of the VDR -/- mice was similar to wildtype controls before the forced swim but the VDR -/- were much less active after the swim compared with wildtype mice which displayed high levels of grooming and rearing. We conclude that VDR -/- mice have muscular and motor impairments that do not affect their ability to swim but significantly alters the ability to float as well as their post-swimming activity. Differences in muscle strength may confound tests of activity that are used to infer an anxious phenotype. (c) 2005 Elsevier Inc. All rights reserved.

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.