Dynamic Precision Phenotyping Reveals Mechanism of Crop Tolerance to Root Herbivory

The western corn rootworm (WCR) is a major pest of maize that is well adapted to most crop management strategies. Breeding for tolerance is a promising alternative to combat WCR, but is currently constrained by a lack of physiological understanding and phenotyping tools. We developed dynamic precision phenotyping approaches using carbon-11 with positron emission tomography, root autoradiography and radiometabolite flux analysis to understand maize tolerance to WCR. Our results reveal that WCR attack induces specific patterns of lateral root growth which are associated with a shift in auxin biosynthesis from indole-3-pyruvic acid to indole-3-acetonitrile. WCR attack also increases transport of newly synthesized amino acids to the roots, including the accumulation of glutamine. Finally, the regrowth zones of WCR attacked roots show an increase in glutamine turnover which strongly correlates with the induction of indole-3-acetonitrile-dependent auxin biosynthesis. In summary, our findings identify local changes in the auxin flux network as a promising marker for induced WCR tolerance.

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.

Simulating the effects of dominance and epistasis on selection response in the CIMMYT wheat breeding program using QuCim

Plant breeders use many different breeding methods to develop superior cultivars. However, it is difficult, cumbersome, and expensive to evaluate the performance of a breeding method or to compare the efficiencies of different breeding methods within an ongoing breeding program. To facilitate comparisons, we developed a QU-GENE module called QuCim that can simulate a large number of breeding strategies for self-pollinated species. The wheat breeding strategy Selected Bulk used by CIMMYT's wheat breeding program was defined in QuCim as an example of how this is done. This selection method was simulated in QuCim to investigate the effects of deviations from the additive genetic model, in the form of dominance and epistasis, on selection outcomes. The simulation results indicate that the partial dominance model does not greatly influence genetic advance compared with the pure additive model. Genetic advance in genetic systems with overdominance and epistasis are slower than when gene effects are purely additive or partially dominant. The additive gene effect is an appropriate indicator of the change in gene frequency following selection when epistasis is absent. In the absence of epistasis, the additive variance decreases rapidly with selection. However, after several cycles of selection it remains relatively fixed when epistasis is present. The variance from partial dominance is relatively small and therefore hard to detect by the covariance among half sibs and the covariance among full sibs. The dominance variance from the overdominance model can be identified successfully, but it does not change significantly, which confirms that overdominance cannot be utilized by an inbred breeding program. QuCim is an effective tool to compare selection strategies and to validate some theories in quantitative genetics.

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.

Molecular Breeding for Rainfed Lowland Rice in the Mekong Region

In the past 20 years, the rice-breeding program in Thailand had little success in developing new cultivars to replace Kao Dawk Mali 105 (KDML105) and Kao Khor 6 (RD6) for the tainted lowland rice environments. The main reason for the poor adoption of new cultivars by farmers is the susceptibility to diseases and unacceptable grain qualities. The conventional breeding program also takes at least 15 years from initial crossing to the release of new cultivars. A new breeding strategy can be established to shorten the period for cultivar improvement by using marker-assisted selection (MAS), rapid generations advance (RGA), and early generation testing in multi-locations for grain yield and qualities. Four generation of MAS backcross breeding were conducted to transfer genes and QTL for bacterial blight resistance (BLB), submergence tolerance (SUB), brown plant hopper resistance (BPH) and blast resistance (BL) into KDML105. Selected backcross lines, introgressed with target gene/QTL, were tolerant to SUB and resistant to BLB, BPH and BL. The agronomic performance and grain quality of these lines were as good as or better than KDML105.

Breeding Rice for Drought-Prone Environments

A large portion of the world’s poor farm in rainfed systems where the water supply is unpredictable and droughts are common. In Asia, about 50% of all the rice land is rainfed and, although rice yields in irrigated systems have doubled and tripled over the past 30 years, only modest gains have occurred in rainfed rice systems. In part, this is because of the difficulty in improving rice varieties for environments that are heterogeneous and variable, and in part because there has been little effort to breed rice for drought tolerance. Information available for other cereals (for example, maize, Bänziger et al 2000) and for wheat and the limited or circumstantial evidence available for rice indicate that we can now breed varieties that have improved yield under drought and produce high yields in the good seasons. This manual aims to help plant breeders develop such varieties. While the manual focuses on drought tolerance, this must be integrated with the mainstream breeding program that also deals with agronomic adaptation, grain quality, and pest and disease resistance. Mackill et al (1996) have written a guide to the overall improvement of rice for rainfed conditions. This manual should be seen as an amplification of and updating of the section on drought tolerance in that book. Because final proof of many approaches for breeding drought-tolerant rice is not yet available, and because some aspects may not work in all environments and germplasm, we recommend that you use this manual with caution. Test the suggested approaches and only implement them on a large scale if they are effective and realistic for your own situation

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.