Rice molecular breeding laboratories in the genomics era: Current status and future considerations

Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

Fate of applied biosolids nitrogen in a cut and remove forage system on an alluvial clay loam soil

The fate of nitrogen (N) applied in biosolids was investigated in a forage production system on an alluvial clay loam soil in south-eastern Queensland, Australia. Biosolids were applied in October 2002 at rates of 6, 12, 36, and 54dryt/ha for aerobically digested biosolids (AE) and 8, 16, 48, and 72dryt/ha for anaerobically digested biosolids (AN). Rates were based on multiples of the Nitrogen Limited Biosolids Application rate (0.5, 1, 3, and 4.5NLBAR) for each type of biosolid. The experiment included an unfertilised control and a fertilised control that received multiple applications of synthetic fertiliser. Forage sorghum was planted 1 week after biosolids application and harvested 4 times between December 2002 and May 2003. Dry matter production was significantly greater from the biosolids-treated plots (21-27t/ha) than from the unfertilised (16t/ha) and fertilised (18t/ha) controls. The harvested plant material removed an extra 148-488kg N from the biosolids-treated plots. Partial N budgets were calculated for the 1NLBAR and 4.5NLBAR treatments for each biosolids type at the end of the crop season. Crop removal only accounted for 25-33% of the applied N in the 1NLBAR treatments and as low as 8-15% with 4.5NLBAR. Residual biosolids N was predominantly in the form of organic N (38-51% of applied biosolids N), although there was also a significant proportion (10-23%) as NO3-N, predominantly in the top 0.90m of the soil profile. From 12 to 29% of applied N was unaccounted for, and presumed to be lost as gaseous nitrogen and/or ammonia, as a consequence of volatilisation or denitrification, respectively. In-season mineralisation of organic N in biosolids was 43-59% of the applied organic N, which was much greater than the 15% (AN)-25% (AE) expected, based on current NLBAR calculation methods. Excessive biosolids application produced little additional biomass but led to high soil mineral N concentrations that were vulnerable to multiple loss pathways. Queensland Guidelines need to account for higher rates of mineralisation and losses via denitrification and volatilisation and should therefore encourage lower application rates to achieve optimal plant growth and minimise the potential for detrimental impacts on the environment.