Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean

It is now clear that hydrogen peroxide (H(2)O(2)) and nitric oxide (NO) function as signalling molecules in plants. A wide range of abiotic and biotic stresses results in H(2)O(2) generation, from a variety of sources. H(2)O(2) is removed from cells via a number of antioxidant mechanisms, both enzymatic and non-enzymatic. Both biotic and abiotic stresses can induce NO synthesis, but the biosynthetic origins of NO in plants have not yet been resolved. Cellular responses to H(2)O(2) and NO are complex, with considerable cross-talk between responses to several stimuli. In this review the potential roles of H(2)O(2) and NO during various stresses and the signalling pathways they activate are discussed. Key signalling components that might provide targets for enhancing crop production are also identified.

Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. Available upon request (http://moulon/~bioinfo/BioMercator/). Free of charge for academic use.