Tobacco plants transformed with the RNA polymerase (RdRp) gene of potato virus X (PVX) that are extremely resistant to infection by potato virus X have previously been described. The PVX‐resistant plants accumulated the RdRp protein at a lower level than fully susceptible plants transformed with the same RdRp construct. In this paper the difference between the PVX‐resistant and susceptible transformed plants is investigated and it is demonstrated that there are three associated phenotypes of the RdRp transgene that vary in parallel between transformed lines. These phenotypes are: accumulation of the transgenic RdRp RNA at a low level; strain‐specific resistance to PVX; and the ability of the transgene to trans‐inactivate homologous transgenes. This gene‐silencing potential of the transgenes conferring PVX resistance was illustrated by analysis of progeny from a cross between a transformant that was extremely resistant to PVX and a second PVX‐susceptible transformant. In other transformants, in which the resistance was less extreme, the same three phenotypes were associated but in a transgene dosage‐dependent manner. The same association of strain‐specific resistance and low‐level accumulation of the transgenic RdRp RNA was observed with plants that were transformed with mutant or wild‐type versions of the RdRp gene. Strain‐specific resistance was also produced in plants transformed with untranslatable versions of the RdRp transgene. Based on these data it is proposed that homology‐dependent gene silencing and transgenic resistance to PVX may be due to the same RNA‐based mechanism. An undefined genomic feature is proposed to account for the variation in the resistance and trans‐inactivation phenotypes of different transformants. It is further proposed that this genome feature influences a cytoplasmic mechanism that degrades RNA with sequence homology to the silencing transgene.

Background: Existing algorithms and methods for forming diverse core subsets currently address either allele representativeness (breeder's preference) or allele richness (taxonomist's preference). The main objective of this paper is to propose a powerful yet flexible algorithm capable of selecting core subsets that have high average genetic distance between accessions, or rich genetic diversity overall, or a combination of both.

The International Maize and Wheat Improvement Center (CIMMYT) acts as a catalyst and leader in a global maize and wheat innovation network that serves the poor in the developing world. Drawing on strong science and effective partnerships, CIMMYT researchers create, share, and use knowledge and technology to increase food security, improve the productivity and profitability of farming systems and sustain natural resources. This peoplecentered mission does not ignore the fact that CIMMYT's unique niche is as a genetic resources enhancement center for the developing world, as shown by this review article focusing on wheat.

BackgroundCore collections provide genebank curators and plant breeders a way to reduce size of their collections and populations, while minimizing impact on genetic diversity and allele frequency. Many methods have been proposed to generate core collections, often using distance metrics to quantify the similarity of two accessions, based on genetic marker data or phenotypic traits. Core Hunter is a multi-purpose core subset selection tool that uses local search algorithms to generate subsets relying on one or more metrics, including several distance metrics and allelic richness.ResultsIn version 3 of Core Hunter (CH3) we have incorporated two new, improved methods for summarizing distances to quantify diversity or representativeness of the core collection. A comparison of CH3 and Core Hunter 2 (CH2) showed that these new metrics can be effectively optimized with less complex algorithms, as compared to those used in CH2. CH3 is more effective at maximizing the improved diversity metric than CH2, still ensures a high average and minimum distance, and is faster for large datasets. Using CH3, a simple stochastic hill-climber is able to find highly diverse core collections, and the more advanced parallel tempering algorithm further increases the quality of the core and further reduces variability across independent samples. We also evaluate the ability of CH3 to simultaneously maximize diversity, and either representativeness or allelic richness, and compare the results with those of the GDOpt and SimEli methods. CH3 can sample equally representative cores as GDOpt, which was specifically designed for this purpose, and is able to construct cores that are simultaneously more diverse, and either are more representative or have higher allelic richness, than those obtained by SimEli.ConclusionsIn version 3, Core Hunter has been updated to include two new core subset selection metrics that construct cores for representativeness or diversity, with improved performance. It combines and outperforms the strengths of other methods, as it (simultaneously) optimizes a variety of metrics. In addition, CH3 is an improvement over CH2, with the option to use genetic marker data or phenotypic traits, or both, and improved speed. Core Hunter 3 is freely available on http://www.corehunter.org.