Background: Bread wheat (Triticum aestivum) is an important staple food. However, wheat gluten proteins cause celiac disease (CD) in 0.5 to 1% of the general population. Among these proteins, the α-gliadins contain several peptides that are associated to the disease.

Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R) genes into potato (Solanum tuberosum) is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity) on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR) in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties.

In this comprehensive review, a range of factors is considered that may influence the significance of genetic diversity for the survival of a population. Genetic variation is essential for the adaptability of a population in which quantitatively inherited, fitness‐related traits are crucial. Therefore, the relationship between genetic diversity and fitness should be studied in order to make predictions on the importance of genetic diversity for a specific population. The level of genetic diversity found in a population highly depends on the mating system, the evolutionary history of a species and the population history (the latter is usually unknown), and on the level of environmental heterogeneity. An accurate estimation of fitness remains complex, despite the availability of a range of direct and indirect fitness parameters. There is no general relationship between genetic diversity and various fitness components. However, if a lower level of heterozygosity represents an increased level of inbreeding, a reduction in fitness can be expected. Molecular markers can be used to study adaptability or fitness, provided that they represent a quantitative trait locus (QTL) or are themselves functional genes involved in these processes. Next to a genetic response of a population to environmental change, phenotypic plasticity in a genotype can affect fitness. The relative importance of plasticity to genetic diversity depends on the species and population under study and on the environmental conditions. The possibilities for application of current knowledge on genetic diversity and population survival for the management of natural populations are discussed.

BackgroundAutomated genotype calling in tetraploid species was until recently not possible, which hampered genetic analysis. Modern genotyping assays often produce two signals, one for each allele of a bi-allelic marker. While ample software is available to obtain genotypes (homozygous for either allele, or heterozygous) for diploid species from these signals, such software is not available for tetraploid species which may be scored as five alternative genotypes (aaaa, baaa, bbaa, bbba and bbbb; nulliplex to quadruplex).ResultsWe present a novel algorithm, implemented in the R package fitTetra, to assign genotypes for bi-allelic markers to tetraploid samples from genotyping assays that produce intensity signals for both alleles. The algorithm is based on the fitting of several mixture models with five components, one for each of the five possible genotypes. The models have different numbers of parameters specifying the relation between the five component means, and some of them impose a constraint on the mixing proportions to conform to Hardy-Weinberg equilibrium (HWE) ratios. The software rejects markers that do not allow a reliable genotyping for the majority of the samples, and it assigns a missing score to samples that cannot be scored into one of the five possible genotypes with sufficient confidence.ConclusionsWe have validated the software with data of a collection of 224 potato varieties assayed with an Illumina GoldenGate™ 384 SNP array and shown that all SNPs with informative ratio distributions are fitted. Almost all fitted models appear to be correct based on visual inspection and comparison with diploid samples. When the collection of potato varieties is analyzed as if it were a population, almost all markers seem to be in Hardy-Weinberg equilibrium. The R package fitTetra is freely available under the GNU Public License from http://www.plantbreeding.wur.nl/UK/software_fitTetra.html and as Additional files with this article.

Analysis of electrically recorded feeding behaviour of aphids was combined with colony‐development tests to search for sources of resistance to Myzus persicae (Sulzer) (Homoptera: Aphididae) in tuber‐bearing Solanum species (Solanaceae), aiming at a reduction of potato leaf roll virus (PLRV) transmission. Twenty genotypes, originating from 14 gene bank accessions, representing 13 wild tuber‐bearing Solanum spp., three Solanum tuberosum L. (potato) cultivars, and one S. tuberosum breeding line, were selected. Colony‐development tests were carried out in no‐choice experiments by placing adult aphids on plants of each genotype and counting numbers of nymphs and adults on young plants after 8 and 15 days, and on flowering plants after 14 and 30 days. Large differences were observed among genotypes: some developed small colonies and others developed large ones. Also, in a few genotypes, resistance in mature plants was different for leaves of different ages; young leaves were resistant to aphids whereas old senescent leaves were susceptible. The electrical penetration graph (DC‐EPG system) technique was used to study aphid feeding behaviour on each Solanum genotype for 6 h. Electrical penetration graph (EPG) results also showed large differences among the genotypes, indicating resistance at the leaf surface and at three different levels of plant tissue (epidermis, mesophyll, and phloem). Therefore, it was concluded that different mechanisms of resistance to M. persicae exist among the genotypes analysed. EPGs recorded from aphids on Solanum berthaultii Hawkes and Solanum tarijense Hawkes with and without glandular trichomes showed that strong surface resistance can bias EPG parameters associated with resistance located in deeper tissues. Experimental evidence is presented that the resistance to aphids in the genotypes with glandular trichomes strongly depends on these morphological structures.

Article 25fa states that the author of a short scientific work funded either wholly or partially by Dutch public funds is entitled to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work.This publication is distributed under The Association of Universities in the Netherlands (VSNU) 'Article 25fa implementation' project. In this project research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication.

Association or linkage disequilibrium (LD)-based mapping strategies are receiving increased attention for the identification of quantitative trait loci (QTL) in plants as an alternative to more traditional, purely linkage-based approaches. An attractive property of association approaches is that they do not require specially designed crosses between inbred parents, but can be applied to collections of genotypes with arbitrary and often unknown relationships between the genotypes. A less obvious additional attractive property is that association approaches offer possibilities for QTL identification in crops with hard to model segregation patterns. The availability of candidate genes and targeted marker systems facilitates association approaches, as will appropriate methods of analysis. We propose an association mapping approach based on mixed models with attention to the incorporation of the relationships between genotypes, whether induced by pedigree, population substructure, or otherwise. Furthermore, we emphasize the need to pay attention to the environmental features of the data as well, i.e., adequate representation of the relations among multiple observations on the same genotypes. We illustrate our modeling approach using 25 years of Dutch national variety list data on late blight resistance in the genetically complex crop of potato. As markers, we used nucleotide binding-site markers, a specific type of marker that targets resistance or resistance-analog genes. To assess the consistency of QTL identified by our mixed-model approach, a second independent data set was analyzed. Two markers were identified that are potentially useful in selection for late blight resistance in potato.

Polysomic inheritance frequently results in the simultaneous occurrence of several microsatellite DNA alleles on a single locus. The MAC-PR (microsatellite DNA allele counting-peak ratios) method was recently developed for the analysis of polyploid plants and makes use of the quantitative values for microsatellite allele peak areas. To date, this approach has only been used in plants with known genetic relationships. We report here the application of MAC-PR for the first time to random samples of unknown pedigrees. We analysed six microsatellite loci using a set of tetraploid ornamental rose ( Rosa x hybrida L.) varieties. For each locus, all alleles were analysed in pairwise combinations in order to determine their copy number in the individual samples. This was accomplished by calculating the ratios between the peak areas for two alleles in all of the samples where these two alleles occurred together. The allele peak ratios observed were plotted in a histogram, and those histograms that produced at least two well-separated groups were selected for further analysis. Mean allelic peak ratio values for these groups were compared to the relationships expected between alleles in hypothetical configurations of the locus investigated. Using this approach, we were able to assign precise allelic configurations (the actual genotype) to almost all of the varieties analysed for five of the six loci investigated. MAC-PR also appears to be a very effective tool for detecting 'null' alleles in polyploid species.