Plants growing in their natural habitats are often challenged simultaneously by multiple stress factors, both abiotic and biotic. Research has so far been limited to responses to individual stresses, and understanding of adaptation to combinatorial stress is limited, but indicative of non-additive interactions. Omics data analysis and functional characterization of individual genes has revealed a convergence of signalling pathways for abiotic and biotic stress adaptation. Taking into account that most data originate from imposition of individual stress factors, this review summarizes these findings in a physiological context, following the pathogenesis timeline and highlighting potential differential interactions occurring between abiotic and biotic stress signalling across the different cellular compartments and at the whole plant level. Potential effects of abiotic stress on resistance components such as extracellular receptor proteins, R-genes and systemic acquired resistance will be elaborated, as well as crosstalk at the levels of hormone, ROS and redox signalling. Breeding targets and strategies are proposed focusing on either manipulation and deployment of individual common regulators such as transcription factors or pyramiding of non- (negatively) interacting components such as R-genes with abiotic stress resistance genes. We propose that dissection of broad spectrum stress tolerance conferred by priming chemicals may provide an insight on stress cross regulation and additional candidate genes for improving crop performance under combined stress. Validation of the proposed strategies in lab and field experiments is a first step towards the goal of achieving tolerance to combinatorial stress in crops.

Background: Single nucleotide polymorphisms (SNPs) are important tools in studying complex genetic traits and genome evolution. Computational strategies for SNP discovery make use of the large number of sequences present in public databases (in most cases as expressed sequence tags (ESTs)) and are considered to be faster and more cost-effective than experimental procedures. A major challenge in computational SNP discovery is distinguishing allelic variation from sequence variation between paralogous sequences, in addition to recognizing sequencing errors. For the majority of the public EST sequences, trace or quality files are lacking which makes detection of reliable SNPs even more difficult because it has to rely on sequence comparisons only.Results: We have developed a new algorithm to detect reliable SNPs and insertions/deletions (indels) in EST data, both with and without quality files. Implemented in a pipeline called QualitySNP, it uses three filters for the identification of reliable SNPs. Filter 1 screens for all potential SNPs and identifies variation between or within genotypes. Filter 2 is the core filter that uses a haplotype-based strategy to detect reliable SNPs. Clusters with potential paralogs as well as false SNPs caused by sequencing errors are identified. Filter 3 screens SNPs by calculating a confidence score, based upon sequence redundancy and quality. Non-synonymous SNPs are subsequently identified by detecting open reading frames of consensus sequences (contigs) with SNPs. The pipeline includes a data storage and retrieval system for haplotypes, SNPs and alignments. QualitySNP's versatility is demonstrated by the identification of SNPs in EST datasets from potato, chicken and humans.Conclusion: QualitySNP is an efficient tool for SNP detection, storage and retrieval in diploid as well as polyploid species. It is available for running on Linux or UNIX systems. The program, test data, and user manual are available athttp://www.bioinformatics.nl/tools/snpweb/and as Additional files.

Potato (Solanum tuberosum) is an important food crop consumed all over the world, but it is generally sensitive to drought conditions. One of the major physiological processes affected by drought stress is carbon partitioning: the plant's choice of where to allocate its photoassimilates. Our aim was to investigate the molecular factors and possible bottlenecks affecting carbon partitioning during drought. We studied potato cultivars with contrasting drought responses in the greenhouse in the years 2013-2015, and further investigated the expression of genes involved in carbon partitioning and metabolite levels. Our results indicate that one of the most severe effects of drought stress on potato is the arrest of stolon differentiation and formation of tubers. We also identified some physiological traits like stomatal conductance and chlorophyll content as affecting carbon assimilation, partitioning and eventual tuber yield. The gene expressions and biochemical analyses highlight the various tissues prioritized by the plant for assimilate transport during drought stress, and give indications of what distinguishes drought tolerance and sensitivity of cultivated potato. Some of the key genes studied (like Sucrose synthase and Sucrose transporters) may be inclusive breeding targets for drought tolerance in potato.