The Transcriptome of Compatible and Incompatible Interactions of Potato (Solanum tuberosum) with Phytophthora infestans Revealed by DeepSAGE Analysis

Late blight, caused by the oomycete Phytophthora infestans, is the most important disease of potato (Solanum tuberosum). Understanding the molecular basis of resistance and susceptibility to late blight is therefore highly relevant for developing resistant cultivars, either by marker-assissted selection or by transgenic approaches. Specific P. infestans races having the Avr1 effector gene trigger a hypersensitive resistance response in potato plants carrying the R1 resistance gene (incompatible interaction) and cause disease in plants lacking R1 (compatible interaction). The transcriptomes of the compatible and incompatible interaction were captured by DeepSAGE analysis of 44 biological samples comprising five genotypes, differing only by the presence or absence of the R1 transgene, three infection time points and three biological replicates. 30.859 unique 21 base pair sequence tags were obtained, one third of which did not match any known potato transcript sequence. Two third of the tags were expressed at low frequency (<10 tag counts/million). 20.470 unitags matched to approximately twelve thousand potato transcribed genes. Tag frequencies were compared between compatible and incompatible interactions over the infection time course and between compatible and incompatible genotypes. Transcriptional changes were more numerous in compatible than in incompatible interactions. In contrast to incompatible interactions, transcriptional changes in the compatible interaction were observed predominantly for multigene families encoding defense response genes and genes functional in photosynthesis and CO2 fixation. Numerous transcriptional differences were also observed between near isogenic genotypes prior to infection with P. infestans. Our DeepSAGE transcriptome analysis uncovered novel candidate genes for plant host pathogen interactions, examples of which are discussed with respect to possible function

Multiple alleles for resistance and susceptibility modulate the defense response in the interaction of tetraploid potato (Solanum tuberosum) with Synchytrium endobioticum pathotypes 1, 2, 6 and 18

The obligate biotrophic, soil-borne fungus Synchytrium endobioticum causes wart disease of potato (Solanum tuberosum), which is a serious problem for crop production in countries with moderate climates. S. endobioticum induces hypertrophic cell divisions in plant host tissues leading to the formation of tumor-like structures. Potato wart is a quarantine disease and chemical control is not possible. From 38 S. endobioticum pathotypes occurring in Europe, pathotypes 1, 2, 6 and 18 are the most relevant. Genetic resistance to wart is available but only few current potato varieties are resistant to all four pathotypes. The phenotypic evaluation of wart resistance is laborious, time-consuming and sometimes ambiguous, which makes breeding for resistance difficult. Molecular markers diagnostic for genes for resistance to S. endobioticum pathotypes 1, 2, 6 and 18 would greatly facilitate the selection of new, resistant cultivars. Two tetraploid half-sib families (266 individuals) segregating for resistance to S. endobioticum pathotypes 1, 2, 6 and 18 were produced by crossing a resistant genotype with two different susceptible ones. The families were scored for five different wart resistance phenotypes. The distribution of mean resistance scores was quantitative in both families. Resistance to pathotypes 2, 6 and 18 was correlated and independent from resistance to pathotype 1. DNA pools were constructed from the most resistant and most susceptible individuals and screened with genome wide simple sequence repeat (SSR), inverted simple sequence region (ISSR) and randomly amplified polymorphic DNA (RAPD) markers. Bulked segregant analysis identified three SSR markers that were linked to wart resistance loci (Sen). Sen1-XI on chromosome XI conferred partial resistance to pathotype 1, Sen18-IX on chromosome IX to pathotype 18 and Sen2/6/18-I on chromosome I to pathotypes 2,6 and 18. Additional genotyping with 191 single nucleotide polymorphism (SNP) markers confirmed the localization of the Sen loci. Thirty-three SNP markers linked to the Sen loci permitted the dissection of Sen alleles that increased or decreased resistance to wart. The alleles were inherited from both the resistant and susceptible parents

Statistical epistasis between candidate gene alleles for complex tuber traits in an association mapping population of tetraploid potato

Association mapping using DNA-based markers is a novel tool in plant genetics for the analysis of complex traits. Potato tuber yield, starch content, starch yield and chip color are complex traits of agronomic relevance, for which carbohydrate metabolism plays an important role. At the functional level, the genes and biochemical pathways involved in carbohydrate metabolism are among the best studied in plants. Quantitative traits such as tuber starch and sugar content are therefore models for association genetics in potato based on candidate genes. In an association mapping experiment conducted with a population of 243 tetraploid potato varieties and breeding clones, we previously identified associations between individual candidate gene alleles and tuber starch content, starch yield and chip quality. In the present paper, we tested 190 DNA markers at 36 loci scored in the same association mapping population for pairwise statistical epistatic interactions. Fifty marker pairs were associated mainly with tuber starch content and/or starch yield, at a cut-off value of q ≤ 0.20 for the experiment-wide false discovery rate (FDR). Thirteen marker pairs had an FDR of q ≤ 0.10. Alleles at loci encoding ribulose-bisphosphate carboxylase/oxygenase activase (Rca), sucrose phosphate synthase (Sps) and vacuolar invertase (Pain1) were most frequently involved in statistical epistatic interactions. The largest effect on tuber starch content and starch yield was observed for the paired alleles Pain1-8c and Rca-1a, explaining 9 and 10% of the total variance, respectively. The combination of these two alleles increased the means of tuber starch content and starch yield. Biological models to explain the observed statistical epistatic interactions are discussed

Loss of a Conserved tRNA Anticodon Modification Perturbs Plant Immunity

[EN] tRNA is the most highly modified class of RNA species, and modifications are found in tRNAs from all organisms that have been examined. Despite their vastly different chemical structures and their presence in different tRNAs, occurring in different locations in tRNA, the biosynthetic pathways of the majority of tRNA modifications include a methylation step(s). Recent discoveries have revealed unprecedented complexity in the modification patterns of tRNA, their regulation and function, suggesting that each modified nucleoside in tRNA may have its own specific function. However, in plants, our knowledge on the role of individual tRNA modifications and how they are regulated is very limited. In a genetic screen designed to identify factors regulating disease resistance and activation of defenses in Arabidopsis, we identified SUPPRESSOR OF CSB3 9 (SCS9). Our results reveal SCS9 encodes a tRNA methyltransferase that mediates the 2'-O-ribose methylation of selected tRNA species in the anticodon loop. These SCS9-mediated tRNA modifications enhance during the course of infection with the bacterial pathogen Pseudomonas syringae DC3000, and lack of such tRNA modification, as observed in scs9 mutants, severely compromise plant immunity against the same pathogen without affecting the salicylic acid (SA) signaling pathway which regulates plant immune responses. Our results support a model that gives importance to the control of certain tRNA modifications for mounting an effective immune response in Arabidopsis, and therefore expands the repertoire of molecular components essential for an efficient disease resistance response.This work was supported by the National Science Foundation of China (grant 31100268 to PC) and the Spanish MINECO (BFU2012 to PV) and Generalitat Valenciana (Prometeo2014/020 to PV). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ramirez Garcia, V.; González-García, B.; López Sánchez, A.; Castelló Llopis, MJ.; Gil, M.; Zheng, B.; Cheng, P.... (2015). Loss of a Conserved tRNA Anticodon Modification Perturbs Plant Immunity. PLoS Genetics. 11(10):1-27. https://doi.org/10.1371/journal.pgen.1005586S127111

Salicylic Acid Inhibits Pathogen Growth in Plants through Repression of the Auxin Signaling Pathway

The phytohormone auxin regulates almost every aspect of plant development. At the molecular level, auxin induces gene expression through direct physical interaction with the TIR1-like F box proteins, which in turn remove the Aux/IAA family of transcriptional repressors 1, 2, 3 and 4. A growing body of evidence indicates that many plant pathogens can either produce auxin themselves or manipulate host auxin biosynthesis to interfere with the host\u27s normal developmental processes 5, 6, 7, 8, 9, 10 and 11. In response, plants probably evolved mechanisms to repress auxin signaling during infection as a defense strategy. Plants overaccumulating the defense signal molecule salicylic acid (SA) frequently display morphological phenotypes that are reminiscent of auxin-deficient or auxin-insensitive mutants, indicating that SA might interfere with auxin responses. By using the Affymetrix ATH1 GeneChip for Arabidopsis thaliana, we performed a comprehensive study of the effects of SA on auxin signaling [12]. We found that SA causes global repression of auxin-related genes, including the TIR1 receptor gene, resulting in stabilization of the Aux/IAA repressor proteins and inhibition of auxin responses. We demonstrate that this inhibitory effect on auxin signaling is a part of the SA-mediated disease-resistance mechanism

Network Biology Analyses and Dynamic Modeling of Gene Regulatory Networks under Drought Stress Reveal Major Transcriptional Regulators in <i>Arabidopsis</i>

Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of high-priority transcription factors (TFs), dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of Arabidopsis. We identified distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficient nodes. Dynamic transcriptional regulatory modeling of integrated TF targets and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs, as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that could potentially be used in future genetic crop engineering programs

HAPLO-ASP: Haplotype inference using answer set programming

Identifying maternal and paternal inheritance is essential to be able to find the set of genes responsible for a particular disease. However, due to technological limitations, we have access to genotype data (genetic makeup of an individual), and determining haplotypes (genetic makeup of the parents) experimentally is a costly and time consuming procedure. With these biological motivations, we study haplotype inference—determining the haplotypes that form a given set of genotypes—using Answer Set Programming; we call our approach Haplo-ASP. This note summarizes the range of problems that can be handled by Haplo-ASP, and its applicability and effectiveness on real data in comparison with the other existing approaches