Phytophthora infestans induced defense response in calli of wild and cultivated potato genotypes: Pathogen induced cell death in cultures - a marker for resistance

Late Blight caused by Phytophthora infestans (Mont.) de Bary is the most destructive foliar disease causing 30% yield losses in the potato (Solanum tuberosum L.) crop globally. Wild potato genotypes AC1 and AC4, and potato cultivar Kufri Girdhari are highly resistant, whereas wild genotype AC6, and cultivars Kufri Chandramuki and Kufri Jyoti are susceptible to Late Blight. In the current study, the calli of these six potato genotypes were used to understand the mechanism of cellular resistance to Late Blight. Exposure to P. infestans or its elicitors significantly induced peroxidase (POX) and superoxide dismutase (SOD) activities, and induced accumulation of phenolics and flavonoids, indicating the capability of the calli cells to mount a defense response. The study is the first to report the extracellular secretion of defense enzymes, SOD and POX when cells encounter the pathogen, implicating a similar whole-plant phenomenon of enhanced defense in the apoplast. Interestingly, the calli of resistant genotypes showed poor survival upon exposure to pathogen or when grown on elicitor medium, while the susceptible genotypes showed better survival. The percentage of calli cells accumulating intracellular H2O2 was high in resistant genotypes, and directly correlated with the observed higher cell death. The study shows that H2O2 accumulation in the cells of resistant genotypes is indeed self-destructive, a whole plant phenomenon termed hypersensitive response - cell death at site of infection. The potato callus system thus can be used to gain new insights into the plant-defense response to P. infestans

Greedy Solution of Ill-Posed Problems: Error Bounds and Exact Inversion

The orthogonal matching pursuit (OMP) is an algorithm to solve sparse approximation problems. Sufficient conditions for exact recovery are known with and without noise. In this paper we investigate the applicability of the OMP for the solution of ill-posed inverse problems in general and in particular for two deconvolution examples from mass spectrometry and digital holography respectively. In sparse approximation problems one often has to deal with the problem of redundancy of a dictionary, i.e. the atoms are not linearly independent. However, one expects them to be approximatively orthogonal and this is quantified by the so-called incoherence. This idea cannot be transfered to ill-posed inverse problems since here the atoms are typically far from orthogonal: The ill-posedness of the operator causes that the correlation of two distinct atoms probably gets huge, i.e. that two atoms can look much alike. Therefore one needs conditions which take the structure of the problem into account and work without the concept of coherence. In this paper we develop results for exact recovery of the support of noisy signals. In the two examples in mass spectrometry and digital holography we show that our results lead to practically relevant estimates such that one may check a priori if the experimental setup guarantees exact deconvolution with OMP. Especially in the example from digital holography our analysis may be regarded as a first step to calculate the resolution power of droplet holography

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes.

GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach

Inherited determinants of Crohn's disease and ulcerative colitis phenotypes: a genetic association study

Crohn's disease and ulcerative colitis are the two major forms of inflammatory bowel disease; treatment strategies have historically been determined by this binary categorisation. Genetic studies have identified 163 susceptibility loci for inflammatory bowel disease, mostly shared between Crohn's disease and ulcerative colitis. We undertook the largest genotype association study, to date, in widely used clinical subphenotypes of inflammatory bowel disease with the goal of further understanding the biological relations between diseases

Genotypic variability in differential expression of lea2 and lea3 genes and proteins in response to salinity stress in Fingermillet (Eleusine coracanagaertn) and rice (Oryza sativa L.) seedlings

Some late embryogeny abundant (LEA) proteins, which are developmentally regulated in embryos, are also known to be expressed in meophytic tissues in response to osmotic stress. Here we report the extent of genetic variability in the level of expression of lea2 and lea3, under stress, in fingermillet and rice seedlings. In both species, the expression of lea genes was seen in the mesophytic tissue in response to salinity, partial dehydration and abscisic acid. Tolerant genotypes exhibited higher expression of rab16A and M3 that code for LEA2 proteins, than susceptible genotypes. A novel approach, that of raising antibodies against the conserved peptides of these proteins was used to study genetic variability in LEA protein levels. Since stress proteins are known to be expressed in response to mild, non-lethal induction-stress (Uma, Prasad and Udayakumar,Annals of Botany76: 43-49, 1995), we developed an optimum induction protocol for salinity stress in rice and fingermillet. We studied the quantitative differences in expression of these proteins by western blot and ELISA techniques in different genotypes. A positive correlation was found between LEA2 and LEA3 protein levels and the growth of seedlings during stress and recovery in both rice and fingermillet, indicating a possible relevance of these proteins in stress tolerance