Many orchid species are seriously endangered at present. Reasons for their disappearing from natural habitats remain often unclear. Orchids depend on mycorrhizal symbiosis in nature, however only little is known about this symbiosis. Seeds of some species do not germinate in vitro, making their cultivation for scientific and rescue purposes impossible. We found that seed germination of one of such reluctant species, Pseudorchis albida, is strongly inhibited by nitrates even at extremely low concentrations. As this species prefers oligotrophic mountain meadows, nitrate-induced inhibition probably take place in natural conditions. Surprisingly, we found similar but slightly weaker inhibitory effect also in typical mesophillic species and even in slightly eutrophic ones. The sensitivity to nitrates correlates with trophy level of species canopy. This inhibitory effect of nitrates could be weakened by application of a range of growth regulators, including auxins, cytokinins and gibberellins, and also by mycorrhizal fungi. The action of nitratereductase is essential for this inhibitory effect of nitrates. Experiments with NO donors, scavengers, and NO quantification are pointing right at NO as compound which perhaps mediates nitrate inhibitory effect. Based on these results, the nitrate inhibitory...

Mental retardation (MR) is a very heterogeneous common neurodevelopmental disorder with a population prevalence of 2.5-3 %. The importance of genetic factors in the development of MR is high but in a significant number of cases the etiology remains unexplained. Recent studies using array methods pointed to frequent occurrence of copy number variants (CNVs) in patients with MR. Pathogenic CNVs were identified in 10-15 % patients with idiopathic MR and normal karyotype. The aim of our work was the analysis of genome-wide gains and losses of genetic material in a group of Czech patients with MR and a thorough bioinformatic analysis of the genetic changes identified aiming at the assessment of their clinical significance. We performed whole genome analysis using the HumanCytoSNP-12 BeadChips (Illumina) in 183 patients with idiopathic MR, normal karyotype and no FMR1 gene expansion. Data analysis was carried out using two independent programmes, GenomeStudio and QuantiSNP. The findings were subjected to two rounds of thorough bioinformatic analysis. Based on this analysis we classified the CNVs into 4 categories: pathogenic CNVs, probably pathogenic CNVs, CNVs with uncertain clinical significance and benign CNVs. With the exception of the benign variants, all CNVs were confirmed using an independent laboratory...

Introduction: Le dalcétrapib est un inhibiteur de la protéine de transfert des esters de cholestérol (CETP) qui augmente le niveau du cholestérol-HDL. Des études d’association pangénomiques ont révélé une association entre les polymorphismes du gène adénylate cyclase de type 9 (ADCY9) et les réponses au dalcétrapib. Le but de cette étude était d’identifier le polymorphisme nucléotidique (SNP) causal, ce qui pourrait mener à comprendre le mécanisme moléculaire modifiant les effets du dalcétrapib sur les bénéfices cardiovasculaires. Méthodes: Des essais d’EMSA (electrophoretic mobility shift assay) ont été réalisés afin d’analyser les effets modificateurs de douze SNPs candidats sur la liaison de protéines nucléaires, provenant de cellules monocytaires THP-1. Ensuite, des essais de transfections avec un gène rapporteur ont été utilisées pour évaluer l’effet transcriptionnel de ces SNPs. La liaison des protéines au SNP rs12920508 a par la suite été étudiée par des chromatographies d’affinité d’ADN suivies par des spectrométries de masse et par MC-EMSA (multiplexed competitor EMSA). Résultats: Sept sur douze SNPs ont démontré une liaison spécifique à un allèle qui n’a pas été influencée par l’exposition des cellules au dalcétrapib. Le résultat des transfections de vecteurs rapporteurs dans les cellules THP-1 a montré que les constructions plasmidiques portant les variants rs1967309 et rs12920508 augmentaient l’activité transcriptionnelle. Onze protéines ont été identifiées comme des candidats potentiels pouvant se lier à la région du SNP rs12920508. De plus, la région contenant les deux variants rs1967309 et rs12920509 a présenté une activité transcriptionnelle accrue et significativement plus élevée pour l’haplotype délétère. Conclusion: Le polymorphisme rs1967309 semble causer la majorité des effets fonctionnels dans la lignée cellulaire THP-1. Cependant, une interaction avec le SNP rs12920508 ou la présence de la région de ce SNP pourrait être nécessaire pour l’activité optimale de rs1967309. Des travaux supplémentaires sont nécessaires pour élucider le lien entre le SNP potentiellement causal et les réponses cardiovasculaires induites par le dalcétrapib. / Introduction: Dalcetrapib is a cholesteryl ester transfer protein (CETP) inhibitor that increases the circulating level of HDL-cholesterol. Genome-wide association studies have revealed an association between polymorphisms found in the adenylate cyclase type 9 (ADCY9) gene and responses to dalcetrapib, including its cardiovascular benefits. The purpose of this study was to identify the causal single nucleotide polymorphisms (SNP) which could lead to understand the molecular mechanisms altering dalcetrapib effects on cardiovascular outcomes. Methods: Electrophoretic mobility shift assays (EMSA) were performed to analyze the allele-specific effects of the best causal SNP candidates on binding with nuclear proteins obtained from a THP-1 monocytic cell line. Afterwards, a dual luciferase reporter assay was used to assess the effect of selected genetic variants on gene transcription. Protein binding to SNP rs12920508 was investigated by DNA-affinity chromatography followed by mass spectrometry and multiplexed competitor EMSA. Results: Seven out of 12 SNPs demonstrated allele-specific protein binding, which was not influenced by dalcetrapib exposure of the cells. Results from dual luciferase reporter assay showed that plasmid constructs bearing variants rs12920508 and rs1967309 increased transcriptional activity when transfected into THP-1 undifferentiated monocytic cells. Eleven proteins were identified as potential candidates binding to region of SNP rs12920508. Additionally, region containing both SNPs rs1967309 and rs12920508 displayed increased transcriptional activity with significantly higher activity for deleterious haplotype. Conclusion: Polymorphism rs1967309 seems to be causing most functional effects in the THP-1 monocytic cell line. However, an interaction with rs12920508 or presence of the DNA region of this SNP may be necessary for optimal activity of rs1967309. Further work is required to elucidate the link between potentially causal SNPs and cardiovascular responses induced by dalcetrapib.

In this study we build solutions to three common challenges in the fields of bioinformatics through utilizing statistical methods and developing computational approaches. First, we address a common problem in genome wide association studies, which is linking genotype features within organisms of the same species to their phenotype characteristics. We specifically studied FHA domain genes in Arabidopsis thaliana distributed within Eurasian regions by clustering those plants that share similar genotype characteristics and comparing that to the regions from which they were taken. Second, we also developed a tool for calculating transposable element density within different regions of a genome. The tool is built to utilize the information provided by other transposable element annotation tools and to provide the user with a number of options for calculating the density for various genomic elements such as genes, piRNA and miRNA or for the whole genome. It also provides a detailed calculation of densities for each family and subamily of the transposable elements. Finally, we address the problem of mapping multi reads in the genome and their effects on gene expression. To accomplish this, we implemented methods to determine the statistical significance of expression values within the genes utilizing both a unique and multi-read weighting scheme. We believe this approach provides a much more accurate measure of gene expression than existing methods such as discarding multi reads completely or assigning them randomly to a set of best assignments, while also providing a better estimation of the proper mapping locations of ambiguous reads. Overall, the solutions we built in these studies provide researchers with tools and approaches that aid in solving some of the common challenges that arise in the analysis of high throughput sequence data.

Indiana University-Purdue University Indianapolis (IUPUI) / Cytokines mediate crucial functions in innate and adaptive immunity. They play valuable roles in immune cell growth and lineage specification, and are associated with various disease pathologies. A large number of low, medium and high throughput studies have implicated association of single nucleotide polymorphisms (SNPs) in cytokine genes with diseases. A preponderance of such experiments have not shown any causality of an identified SNP to the associated disease. Instead, they have identified statistically significant SNP-disease associations; hence, it is likely that some of these cytokine gene variants may directly or indirectly cause the disease phenotype(s). To fill this knowledge gap and derive study parameters for cytokine SNP-disease causality relationships, we have designed and developed the Disease Associated Cytokine SNP Database (DACS-DB). DACS-DB has data on 456 cytokine genes, approximately 61,000 SNPs, and 891 SNP-associated diseases. In DACS-DB, among other attributes, we present functional annotation, and heterozygosity allele frequency for the SNPs, and literature-validated SNP association for diseases. Users of the DB can run queries such as the ones to find disease-associated SNPs in a cytokine gene, and all the SNPs involved in a disease. We have developed a web front end (available at http://www.iupui.edu/~cytosnp) to disseminate this information for immunologists, biomedical researchers, and other interested biological researchers. Since there is no such comprehensive collection of disease associated cytokine SNPs, this DB will be vital to understanding the role of cytokine SNPs as markers in disease, and, more importantly, in causality to disease thus helping to identify drug targets for common inflammatory diseases. Due to the presence of rich annotations, the DACS-DB can be a good source for building a tool for the prediction of the "disease association potential (DAP)" of a given SNP. In a preliminary effort to devise such a methodology for DAP prediction, we have applied a support vector machine (SVM) to classify SNPs. Employing the SNP attributes of function class, heterozygosity value, and heterozygosity standard error, 864 SNPs were classified into two classes, "disease" and "non-disease". The SVM returned a classification of these SNPs into the disease and non-disease classes with an accuracy of 74%. By modifying various SNP and disease attributes in the training data sets, such a predictive algorithm can be extrapolated to identify potential disease associated SNPs among newly sequenced cytokine variations. In the long run, this approach can provide a means for future gene variation based therapeutic regimens.

Mycobacterium tuberculosis (Mtb) is the pathogen that causes Tuberculosis (TB) and is responsible for an average of 1.5 million deaths annually. Although a treatment regimen does exist, Multi-Drug Resistant (MDR-TB) and eXtremely Drug Resistant (XDR-TB) TB strains are becoming a more prevalent concern partly due to failure of patient compliance with the current six to nine month drug treatment regimen. The current diagnostic methods are not able to identify these MDR and XDR-TB strains efficiently therefore more effective point-of-care (POC) diagnostics and drug susceptibility testing (DST) are urgently needed to detect drug resistance and facilitate prompt, appropriate treatment plans. In order to detect TB and efficiently identify drug resistance, this project seeks to develop a novel diagnostic technology based on deoxyribozyme (DNAzyme) sensors. The overall goal of this project is to create an assay which combines Polymerase Chain Reaction (PCR) and DNAzymes to identify drug resistance conferring Single Nucleotide Polymorphisms (SNPs). To safely test the ability of DNAzyme sensors to detect SNPs indicative of multi-drug resistant TB, we have constructed a panel of drug resistant (drugR) nonpathogenic M. bovis BCG. We have designed a multiplex PCR that amplifies 6 chromosomal regions of the genome necessary for the species specific detection of TB and determination of a drug susceptibility profile based on the presence of SNPs. To improve the sensitivity and selectivity of the detection and DST of Mtb, we have designed and optimized DNAzyme sensor assays combined with multiplex PCR analytes that will enable the rapid, POC detection of drug resistance. This work aims to develop novel tools for the prompt and specific diagnosis of TB allowing for the implementation of an iv effective treatment regimen that will ultimately lessen transmission and control the emerging global threat of MDR and XDR-TB.

No description available.

A narrow germplasm base and a complex allotetraploid genome have historically made the discovery of single nucleotide polymorphism (SNP) markers difficult in cotton (Gossypium hirsutum). We conducted a genome reduction experiment to identify SNPs from two accessions of G. hirsutum and two accessions of G. barbadense. Approximately 2 million sequence reads were assembled into contigs with an N50 of 508 bp and analyzed for SNPs. A total of 11,834 and 1,679 SNPs between the accessions G. hirsutum and G. barbadense, respectively, were identified with highly conservative parameters (a minimum read depth of 8x at each SNP and a 100% identity of all reads within an accession at the SNP). Additionally, 4,327 SNPs were identified between accessions of G. hirsutum in and assembly of Expressed Sequence Tags (ESTs). 320 and 252 KASPAR assays were designed for SNP mapping in non-genic and genic regions respectively. 187 markers in total (136 non-genic, 51 genic) were mapped using KBioscience KASPar genotyping assays in a segregating F2 population using the Fluidigm EP1 system. EST The target genome of EST markers was successfully predicted bioinformaticly diploid reference sequences. Examination of nucleotide substitutions and SNP frequencies further confirms validity of new markers. A genetic map was constructed using a large G. hirsutum segregating F2 population. Genetic maps generated by these newly identified markers will be used to locate quantitative, economically important regions within the cotton genome.

Following its introduction to North America in the late nineteenth century, Bromus tectorum L., an inbreeding invasive winter annual grass, has become dominant on millions of hectares of sagebrush steppe habitat throughout Intermountain Western North America. It appears that within the last 30-40 years, B. tectorum has expanded its range southward into the Mojave Desert and also into more climatically extreme salt desert environments. Previous research using microsatellite markers and experimental studies has suggested that lineages found in desert habitats are genetically distinct from those found in the sagebrush-steppe habitat and possess suites of traits that pre-adapt them to these environments. To provide additional support for our hypothesis that desert habitat-specific haplotypes dominate and are widely distributed across warm and salt desert habitats, we genotyped approximately 20 individuals from each of 39 B. tectorum populations from these habitats and adjacent sagebrush steppe habitats using 71 single nucleotide polymorphic (SNP) markers. Our data clearly demonstrate that populations throughout the Mojave Desert region, as well as in salt desert habitats further north, are dominated by a small number of closely related SNP haplotypes that belong to the desert clade. In contrast, populations from adjacent environments are largely dominated by haplotypes of the common clade, which is widely distributed throughout the North American sagebrush steppe. Populations across all habitats were usually dominated by 1-2 SNP haplotypes. This suggests that inbreeding B. tectorum lineages can often maintain their genetic integrity. It also explains the strong association between marker fingerprints and suites of adaptive traits in this species.

Many diseases of genetic origin originate from non-synonymous single nucleotide polymorphisms (nsSNPs). These cause changes in the final protein product encoded by a gene. Through large scale sequencing and population studies, there is growing availability of information of which variations are tolerated and which are not. Variant effect predictors use a wide range of information about such variations to predict their effect, often focusing on evolutionary information. Here, a novel amino acid substitution variant effect predictor is developed. The predictor is a deep convolutional neural network incorporating evolutionary information, sequence information, as well as structural information, to predict both the pathogenicity as well as the severity of amino acid substitutions. The model achieves state-of-the-art performance on benchmark datasets.