Genome-wide association mapping of iron homeostasis in the maize association population

BACKGROUND: Iron (Fe) deficiency in plants is the result of low Fe soil availability affecting 30% of cultivated soils worldwide. To improve our understanding on Fe-efficiency this study aimed to (i) evaluate the influence of two different Fe regimes on morphological and physiological trait formation, (ii) identify polymorphisms statistically associated with morphological and physiological traits, and (iii) dissect the correlation between morphological and physiological traits using an association mapping population. RESULTS: The fine-mapping analyses on quantitative trait loci (QTL) confidence intervals of the intermated B73 × Mo17 (IBM) population provided a total of 13 and 2 single nucleotide polymorphisms (SNPs) under limited and adequate Fe regimes, respectively, which were significantly (FDR = 0.05) associated with cytochrome P450 94A1, invertase beta-fructofuranosidase insoluble isoenzyme 6, and a low-temperature-induced 65 kDa protein. The genome-wide association (GWA) analyses under limited and adequate Fe regimes provided in total 18 and 17 significant SNPs, respectively. CONCLUSIONS: Significantly associated SNPs on a genome-wide level under both Fe regimes for the traits leaf necrosis (NEC), root weight (RW), shoot dry weight (SDW), water (H (2)O), and SPAD value of leaf 3 (SP3) were located in genes or recognition sites of transcriptional regulators, which indicates a direct impact on the phenotype. SNPs which were significantly associated on a genome-wide level under both Fe regimes with the traits NEC, RW, SDW, H (2)O, and SP3 might be attractive targets for marker assisted selection as well as interesting objects for future functional analyses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-014-0153-0) contains supplementary material, which is available to authorized users

Influence of Temperature and Concentration on the Self-Assembly of Nonionic CiEjSurfactants: A Light Scattering Study

Nonionic poly(ethylene oxide) alkyl ether (C$_{i}$iE$_{j}$) surfactants self-assemble into aggregates of various sizes and shapes above their critical micelle concentration (CMC). Knowledge on solution attributes such as CMC as well as aggregate characteristics is crucial to choose the appropriate surfactant for a given application, e.g., as a micellar solvent system. In this work, we used static and dynamic light scattering to measure the CMC, aggregation number (N$_{agg}$), and hydrodynamic radius (R$_{h}$) of four different C$_{i}$E$_{j}$ surfactants (C$_{8}$E$_{5}$, C$_{8}$E$_{6}$, C$_{10}$E$_{6}$, and C$_{10}$E$_{8}$). We examined the influence of temperature, concentration, and molecular structure on the self-assembly in the vicinity of the CMC. A minimum in the CMC vs temperature curve was identified for all surfactants investigated. Further, extending the hydrophilic and hydrophobic chain lengths leads to an increase and decrease of the CMC, respectively. The size of the aggregates strongly depends on temperature. N$_{agg}$ and R$_{h}$ increase with increasing temperature for all surfactants investigated. Additionally, N$_{agg}$ and R$_{h}$ both increase with increasing surfactant concentration. The data obtained in this work further improve the understanding of the influence of temperature and molecular structure on the self-assembly of C$_{i}$iE$_{j}$ surfactants and will further foster their use in micellar solvent systems

The genetic basis of natural variation for iron homeostasis in the maize IBM population

BACKGROUND: Iron (Fe) deficiency symptoms in maize (Zea mays subsp. mays) express as leaf chlorosis, growth retardation, as well as yield reduction and are typically observed when plants grow in calcareous soils at alkaline pH. To improve our understanding of genotypical variability in the tolerance to Fe deficiency-induced chlorosis, the objectives of this study were to (i) determine the natural genetic variation of traits related to Fe homeostasis in the maize intermated B73 × Mo17 (IBM) population, (ii) to identify quantitative trait loci (QTLs) for these traits, and (iii) to analyze expression levels of genes known to be involved in Fe homeostasis as well as of candidate genes obtained from the QTL analysis. RESULTS: In hydroponically-grown maize, a total of 47 and 39 QTLs were detected for the traits recorded under limited and adequate supply of Fe, respectively. CONCLUSIONS: From the QTL results, we were able to identify new putative candidate genes involved in Fe homeostasis under a deficient or adequate Fe nutritional status, like Ferredoxin class gene, putative ferredoxin PETF, metal tolerance protein MTP4, and MTP8. Furthermore, our expression analysis of candidate genes suggested the importance of trans-acting regulation for 2’-deoxymugineic acid synthase 1 (DMAS1), nicotianamine synthase (NAS3, NAS1), formate dehydrogenase 1 (FDH1), methylthioribose-1-phosphate isomerase (IDI2), aspartate/tyrosine/aromatic aminotransferase (IDI4), and methylthioribose kinase (MTK)

OccIDEAS: Retrospective Occupational Exposure Assessment in Community-Based Studies Made Easier

Assessing occupational exposure in retrospective community-based case-control studies is difficult as measured exposure data are very seldom available. The expert assessment method is considered the most accurate way to attribute exposure but it is a time consuming and expensive process and may be seen as subjective, nonreproducible, and nontransparent. In this paper, we describe these problems and outline our solutions as operationalized in a web-based software application (OccIDEAS). The novel aspects of OccIDEAS are combining all steps in the assessment into one software package; enmeshing the process of assessment into the development of questionnaires; selecting the exposure(s) of interest; specifying rules for exposure assignment; allowing manual or automatic assessments; ensuring that circumstances in which exposure is possible for an individual are highlighted for review; providing reports to ensure consistency of assessment. Development of this application has the potential to make high-quality occupational assessment more efficient and accessible for epidemiological studies

The effects of acute and elective cardiac surgery on the anxiety traits of patients with Marfan syndrome

BACKGROUND: Marfan syndrome is a genetic disease, presenting with dysfunction of connective tissues leading to lesions in the cardiovascular and skeletal muscle system. Within these symptoms, the most typical is weakness of the connective tissue in the aorta, manifesting as aortic dilatation (aneurysm). This could, in turn, become annuloaortic ectasia, or life-threatening dissection. As a result, life-saving and preventative cardiac surgical interventions are frequent among Marfan syndrome patients. Aortic aneurysm could turn into annuloaortic ectasia or life-threatening dissection, thus life-saving and preventive cardiac surgical interventions are frequent among patients with Marfan syndrome. We hypothesized that patients with Marfan syndrome have different level of anxiety, depression and satisfaction with life compared to that of the non-clinical patient population. METHODS: Patients diagnosed with Marfan syndrome were divided into 3 groups: those scheduled for prophylactic surgery, those needing acute surgery, and those without need for surgery (n = 9, 19, 17, respectively). To examine the psychological features of the patients, Spielberger's anxiety (STAI) test, Beck's Depression questionnaire (BDI), the Berne Questionnaire of Subjective Well-being, and the Satisfaction with Life scale were applied. RESULTS: A significant difference was found in trait anxiety between healthy individuals and patients with Marfan syndrome after acute life-saving surgery (p 0.1). Finally, a significant, medium size effect was found between patient groups on the Joy in Living scale (F (2.39) = 3.51, p = 0.040, eta2 = 0.15). CONCLUSIONS: Involving psychiatric and mental-health care, in addition to existing surgical treatment interventions, is essential for more successful recovery of patients with Marfan syndrome

Parametricity and Dependent Types

Reynolds' abstraction theorem shows how a typing judgement in System F can be translated into a relational statement (in second order predicate logic) about inhabitants of the type. We (in second order predicate logic) about inhabitants of the type. We obtain a similar result for a single lambda calculus (a pure type system), in which terms, types and their relations are expressed. Working within a single system dispenses with the need for an interpretation layer, allowing for an unusually simple presentation. While the unification puts some constraints on the type system (which we spell out), the result applies to many interesting cases, including dependently-typed ones

Array-Based FMR1 Sequencing and Deletion Analysis in Patients with a Fragile X Syndrome–Like Phenotype

Background: Fragile X syndrome (FXS) is caused by loss of function mutations in the FMR1 gene. Trinucleotide CGG-repeat expansions, resulting in FMR1 gene silencing, are the most common mutations observed at this locus. Even though the repeat expansion mutation is a functional null mutation, few conventional mutations have been identified at this locus, largely due to the clinical laboratory focus on the repeat tract. Methodology/Principal Findings: To more thoroughly evaluate the frequency of conventional mutations in FXS-like patients, we used an array-based method to sequence FMR1 in 51 unrelated males exhibiting several features characteristic of FXS but with normal CGG-repeat tracts of FMR1. One patient was identified with a deletion in FMR1, but none of the patients were found to have other conventional mutations. Conclusions/Significance: These data suggest that missense mutations in FMR1 are not a common cause of the FXS phenotype in patients who have normal-length CGG-repeat tracts. However, screening for small deletions of FMR1 may be of clinically utility

Selection of multiple donor gauges via Graphical Lasso for estimation of daily streamflow time series

A fundamental challenge in estimations of daily streamflow time series at sites with incomplete records is how to effectively and efficiently select reference or donor gauges from an existing gauge network to infer the missing data. While research on estimating missing streamflow time series is not new, the existing approaches either use a single reference streamflow gauge or employ a set of "ad-hoc" reference gauges, leaving a systematic selection of reference gauges as a long-standing open question. In this work, a novel method is introduced that facilitates systematical selection of multiple reference gauges from any given streamflow network. The idea is to mathematically characterize the network-wise correlation structure of a streamflow network via graphical Markov modeling, and further transforms a dense network into a sparsely connected one. The resulted underlying sparse graph from the graphical model encodes conditional independence conditions among all reference gauges from the streamflow network, allowing determination of an optimum subset of the donor gauges. The sparsity is discovered by using the Graphical Lasso algorithm with an L1-norm regularization parameter and a thresholding parameter. These two parameters are determined by a multi-objective optimization process. Furthermore, the graphical modeling approach is employed to solve another open problem in gauge removal planning decision (e.g., due to operation budget constraints): which gauges to remove would statistically guarantee the least loss of information by estimations from the remaining gauges? Our graphical model-based method is demonstrated with daily streamflow data from a network of 34 gauges over the Ohio River basin.Comment: arXiv admin note: substantial text overlap with arXiv:2004.0137