Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

The application of NMR and MS methods for detection of adulteration of wine, fruit juices, and olive oil. A review

This review covers two important techniques, high resolution nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), used to characterize food products and detect possible adulteration of wine, fruit juices, and olive oil, all important products of the Mediterranean Basin. Emphasis is placed on the complementary use of SNIF-NMR (site-specific natural isotopic fractionation nuclear magnetic resonance) and IRMS (isotope-ratio mass spectrometry) in association with chemometric methods for detecting the adulteration.

Forecasting the effects of global warming on biodiversity

The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. in this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean-atmosphere-biosphere models, and (4) specics-area curve models that consider all species or large aggregates of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in the solution to the different problems.

Conceptos generales y métodos de estudio en farmacogenética [General concepts and study methods in pharmacogenetics.]

Pharmacogenetics, the study of how individual genetic profiles influence the response to drugs, is an important topic. Results from pharmacogenetics studies in various clinical settings may lead to personalized medicine. Herein, we present the most important concepts of this discipline, as well as currently-used study methods.

Minimum requirements for application of ink dating methods based on solvent analysis in casework

Several ink dating methods based on solvents analysis using gas chromatography/mass spectrometry (GC/MS) were proposed in the last decades. These methods follow the drying of solvents from ballpoint pen inks on paper and seem very promising. However, several questions arose over the last few years among questioned documents examiners regarding the transparency and reproducibility of the proposed techniques. These questions should be carefully studied for accurate and ethical application of this methodology in casework. Inspired by a real investigation involving ink dating, the present paper discusses this particular issue throughout four main topics: aging processes, dating methods, validation procedures and data interpretation. This work presents a wide picture of the ink dating field, warns about potential shortcomings and also proposes some solutions to avoid reporting errors in court.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Oxylipin analysis methods.

Practical guidelines for monitoring and measuring compounds such as jasmonates, ketols, ketodi(tri)enes and hydroxy-fatty acids as well as detecting the presence of novel oxylipins are presented. Additionally, a protocol for the penetrant analysis of non-enzymatic lipid oxidation is described. Each of the methods, which employ gas chromatography/mass spectrometry, can be applied without specialist knowledge or recourse to the latest analytical instrumentation. Additional information on oxylipin quantification and novel protocols for preparing oxygen isotope-labelled internal standards are provided. Four developing areas of research are identified: (i) profiling of the unbound cellular pools of oxylipins; (ii) profiling of esterified oxylipins and/or monitoring of their release from parent lipids; (iii) monitoring of non-enzymatic lipid oxidation; (iv) analysis of unstable and reactive oxylipins. The methods and protocols presented herein are designed to give technical insights into the first three areas and to provide a platform from which to enter the fourth area.

Application of real-time PCR for total airborne bacterial assessment : comparison with epifluorescence microscopy and culture-dependent methods

Traditional culture-dependent methods to quantify and identify airborne microorganisms are limited by factors such as short-duration sampling times and inability to count nonculturableor non-viable bacteria. Consequently, the quantitative assessment of bioaerosols is often underestimated. Use of the real-time quantitative polymerase chain reaction (Q-PCR) to quantify bacteria in environmental samples presents an alternative method, which should overcome this problem. The aim of this study was to evaluate the performance of a real-time Q-PCR assay as a simple and reliable way to quantify the airborne bacterial load within poultry houses and sewage treatment plants, in comparison with epifluorescencemicroscopy and culture-dependent methods. The estimates of bacterial load that we obtained from real-time PCR and epifluorescence methods, are comparable, however, our analysis of sewage treatment plants indicate these methods give values 270-290 fold greater than those obtained by the ''impaction on nutrient agar'' method. The culture-dependent method of air impaction on nutrient agar was also inadequate in poultry houses, as was the impinger-culture method, which gave a bacterial load estimate 32-fold lower than obtained by Q-PCR. Real-time quantitative PCR thus proves to be a reliable, discerning, and simple method that could be used to estimate airborne bacterial load in a broad variety of other environments expected to carry high numbers of airborne bacteria. [Authors]

Comparison of the interobserver variability of 2 different methods of dietary assessment in a geriatric ward: a pilot study.

BACKGROUND: Protein-energy malnutrition is highly prevalent in aged populations. Associated clinical, economic, and social burden is important. A valid screening method that would be robust and precise, but also easy, simple, and rapid to apply, is essential for adequate therapeutic management. OBJECTIVES: To compare the interobserver variability of 2 methods measuring food intake: semiquantitative visual estimations made by nurses versus calorie measurements performed by dieticians on the basis of standardized color digital photographs of servings before and after consumption. DESIGN: Observational monocentric pilot study. SETTING/PARTICIPANTS: A geriatric ward. The meals were randomly chosen from the meal tray. The choice was anonymous with respect to the patients who consumed them. MEASUREMENTS: The test method consisted of the estimation of calorie consumption by dieticians on the basis of standardized color digital photographs of servings before and after consumption. The reference method was based on direct visual estimations of the meals by nurses. Food intake was expressed in the form of a percentage of the serving consumed and calorie intake was then calculated by a dietician based on these percentages. The methods were applied with no previous training of the observers. Analysis of variance was performed to compare their interobserver variability. RESULTS: Of 15 meals consumed and initially examined, 6 were assessed with each method. Servings not consumed at all (0% consumption) or entirely consumed by the patient (100% consumption) were not included in the analysis so as to avoid systematic error. The digital photography method showed higher interobserver variability in calorie intake estimations. The difference between the compared methods was statistically significant (P < .03). CONCLUSIONS: Calorie intake measures for geriatric patients are more concordant when estimated in a semiquantitative way. Digital photography for food intake estimation without previous specific training of dieticians should not be considered as a reference method in geriatric settings, as it shows no advantages in terms of interobserver variability.

A comparison of methods for differential expression analysis of RNA-seq data.

BACKGROUND: Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data. RESULTS: We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data. CONCLUSIONS: Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.