MALDI-TOF mass spectrometry: a versatile tool for high-performance DNA analysis

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) has developed during the past decade into a versatile tool for biopolymer analysis. The aim of this review is to summarize this development and outline the applications, which have been enabled for routine use in the field of nucleic acid analysis. These include the analysis of mutations, the resequencing of amplicons with a known reference sequence, and the quantitative analysis of gene expression and allelic frequencies in complex DNA mixtures.     

Protection analysis (or "footprinting") of specific protein-DNA complexes in crude nuclear extracts using methidiumpropyl-EDTA-iron (II)

Endonuclease protection or "footprinting" analysis is a powerful technique for identifying the nucleotides involved in a protein-DNA interaction. DNase I is the most often employed endonucleolytic agent; however, this endonuclease does not exhibit the true nonsequence-specific cleavage desired for this type of analysis. Methidiumpropyl-EDTA (MPE) is a synthetic DNA intercalator that cleaves DNA in the presence of ferrous ion and oxygen. Cleavage by MPE exhibits no sequence specificity, a characteristic that makes this reagent better suited for protection analysis. Here we report a generally applicable technique for MPE protection (or "footprinting") analysis of specific DNA-protein complexes from a crude nuclear extract. We have used this method to identify the nucleotides of the immunoglobulin (Ig) heavy chain promoter region that are involved in complex formation with a protein that binds the octameric sequence ATGCAAAT, and we compare our results to those obtained previously using DNase I.     

A genetic analysis of seed and berry weight in grapevine.

Fruit size and seedlessness are highly relevant traits in many fruit crop species, and both are primary targets of breeding programs for table grapes. In this work we performed a quantitative genetic analysis of size and seedlessness in an F1 segregating population derived from the cross between a classical seeded (Vitis vinifera L. 'Dominga') and a newly bred seedless ('Autumn Seedless') cultivar. Fruit size was scored as berry weight (BW), and for seedlessness we considered both seed fresh weight (SFW) and the number of seeds and seed traces (SN) per berry. Quantitative trait loci (QTL) analysis of BW detected 3 QTLs affecting this trait and accounting for up to 67% of the total phenotypic variance. QTL analysis for seedlessness detected 3 QTLs affecting SN (explaining up to 35% of total variance) and 6 affecting SFW (explaining up to 90% of total variance). Among them, a major effect QTL explained almost half of the phenotypic variation for SFW. Comparative analysis of QTLs for these traits reduced the number of grapevine genomic regions involved, one of them being a major effect QTL for seedlessness. Association analyses showed that microsatellite locus VMC7F2, closely linked to this QTL, is a useful marker for selection of seedlessnes.     

A novel DNA methylation-based model that effectively predicts prognosis in hepatocellular carcinoma

Purpose: To build a novel predictive model for hepatocellular carcinoma (HCC) patients based on DNA methylation data.Methods: Four independent DNA methylation datasets for HCC were used to screen for common differentially methylated genes (CDMGs). Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to explore the biological roles of CDMGs in HCC. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis were performed to identify survival-related CDMGs (SR-CDMGs) and to build a predictive model. The importance of this model was assessed using Cox regression analysis, propensity score-matched (PSM) analysis and stratification analysis. A validation group from the Cancer Genome Atlas (TCGA) was constructed to further validate the model.Results: Four SR-CDMGs were identified and used to build the predictive model. The risk score of this model was calculated as follows: risk score = (0.01489826 × methylation level of WDR69) + (0.15868618 × methylation level of HOXB4) + (0.16674959 × methylation level of CDKL2) + (0.16689301 × methylation level of HOXA10). Kaplan–Meier analysis demonstrated that patients in the low-risk group had a significantly longer overall survival (OS; log-rank P-value =0.00071). The Cox model multivariate analysis and PSM analysis identified the risk score as an independent prognostic factor (P<0.05). Stratified analysis results further confirmed this model performed well. By analyzing the validation group, the results of receiver operating characteristic (ROC) curve analysis and survival analysis further validated this model.Conclusion: Our DNA methylation-based prognosis predictive model is effective and reliable in predicting prognosis for patients with HCC.     

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate independent ‘super traits'' from the original multivariate phenotypic traits for the univariate analysis. However, parameter estimates in this framework may not be the same as those from the joint analysis of all traits, leading to spurious linkage results. In this paper, we propose to perform the PCA for residual covariance matrix instead of the phenotypical covariance matrix, based on which multiple traits are transformed to a group of pseudo principal components. The PCA for residual covariance matrix allows analyzing each pseudo principal component separately. In addition, all parameter estimates are equivalent to those obtained from the joint multivariate analysis under a linear transformation. However, a fast least absolute shrinkage and selection operator (LASSO) for estimating the sparse oversaturated genetic model greatly reduces the computational costs of this procedure. Extensive simulations show statistical and computational efficiencies of the proposed method. We illustrate this method in a GWAS for 20 slaughtering traits and meat quality traits in beef cattle.     

Life cycle assessment and eco-efficiency analysis of drinking cups used at public events

Background, aim, and scope  

At the request of the Public Waste Agency for the Flemish Region, the Flemish Institute for Technological Research performed a life cycle assessment (LCA), according to the International Organization for Standardization (ISO) 14040 procedures (ISO 1997, 1998, 2000, and ISO 2006), followed by an eco-efficiency analysis of four alternative types of drinking cups for use at public events. The results of the LCA study served as input for the eco-efficiency analysis in which the costs related to the four cup systems were studied and combined with the environmental impacts. The objective of this study was to gain insight into the current environmental impacts and costs related to existing systems for drinking cups at public events in Flanders (Belgium) in order to outline a well-founded policy with regard to this subject. Since the results of this comparative study are publicly available, a critical review was performed according to ISO 14040 (review by interested parties, using a review panel) after each stage (goal and scope, data inventory, impact analysis/interpretation, eco-efficiency analysis) during the study.     

Order patterns recurrence plots in the analysis of ERP data

Recurrence quantification analysis (RQA) is an established tool for data analysis in various behavioural sciences. In this article we present a refined notion of RQA based on order patterns. The use of order patterns is commonplace in time series analysis. Exploiting this concept in combination with recurrence plots (RP) and their quantification (RQA) allows for advances in contemporary EEG research, specifically in the analysis of event related potentials (ERP), as the method is known to be robust against non-stationary data. The use of order patterns recurrence plots (OPRPs) on EEG data recorded during a language processing experiment exemplifies the potentials of the method. We could show that the application of RQA to ERP data allows for a considerable reduction of the number of trials required in ERP research while still maintaining statistical validity.     

Complete multipoint sib-pair analysis of qualitative and quantitative traits.

Sib-pair analysis is an increasingly important tool for genetic dissection of complex traits. Current methods for sib-pair analysis are primarily based on studying individual genetic markers one at a time and thus fail to use the full inheritance information provided by multipoint linkage analysis. In this paper, we describe how to extract the complete multipoint inheritance information for each sib pair. We then describe methods that use this information to map loci affecting traits, thereby providing a unified approach to both qualitative and quantitative traits. Specifically, complete multipoint approaches are presented for (1) exclusion mapping of qualitative traits; (2) maximum-likelihood mapping of qualitative traits; (3) information-content mapping, showing the extent to which all inheritance information has been extracted at each location in the genome; and (4) quantitative-trait mapping, by two parametric methods and one nonparametric method. In addition, we explore the effects of marker density, marker polymorphism, and availability of parents on the information content of a study. We have implemented the analysis methods in a new computer package, MAPMAKER/SIBS. With this computer package, complete multipoint analysis with dozens of markers in hundreds of sib pairs can be carried out in minutes.     

The application of preirradiation combustion and neutron activation analysis technique for the determination of iodine in food and environmental reference materials

The pre-irradiation combustion (PC) of samples to liberate iodine, followed by trapping the iodine on charcoal and quantifying the element by neutron activation analysis (NAA), has been used at the National Institute of Standards and Technology for the determination of iodine in biological materials. The applicability of this technique to numerous environmental and dietary matrices is illustrated by analysis of a range of certified reference materials (CRMs) and a powdered grass material that was prepared as an in-house reference material (RM). Because of the combustion step involved, samples with low or no fat content (e.g., cereal products, selected botanical specimens, and nonfat milk powder) and inorganic materials (e.g., coal fly ash and dried sediments) are more suited for analysis by this method. In general, the results for several types of samples obtained by this method agreed with those obtained by a second radiochemical (R) NAA, as well as by a third method using inductively coupled plasma mass spectrometry (ICP-MS). PC-NAA is a useful technique for determining iodine in biological and environmental samples, especially for verification of iodine results obtained from other methods.     

A quantitative trait loci analysis of zinc hyperaccumulation in Arabidopsis halleri

The mechanisms of metal hyperaccumulation are still not understood, so we conducted a quantitative trait locus (QTL) analysis of zinc (Zn) hyperaccumulation in Arabidopsis halleri, in a cross between this and its sister species, A. petraea, in order to determine the number and approximate location of the genomic regions significantly contributing to this adaptation. An F2 cross between the two species was made, and the leaf Zn concentration of 92 individuals was measured at both low (10 microm) and high (100 microm) Zn concentrations. Twenty-five markers were established that were distributed on all of the eight chromosomes. Mapping of the markers established that they were essentially collinear with previous studies. QTLs exceeding a logarithm to the base 10 of the odds (LOD) value of 3 were found on chromosomes 4 (low Zn), 6 (high Zn) and 7 (both high and low Zn). Evidence for a QTL on chromosome 3 (low Zn) was also found. This analysis validates a previously used method of QTL analysis, based on microarray analysis of segregating families. Genes that have altered during the evolution of this character should also be QTL: this analysis calls into question a number of candidate genes from consideration as such primary genes because they do not appear to be associated with QTLs.     

Towards enabling a cardiovascular digital twin for human systemic circulation using inverse analysis

An exponential rise in patient data provides an excellent opportunity to improve the existing health care infrastructure. In the present work, a method to enable cardiovascular digital twin is proposed using inverse analysis. Conventionally, accurate analytical solutions for inverse analysis in linear problems have been proposed and used. However, these methods fail or are not efficient for nonlinear systems, such as blood flow in the cardiovascular system (systemic circulation) that involves high degree of nonlinearity. To address this, a methodology for inverse analysis using recurrent neural network for the cardiovascular system is proposed in this work, using a virtual patient database. Blood pressure waveforms in various vessels of the body are inversely calculated with the help of long short-term memory (LSTM) cells by inputting pressure waveforms from three non-invasively accessible blood vessels (carotid, femoral and brachial arteries). The inverse analysis system built this way is applied to the detection of abdominal aortic aneurysm (AAA) and its severity using neural networks.

     

Prescription et pratique de la recherche des microdélétions du chromosome Y en France: résultats de l’enquête nationale réalisée sous l’égide de la Société d’Andrologie de Langue Française

Screening for Y chromosome microdeletions is recommended in cases of severe impaired spermatogenesis. Improvement of molecular biology techniques has made this diagnosis more accessible in routine practice when evaluation of male infertility is necessary. However, the diagnosis of Y chromosome microdeletions is not proposed by all IVF centres. The aim of the present study was to specify the prescribing conditions (indication, financing) and practical conduct (methods, billing) for this analysis in France. We observed that microdeletion screening is a rapidly expanding activity. The development of a consensus on the indications for this screening and a standardised technique, with a national quality control, appears to be necessary. The funding of this analysis by French Social Security appears to be an essential step to ensure widespread use in routine practice. Lastly, the answers to our questionnaire revealed a strong demand for information concerning this analysis.     

Liquid chromatographic analysis of amino acids: Using dimethylamino-azobenzenesulfonyl chloride and hypersil ODS column to analyze the composition of apo B peptides

A reliable high-performance liquid chromatography (HPLC) method is described for the separation of dimethylamino-azobenzenesulfonyl-amino acid (DABS-AA). The separation is accomplished by reversed-phase chromatography on a Hypersil ODS column (4.6×150 mm) withe a Hewlett-Packard liquid chromatography system. In addition to the developed sample and solvent preparation procedure, this precolumn modification method using dimethylaminoazobenzene sulfonyl chloride (DABS-CL) for amino acid analysis is proved reliable and sensitive. Five apolipoprotein B-100 tryptic peptides, two of them containing cysteine, were demonstrated as examples for the general application of this method in amino acid analysis. It is a useful method for analysis of cysteine- and cysteine-containing peptide and, furthermore, for determination of sulfhydryl and disulfide linkages of proteins.     

Pathway analysis for genome-wide genetic variation data: Analytic principles,latest developments,and new opportunities

Pathway analysis, also known as gene-set enrichment analysis, is a multilocus analytic strategy that integrates a priori, biological knowledge into the statistical analysis of high-throughput genetics data. Originally developed for the studies of gene expression data, it has become a powerful analytic procedure for indepth mining of genome-wide genetic variation data. Astonishing discoveries were made in the past years,uncovering genes and biological mechanisms underlying common and complex disorders. However, as massive amounts of diverse functional genomics data accrue, there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data. In this review, we provide an intellectual foundation of this powerful analytic strategy, as well as an update of the state-of-the-art in recent method developments. The goal of this review is threefold:(1) introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data;(2) review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools; and(3)discuss remaining challenges and future directions for further method developments.     

Integrated function of a kinetic proofreading mechanism: steady-state analysis testing internal consistency of data obtained in vivo and in vitro and predicting parameter values

Experimental measurements of the kinetic mechanism involving isoleucyl-tRNA synthetase proofreading valyl-tRNAIle in Escherichia coli have been incorporated into the conventional Michaelis-Menten model for this system. The model was subjected to a detailed mathematical analysis in the steady state. The results of this analysis provide an excellent illustration of the value of integrating fragmentary data into a model of the intact system. (1) Such integration provides a rigorous test for consistency of the individual measurements. For the above synthetase system, the published experimental data were found to be internally inconsistent. (2) Such integration predicts which experimental data are most suspect. In this case, one of the three most questionable measurements, the isoleucine pool size in vivo, was found upon reexamination to be in error by 10-15-fold. Correction of this error produced a self-consistent set of parameter values. (3) The integrated analysis provides predictions for various parameter values. In many cases, these predictions provide estimates for parameter values that are difficult to determine directly or that have yet to be measured experimentally. (4) A sensitivity analysis provides an indication of the relative importance of various parameter values and, hence, an indication of where future experimental effort might be focused most profitably.     

A Pilot Application of Regional Scale Risk Assessment to the Forestry Management of the Upper Grande Ronde Watershed,Oregon

An issue in forestry management has been the integration of a variety of different information into a threat analysis or risk assessment. In this instance, regional scale risk assessment was applied to the Upper Grande Ronde watershed in eastern Oregon to examine the potential of risk assessment for use in the management of broad landscapes. The site was a focus of study for the U.S. Forest Service through the Interior Northwest Landscape Analysis System (INLAS) project. In the study, a range of stressors, habitats, and endpoints were identified from previous studies in the watershed, and endpoints were determined from meeting with the primary stakeholder, the U.S. Forest Service. These endpoints were focused around the historic range of variability (HRV) defined for the area. The relative risk model (RRM) incorporating a Monte Carlo analysis was used as the analysis tool. The risk model output showed the HRV fire regime was the endpoint most at risk. The results of this analysis were compared to the Wallowa-Whitman National Forest prioritization of watershed restoration analysis. The RRM demonstrated similar results but with a better accounting for uncertainty. From this trial the RRM has proven to be a potential management tool for forestry management.     

Mechanistic kinetic model for symmetric carboligations using benzaldehyde lyase

For reactions using thiamine diphosphate (ThDP)-dependent enzymes many empirically-derived kinetic models exist. However, there is a lack of mechanistic kinetic models. This is especially true for the synthesis of symmetric 2-hydroxy ketones from two identical aldehydes, with one substrate acting as the donor and the other as the acceptor. In this contribution, a systematic approach for deriving such a kinetic model for thiamine diphosphate (ThDP)-dependent enzymes is presented. The derived mechanistic kinetic model takes this donor-acceptor principle into account by containing two K(m)-values even for identical substrate molecules. As example the stereoselective carbon-carbon coupling of two 3,5-dimethoxy-benzaldehyde molecules to (R)-3,3',5,5'-tetramethoxy-benzoin using benzaldehyde lyase (EC 4.1.2.38) from Pseudomonas fluorescens is studied. The model is derived using a model-based experimental analysis method which includes parameter estimation, model analysis, optimal experimental design, in silico experiments, sensitivity analysis and model revision. It is shown that this approach leads to a robust kinetic model with accurate parameter estimates and an excellent prediction capability.     

Strategies for conditional two-locus nonparametric linkage analysis

In this article we deal with two-locus nonparametric linkage (NPL) analysis, mainly in the context of conditional analysis. This means that one incorporates single-locus analysis information through conditioning when performing a two-locus analysis. Here we describe different strategies for using this approach. Cox et al. [Nat Genet 1999;21:213-215] implemented this as follows: (i) Calculate the one-locus NPL process over the included genome region(s). (ii) Weight the individual pedigree NPL scores using a weighting function depending on the NPL scores for the corresponding pedigrees at speci fi c conditioning loci. We generalize this by conditioning with respect to the inheritance vector rather than the NPL score and by separating between the case of known (prede fi ned) and unknown (estimated) conditioning loci. In the latter case we choose conditioning locus, or loci, according to prede fi ned criteria. The most general approach results in a random number of selected loci, depending on the results from the previous one-locus analysis. Major topics in this article include discussions on optimal score functions with respect to the noncentrality parameter (NCP), and how to calculate adequate p values and perform power calculations. We also discuss issues related to multiple tests which arise from the two-step procedure with several conditioning loci as well as from the genome-wide tests.