Segregation analysis of a complex quantitative trait: approaches for identifying influential data points

BACKGROUND/AIMS: Complex traits pose a particular challenge to standard methods for segregation analysis (SA), and for such traits it is difficult to assess the ability of complex SA (CSA) to approximate the true mode of inheritance. Here we use an oligogenic Bayesian Markov chain Monte Carlo method for SA (OSA) to verify results from a single-locus likelihood-based CSA for data on a quantitative measure of reading ability. METHODS: We compared the profile likelihood from CSA, maximized over the trait allele frequency, to the posterior distribution of genotype effects from OSA to explore differences in the overall parameter estimates from SA on the original phenotype data and the same data Winsorized to reduce the potential influence of three outlying data points. RESULTS: Bayesian OSA revealed two modes of inheritance, one of which coincided with the QTL model from CSA. Winsorizing abolished the model originally estimated by CSA; both CSA and OSA identified only the second OSA model. CONCLUSION: Differences between the results from the two methods alerted us to the presence of influential data points, and identified the QTL model best supported by the data. Thus, the Bayesian OSA proved a valuable tool for assessing and verifying inheritance models from CSA.     

The QUEST system for quantitative analysis of two-dimensional gels

The strategies and methods used by the QUEST system for two-dimensional gel analysis are described, and the performance of the system is evaluated. Radiolabeled proteins, resolved on two-dimensional gels and detected using calibrated exposures to film, are quantified in units of disintegrations per minute or as a fraction of the total protein radioactivity applied to the gel. Spot quantitation and resolution of overlapping spots is performed by two-dimensional gaussian fitting. Pattern matching is carried out for groups of gels called matchsets, and within each matchset every gel is matched to every other gel. During the matching process, spots are automatically added to each pattern at positions where unmatched spots were detected in other patterns. This results in enhanced accuracy for both spot detection and for matching. The spot fitting procedure is repeated after matching. Tests show that up to 97% of spots in each pattern can be matched and that fewer than 1% of the spots are matched inconsistently. Approximately 2000 proteins are detected from typical gels. Of these 1600 are high quality spots. Tests to measure the coefficient of variation of spot quantitation versus spot quality show that the average coefficient of variation for high quality spots is 21%. The intensities of the detected proteins range from 4 to 20,000 ppm of total protein synthesis. The QUEST analysis system has been used to build a quantitative database for the proteins of normal and transformed REF52 cells, as presented in the accompanying reports (Garrels, J., and Franza, B. R., Jr. (1989) J. Biol. Chem. 264, 5283-5298, 5299-5312).     

Molecular analysis of predation: a review of best practice for DNA-based approaches

Molecular analysis of predation, through polymerase chain reaction amplification of prey remains within the faeces or digestive systems of predators, is a rapidly growing field, impeded by a lack of readily accessible advice on best practice. Here, we review the techniques used to date and provide guidelines accessible to those new to this field or from a different molecular biology background. Optimization begins with field collection, sample preservation, predator dissection and DNA extraction techniques, all designed to ensure good quality, uncontaminated DNA from semidigested samples. The advantages of nuclear vs. mitochondrial DNA as primer targets are reviewed, along with choice of genes and advice on primer design to maximize specificity and detection periods following ingestion of the prey by the predators. Primer and assay optimization are discussed, including cross-amplification tests and calibratory feeding experiments. Once primers have been made, the screening of field samples must guard against (through appropriate controls) cross contamination. Multiplex polymerase chain reactions provide a means of screening for many different species simultaneously. We discuss visualization of amplicons on gels, with and without incorporation of fluorescent primers. In more specialized areas, we examine the utility of temperature and denaturing gradient gel electrophoresis to examine responses of predators to prey diversity, and review the potential of quantitative polymerase chain reaction systems to quantify predation. Alternative routes by which prey DNA might get into the guts of a predator (scavenging, secondary predation) are highlighted. We look ahead to new technologies, including microarrays and pyrosequencing, which might one day be applied to this field.     

A quantitative analysis software tool for mass spectrometry-based proteomics

We describe Census, a quantitative software tool compatible with many labeling strategies as well as with label-free analyses, single-stage mass spectrometry (MS1) and tandem mass spectrometry (MS/MS) scans, and high- and low-resolution mass spectrometry data. Census uses robust algorithms to address poor-quality measurements and improve quantitative efficiency, and it can support several input file formats. We tested Census with stable-isotope labeling analyses as well as label-free analyses.     

Assessment of microbial quality of commercial and home-made tiger-nut beverages

Aims: We aimed to assess the microbiological quality of Spanish commercial tiger‐nut beverages as well as home‐made samples collected from supermarkets, street vendors, juice bars and ice‐cream parlours located in Valencia. Methods and Results: Microbiological analysis of 44 tiger‐nut beverages samples were carried out according to International Standard Organization (ISO) norms and published works which included the total viable count, Enterobacteriaceae, Escherichia coli, Staphylococcus aureus, Salmonella, Bacillus cereus, yeasts, moulds, Yersinia enterocolitca, Clostridium perfringens, Vibrio spp. and Listeria monocytogenes. The obtained results indicated that all the commercial samples were below the detection limit for the viable microorganisms. Results of analysis of those home‐made tiger‐nut samples revealed that 67% (16 samples) harboured total plate counts while the rest of samples were free from these microorganisms. Enterobacteriaceae were detected in 62% (15 samples). E. coli were found in only one sample (4%), yeasts and moulds were detected in 62% (15 samples) each, Shigella was found in 21% (five samples); however, all samples were free from S. aureus, Salmonella, Y. enterocolotica, C. perfringens, Vibrio spp. and L. monocytogenes. Conclusions: These results reflected that there exists a rather high contamination level in home‐made tiger‐nut beverages indicating the need to apply correct and strict HACCP system(s) during manufacturing and storage of these food products. Significance and Impact of Study: This study demonstrates the great need to carry out microbiological tests frequently in these products and even more the need to apply correct HACCP system (s). Tiger‐nut beverages are especially well‐known products in Spain, hence it is extremely important to ensure an adequate microbiological quality to guarantee consumers health.     

Computational approaches for microRNA studies: a review

MicroRNAs (miRNAs) are one class of tiny, endogenous RNAs that can regulate messenger RNA (mRNA) expression by targeting homologous sequences in mRNAs. Their aberrant expressions have been observed in many cancers and several miRNAs have been convincingly shown to play important roles in carcinogenesis. Since the discovery of this small regulator, computational methods have been indispensable tools in miRNA gene finding and functional studies. In this review we first briefly outline the biological findings of miRNA genes, such as genomic feature, biogenesis, gene structure, and functional mechanism. We then discuss in detail the three main aspects of miRNA computational studies: miRNA gene finding, miRNA target prediction, and regulation of miRNA genes. Finally, we provide perspectives on some emerging issues, including combinatorial regulation by miRNAs and functional binding sites beyond the 3′-untranslated region (3′UTR) of target mRNAs. Available online resources for miRNA computational studies are also provided.     

Real and imaginary artefacts in proteome analysis via two-dimensional maps

The present review touches on a long-lasting debate on possible artefacts (i.e. generation of spurious spots, not belonging to the biological sample under analysis) induced by the separation technique (in this case, two-dimensional mapping) per se. It is shown here that some of the biggest offenders, always blamed in the past (at least since 1970, i.e. since the inception of gel-base isoelectric focusing protocols), namely deamidation (of Asn and Gln residues) and carbamylation (due to cyanate produced in urea solution), simply do not occur in properly handled samples and have never indeed been demonstrated in real samples, except when forced in purpose. Conversely, two unexpected major artefacts have been recently shown to plague 2D mapping. One is formation of homo- and hetero-oligomers in samples that have been reduced but not alkylated prior to entering the electric field. The phenomenon is highly aggravated in alkaline pH regions and can lead to an impressive number of spurious spots not existing in the original sample. Thus, alkylation (best if performed with acrylamide or vinylpyridines) is a must for avoiding such spurious spots, as well as sample streaking and smearing in the alkaline gel region, and for maintaining sample integrity. In fact, the other unexpected artefact is desulfuration (beta-elimination) by which, upon prolonged electrophoresis, the sample looses an -SH group fro Cys residues. This loss, in the long run, is accompanied by massive protein degradation due to lysis of a C-N bond along the polypeptide chain. Here too, alkylation of -SH groups of Cys almost completely prevents this noxious degradation phenomenon.     

Targeting toll-like receptors for drug development: a summary of commercial approaches

Toll-like receptors (TLRs) play a fundamental role in recognizing infectious and noxious agents as well as products of tissue damage. They are capable of initiating both protective and damaging inflammatory and immune responses. Several biotechnology and pharmaceutical companies have programmes to develop new drugs that are either: agonists of TLRs to enhance immune responses against tumours and infectious agents, or to correct allergic responses; or antagonists designed to reduce inflammation due to infection or autoimmune disease. This article reviews the commercial approaches being undertaken to develop new TLR drugs.     

Microcomputer-based image analysis systems for two-dimensional electrophoresis gels

The intent of this overview is to provide the readers, especially those who are currently conducting two-dimentional electrophoresis, a basic understanding in the construction and use of microcomputer-based systems for the analysis of protein profiles generated by two-dimensional gel electrophoresis. In addition, a microcomputer-based system, employing fixed-point operations and effective algorithms, has been evaluated. The validity of this system has been demonstrated by using the two-dimensional silver-stained gels and fluorograms derived from the rat prostate. It is concluded that the present system can be used to aid the analysis of two-dimensional electrophoresis gels. An overall consideration of hardware and software components of a computer-based system is briefly discussed.     

Real-time PCR: approaches to data analysis (a review)

The registration of the accumulation of polymerase chain reaction (PCR) products in the course of amplification (real-time PCR) requires specific equipment, i.e., detecting amplifiers capable of recording the level of fluorescence in the reaction tube during amplicon formation. By the time the reaction is completed, researchers obtain DNA accumulation graphs. The review discusses the most promising algorithms of analysis of real-time PCR curves and possible errors, whether caused by the software used or the operators' mistakes. The data included will assist researchers in understanding the features of the method to obtain more reliable results.     

ODS2: a multiplatform software application for creating integrated physical and genetic maps

A contig map is a physical map that shows the native order of a library of overlapping genomic clones. One common method for creating such maps involves using hybridization to detect clone overlaps. False- positive and false-negative hybridization errors, the presence of chimeric clones, and gaps in library coverage lead to ambiguity and error in the clone order. Genomes with good genetic maps, such as Neurospora crassa, provide a means for reducing ambiguities and errors when constructing contig maps if clones can be anchored with genetic markers to the genetic map. A software application called ODS2 for creating contig maps based on clone-clone hybridization data is presented. This application is also designed to exploit partial ordering information provided by anchorage of clones to a genetic map. This information, along with clone-clone hybridization data, is used by a clone ordering algorithm and is represented graphically, allowing users to interactively align physical and genetic maps. ODS2 has a graphical user interface and is implemented entirely in Java, so it runs on multiple platforms. Other features include the flexibility of storing data in a local file or relational database and the ability to create full or minimum tiling contig maps.     

Comparing the success of different prediction software in sequence analysis: a review

The abundance of computer software for different types of prediction in DNA and protein sequence analyses raises the problem of adequate ranking of prediction program quality. A single measure of success of predictor software, which adequately ranks the predictors, does not exist. A typical example of such an incomplete measure is the so-called correlation coefficient. This paper provides an overview and short analysis of several different measures of prediction quality. Frequently, some of these measures give results contradictory to each other even when they relate to the same prediction scores.This may lead to confusion. In order to overcome some of the problems, a few new measures are proposed including some variants of a 'generalised distance from the ideal predictor score'; these are based on topological properties, rather than on statistics. In order to provide a sort of a balanced ranking, the averaged score measure (ASM) is introduced.The ASM provides a possibility for the selection of the predictor that probably has the best overall performance.The method presented in the paper applies to the ranking problem of any prediction software whose results can be properly represented in a true positive-false positive framework, thus providing a natural set-up for linear biological sequence analysis.     

ShapeFinder: a software system for high-throughput quantitative analysis of nucleic acid reactivity information resolved by capillary electrophoresis

Analysis of the long-range architecture of RNA is a challenging experimental and computational problem. Local nucleotide flexibility, which directly reports underlying base pairing and tertiary interactions in an RNA, can be comprehensively assessed at single nucleotide resolution using high-throughput selective 2'-hydroxyl acylation analyzed by primer extension (hSHAPE). hSHAPE resolves structure-sensitive chemical modification information by high-resolution capillary electrophoresis and typically yields quantitative nucleotide flexibility information for 300-650 nucleotides (nt) per experiment. The electropherograms generated in hSHAPE experiments provide a wealth of structural information; however, significant algorithmic analysis steps are required to generate quantitative and interpretable data. We have developed a set of software tools called ShapeFinder to make possible rapid analysis of raw sequencer data from hSHAPE, and most other classes of nucleic acid reactivity experiments. The algorithms in ShapeFinder (1) convert measured fluorescence intensity to quantitative cDNA fragment amounts, (2) correct for signal decay over read lengths extending to 600 nts or more, (3) align reactivity data to the known RNA sequence, and (4) quantify per nucleotide reactivities using whole-channel Gaussian integration. The algorithms and user interface tools implemented in ShapeFinder create new opportunities for tackling ambitious problems involving high-throughput analysis of structure-function relationships in large RNAs.     

Elsie 4: quantitative computer analysis of sets of two-dimensional gel electrophoretograms

We have developed and refined a system for quantitative computer analysis of two-dimensional polyacrylamide gel electrophoretograms. The system, named Elsie 4, is based on one described by Vo et al. (Anal. Biochem. 112, 258 (1981]. It is highly automated. Elsie 4 can find, and measure the intensity of, almost any spot resolvable on two-dimensional gels, including spots visible only as shoulders off larger spots and spots so close together that there is no valley between them. It can automatically match the spot patterns of different gels, potentially without the need for a user to provide landmark matches. The matches between paired gels let us follow the synthesis of any spot through a set of gels. Information about a group of matched spots can be obtained by referring to any spot in the group. There is generally no need for a standard or reference gel. Data for two experiments can be combined and compared by matching any gel in one experiment with any gel in the other. There are ways to automatically find possible mismatches in sets of gels. Scans and the results of the analysis can be shown on an image displayer. The programs use function libraries; this helps ensure consistency and increase portability. The programs and functions can be linked together in many ways; this lets users build custom programs for analysis of specific experiments.     

Spot overlapping in two-dimensional maps: a serious problem ignored for much too long

In the analysis of a neuroblastoma xenograft implanted in mice using two-dimensional maps, some 85 proteins were found to be up- or down-regulated (out of a total of 264 detected by a medium-sensitivity colloidal Coomassie stain). When these spots were eluted and analysed by mass spectrometry in a quadrupole time of flight mass spectrometer, a number of spots were found to be envelopes of different polypeptide chains. Out of a total of 74 proteins identified, 52 (71%) were found to be singlets, 14 (19%) were doublets, 6 (8%) were triplets, 1 was a quadruplet and 1 a quintuplet. Analysis of the DeltapI and DeltaMr of all species contained in a single gel segment eluted helped point out potential errors in protein identification. This was a unique case, in that very minute bioptic sample loads were applied to the gel. In normal cases, where sample loads of ca. 1 mg of total protein are applied and typically at least 1000 spots are visualised, the singlets will be the minority, rarely exceeding 30% of all spots analysed. The experimental data on the abundance of overlapping spots were in excellent agreement with theoretical data calculated on the basis of the statistical theory of spot overlapping, originally proposed by Davis and further developed by some of the authors. Ways and means for minimizing spot overlap and visualising a greater number of spots in a two-dimensional map are discussed.     

Bootstrap resampling for voxel-wise variance analysis of three-dimensional density maps derived by image analysis of two-dimensional crystals

Difference density maps are commonly used in structural biology for identifying conformational changes in macromolecular complexes. For interpretation of the results, it is essential to estimate the variance or standard deviation of the difference density and the distribution of errors in space. In order to compare three-dimensional density maps of gap junction channels with and without the C-terminal regulatory domain, we developed a bootstrap resampling method for estimation of the voxel-wise standard deviation. The bootstrap approach has been successfully used for estimating the sampling distribution from a limited data set and for estimating the statistical properties of the derived quantities [Efron, B., 1979. Bootstrap methods: another look at the jackknife. Ann. Stat. 7, 1-26]. In our application, the standard deviation map can be estimated by bootstrapping the images. Our results show that, apart from the symmetry axes and small regions bordering the lumen of the extracellular vestibule, difference maps normalized by the mean of the standard deviation map can be used as a good approximation of the t-test map of the gap junction crystals.