Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.     

Geometric morphometrics in entomology: Basics and applications

The recent expansion of a variety of morphometric tools has brought about a revolution in the comparison of morphology in the context of the size and shape in various fields including entomology. First, an overview of the theoretical issues of geometric morphometrics is presented with a caution about the usage of traditional morphometric measurements. Second, focus is then placed on two broad approaches as tools for geometric morphometrics; that is, the landmark‐based and the outline‐based approaches. A brief outline of the two methodologies is provided with some important cautions. The increasing trend of entomological studies in using the procedures of geometric morphometrics is then summarized. Finally, information is provided on useful toolkits such as computer software as well as codes and packages of the R statistical software that could be used in geometric morphometrics.     

The role of bioinformatics in two-dimensional gel electrophoresis

Over the last two decades, two-dimensional electrophoresis (2-DE) gel has established itself as the de facto approach to separating proteins from cell and tissue samples. Due to the sheer volume of data and its experimental geometric and expression uncertainties, quantitative analysis of these data with image processing and modelling has become an actively pursued research topic. The results of these analyses include accurate protein quantification, isoelectric point and relative molecular mass estimation, and the detection of differential expression between samples run on different gels. Systematic errors such as current leakage and regional expression inhomogeneities are corrected for, followed by each protein spot in the gel being segmented and modelled for quantification. To assess differential expression of protein spots in different samples run on a series of two-dimensional gels, a number of image registration techniques for correcting geometric distortion have been proposed. This paper provides a comprehensive review of the computation techniques used in the analysis of 2-DE gels, together with a discussion of current and future trends in large scale analysis. We examine the pitfalls of existing techniques and highlight some of the key areas that need to be developed in the coming years, especially those related to statistical approaches based on multiple gel runs and image mining techniques through the use of parallel processing based on cluster computing and the grid technology.     

Soil ingestion in children: Outdoor soil or indoor dust?

Soil ingestion estimates may play a prominent role in exposure estimation for risk assessments involving tightly bound soil contaminants such as dioxin, PCBs, and lead in soil. Since contamination is often localized to specific areas, the relative contribution of ingested soil due to outdoor soil and indoor dust may have a large impact on the risk assessment. This article examines data on 64 preschool children over 2 weeks to estimate the relative contribution of ingested soil from outdoor soil and indoor dust. Four principal methodological approaches are developed and presented to form the estimates, and their relative strengths and weaknesses are discussed.

The four approaches differ in their assumptions and their ability to detail differences in ingestion source. Two approaches (i.e., duration correlation method — approach 1 and group tracer ratio method — approach 2) were used that can only estimate the average ingestion source, where averages are calculated over subjects and weeks. Both of these approaches have sufficient limitations to preclude confidence in the resulting estimates.

The final two approaches (approach 3 — individual tracer ratio method and approach 4 — multiple statistical model method) were able to characterize ingestion source for individual subject‐weeks and offered more plausible estimates of soil ingestion. Greater emphasis is placed on approach 3 since it was biologically plausible and conceptually straightforward. Approach 3 indicated that 49.2% ± 29.2% of the residual fecal tracers were estimated to be of soil origin. These findings, which represent the first quantitative differentiation of soil vs. dust ingestion, have considerable application for a variety of environmental settings requiring exposure assessment.     

The cell cycle hypothesis of Alzheimer's disease: suggestions for drug development

The cell cycle of hypothesis of neural dysfunction in chronic neurodegenerative conditions such as Alzheimer's disease (AD) offers a unified approach to understanding both existing and novel strategies for drug development. At the present time, a ligand based approach is a pragmatic solution for identifying new chemical leads on which to base future discovery and optimisation. We have pursued a ligand based approach on the basis of public domain data to identify existing compounds capable of abrogating the cell cycle at the G0-G1 interface. Selected on this basis, irrespective of the tissue under study, we identified several classes of compounds as potential chemical leads. Of these compounds, at least ten have already been shown to be neuroprotective in animal models of acute neurodegeneration. Such compounds could form the basis of a screening exercise after development of suitable screening tools. Progressing of chemical leads through such an approach will be more efficient if future leads display relevant "drug-like" properties. Further, drug development in this arena should take account of the special concerns raised by targeting an elderly population. This will involve accounting for frequent polypharmacy in the aging population, and age-related alterations in physiology.     

PBL与图表相结合的教学法在《基础生物化学》课程教学中的初步实践

针对生物化学课程的特点,以改革当前传统的课堂讲授式教学模式作为突破口,采用基于问题学习（PBL）与图表结合的教学模式在《基础生物化学》中进行教学尝试。初步教学实践表明,通过PBL与图表教学法的互补结合,基本能克服《基础生物化学》教学活动中存在的两类矛盾,使传统的以＂教＂为主的教学模式,转变为以＂学＂与＂教＂相互平衡和促进的教学模式,使学生在掌握所学课程核心内容的同时又能获得学习方法、提高学习兴趣和学习主动性。     

Prospects of a Computational Origin of Life Endeavor

While the last century brought an exquisite understanding of the molecular basis of life, very little is known about the detailed chemical mechanisms that afforded the emergence of life on early earth. There is a broad agreement that the problem lies in the realm of chemistry, and likely resides in the formation and mutual interactions of carbon-based molecules in aqueous medium. Yet, present-day experimental approaches can only capture the synthesis and behavior of a few molecule types at a time. On the other hand, experimental simulations of prebiotic syntheses, as well as chemical analyses of carbonaceous meteorites, suggest that the early prebiotic hydrosphere contained many thousands of different compounds. The present paper explores the idea that given the limitations of test-tube approaches with regards to such a 'random chemistry' scenario, an alternative mode of analysis should be pursued. It is argued that as computational tools for the reconstruction of molecular interactions improve rapidly, it may soon become possible to perform adequate computer-based simulations of prebiotic evolution. We thus propose to launch a computational origin of life endeavor (http://ool.weizmann.ac.il/CORE), involving computer simulations of realistic complex prebiotic chemical networks. In the present paper we provide specific examples, based on a novel algorithmic approach, which constitutes a hybrid of molecular dynamics and stochastic chemistry. As one potential solution for the immense hardware requirements dictated by this approach, we have begun to implement an idle CPU harvesting scheme, under the title ool@home.     

Woodstoich III: Integrating tools of nutritional geometry and ecological stoichiometry to advance nutrient budgeting and the prediction of consumer‐driven nutrient recycling

Within the last two decades, ecological stoichiometry (ES) and nutritional geometry (NG, also known as geometric framework for nutrition) have delivered novel insights into core questions of nutritional ecology. These two nutritionally explicit frameworks differ in the ‘nutrient currency’ used and the focus of their past research; behavioural feeding strategies in NG, mainly investigating terrestrial organisms, and trophic ecology in ES, mainly in aquatic settings. However, both NG and ES have developed in explaining patterns across various scales of biological organization. Integrating specific tools of these frameworks could advance the field of nutritional ecology by unifying theoretical and empirical approaches from the organismal to ecosystem level processes. Toward this integration, we identified 1) nutrient/element budgets as a shared concept of both frameworks that encompass nutrient intake, retention, and release, 2) response surface plots of NG as powerful tools to illustrate processes at the organismal level and 3) the concept of consumer‐driven nutrient recycling (CNR) of ES as a useful tool bridging organism and ecosystem scales. We applied response surface plots to element budget data from an ES study to show how this approach can deliver new insights at the organismal level, e.g. by showing the interplay between egestion and excretion depending simultaneously on the consumed amount of carbon and phosphorus based on variation across individuals. By integrating concepts of ES and NG to model microbial uptake and mineralization of nitrogenous wastes reported in a NG study, we also demonstrate that considering biochemically explicit mineralization rates of organic wastes can improve predictions of CNR by reducing over‐ or underestimation of mineralization depending on the quality of the consumer's diet. Our presented tools and approaches can help to bridge the organismal and ecosystem level, advancing the predictive power of studies in nutritional ecology at multiple ecological scales.     

Novel Genomic Tools and Modern Genetic and Breeding Approaches for Crop Improvement

In recent past, genomic tools especially molecular markers have been extensively used for understanding genome dynamics as well for applied aspects in crop breeding. Several new genomics technologies such as next generation sequencing (NGS), high-throughput marker genotyping, -omics technologies have emerged as powerful tools for understanding genome variation in crop species at DNA, RNA as well as protein level. These technologies promise to provide an insight into the way gene(s) are expressed and regulated in cell and to unveil metabolic pathways involved in trait(s) of interest for breeders not only in model-/major- but even for under-resourced crop species which were once considered “orphan” crops. In parallel, genetic variation for a species present not only in cultivated genepool but even in landraces and wild species can be harnessed by using new genetic approaches such as advanced-backcross QTL (AB-QTL) analysis, introgression libraries (ILs), multi-parent advanced generation intercross (MAGIC) population and association genetics. The gene(s) or genomic regions, responsible for trait(s) of interest, identified either through conventional linkage mapping or above mentioned approaches can be introgressed or pyramided to develop superior genotypes through molecular breeding approaches such as marker-assisted back crossing (MABC), marker assisted recurrent selection (MARS) and genome wide selection (GWS). This article provides an overview on some recent genomic tools and novel genetic and breeding approaches as mentioned above with a final aim of crop improvement.     

Modeling and design optimization of asynchronous flexible assembly systems with statistical process control and repair

This article presents the implementation of hybrid procedures involving the use of analytical performance evaluation techniques, discrete event simulation, and Monte Carlo optimization methods for the stochastic design optimization of asynchronous flexible assembly systems (AFASs) with statistical process control (SPC) and repair loops. AFASs are extremely complex and difficult to analyze in that such systems are subject to starvation and blocking effects, random jam occurrences at workstations, and splitting and merging of the assembly flow due to repair loops. Hence, an integrated approach simultaneously analyzing the interactions between product quality and optimal/near optimal system design is pursued. In the analytical analysis stage, a model based on GI/G/1 queueing network theory is used. In the Monte Carlo optimization stage, two alternative stochastic optimization approaches, namely, heuristic versions of stochastic quasigradient and simulated annealing algorithms, are implemented and compared in terms of their capabilities of solving complex AFAS design problems. The hybrid procedures presented appear to perform reasonably well in designing AFASs to reach a target production rate.     

Multiple alignment by aligning alignments

MOTIVATION: Multiple sequence alignment is a fundamental task in bioinformatics. Current tools typically form an initial alignment by merging subalignments, and then polish this alignment by repeated splitting and merging of subalignments to obtain an improved final alignment. In general this form-and-polish strategy consists of several stages, and a profusion of methods have been tried at every stage. We carefully investigate: (1) how to utilize a new algorithm for aligning alignments that optimally solves the common subproblem of merging subalignments, and (2) what is the best choice of method for each stage to obtain the highest quality alignment. RESULTS: We study six stages in the form-and-polish strategy for multiple alignment: parameter choice, distance estimation, merge-tree construction, sequence-pair weighting, alignment merging, and polishing. For each stage, we consider novel approaches as well as standard ones. Interestingly, the greatest gains in alignment quality come from (i) estimating distances by a new approach using normalized alignment costs, and (ii) polishing by a new approach using 3-cuts. Experiments with a parameter-value oracle suggest large gains in quality may be possible through an input-dependent choice of alignment parameters, and we present a promising approach for building such an oracle. Combining the best approaches to each stage yields a new tool we call Opal that on benchmark alignments matches the quality of the top tools, without employing alignment consistency or hydrophobic gap penalties. AVAILABILITY: Opal, a multiple alignment tool that implements the best methods in our study, is freely available at http://opal.cs.arizona.edu.     

Allometric covariation: a hallmark behavior of plants and leaves

Size is one of the most important axes of variation among plants. As such, plant biologists have long searched for unifying principles that can explain how matter and energy flux and organ partitioning scale with plant size. Several recent models have proposed a universal biophysical basis for numerous scaling phenomena in plants based on vascular network geometry. Here, we review statistical analyses of several large-scale plant datasets that demonstrate that a true hallmark of plant form variability is systematic covariation among traits. This covariation is constrained by allometries that combine and trade off with one another, rather than any single universal allometric scaling exponent for a trait or suite of traits. Further, we show that covariation can be successfully modeled using network approaches that allow for species-specific designs in plants and geometric approaches that constrain relationships among economic traits in leaves. Finally, we report large-scale efforts utilizing semi-automated software tools that quantify physical networks and can inform our attempts to link vascular network structure to plant form and function. Collectively, this work highlights how the linking of morphology, biomass partitioning and the structure of physical distribution networks can improve our empirical and theoretical understanding of important drivers of plant functional diversity.     

Taphonomic implications of orientation of plotted finds from Pinnacle Point 13B (Mossel Bay, Western Cape Province, South Africa)

An understanding of site taphonomy is crucial to stratigraphic and artifact/ecofact interpretation. Numerous geogenic, biogenic, and anthropogenic activities have the potential to move artifacts after deposition and distort the patterning once present in hominid discarded debris. Taphonomy at a Middle Stone Age cave (Pinnacle Point 13B) near Mossel Bay, South Africa is investigated here using artifact orientation data collected during excavation. Two angle measurements (bearing and plunge) were taken for all artifacts with a distinct long axis. The data are analyzed here using both graphical and statistical approaches, and a new graphical approach is presented. Using these measurements it is possible to distinguish between layers and areas of the site that are minimally disturbed and those that have been reworked to varying degrees. Data of this type are still not usually presented in publications of stone age sites. Given the complexities of the taphonomic history of these ancient sites, such data and analyses should become standard practice.     

Getting into Shape: An Empirical Comparison of Traditional Truss-Based Morphometric Methods with a Newer Geometric Method Applied to New World Cichlids

Body shape is a difficult, but important, trait to quantify. Researchers have traditionally used multivariate analysis of several linear measures ('trusses') across the body form to quantify shape. Newer geometric morphometric methods claim to better estimate shape because they analyze the geometry among the locations of all landmarks simultaneously rather than the linear distances between pairs of landmarks. We tested this claim by comparing the results of several traditional morphometric analyses against a newer geometric analysis involving thin-plate splines (TPS), all applied to a common data set of morphologically variable new world cichlids Amphilophus citrinellus and A. zaliosus. The TPS method yielded slightly stronger evidence of morphological differences among forms, although traditional methods also distinguished the two species. Perhaps our most important result was the idiosyncratic interpretation of shape variation among the traditional truss-based methods, whereas the generation of deformation grids using the TPS approach yielded clear and visually interpretable figures. Our results indicate that geometric morphometrics can be a more effective way to analyze and interpret body form, but also that traditional methods can be relied upon to provide statistical evidence of shape differences, although not necessarily accurate information about the nature of variation in shape.     

AnthropMMD: An R package with a graphical user interface for the mean measure of divergence

The mean measure of divergence is a dissimilarity measure between groups of individuals described by dichotomous variables. It is well suited to datasets with many missing values, and it is generally used to compute distance matrices and represent phenograms. Although often used in biological anthropology and archaeozoology, this method suffers from a lack of implementation in common statistical software. A package for the R statistical software, AnthropMMD, is presented here. Offering a dynamic graphical user interface, it is the first one dedicated to Smith's mean measure of divergence. The package also provides facilities for graphical representations and the crucial step of trait selection, so that the entire analysis can be performed through the graphical user interface. Its use is demonstrated using an artificial dataset, and the impact of trait selection is discussed. Finally, AnthropMMD is compared to three other free tools available for calculating the mean measure of divergence, and is proven to be consistent with them.     

Metabolic engineering as an integrating platform for strain development

Integration of the analytical framework and experimental tools of metabolic engineering with emerging technologies such as DNA microarrays and directed evolution stands to dramatically improve the approaches by which strain improvement and biocatalyst design are pursued in the future. Progress in genomics and applied molecular biology, together with increasing emphasis on renewable resource utilization for chemical production, has advanced metabolic engineering to the forefront of biotechnological interest.     

Geometric modeling of functional trileaflet aortic valves: development and clinical applications

The dimensions of the aortic valve components condition its ability to prevent blood from flowing back into the heart. While the theoretical parameters for best trileaflet valve performance have already been established, an effective approach to describe other less optimal, but functional models has been lacking. Our goal was to establish a method to determine by how much the dimensions of the aortic valve components can vary while still maintaining proper function. Measurements were made on silicone rubber casts of human aortic valves to document the range of dimensional variability encountered in normal adult valves. Analytical equations were written to describe a fully three-dimensional geometric model of a trileaflet valve in both the open and closed positions. A complete set of analytical, numerical and graphical tools was developed to explore a range of component dimensions within functional aortic valves. A list of geometric guidelines was established to ensure safe operation of the valve during the cardiac cycle, with practical safety margins. The geometry-based model presented here allows determining quickly if a certain set of valve component dimensions results in a functional valve. This is of great interest to designers of new prosthetic heart valve models, as well as to surgeons involved in valve-sparing surgery.