Mapping shape quantitative trait loci using a radius-centroid-contour model

As the consequence of complex interactions between different parts of an organ, shape can be used as a predictor of structural-functional relationships implicated in changing environments. Despite such importance, however, it is no surprise that little is known about the genetic detail involved in shape variation, because no approach is currently available for mapping quantitative trait loci (QTLs) that control shape. Here, we address this problem by developing a statistical model that integrates the principle of shape analysis into a mixture-model-based likelihood formulated for QTL mapping. One state-of-the-art approach for shape analysis is to identify and analyze the polar coordinates of anatomical landmarks on a shape measured in terms of radii from the centroid to the contour at regular intervals. A procrustes analysis is used to align shapes to filter out position, scale and rotation effects on shape variation. To the end, the accurate and quantitative representation of a shape is produced with aligned radius-centroid-contour (RCC) curves, that is, a function of radial angle at the centroid. The high dimensionality of the RCC data, crucial for a comprehensive description of the geometric feature of a shape, is reduced by principal component (PC) analysis, and the resulting PC axes are treated as phenotypic traits, allowing specific QTLs for global and local shape variability to be mapped, respectively. The usefulness and utilization of the new model for shape mapping in practice are validated by analyzing a mapping data collected from a natural population of poplar, Populus szechuanica var tibetica, and identifying several QTLs for leaf shape in this species. The model provides a powerful tool to compute which genes determine biological shape in plants, animals and humans.

Systems mapping: how to map genes for biomass allocation toward an ideotype

The recent availability of high-throughput genetic and genomic data allows the genetic architecture of complex traits to be systematically mapped. The application of these genetic results to design and breed new crop types can be made possible through systems mapping. Systems mapping is a computational model that dissects a complex phenotype into its underlying components, coordinates different components in terms of biological laws through mathematical equations and maps specific genes that mediate each component and its connection with other components. Here, we present a new direction of systems mapping by integrating this tool with carbon economy. With an optimal spatial distribution of carbon fluxes between sources and sinks, plants tend to maximize whole-plant growth and competitive ability under limited availability of resources. We argue that such an economical strategy for plant growth and development, once integrated with systems mapping, will not only provide mechanistic insights into plant biology, but also help to spark a renaissance of interest in ideotype breeding in crops and trees.

Extracellular matrix metalloproteinase inducer is associated with severity of brain oedema following experimental subarachnoid haemorrhage in rats

OBJECTIVE

Brain oedema is a major cause of clinical deterioration and death following brain trauma; cellular mechanisms involved in its development remain elusive. This study investigated the role of extracellular matrix metalloproteinase inducer (EMMPRIN) in brain oedema.

METHODS

The monofilament puncture model was used to induce subarachnoid haemorrhage. Adult male Sprague-Dawley rats were divided into five groups (n = 20 per group): sham-operated, sacrificed immediately after surgery (sham group); sacrificed 12, 24 or 72 h after subarachnoid haemorrhage induction (SAH-12, SAH-24 and SAH-72 groups, respectively); treated with EMMPRIN inhibitor immediately after subarachnoid haemorrhage, sacrificed at 24 h (SAH-inhibition group). Mean brain water content, and EMMPRIN mRNA and protein levels, were determined.

RESULTS

Compared with the sham group, mean brain water content, EMMPRIN mRNA and protein levels in the SAH-12, SAH-24 and SAH-72 groups increased rapidly and significantly (maximal at 24 h). EMMPRIN inhibition significantly reduced mean brain water content and EMMPRIN mRNA and protein levels in the SAH-inhibition group, compared with the SAH-24 group.

CONCLUSIONS

EMMPRIN upregulation may be important in the formation of brain oedema; inhibition of EMMPRIN activity may provide a potential approach to reduce oedema after subarachnoid haemorrhage.

First Report of Leaf Spot Caused by Alternaria porri on Velvet Bean (Mucuna pruriens) in China

Mucuna pruriens is a tropical legume known as velvet bean. It has many traditional and medicinal usages in treating Parkinson's disease (1), abdominal pain, cholera, infertility, scorpion bites, diabetes (3) and is found in tropical Africa, India, the Caribbean and China. During the fall of 2011, the velvet bean plants in Longan County, Guangxi, China, were damaged by a leaf disease previously unreported in China. Field inspections revealed disease incidences as high as 80%. Symptoms consisted of large spots developing between the leaf veins that ranged in length from 1 to 3 cm. Spots were dark brown, generally rectangular, and were visible from both sides of the leaf. Lots of black mycelia and conidia were found on the backs of the lesions. Lesions typically expanded and affected the entire leaf, resulting in leaves withered and killed. An Alternaria sp. having conidia with prominent beaks and spores produced singly was consistently observed on and isolated from symptomatic leaf tissue. The conidia body was brown, ovoid, obclavate, muriform, and septate, with transverse and longitudinal septa that varied from 6 to 9 and 0 to 2, respectively, and its dimensions varied from 60 to 120 × 15 to 20 μm. The beaks were 10 to 70 × 3 to 6 μm and were filamentous, slender, and unbranched. Pure culture of the fungus was made from a single spore. DNA was extracted and used in an internal transcribed spacer (ITS) PCR used ITS1 and ITS4 primers. The PCR products were purified and sequenced. The sequences were used in BLAST searches to interrogate the GenBank for sequence similarity. High sequence similarity of 100% was obtained with Alternaria porri isolate AP-18. Based on the morphological and molecular characterization, the isolate was identified as A. porri (Ellis) Ciferri (GenBank Accession No. JX556683) (2). The pathogenicity of five isolates was investigated to demonstrate Koch's postulates. Forty 8-week-old seedlings of M. pruriens, without wounding on their leaves, were sprayed with the spore suspension (10⁵ spores per ml), prepared by using 10-day-old cultures of the isolates grown on potato dextrose agar at 28°C in the dark. Every plant was sprayed with 4 ml of spore suspension. The inoculated plants were incubated in a humid chamber for 48 h and then maintained in a greenhouse. After 5 to 7 days, leaf spots similar to those observed in the field developed on all inoculated plants. The pathogen was reisolated and identified as A. porri. Control plants sprayed with distilled water remained symptomless. The inoculation test was repeated and results were the same. Because A. porri was reported to infect plants of Allium spp and cause purple blotch, we also inoculated this isolate to small onion plants, and the symptoms of purple blotch appeared after 13 days at 25 to 28°C in a greenhouse. To our knowledge, this is the first report of leaf spot caused by A. porri on velvet bean in China. References: (1) R. Katzenschlager et al. J. Neurol. Neurosurg Psychiatry. 75:1672, 2004. (2) S. T. Koike and D. H. Henderson. Plant Dis. 82:710, 1998. (3) S. O. Majekodunmi et al. Asian Pac. J. Trop. Med. 4:632, 2011.

Dynamic semiparametric Bayesian models for genetic mapping of complex trait with irregular longitudinal data

Many phenomena of fundamental importance to biology and biomedicine arise as a dynamic curve, such as organ growth and HIV dynamics. The genetic mapping of these traits is challenged by longitudinal variables measured at irregular and possibly subject-specific time points, in which case nonnegative definiteness of the estimated covariance matrix needs to be guaranteed. We present a semiparametric approach for genetic mapping within the mixture-model setting by jointly modeling mean and covariance structures for irregular longitudinal data. Penalized spline is used to model the mean functions of individual quantitative trait locus (QTL) genotypes as latent variables, whereas an extended generalized linear model is used to approximate the covariance matrix. The parameters for modeling the mean-covariances are estimated by MCMC, using the Gibbs sampler and the Metropolis-Hastings algorithm. We derive the full conditional distributions for the mean and covariance parameters and compute Bayes factors to test the hypothesis about the existence of significant QTLs. We used the model to screen the existence of specific QTLs for age-specific change of body mass index with a sparse longitudinal data set. The new model provides powerful means for broadening the application of genetic mapping to reveal the genetic control of dynamic traits.

Germline transformation of the diamondback moth, Plutella xylostella L., using the piggyBac transposable element

The diamondback moth, Plutella xylostella, is one of the most economically important agricultural pests. The larvae of this moth cause damage by feeding on the foliage of cruciferous vegetables such as cabbage, broccoli, cauliflower and rapeseed. Control generally comprises chemical treatment; however, the diamondback moth is renowned for rapid development of resistance to pesticides. Other methods, such as biological control, have not been able to provide adequate protection. Germline transformation of pest insects has become available in recent years as an enabling technology for new genetics-based control methods, such as the Release of Insects carrying a Dominant Lethal (RIDL(®) ). In the present study, we report the first transformation of the diamondback moth, using the piggyBac transposable element, by embryo microinjection. In generating transgenic strains using four different constructs, the function of three regulatory sequences in this moth was demonstrated in driving expression of fluorescent proteins. The transformation rates achieved, 0.48-0.68%, are relatively low compared with those described in other Lepidoptera, but not prohibitive, and are likely to increase with experience. We anticipate that germline transformation of the diamondback moth will permit the development of RIDL strains for use against this pest and facilitate the wider use of this species as a model organism for basic studies.

Genetic mapping of complex traits by minimizing integrated square errors

BACKGROUND

Genetic mapping has been used as a tool to study the genetic architecture of complex traits by localizing their underlying quantitative trait loci (QTLs). Statistical methods for genetic mapping rely on a key assumption, that is, traits obey a parametric distribution. However, in practice real data may not perfectly follow the specified distribution.

RESULTS

Here, we derive a robust statistical approach for QTL mapping that accommodates a certain degree of misspecification of the true model by incorporating integrated square errors into the genetic mapping framework. A hypothesis testing is formulated by defining a new test statistics--energy difference.

CONCLUSIONS

Simulation studies were performed to investigate the statistical properties of this approach and compare these properties with those from traditional maximum likelihood and non-parametric QTL mapping approaches. Lastly, analyses of real examples were conducted to demonstrate the usefulness and utilization of the new approach in a practical genetic setting.

Statistical models for genetic mapping in polyploids: challenges and opportunities

Statistical methods for genetic mapping have well been developed for diploid species but are lagging in the more complex polyploids. The genetic mapping of polyploids, where genome number is higher than two, is complicated by uncertainty about the genotype-phenotype correspondence, inconsistent meiotic mechanisms, heterozygous genome structures, and increased allelic (action) and nonallelic (interaction) combinations. According to their meiotic configurations, polyploids can be classified as bivalent polyploids, in which only two chromosomes pair during meiosis at a time, and multivalent polyploids, where multiple chromosomes pair simultaneously. For some polyploids, these two types of pairing occur at the same time, leading to a mixed category. This chapter reviews several challenges due to the complexities of linkage analysis in polyploids and describes statistical models and algorithms that have been developed for linkage mapping based on their distinct meiotic characteristics. We discuss several issues that should be addressed to better understand the genome structure and organization of polyploids and the genetic architecture of complex traits for this unique group of plants.

Genome-wide association studies for bivariate sparse longitudinal data

OBJECTIVE

Longitudinal measurements with bivariate response have been analyzed by several authors using two separate models for each response. However, for most of the biological or medical experiments, the two responses are highly correlated and hence a separate model for each response might not be a desirable way to analyze such data. A single model considering a bivariate response provides a more powerful inference as the correlation between the responses is modeled appropriately. In this article, we propose a dynamic statistical model to detect the genes controlling human blood pressure (systolic and diastolic).

METHODS

By modeling the mean function with orthogonal Legendre polynomials and the covariance matrix with a stationary parametric structure, we incorporate the statistical ideas in functional genome-wide association studies to detect SNPs which have significant control on human blood pressure. The traditional false discovery rate is used for multiple comparisons.

RESULTS

We analyze the data from the Framingham Heart Study to detect such SNPs by appropriately considering gender-gene interaction. We detect 8 SNPs for males and 7 for females which are most significant in controlling blood pressure. The genotype-specific mean curves and additive and dominant effects over time are shown for each significant SNP for both genders. Simulation studies are performed to examine the statistical properties of our model. The current model will be extremely useful in detecting genes controlling different traits and diseases for humans or non-human subjects.

A mathematical framework for functional mapping of complex phenotypes using delay differential equations

All biological phenomena occurring at different levels of organization from cells to organisms can be modeled as a dynamic system, in which the underlying components interact dynamically to comprehend its biological function. Such a systems modeling approach facilitates the use of biochemically and biophysically detailed mathematical models to describe and quantify "living cells," leading to an in-depth and precise understanding of the behavior, development and function of a biological system. Here, we illustrate how this approach can be used to map genes or quantitative trait loci (QTLs) that control a complex trait using the example of the circadian rhythm system which has been at the forefront of analytical mathematical modeling for many years. We integrate a system of biologically meaningful delay differential equations (DDEs) into functional mapping, a statistical model designed to map dynamic QTLs involved in biological processes. The DDEs model the ability of circadian rhythm to generate autonomously sustained oscillations with a period close to 24h, in terms of time-varying mRNA and protein abundances. By incorporating the Runge-Kutta fourth order algorithm within the likelihood-based context of functional mapping, we estimated the genetic parameters that define the periodic pattern of QTL effects on time-varying mRNA and protein abundances and their dynamic association as well as the linkage disequilibrium of the QTL and a marker. We prove theorems about how to choose appropriate parameters to guarantee periodic oscillations. We further used simulation studies to investigate how a QTL influences the period and the amplitude of circadian oscillations through changing model parameters. The model provides a quantitative framework for assessing the interplay between genetic effects of QTLs and rhythmic responses.

Cerium (IV) oxide nanotubes prepared by low temperature deposition at normal pressure

This paper reports the synthesis of cerium dioxide nanotubes (CeNTs) by electroless deposition using ion-track-etched polycarbonate templates. To achieve nanotubes with thin walls and small surface roughness the tubes were generated by a several-step-containing procedure under aqueous conditions. The approach reported below will process open end nanotubes with well-defined outer diameter and wall thickness.

Em algorithm for mapping quantitative trait Loci in multivalent tetraploids

Multivalent tetraploids that include many plant species, such as potato, sugarcane, and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus (QTL) mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such as double reduction. We develop a statistical method for mapping multivalent tetraploid QTLs by considering these cytogenetic properties. This method is built in the mixture model-based framework and implemented with the EM algorithm. The method allows the simultaneous estimation of QTL positions, QTL effects, the chromosomal pairing factor, and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We used simulated data to examine the statistical properties of the method and validate its utilization. The new method and its software will provide a useful tool for QTL mapping in multivalent tetraploids that undergo double reduction.

A dynamic model for functional mapping of biological rhythms

Functional mapping is a statistical method for mapping quantitative trait loci (QTLs) that regulate the dynamic pattern of a biological trait. This method integrates mathematical aspects of biological complexity into a mixture model for genetic mapping and tests the genetic effects of QTLs by comparing genotype-specific curve parameters. As a way of quantitatively specifying the dynamic behavior of a system, differential equations have proven to be powerful for modeling and unraveling the biochemical, molecular, and cellular mechanisms of a biological process, such as biological rhythms. The equipment of functional mapping with biologically meaningful differential equations provides new insights into the genetic control of any dynamic processes. We formulate a new functional mapping framework for a dynamic biological rhythm by incorporating a group of ordinary differential equations (ODE). The Runge-Kutta fourth order algorithm was implemented to estimate the parameters that define the system of ODE. The new model will find its implications for understanding the interplay between gene interactions and developmental pathways in complex biological rhythms.

The Bayesian lasso for genome-wide association studies

MOTIVATION

Despite their success in identifying genes that affect complex disease or traits, current genome-wide association studies (GWASs) based on a single SNP analysis are too simple to elucidate a comprehensive picture of the genetic architecture of phenotypes. A simultaneous analysis of a large number of SNPs, although statistically challenging, especially with a small number of samples, is crucial for genetic modeling.

METHOD

We propose a two-stage procedure for multi-SNP modeling and analysis in GWASs, by first producing a 'preconditioned' response variable using a supervised principle component analysis and then formulating Bayesian lasso to select a subset of significant SNPs. The Bayesian lasso is implemented with a hierarchical model, in which scale mixtures of normal are used as prior distributions for the genetic effects and exponential priors are considered for their variances, and then solved by using the Markov chain Monte Carlo (MCMC) algorithm. Our approach obviates the choice of the lasso parameter by imposing a diffuse hyperprior on it and estimating it along with other parameters and is particularly powerful for selecting the most relevant SNPs for GWASs, where the number of predictors exceeds the number of observations.

RESULTS

The new approach was examined through a simulation study. By using the approach to analyze a real dataset from the Framingham Heart Study, we detected several significant genes that are associated with body mass index (BMI). Our findings support the previous results about BMI-related SNPs and, meanwhile, gain new insights into the genetic control of this trait.

AVAILABILITY

The computer code for the approach developed is available at Penn State Center for Statistical Genetics web site, http://statgen.psu.edu.

[Comparative research on pharmacognostic characteristics and microscopic characteristics of Radix Paeoniae Rubra from different areas]

OBJECTIVE

To compare pharmacognostic characteristics and microscopic characteristics of Radix Paeoniae Rubra (chishao) from different areas.

METHOD

Pharmacognostic characteristics and microscopic characteristics of Radix Paeoniae Rubra were compared by microscope count methods.

RESULT

Chishao in duolun was more straighter and longer, cortex with a set of closely spaced rill, peel off easily, pink section, etc. The wild chishao were different from the cultivated chishao on pharmacognostic characteristics and microscopic characteristics, such as appearance shape, smell, vessel arrangement, and number of crystal and starch in unit area.

CONCLUSION

Chishao in duolun were different form others, appearance shape, wood fiber, difference of appearance shape, vessel arrangement, and number of crystal and starch in unit area can be used as identificatin feature of the wild chishao and the cultivated chishao.

A statistical model for mapping morphological shape

BACKGROUND

Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine.

RESULTS

We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs) that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model.

CONCLUSION

By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.

Accelerating X-ray fluorescence computed tomography

This paper presents new approaches to accelerating X-ray fluorescence tomography (XFCT) that are grounded in both novel image acquisition strategies that improve the quality of the data acquired and in image reconstruction strategies that reduce the amount of data acquired. First, we introduce an alternative imaging scheme that uses an emission tomography (ET) system to collect the fluorescence photons representing an entire 2D slice or volumetric projection of the object at one time. Preliminary results indicate that this could achieve a ten to hundredfold improvement in imaging speed. Secondly, novel image reconstruction algorithms are introduced that allow for improved quantitative accuracy as well as for imaging of regions of interest, which will lead to further reduction in data-acquisition time.

Serological surveillance of influenza A virus infection in swine populations in Fujian province, China: no evidence of naturally occurring H5N1 infection in pigs

Several highly pathogenic H5N1 avian influenza viruses were isolated from swine populations in Fujian Province, China, since 2001. Because it is thought that H5N1 infection in pigs might result in virus adaptation to humans, we surveyed swine populations in Fujian Province in 2004 and 2007 for serological evidence of the infection. Twenty-five pig farms covering all nine administrative districts of Fujian Province were sampled and a total of 1407 serum specimens were collected. The haemagglutination inhibition (HI) tests revealed no evidence of H5 infection and only a few cases of H9 infection. The negative results for H5 infection were further verified by micro-neutralization tests. By contrast, H1 influenza virus infections were prevalent in swine in both surveys according to the results of enzyme-linked immunosorbent assay (ELISA). The H3 infection rate was reduced dramatically in 2007 compared with 2004, when examined by HI and ELISA. In summary, the results imply that the swine populations in Fujian Province had not been affected greatly by the H5N1 avian influenza virus, given that there is no serological evidence that H5N1 influenza virus has infected the pig populations. The reported isolates represent only sporadic cases.

[Difference of shapes and propertiesand microscopic frameworks between wild and cultivated Radix Saposhnikovia]

OBJECTIVE

To find the difference of the shapes and properties and the microscopic frameworks between wild and cultivated Radix Saposhnikovia.

METHOD

The shapes and properties, the characters of transverse section, the powder and disintegrated tissue of roots of medical materials were compared by microscopic measuring.

RESULT

Wild Radix Saposhnikovia had a long conical or cylindrical root, and fewer root branches. It showed a close annulus grain on top root, cortical section of root in light brown colour, many brown oil spots and possessed typical odor, While cultivated Radix Saposhnikovia had many root branches, and showed less annulus grain on top root, cortical section of root in light yellow brown colour, less brown oil spots and possessed light odor. The difference of microscopic histological structure was that wild Radix Saposhnikovia had phloem transverse section of root with many rotundity oil tube lining up 10-22 rings, xylem vessel with radiate rank, and indistinct annual ring. While cultivated Radix Saposhnikovia had phloem transverse section of root with oil tube lining up 10-11 rings and xylem vessel with distinct annual ring.

CONCLUSION

There exists several differences between wild and cultivated Radix Saposhnikovia in shapes and properties and differences of microscopic frameworks. The main characteristics are the differences of shapes and numbers of oil tube of phloem transverse section of root. The cultivated Radix Saposhnikovia of 1-4 years can be recognized by annual rings of xylem vessel.