鸡枞的驯化栽培现状

本文论述了当前鸡枞菌驯化栽培的两种模式即:以培养鸡枞菌为重心的腐生菌模式、以扩繁鸡枞菌共生白蚁为重心的原生态模式,并对其驯化栽培过程中所面临的问题及其可能的解决方案进行了阐述。     

Log-linear model-based multifactor dimensionality reduction method to detect gene gene interactions

MOTIVATION: The identification and characterization of susceptibility genes that influence the risk of common and complex diseases remains a statistical and computational challenge in genetic association studies. This is partly because the effect of any single genetic variant for a common and complex disease may be dependent on other genetic variants (gene-gene interaction) and environmental factors (gene-environment interaction). To address this problem, the multifactor dimensionality reduction (MDR) method has been proposed by Ritchie et al. to detect gene-gene interactions or gene-environment interactions. The MDR method identifies polymorphism combinations associated with the common and complex multifactorial diseases by collapsing high-dimensional genetic factors into a single dimension. That is, the MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups based on a comparison of the ratios of the numbers of cases and controls. When a high-order interaction model is considered with multi-dimensional factors, however, there may be many sparse or empty cells in the contingency tables. The MDR method cannot classify an empty cell as high risk or low risk and leaves it as undetermined. RESULTS: In this article, we propose the log-linear model-based multifactor dimensionality reduction (LM MDR) method to improve the MDR in classifying sparse or empty cells. The LM MDR method estimates frequencies for empty cells from a parsimonious log-linear model so that they can be assigned to high-and low-risk groups. In addition, LM MDR includes MDR as a special case when the saturated log-linear model is fitted. Simulation studies show that the LM MDR method has greater power and smaller error rates than the MDR method. The LM MDR method is also compared with the MDR method using as an example sporadic Alzheimer's disease.     

Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions

MOTIVATION: The identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases is a challenging task in genetic association studies. The multifactor dimensionality reduction (MDR) method has been proposed and implemented by Ritchie et al. (2001) to identify the combinations of multilocus genotypes and discrete environmental factors that are associated with a particular disease. However, the original MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups in an ad hoc manner based on a simple comparison of the ratios of the number of cases and controls. Hence, the MDR approach is prone to false positive and negative errors when the ratio of the number of cases and controls in a combination of genotypes is similar to that in the entire data, or when both the number of cases and controls is small. Hence, we propose the odds ratio based multifactor dimensionality reduction (OR MDR) method that uses the odds ratio as a new quantitative measure of disease risk. RESULTS: While the original MDR method provides a simple binary measure of risk, the OR MDR method provides not only the odds ratio as a quantitative measure of risk but also the ordering of the multilocus combinations from the highest risk to lowest risk groups. Furthermore, the OR MDR method provides a confidence interval for the odds ratio for each multilocus combination, which is extremely informative in judging its importance as a risk factor. The proposed OR MDR method is illustrated using the dataset obtained from the CDC Chronic Fatigue Syndrome Research Group. AVAILABILITY: The program written in R is available.     

Molecular systematics and biogeography of Crawfurdia, Metagentiana and Tripterospermum (Gentianaceae) based on nuclear ribosomal and plastid DNA sequences

BACKGROUND AND AIMS: The systematic position of the genus Metagentiana and its phylogenetic relationships with Crawfurdia, Gentiana and Tripterospermum have not been explicitly addressed. These four genera belong to one of two subtribes (Gentianinae) of Gentianeae. The aim of this paper is to examine the systematic position of Crawfurdia, Metagentiana and Tripterospermum and to clarify their phylogenetic affinities more clearly using ITS and trnL intron sequences. METHODS: Nucleotide sequences from the internal transcribed spacers (ITS) of nuclear ribosomal DNA and the plastid DNA trnL (UAA) intron were analysed phylogenetically. Ten of fourteen Metagentiana species were sampled, together with 40 species of other genera in the subtribe Gentianinae. KEY RESULTS: The data support several previously published conclusions relating to the separation of Metagentiana from Gentiana and its closer relationships to Crawfurdia and Tripterospermum based on studies of gross morphology, floral anatomy, chromosomes, palynology, embryology and previous molecular data. The molecular clock hypothesis for the tested sequences in subtribe Gentianinae was not supported by the data (P < 0.05), so the clock-independent non-parametric rate smoothing method was used to estimate divergence time. This indicates that the separation of Crawfurdia, Metagentiana and Tripterospermum from Gentiana occurred about 11.4-21.4 Mya (million years ago), and the current species of these three genera diverged at times ranging from 0.4 to 6.2 Mya. CONCLUSIONS: The molecular analyses revealed that Crawfurdia, Metagentiana and Tripterospermum do not merit status as three separate genera, because sampled species of Crawfurdia and Tripterospermum are embedded within Metagentiana. The speciation and rapid radiation of these three genera is likely to have occurred in western China as a result of upthrust of the Himalayas during the late Miocene and the Pleistocene.     

The conserved core domains of annexins A1, A2, A5, and B12 can be divided into two groups with different Ca2+-dependent membrane-binding properties

The hallmark of the annexin super family of proteins is Ca(2+)-dependent binding to phospholipid bilayers, a property that resides in the conserved core domain of these proteins. Despite the structural similarity between the core domains, studies reported herein showed that annexins A1, A2, A5, and B12 could be divided into two groups with distinctively different Ca(2+)-dependent membrane-binding properties. The division correlates with the ability of the annexins to form Ca(2+)-dependent membrane-bound trimers. Site-directed spin-labeling and Forster resonance energy transfer experimental approaches confirmed the well-known ability of annexins A5 and B12 to form trimers, but neither method detected self-association of annexin A1 or A2 on bilayers. Studies of chimeras in which the N-terminal and core domains of annexins A2 and A5 were swapped showed that trimer formation was mediated by the core domain. The trimer-forming annexin A5 and B12 group had the following Ca(2+)-dependent membrane-binding properties: (1) high Ca(2+) stoichiometry for membrane binding ( approximately 12 mol of Ca(2+)/mol of protein); (2) binding to membranes was very exothermic (> -60 kcal/ mol of protein); and (3) binding to bilayers that were in the liquid-crystal phase but not to bilayers in the gel phase. In contrast, the nontrimer-forming annexin A1 and A2 group had the following Ca(2+)-dependent membrane-binding properties: (1) lower Ca(2+) stoichiometry for membrane binding (相似文献