Multiblock principal component analysis: an efficient tool for analyzing metabolomics data which contain two influential factors

Principal component analysis (PCA) is probably one of the most used methods for exploratory data analysis. However, it may not be always effective when there are multiple influential factors. In this paper, the use of multiblock PCA for analysing such types of data is demonstrated through a real metabolomics study combined with a series of data simulating two underlying influential factors with different types of interactions based on 2 × 2 experiment designs. The performance of multiblock PCA is compared with those of PCA and also ANOVA-PCA which is another PCA extension developed to solve similar problems. The results demonstrate that multiblock PCA is highly efficient at analysing such types of data which contain multiple influential factors. These models give the most comprehensive view of data compared to the other two methods. The combination of super scores and block scores shows not only the general trends of changing caused by each of the influential factors but also the subtle changes within each combination of the factors and their levels. It is also highly resistant to the addition of ‘irrelevant’ competing information and the first PC remains the most discriminant one which neither of the other two methods was able to do. The reason of such property was demonstrated by employing a 2 × 3 experiment designs. Finally, the validity of the results shown by the multiblock PCA was tested using permutation tests and the results suggested that the inherit risk of over-fitting of this type of approach is low.

     

Regularized projection pursuit for data with a small sample-to-variable ratio

As a systematic and holistic study of metabolites in plants, animals, and human beings, metabolomics has advanced considerably in recent years, due largely to the rapid development of analytical technology and the application of multivariate data analysis methods. Exploratory data analysis, which has played a crucial role in this advance, aims to examine the natural data structure to reveal important information. Principal components analysis (PCA) is probably the most widely used technique for exploratory data analysis, but projection pursuit (PP) is another important method that often outperforms PCA because it is based on distributional rather than variance optimization. Recent algorithmic improvements have made the implementation of PP easier, but, when the sample size is small compared to the number of variables, it is found that PP (with kurtosis as a projection index) fails to gives meaningful information. Mathematically, this involves the ill-posed inverse problem that also occurs for many other multivariate data analysis methods that result in overfitting. In this work, a regularized projection pursuit (RPP) method is proposed to solve this problem and iterative optimization algorithms are developed for both step-wise univariate and multivariate PP. The utility of the algorithms is established using simulated data, which also demonstrates the use of ridge trace plots for the optimization of the ridge parameter. Three experimental data sets in the public domain are also analyzed, including a study on soy bean disease (47 samples × 35 variables), NMR spectral data for glomerulonephritis patients (50 × 200) and metabolomics data from a bovine diet study (39 × 47). In all cases, RPP showed superior class separation compared to PCA or ordinary PP.     

Genetic relationship analysis for avocado cultivars from Venezuelan germplasm bank (INIA-CENIAP) using molecular markers

Avocado has been characterized using morphological and molecular traits, leading to establish three different horticultural groups: Mexican, Guatemalan, and West Indian. Microsatellites have allowed the identification of hybridization and/or backcross processes which have led to crop improvement. Reticulated phylogenies from evolutionary distances among species can also allow to identify hybridization and allopolyploid phenomena among accessions or species, but they were not conclusive to identify genetic kinship between pure and hybrid cultivars nor lineages in avocado. From 13 microsatellite markers, 96 accessions representing 49 cultivars were sampled from the Venezuelan avocado germplasm collection at the INIA-CENIAP bank in Maracay, Venezuela. Data were analyzed considering two groups: only pure cultivars and every sampled cultivar (pure and hybrids). In order to identify influential alleles in each data group, determination coefficients were obtained from PCA scores performed, identifying determination percentage for each allele and contrasting with the scatter plot. Based on the presence/absence character matrix of an allele for each microsatellite marker, reticulograms were obtained using the T-Rex software. Mexican (M) and Guatemalan (G) genotypes can be recognized and molecularly differentiated from WI. Polytomy between pure and hybrid Mexican specimens shows that the collection has three different lineages, at least, from different regions, and also West Indian accessions are represented from two different genetic groups. Genetic consistent cultivars were identified from clustering. Native Guatemalan × West Indian (G × WI) hybrid cultivars are genetically different from foreign G × WI in loci AVD006, AVD022, AVAG22, and AVAG25. This is a valuable tool for identifying alleles associated with Venezuelan avocado materials.     

Identification of genetic loci stratified by diabetic status and microRNA related SNPs influencing kidney function in Korean populations

Chronic kidney disease (CKD) is characterized by a progressive loss of kidney function over a period of months or years. It is estimated that about 7.2 % of adults over the age of 30 have CKD worldwide. Although one of the major risk factors of CKD is family history, the heritability of CKD is not fully understood. It is also known that the diabetic condition is highly influential on the onset of CKD. To understand the genetic bases of CKD that remain unidentified, we performed genetic association analyses for kidney function-related traits such as blood urea nitrogen (BUN) and albumin in subjects stratified by diabetic status. In the discovery stage of the study, we used genome-wide scan data and clinical data in about 8800 subjects from the Korean Association Resource (KARE) project. Health2 study data comprising about 1800 subjects were used for the replication stage. Our two stage association analyses demonstrated that the LOC105374266 locus (rs9820070) showed strong evidence of association with BUN (P = 8.47 × 10^?14) in nondiabetic normal subjects (n = ~4300). To extend our knowledge of the genetic determinants influencing kidney function, we also analyzed the association between kidney function-related traits and microRNA related variants. For this analysis, miRNA related SNPs were selected from KARE and Health2 cohort genotype data. Our study suggests the potential relevance of miRNA to the kidney function (miR-518b for BUN; miR-146a and miR-1295a for albumin) in Korean populations.     

Vascular plant species richness along environmental gradients in a cool temperate to sub-alpine mountainous zone in central Japan

In order to clarify how vegetation types change along the environmental gradients in a cool temperate to sub-alpine mountainous zone and the determinant factors that define plant species richness, we established 360 plots (each 4 × 10 m) within which the vegetation type, species richness, elevation, topographic position index (TPI), slope inclination, and ground light index (GLI) of the natural vegetation were surveyed. Mean elevation, TPI, slope inclination, and GLI differed across vegetation types. Tree species richness was negatively correlated with elevation, whereas fern and herb species richness were positively correlated. Tree species richness was greater in the upper slope area than the lower slope area, whereas fern and herb species richness were greater in the lower slope area. Ferns and trees species richness were smaller in the open canopy, whereas herb species richness was greater in the open canopy. Vegetation types were determined firstly by elevation and secondary by topographic configurations, such as topographic position, and slope inclination. Elevation and topography were the most important factors affecting plant richness, but the most influential variables differed among plant life-form groups. Moreover, the species richness responses to these environmental gradients greatly differed among ferns, herbs, and trees.     

Hendra Virus Spillover is a Bimodal System Driven by Climatic Factors

Understanding environmental factors driving spatiotemporal patterns of disease can improve risk mitigation strategies. Hendra virus (HeV), discovered in Australia in 1994, spills over from bats (Pteropus sp.) to horses and thence to humans. Below latitude ? 22°, almost all spillover events to horses occur during winter, and above this latitude spillover is aseasonal. We generated a statistical model of environmental drivers of HeV spillover per month. The model reproduced the spatiotemporal pattern of spillover risk between 1994 and 2015. The model was generated with an ensemble of methods for presence–absence data (boosted regression trees, random forests and logistic regression). Presences were the locations of horse cases, and absences per spatial unit (2.7 × 2.7 km pixels without spillover) were sampled with the horse census of Queensland and New South Wales. The most influential factors indicate that spillover is associated with both cold-dry and wet conditions. Bimodal responses to several variables suggest spillover involves two systems: one above and one below a latitudinal area close to ? 22°. Northern spillovers are associated with cold-dry and wet conditions, and southern with cold-dry conditions. Biologically, these patterns could be driven by immune or behavioural changes in response to food shortage in bats and horse husbandry. Future research should look for differences in these traits between seasons in the two latitudinal regions. Based on the predicted risk patterns by latitude, we recommend enhanced preventive management for horses from March to November below latitude 22° south.     

The application of MANOVA to analyse <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis> metabolomic data from factorially designed experiments

Metabolomic technologies produce complex multivariate datasets and researchers are faced with the daunting task of extracting information from these data. Principal component analysis (PCA) has been widely applied in the field of metabolomics to reduce data dimensionality and for visualising trends within the complex data. Although PCA is very useful, it cannot handle multi-factorial experimental designs and, often, clear trends of biological interest are not observed when plotting various PC combinations. Even if patterns are observed, PCA provides no measure of their significance. Multivariate analysis of variance (MANOVA) applied to these PCs enables the statistical evaluation of main treatments and, more importantly, their interactions within the experimental design. The power and scope of MANOVA is demonstrated through two different factorially designed metabolomic investigations using Arabidopsis ethylene signalling mutants and their wild-type. One investigation has multiple experimental factors including challenge with the economically important pathogen Botrytis cinerea and also replicate experiments, while the second has different sample preparation methods and one level of replication ‘nested’ within the design. In both investigations there are specific factors of biological interest and there are also factors incorporated within the experimental design, which affect the data. The versatility of MANOVA is displayed by using data from two different metabolomic techniques; profiling using direct injection mass spectroscopy (DIMS) and fingerprinting using fourier transform infra-red (FT-IR) spectroscopy. MANOVA found significant main effects and interactions in both experiments, allowing a more complete and comprehensive interpretation of the variation within each investigation, than with PCA alone. Canonical variate analysis (CVA) was applied to investigate these effects and their biological significance. In conclusion, the application of MANOVA followed by CVA provided extra information than PCA alone and proved to be a valuable statistical addition in the overwhelming task of analysing metabolomic data.     

Reconstructing community relationships: the impact of sampling error, ordination approach, and gradient length

Effectively summarizing complex community relationships is an important feature in studies such as biodiversity, global change, and invasion ecology. The reliability of such community summaries depends on the degree of sampling variability that is present in the data, the structure of the data, and the choice of ordination method, but the relative importance of these factors is not understood. We compared the validity of results from different ordination methods by applying five levels of sampling error to a simulated coenoplane model at two gradient lengths using two types of data (abundance and presence–absence). The multivariate methods we compared were correspondence analysis (CA), detrended correspondence analysis (DCA), non-metric multidimensional scaling (NMDS), principal component analysis (PCA) and principal coordinates analysis (PCoA). Our results showed CA and PCA using presence–absence data were the most successful methods regardless of sampling error and gradient length, closely followed by the other methods using presence–absence data. With abundance data, PCA and CA were the most successful approaches with the short and long gradients, respectively. Approaches based on PCoA and NMDS using abundance data did not perform well regardless of the choice of distance measure used in the analysis. Both of these methods, along with the PCA using abundance data, were strongly affected by the longer gradient, leading to more distorted results.     

Characterisation,applicability and defect analysis for tiles nanostructure of quantum dot cellular automata

Quantum dot cellular automata (QCA) is an emerging technology for nanoscale computing. In this paper, our contribution is to enhance the applicability of 3 × 3 tile nanostructure in QCA. We introduced few novel 3 × 3 active-type tiles, namely triple fan-output tiles or butterfly tile, five-input majority voter (MV) and fault-tolerant 3 × 3 tile-coupled majority–minority voter. We also explored the cascading effect on 3 × 3 tile. Triple fan-out tile is applicable to drive three outputs simultaneously. Five-input MV, which is another active-type tile we proposed, is applicable for designing five-variable or five addressing, advanced computations. In passive-type 3 × 3 tiles, we introduce symmetrical baseline tiles and asymmetrical fully populated fan-in tiles. QCA design was found to be having high error during fabrication of device. We made exhaustive simulation for analysing the defect that can occur during fabrication process. Defects such as extra cell deposition, missing cell deposition and displaced cell deposition for QCA are prone to occur. Fault analyses of the above-mentioned 3 × 3 tiles are performed. We also focused on the effect of extra dot or missing dot deposition, during the chemical synthesis phase.     

Phenazine-1-carboxylic acid production in a chromosomally non-scar triple-deleted mutant Pseudomonas aeruginosa using statistical experimental designs to optimize yield

We constructed a non-scar triple-deleted mutant Pseudomonas aeruginosa to improve phenazine-1-carboxylic acid (PCA) yield and then optimized the culture conditions for PCA production. Using a non-scar deletion strategy, the 5′-untranslated region of the phz1 gene cluster and two genes, phzM and phzS, were knocked out of the P. aeruginosa strain M18 genome. The potential ability for high-yield PCA production in this triple-deleted mutant M18MSU1 was successfully realized by using statistical experimental designs. A 2^5–1 fractional factorial design was used to show that the three culture components of soybean meal, corn steep liquor and ethanol had the most significant effect on PCA production. Using a central composite design, the concentration of the three components was optimized. The maximum PCA production was predicted to be 4,725.1 mg/L. With the optimal medium containing soybean meal 74.25 g/L, corn steep liquor 13.01 g/L and ethanol 21.84 ml/L, a PCA production of 4,771.2 mg/L was obtained in the validation experiments, which was nearly twofold of that before optimization and tenfold of that in the wild-type strain. This non-scar triple-deleted mutant M18MSU1 may be a suitable strain for industrial production of this biologically synthesized fungicide due to its high PCA production, presumed safety, thermal adaptability and cost-effectiveness.     

A new chemical complex can rapidly concentrate lentivirus and significantly enhance gene transduction

In this study, we developed a new purification method using chondroitin sulfate C (CSC) and protamine sulfate (PS) to concentrate lentivirus. To evaluate the efficiency of this new method, we compared it with several previously described purification protocols, including virus concentrated by ultracentrifugation (Ultra), precipitated by polyethylene glycol (PEG), and sedimented by CSC combined with polybrene (PB). After using the different methods to purify and concentrate equivalent amounts of lentivirus supernatant, the virus pellets precipitated by the different methods were resuspended using the equivalent volumes of DMEM. Subsequently, 10 μl of each lentivirus stock carrying EGFP gene was used to transduce two types of cells, human embryonic kidney 293T (HEK293T) cells and mouse mesenchymal stem cells (mMSC). It was obvious that HEK293T and mMSC appeared much intensiver green fluorescence through virus transduction from PS method than from other methods. To quantitate the transduction efficiency of the viruses, we examined virus titer in the cells after transduction using a real-time PCR-based analysis. Accordingly, we verified that PS precipitation could generate virus with a higher titer (4.39 × 10⁸ IU/ml) than PB (2.43 × 10⁸ IU/ml), Ultra (1.16 × 10⁸ IU/ml), and PEG (0.56 × 10⁸ IU/ml) in HEK293T cells. As for HEK293T cells in mMSC, the PS method also generated virus with a higher titer (4.66 × 10⁸ IU/ml) than the Ultra method (2.36 × 10⁸ IU/ml), and a much higher titer than those of the other chemical-based precipitation methods using PB (4.82 × 10⁶ IU/ml) and PEG (8.98 × 10⁴ IU/ml). Furthermore, the HEK293T cells and mMSC transduced by PS(1X)-virus appeared to have higher cell growth ratios, respectively, than the HEK293T cells and mMSC transduced by lentivirus using the other methods. We conclude that our new method for purifying lentivirus is cost-effective, time-saving, and highly efficient, and that lentivirus purification by this means could possibly be used to transduce a variety of cells, including stem cells.     

Understanding ageing effects using complexity analysis of foot–ground clearance during walking

Ageing influences gait patterns which in turn can affect the balance control of human locomotion. Entropy-based regularity and complexity measures have been highly effective in analysing a broad range of physiological signals. Minimum toe clearance (MTC) is an event during the swing phase of the gait cycle and is highly sensitive to the spatial balance control properties of the locomotor system. The aim of this research was to investigate the regularity and complexity of the MTC time series due to healthy ageing and locomotors' disorders. MTC data from 30 healthy young (HY), 27 healthy elderly (HE) and 10 falls risk (FR) elderly subjects with balance problems were analysed. Continuous MTC data were collected and using the first 500 data points, MTC mean, standard deviation (SD) and entropy-based complexity analysis were performed using sample entropy (SampEn) for different window lengths (m) and filtering levels (r). The MTC SampEn values were lower in the FR group compared to the HY and HE groups for all m and r. The HY group had a greater mean SampEn value than both HE and FR reflecting higher complexity in their MTC series. The mean SampEn values of HY and FR groups were found significantly different for m = 2, 4, 5 and r = (0.1–0.9) × SD, (0.3–0.9) × SD and (0.3–0.9) × SD, respectively. They were also significant difference between HE and FR groups for m = 4–5 and r = (0.3–0.7) × SD, but no significant differences were seen between HY and HE groups for any m and r. A significant correlation of SampEn with SD of MTC was revealed for the HY and HE groups only, suggesting that locomotor disorders could significantly change the regularity or the complexity of the MTC series while healthy ageing does not. These results can be usefully applied to the early diagnosis of common gait pathologies.     

Pollen limitation and seed set associated with year-to-year variation in flowering of Gmelina arborea in a natural tropical forest

The year-to-year variations in flowering, pollen and fruit production in ten Gmelina arborea individuals in a natural forest were observed over a period of five years, 2009?2013, and pollinator visits were observed closely over two years, 2011 and 2012. A pollen supplementation experiment was also undertaken in two years (2011 and 2012) of contrasting flowering levels. Considerable year-to-year variations were observed in flower, pollen and fruit production. The observed variation represented a normal sequence of good-year and poor-year cycling which is most parsimoniously attributed to resource allocation. The average level of pollen production per individual tree in good flowering years oscillated between 6.6 and 9.62 × 10⁸, which in the poor flowering years was between 1.92 and 3.07 × 10⁸. The magnitude of pollen limitation across years was highly significant (p < 0.0001). Fruit set through supplemental pollination was 73% and 96% greater than that of the open-pollinated branches in the year 2011 and 2012, respectively. Pollen limitation, irrespective of the arrival of outcross pollen, can reduce annual seed set in predominantly bee-pollinated trees. However, various other factors may cause flower abortion in addition to pollen limitation. The results of this study would be very valuable to the seed orchard managers and the silviculturists to manage the seed production areas (SPAs) of G. arborea. The study ultimately recommends supplemental pollination in seed orchards of G. arborea for better genetic gain and good seed yield.     

Antineoplastic and immunomodulatory effect of polyphenolic components of Achyranthes aspera (PCA) extract on urethane induced lung cancer in vivo

Polyphenolic compounds of Achyranthes aspera (PCA) extract is evaluated for anti-cancerous and cytokine based immunomodulatory effects. The PCA extract contains known components of phenolic acid and flavonoids such as mixture of quinic acid, chlorogenic acid, kaempferol, quercetin and chrysin along with many unknown components. PCA has been orally feed to urethane (ethyl carbamate) primed lung cancerous mice at a dosage of 100 mg/kg body weight for 30 consecutive days. 100 mg powder of A. aspera contains 2.4 mg phenolic acid and 1.1 mg flavonoid (2:1 ratio). Enhanced activities and expression of antioxidant enzymes GST, GR, CAT, SOD, while down regulated expression and activation of LDH enzymes in PCA feed urethane primed lung cancerous tissues as compared to PCA non-feed urethane primed lung cancerous tissues were observed. PCA feed urethane primed lung tissues showed down regulated expression of pro-inflammatory cytokines IL-1β, IL-6 and TNF-α along with TFs, NF-κB and Stat3 while the expression of pro-apoptotic proteins Bax and p53 were enhanced in PCA feed urethane primed lung tissues. FTIR and CD spectroscopy data revealed that PCA resisted the urethane mediated conformational changes of DNA which is evident by the shift in guanine and thymine bands in FTIR from 1,708 to 1,711 cm^?1 and 1,675 to 1,671 cm^?1, respectively in PCA feed urethane primed lung cancerous tissues DNA in comparison to urethane primed lung cancerous tissues DNA. The present study suggests that PCA components have synergistic anti-cancerous and cytokine based immunomodulatory role and DNA conformation restoring effects. However, more research is required to show the effects of each component separately and in combination for effective therapeutic use to cure and prevent lung cancer including other cancers.     

Assessment of association of rs2200733 on chromosome 4q25 with atrial fibrillation and ischemic stroke in a Chinese Han population

Atrial fibrillation (AF) is the most common arrhythmia in the clinical setting and an independent risk factor for stroke. Approximately 10 million Chinese people are affected by AF, but the genetic basis is largely unknown. A recent genome-wide association study in Iceland identified association between SNP rs2200733 on 4q25 and AF; however, many independent replication studies are essential to unequivocally validate this association. To assess the association between rs2200733 and AF as well as that between rs2200733 and ischemic stroke in a mainland Chinese Han population, we carried out case–control association studies with 383 AF patients versus 851 non-AF controls and 811 ischemic stroke patients versus 688 non-stroke controls. Highly significant association was detected between rs2200733 and AF in a Chinese Han population (allelic P = 3.7 × 10^?11 with OR = 1.81; genotypic P = 4.1 × 10^?12 with a dominant model). When the AF cases were divided into lone AF (32.6%) and other types of AF (67.4%), significantly stronger association was found with lone AF (OR = 2.40, P = 1.3 × 10^?9 compared to OR = 1.59, P = 6.2 × 10^?7 for other types of AF; P = 0.02 for two ORs). No significant association was found between rs2200733 and ischemic stroke. Our results suggest that SNP rs2200733 confers a highly significant risk of AF, but not ischemic stroke, in a more representative Chinese Han population in the mainland China.     

Homocysteine induces procoagulant activity of red blood cells via phosphatidylserine exposure and microparticles generation

Increased homocysteine (Hcy) levels in plasma correlate with the risk of thromboic events. Red blood cells (RBCs), the most abundant blood cells in circulation, also play an active role in the process of thrombus formation. However, the effect of Hcy on procoagulant activity (PCA) of RBCs is unclear. In the present study, RBCs from healthy adults were treated with Hcy (8, 20, 80, 200, 800 μmol/L) for 24 h. Phosphatidylserine (PS) exposure of RBCs and red blood cell-derived microparticles (RMPs) release were detected using Alexa Fluor 488-lactadherin. PCA was assessed by coagulation time and purified clotting complexes testes. We found that Hcy treatment dose dependently enhanced PS exposure and consequent PCA of RBCs. Hcy also elevated the formation of procoagulant RMPs, with statistical significance at 800 μmol/L of Hcy. Moreover, 128 nmol/L lactadherin inhibited about 90 % PCA of RBCs and RMPs. Our data suggest that PS exposure and RMPs shedding are key sources for Hcy-induced PCA of RBCs. Lactadherin could be used to modulate the anticoagulant and procoagulant balance in this process.     

Parent Material and Topography Determine Soil Phosphorus Status in the Luquillo Mountains of Puerto Rico

Phosphorus (P) availability in terrestrial ecosystems depends on soil age, climate, parent material, topographic position, and biota, but the relative importance of these drivers has not been assessed. To ask which factor has the strongest influence on long- and short-timescale metrics of P availability, we sampled soils across a full-factorial combination of two parent materials [quartz diorite (QD) and volcaniclastic (VC)], three topographic positions (ridge, slope, and valley), and across 550 m in elevation in 17 sub-watersheds of the Luquillo Mountains, Puerto Rico. VC rocks had double the P content of QD (600 vs. 300 ppm; P < 0.0001), and soil P was similarly approximately 2× higher in VC-derived soils (P < 0.0001). Parent material also explained the most variance in our two other long-timescale metrics of P status: the fraction of recalcitrant P (56% variance explained) and the loss of P relative to parent material (35% variance explained), both of which were higher on VC-derived soils (P < 0.0001 for both). Topographic position explained an additional 10–15% of the variance in these metrics. In contrast, there was no parent material effect on the more labile NaHCO₃- and NaOH-extractable P soil pools, which were approximately 2.5× greater in valleys than on ridges (P < 0.0001). Taken together, these data suggest that the relative importance of different state factors varies depending on the ecosystem property of interest and that parent material and topography can play sub-equal roles in driving differences in ecosystem P status across landscapes.     

Construction of fingerprinting for tea plant (<Emphasis Type="Italic">Camellia sinensis</Emphasis>) accessions using new genomic SSR markers

As one of the most popular non-alcoholic beverage crops, the tea plant (Camellia sinensis) plays an important role in human health and lifestyle. Genetic fingerprinting based on genomic-derived markers in tea, however, is still in the initial stages, which has limited tea germplasm resource utilization and cultivar protection. In the current study, we identified whole genome-based simple sequence repeat (SSR) loci and successfully developed 36 new genomic SSR markers, which are highly polymorphic with average allele number and polymorphic information content (PIC) of 14.9 and 0.862, respectively. A phylogenetic tree for 80 tea plant accessions was subsequently constructed based on their genotypic scores for these 36 markers. The phylogenetic relationships among the 80 accessions are highly consistent with their genetic backgrounds or original places. Noteworthy, robust fingerprinting power was performed, and the overall probability of finding two random individuals sharing identical genotypes across the 36 loci was estimated to be 1.5 × 10^?56. We subsequently identified five SSR markers as a recommended core marker set for fingerprinting the tea plant cultivars or accessions. The combined PI and PIsibs of the marker set were 1.49 × 10^?9 and 2.57 × 10^?3, respectively, which allowed us to fully discriminate all 80 tea plant accessions from one another. The SSR markers developed here will provide a valuable resource for tea plant genetics and genomic studies, as well as breeding programs. The fingerprinting profiles can serve as a database that is essential for the tea industry and commercial breeding, and for tea plant cultivar identification, utilization, and protection.     

Modeling the distribution of wild rabbits (Oryctolagus cuniculus) on a Mediterranean island

The European rabbit (Oryctolagus cuniculus) is a widely distributed mammal with an often contradictory ecological role, imposing the need for population management. Sound management requires an in-depth understanding of the complex species–habitat relationships. In this study, CART analysis was employed to identify the most important environmental and anthropogenic factors affecting the spatial distribution of wild rabbit on Lemnos Island, northeastern Aegean Sea in Greece. On Lemnos, this species is considered an agricultural pest due to its overabundance resulting from the long-term absence of viral diseases, limited predation pressure, and lack of effective management. The study was carried out during the summer of 2008 by surveying rabbit densities in 181 2 × 2-km squares. Seven environmental and 14 anthropogenic variables, measured at two spatial scales, were used as explanatory variables. Soil hardness was the most influential variable, dividing the island into two distinct areas, namely the rabbit-poor areas with hard rocky soils and the rabbit-rich areas where soft soils prevail. In the former, the presence of a sharp relief can lead to complete absence of the species, while a combination of gentle relief, low altitudes, and low presence of arable land can lead to moderate rabbit density. In the latter, human-caused disturbance can reduce the number of rabbits, while a high density of ecotones and streams and a high presence of riparian vegetation can increase population densities to its highest levels observed. Our findings can formulate a scientific basis for the development of an effective management strategy for its population control.     

典范相关分析技术在植被生态信息中的应用研究

典范相关分析是一种检验两组变量间最大相关的多元统计技术。本文运用此技术结合Pearson's相关系数、PCA分析,对植物群落中植物重要值与土壤组分的相关研究表明:典范相关分析能极好地定量解释生态学中两组变量的相关,并能指示出多个因子的复合作用。同时强调,由于典范相关分析技术对原始数据的线性要求,从而有必要对数据进行标准化和预先的PCA分析。