Comparison of ordinations and classifications of vegetation data

The methodology of comparing the results of multivariate community studies (resemblance matrices, ordinations, hierarchical and nonhierarchical classifications) is reviewed from two viewpoints: basic strategy and measure employed. The basic strategy is determined by 7 choices concerning the type of results, consensus methods or resemblance measures, hypothesis testing or exploratory analysis, lack or presence of reference basis, data set congruence or algorithmic effects, number of factors responsible for differences among results, and the number of properties considered in the comparison. Included is a brief summary of methods applicable to vegetation studies. Examples from a grassland survey demonstrate the utility of comparisons in evaluating the effects of plot size, data type, standardization, taxonomic level and number of species on classifications and ordinations.Abbreviations OUC = Operational Unit of Comparison - PCA = Principal Components Analysis - PCoA = Principal Coordinates Analysis - SSA = Incremental Sum of Squares Agglomeration     

Dermatoglyphic study among sex and other crime convicts

An attempt was made to investigate dermatoglyphic variation between four sex-crimes (SC) and four sex and other crime (SOC) convicts. These were compared with 10 endogamous and 11 penal populations. The results indicate that the two closely related sex crime cases IPC-363 and IPC 366 («kidnap» and «abducting») show wide differences in dermatoglyphic characters. A comparison of sex crimes with sex and other crime cases showed least differences in the case of IPC-363, IPC-363 KC and in IPC 366 and IPC-366 AC but wide differences in IPC-354 («molestation») cases. The dendrograms suggest that the eight sex crime cases cluster together and are different from other endogamous and penal populations. The significant low mean finger ridge count observed in the case of IPC-366 is in agreement with other studies, suggesting a strong association between crime (sex) and dermatoglyphics.     

华东地区黑果蝇自然群体同工酶遗传多态的研究

我们用标准垂直板聚丙烯酰胺凝胶电泳和水平板琼脂糖凝胶电泳技术检测了黑果蝇(D.virilis)在合肥、芜湖、九江、南昌、福州、泉州和常州7个自然群体中Est-α、Est-β、Amy、Acph和α-Gpdh 5个座位的遗传变异,发现Est-α、Est-β和Amy 3个座位是高度多态的,Acph、α-Gpdh两个座位则是单态的。根据这5个座位等位基因的频率,我们计算了群体间的遗传距离。综合何朝珍报道的宁波、杭州、南京和洪泽4个群体的结果和我们的结果,我们作出系统树并发现泉州、福州两群体和其他群体在基因频率的分布和遗传距离方面有显著差异;分析显示这种差异与群体间地理隔离有关。     

Taxonomic discrimination of higher plants by pyrolysis mass spectrometry

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum and has been widely applied to the discrimination of closely related microbial strains. Leaf samples of six species and one variety of higher plants (Rosa multiflora, R. multiflora var. platyphylla, Sedum kamtschaticum, S. takesimense, S. sarmentosum, Hepatica insularis, and H. asiatica) were subjected to PyMS for spectral fingerprinting. Principal component analysis of PyMS data was not able to discriminate these plants in discrete clusters. However, canonical variate analysis of PyMS data separated these plants from one another. A hierarchical dendrogram based on canonical variate analysis was in agreement with the known taxonomy of the plants at the variety level. These results indicate that PyMS is able to discriminate higher plants based on taxonomic classification at the family, genus, species, and variety level.Abbreviations ANNs Artificial neural networks - CVA Canonical variate analysis - GC/MS Gas chromatography/mass spectrometry - PCA Principal component analysis - PyMS Pyrolysis mass spectrometry - UPGMA Unweighted pair group method with arithmetic mean Communicated by I.S. Chung     

Potential natural product discovery from microbes through a diversity-guided computational framework

As the occurrence of natural compounds is related to the spatial distribution and evolution of microorganisms for biological and ecological relevance, the data integration of chemistry, geography, and phylogeny within an analytical framework is needed to make better decisions on sourcing the microbes for drug discovery. Such a framework should help researcher to decide on (a) which microorganisms are capable to produce the structurally diverse-bioactive compounds and (b) where those microbes could be found. Here, we present GIST (Geospatial Integrated Species, sites and bioactive compound relationships Tracking tool), a computational framework that could describe and compare how the chemical and genetic diversity varied among microbes in different areas. GIST mainly exploits the measures of bioactive diversity (BD) and phylogenetic diversity (PD), derived from the branch length of bioactive dendrogram and phylogenetic tree, respectively. Based on BD and PD, our framework could provide guidance and tools for measuring, monitoring, and evaluating of patterns and changes in biodiversity of microorganisms to improve the success rate of drug discovery. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Unraveling the efficiency of RAPD and SSR markers in diversity analysis and population structure estimation in common bean

Increase in food production viz-a-viz quality of food is important to feed the growing human population to attain food as well as nutritional security. The availability of diverse germplasm of any crop is an important genetic resource to mine the genes that may assist in attaining food as well as nutritional security. Here we used 15 RAPD and 23 SSR markers to elucidate diversity among 51 common bean genotypes mostly landraces collected from the Himalayan region of Jammu and Kashmir, India. We observed that both the markers are highly polymorphic. The discriminatory power of these markers was determined using various parameters like; percent polymorphism, PIC, resolving power and marker index. 15 RAPDs produced 171 polymorphic bands, while 23 SSRs produced 268 polymorphic bands. SSRs showed a higher PIC value (0.300) compared to RAPDs (0.243). Further the resolving power of SSRs was 5.241 compared to 3.86 for RAPDs. However, RAPDs showed a higher marker index (2.69) compared to SSRs (1.279) that may be attributed to their higher multiplex ratio. The dendrograms generated with hierarchical UPGMA cluster analysis grouped genotypes into two main clusters with various degrees of sub clustering within the cluster. Here we observed that both the marker systems showed comparable accuracy in grouping genotypes of common bean according to their area of cultivation. The model based STRUCTURE analysis using 15 RAPD and 23 SSR markers identified a population with 3 sub-populations which corresponds to distance based groupings. High level of genetic diversity was observed within the population. These findings have further implications in common bean breeding as well as conservation programs.     

Deteriogenic cyanobacteria on historic buildings in Brazil detected by culture and molecular techniques

There are few modern analyses of the cyanobacterial communities in biofilms on external building surfaces. As the classification of cyanobacteria is rapidly changing, we aimed to identify them on historic buildings in Brazil using both established and molecular techniques. In mature biofilms, cyanobacteria of subsections I and II were generally the major biomass; occasionally filamentous genera of the Scytonemataceae, Microchaetaceae and Rivularaceae were dominant. Filamentous organisms of subsections III and IV were more frequently isolated in culture. PCR products using cyanobacteria-specific 16S rDNA primers were sequenced from morphologically identified organisms. Homologies with deposited sequences were generally low. Phylogenetic analysis showed that many isolates were distant from their nearest neighbours, even though they grouped with their appropriate taxa. The majority of cyanobacterial DNA sequences deposited in data banks are aquatic; our results indicate that cyanobacteria from external walls are an ecologically isolated group.     

Genetic diversity in Indian cucumber based on microsatellite and morphological markers

Genetic variation among 44 cucumber accessions was assessed using morphological and SSR markers. High genetic variability was observed for days to 50% female flowering (37–46 days from sowing), number of fruits per plant (1.4–6.0), individual fruit weight (0.04–0.552 kg) and root length (14.25–32.8 cm). The pair-wise Jaccard similarity coefficient ranged between 0.25 and 0.85 indicating that the accessions represent genetically diverse populations. The allelic diversity of polymorphic markers ranged from 0.001 to 0.9396 with an average of 0.31 based on polymorphic information content. The clustering pattern of SSR markers was not in consonance with the groupings based on quantitative traits. The accession of Indian state i.e.; Madhya Pradesh and Uttar Pradesh were diverged from the accessions of other parts of India. The study provides information for future exploration and collection of cucumber germplasm in India and utilization of diverse germplasm for developing cultivars/hybrids for specific traits.     

Community Structure of Plant-parasitic Nematodes Related to Soil Types in Illinois and Indiana Soybean Fields

Comparisons of plant parasitic nematode populations using a resemblance equation and community ordination showed that community structure tends to be similar on dark-colored, highly productive soybean soils throughout Indiana and Illinois. On lighter-colored soils community structures differed somewhat from those of darker soils and from each other.     

Heterogeneity ratio: a measure of beta-diversity and its use in community classification

Fifteen previously proposed similarity indices are examined for the effects of sample size and/or group size (the number of samples included in a cluster). The three indices ofCλ,NESS, andC′λ are free from effects, but the former two are unsuitable for arithmetic averaging unless all of the sample sizes are equal. Thus clustering usingC′λ is found to be superior to the combination of any other similarity index and the group-average strategy. Unfortunately none of these measures have the desirable property of measuring the difference in component species among samples independent of the alpha-diversity. A new index of similarity (HR) is developed based on the assumption that community from which samples are taken is described by a logseries distribution. This new index measures the beta-diversity among samples without the influence of sample size and group size, and has the advantage that the significance of fusing samples can statistically be tested. An example clustering withHR is shown and compared with those obtained by other clustering strategies.