Binary Data Matrix Research Articles

Msap: a tool for the statistical analysis of methylation‐sensitive amplified polymorphism data

In this study msap, an R package which analyses methylation-sensitive amplified polymorphism (MSAP or MS-AFLP) data is presented. The program provides a deep analysis of epigenetic variation starting from a binary data matrix indicating the banding pattern between the isoesquizomeric endonucleases HpaII and MspI, with differential sensitivity to cytosine methylation. After comparing the restriction fragments, the program determines if each fragment is susceptible to methylation (representative of epigenetic variation) or if there is no evidence of methylation (representative of genetic variation). The package provides, in a user-friendly command line interface, a pipeline of different analyses of the variation (genetic and epigenetic) among user-defined groups of samples, as well as the classification of the methylation occurrences in those groups. Statistical testing provides support to the analyses. A comprehensive report of the analyses and several useful plots could help researchers to assess the epigenetic and genetic variation in their MSAP experiments. msap is downloadable from CRAN (http://cran.r-project.org/) and its own webpage (http://msap.r-forge.R-project.org/). The package is intended to be easy to use even for those people unfamiliar with the R command line environment. Advanced users may take advantage of the available source code to adapt msap to more complex analyses.

Evaluation of Pulasan (Nephelium ramboutan-ake) Genetic Diversity in Bogor, West Java, Using Microsatellite Markers

Pulasan (Nephelium ramboutan-ake (Labill.) Leenh) fruit is highly similar to rambutan rapiah (Nephelium lappaceum) fruit with ovate shape, sweet and sour fresh taste, but it has a thick rind. The diversity of pulasan is little informed including in Bogor. The objective of this study was to analyze the genetic diversity of pulasan from Bogor revealed by microsatellite marker. The DNA of 63 individuals from 10 populations of pulasan were extracted using CTAB method and amplified using two primer sets, LMLY6 (GA)9(CA)2(GA)4 dan LMLY12 (CT)11. DNA amplification product was visualized and arranged in a matrix of binary data then analyzed the value of the number of different alleles (Na), the number of effective alleles (Ne), Shannon information index (I), heterozygosity (He), and the percentage of polymorphism (PLP). The results of the analysis showed the highest genetic diversity was found in North Bogor (He=0.313). The genetic diversity within a population (61%) was higher than that among populations (39%). A dendrogram was constructed using the Unweighted Pair Group Method with arithmetic Mean (UPGMA). The similarity index ranged from 52 to 100% that means there are close relationships among individuals. Cluster analyses grouped some individuals originated from different locations in the same group. The levels of heterozygosity within a population was determined by the history of each individual in a population.

Molecular genetic diversity analysis in emmer wheat (Triticum dicoccon Schrank) from India

Emmer wheat (Triticum dicoccon Schrank) is still largely cultivated in India, and highly appreciated for the preparation of traditional dishes. Moreover, its nutritional characteristics could justify a development of its cultivation. The perspective of genetic improvement however requires a good knowledge of the genetic diversity existing within the eco-geographic group of Indian emmer wheats. A set of 48 emmer wheat accessions from India including 28 from a local collection and 20 Indian accessions obtained from CIMMYT, Mexico, was assessed for genetic variability using 47 microsatellite (SSR) markers, distributed over all the 14 chromosomes. The number of alleles per locus ranged from 2 to 9, with an average of 3.87 alleles per locus. A total of 201 alleles were detected at 52 loci with average polymorphic information content of 0.35 per locus and a mean resolving power of 1. The pair-wise similarity coefficients calculated from binary data matrix based on presence or absence of alleles varied from 0.15 to 0.98, but was greater than 0.5 for most accessions, indicating a high level of similarity. A cluster analysis based on the similarity matrix identified nine distinct accessions and three clusters. All the recently developed commercial varieties were distinctly different from the clusters. Based on the analysis, it appears that Indian emmer wheats are not very diverse. Consequently, there is a need to increase the diversity within the Indian emmer wheat eco-geographic group, by introducing diversity from other eco-geographic groups, or even from other wheat species.

A comparison of RAPD and ISSR markers reveals genetic diversity among sweet potato landraces (Ipomoea batatas (L.) Lam.)

Small farmers have played an important role in maintaining genetic resources of traditional varieties. Collecting and characterizing germplasm, especially landraces and heirloom varieties, are strategic activities that would create a knowledge base describing the traditional varieties of a given region and reduce the risk of genetic erosion. The objectives of this work were as follows: collect sweet potato roots from rural properties and local markets in Rio de Janeiro State, Brazil; characterize the accessions using RAPD and ISSR molecular markers, comparing the efficiency in discrimination of these two types of molecular markers; and estimate the genetic variability of the population. Fifty-nine samples from rural properties and 19 from local markets were studied. A matrix of binary data was developed to analyze the molecular data using the Jaccard index to estimate genetic differences among accessions, and clusters were made using the UPGMA method. The molecular techniques detected genetic variability among the accessions, with cophenetic correlation coefficients (CCC) of 0.80 for RAPDs and 0.89 for ISSRs. The RAPD and ISSR marker results corresponded well, with a correlation of 0.55. All of the accessions were considered distinct, which demonstrates that traditional farmers maintain sweet potato genotypes that have good genetic diversity.

Contrastant banana accessions for resistance to the burrowing nematode, based on molecular markers RAPD

This work aimed to proceed molecular characterization of seven banana accessions (Borneo, Grand Naine, 1304-06, 4249-05, 0337-02, 0323-03 and 4279-06) resistance to the nematode Radopholus similis. These accessions were selected taking in account the reproduction factor (RF) among 26 banana genotypes from a working collection belonging to Embrapa Mandioca e Fruticultura Tropical. The genomic DNA of the seven accessions was extracted, and 36 decamere primers had been used to obtain RAPD markers. The resulting markers were converted into a matrix of binary data. From that matrix the genetic distance between the accessions were estimated, for further clustering and graphic dispersion analyses. From a total of 521 RAPD markers generated, 420 (81%) were polymorphic, including 140 (27%) potentially promising for application on works related to genetic mapping of the resistance to R. similis. OPE-15, OPH-17, and OPG-09 were the primers that contributed to the highest number of bands promising for genetic mapping of resistance (12, 8, and 8, respectively). The genetic distances between accessions ranged from 0.106 to 0.455, with the longest one observed between cv. Borneo and the genotype 4279-06, considered as highly susceptible and resistant, respectively, to the nematode according to the RF. The graphic dispersion distinguished three groups of accessions, and most of resistant genotypes clustered together in the same group. The most contrastant genotypes for resistance (Borneo and 4249-05) were separated by a genetic distance of 0.374, and possessed a total of 114 polymorphic bands promising for genetic mapping of resistance. In addition, the results of pathogenicity tests were congruent with those obtained by RAPD analyses.

Variabilidade genética de acessos obtidos de populações cultivadas e silvestres de maracujazeiro-doce com base em marcadores rapd

O maracujazeiro-doce (Passiflora alata Curtis), devido a preços diferenciados, vem ganhando importância dentro do mercado de frutas in natura. O melhoramento genético é fundamental para elevar a qualidade e a produtividade da cultura. Os marcadores moleculares do DNA têm sido muito úteis por permitirem a obtenção de um número praticamente ilimitado de polimorfismo genético sem influência do ambiente. Objetivou-se, neste trabalho, estudar a variabilidade genética de 17 acessos de maracujá-doce, com base em marcadores moleculares RAPD. Um acesso de P. quadrangularis e um de P. edulis foram utilizados como outgroups. Amostras de DNA genômico de cada acesso foram extraídas e 11 iniciadores decâmeros (OPD 04; 07; 08 e16; OPE 18 e 20; OPF 01 e 14; OPG 08; OPH 12 e 16) foram utilizados para a obtenção dos marcadores. Os marcadores obtidos foram convertidos em uma matriz de dados binários, a partir da qual foram estimadas as distâncias genéticas entre os acessos e realizadas análises de agrupamento e de dispersão gráfica. Do total de marcadores, considerando-se apenas os acessos de P. alata, observaram-se 87 (62,12%) bandas polimórficas, evidenciando a grande variabilidade intraespecífica. A análise de agrupamento realizada com base nas distâncias genéticas permitiu subdividir os 17 acessos de P. alata em, pelo menos, cinco grupos de similaridade genética. Os acessos silvestres foram os que mais contribuíram para a ampliação da base genética dos materiais estudados, abrindo perspectivas para o uso desses materiais em programas de melhoramento.

Análise da recuperação do genitor recorrente em maracujazeiro-azedo por meio de marcadores RAPD

O Brasil é o maior produtor mundial de maracujá, entretanto tem-se observado redução na produtividade do maracujazeiro nos últimos anos, devido, principalmente, a fatores fitossanitários. Na Embrapa Cerrados, a transferência de genes de resistência de espécies silvestres para as comerciais de maracujazeiro tem sido feita por meio de hibridações interespecíficas seguidas de um programa de retrocruzamentos auxiliados por marcadores moleculares. Este trabalho teve por objetivo verificar a recuperação do genoma recorrente nas plantas RC4 e RC5 [(Passiflora edulis x Passiflora setacea) x Passiflora edulis ] com base em marcadores RAPD. O estudo foi desenvolvido no Laboratório de Genética e Biologia Molecular da Embrapa Cerrados. Amostras de DNA de cada material genético (17 plantas RC4, 16 plantas RC5, Passiflora edulis e Passiflora setacea) foram amplificadas para obtenção de marcadores RAPD. Foram utilizados 12 primers decâmeros para as plantas RC4 e 14 primers decâmeros para as plantas RC5. Os marcadores RAPD gerados foram convertidos em matriz de dados binários. Verificou-se alta porcentagem de marcadores polimórficos em consequência do cruzamento-base interespecífico. A menor similaridade genética foi observada entre as espécies P. edulis e P. setacea, evidenciando a grande distância genética dessas espécies.

Benthic isopods (Crustacea, Malacostraca) from the Ross Sea, Antarctica: species checklist and their zoogeography in the Southern Ocean

In this study isopod species of the Ross Sea were investigated. Literature until May 2008 was checked to provide an overview of all known and described species in the Ross Sea. This species checklist was then enlarged through material of the 19th Italica expedition in 2004. During this expedition for the first time a small mesh net (500 μm) was used. Nine thousand four hundred and eighty one isopod specimens were collected during this expedition. Through this material the number of isopod species in the Ross Sea increased from 42 to 117 species, which belong to 20 families and 49 genera. Fifty-six percentage of the isopods species collected during the Italica expedition are new to science. The zoogeography of the 117 species was investigated. A non-transformed binary presence-absence data matrix was constructed using the Bray–Curtis coefficient. The results were displayed in a cluster analysis and by nonmetric multidimensional scaling (MDS). This paper gives a first insight into the occurrence and distribution of the isopod species of the Ross Sea.

Identifying molecular markers associated with classification of genotypes by External Logistic Biplots

For characterization of genetic diversity in genotypes several molecular techniques, usually resulting in a binary data matrix, have been used. Despite the fact that in Cluster Analysis (CA) and Principal Coordinates Analysis (PCoA) the interpretation of the variables responsible for grouping is not straightforward, these methods are commonly used to classify genotypes using DNA molecular markers. In this article, we present a novel algorithm that uses a combination of PCoA, CA and Logistic Regression (LR), as a better way to interpret the variables (alleles or bands) associated to the classification of genotypes. The combination of three standard techniques with some new ideas about the geometry of the procedures, allows constructing an External Logistic Biplot (ELB) that helps in the interpretation of the variables responsible for the classification or ordination. An application of the method to study the genetic diversity of four populations from Africa, Asia and Europe, using the HapMap data is included. The Matlab code for implementing the methods may be obtained from the web site: http://biplot.usal.es.

The CHIC Model: A Global Model for Coupled Binary Data

Often problems result in the collection of coupled data, which consist of different N-way N-mode data blocks that have one or more modes in common. To reveal the structure underlying such data, an integrated modeling strategy, with a single set of parameters for the common mode(s), that is estimated based on the information in all data blocks, may be most appropriate. Such a strategy implies a global model, consisting of different N-way N-mode submodels, and a global loss function that is a (weighted) sum of the partial loss functions associated with the different submodels. In this paper, such a global model for an integrated analysis of a three-way three-mode binary data array and a two-way two-mode binary data matrix that have one mode in common is presented. A simulated annealing algorithm to estimate the model parameters is described and evaluated in a simulation study. An application of the model to real psychological data is discussed.

Using AFLP Markers for the Analysis of the Genetic Diversity of Apricot Cultivars in Tunisia

Apricot (Prunus armeniaca L.) culture is present in a wide range of areas and microclimates in Tunisia. Each of them contains several specific cultivars and shows a high level of morphological diversity. To characterize the related diversity, surveys were performed in the four main apricot cultivation areas, where 31 cultivars representing apricot landraces were sampled. DNA was extracted and amplified with five different EcoRI–MseI AFLP primer combinations. Autoradiographs revealed 203 polymorphic markers in a total of 295 detected fragments. A set of redundant marker patterns was identified and deleted from the binary data matrix, data analysis being performed on a total of 167 polymorphic markers. In a dendrogram calculated by the Ward clustering technique, two major groups were identified, separating nine cultivars from the other 22. Three subgroups have been revealed in each of the main groups. The groups and subgroups identified on the genetic basis are closely related to the geographic origin of the cultivars. Analysis of the actual repartition suggested at least the introduction of two independent gene funds in the northern and central prospected areas, followed by a local diversification and then a dissemination phase. Their interaction occurred at least in the two sites of Testour and Sbikha.

Markov transition models for binary repeated measures with ignorable and nonignorable missing values

Motivated by problems encountered in studying treatments for drug dependence, where repeated binary outcomes arise from monitoring biomarkers for recent drug use, this article discusses a statistical strategy using Markov transition model for analyzing incomplete binary longitudinal data. When the mechanism giving rise to missing data can be assumed to be ;ignorable', standard Markov transition models can be applied to observed data to draw likelihood-based inference on transition probabilities between outcome events. Illustration of this approach is provided using binary results from urine drug screening in a clinical trial of baclofen for cocaine dependence. When longitudinal data have ;nonignorable' missingness mechanisms, random-effects Markov transition models can be used to model the joint distribution of the binary data matrix and the matrix of missingness indicators. Categorizing missingness patterns into those for occasional or ;intermittent' missingness and those for monotonic missingness or ;missingness due to dropout', the random-effects Markov transition model was applied to a data set containing repeated breath samples analyzed for expired carbon monoxide levels among opioid-dependent, methadone-maintained cigarette smokers in a smoking cessation trial. Markov transition models provide a novel reconceptualization of treatment outcomes, offering both intuitive statistical values and relevant clinical insights.

Evaluation of Different Wheat Varieties by SDS-PAGE Electrophoresis

Wheat seed-storage proteins represent not only an important source of food and energy but it is also involved in the determination of bread-making quality. Wheat grains of thirteen wheat varieties were collected from different ecological regions of Pakistan. The variability of seed storage-proteins was analyzed by using SDS-PAGE electrophoresis. Electrophorogram for each variety was scored and presence or absence of each band noted and entered in a binary data matrix. Based on electrophoresis band spectra, Jaccard's Similarity Index (JSI) was calculated. Genetic diversity of wheat was evaluated by constructing the dendrogram for High Molecular Weight (HMW) and Low Molecular Weight (LMW) gluten subunit bands. It is concluded that seed storage protein profiles could be useful markers in the studies of genetic diversity and classification of adapted cultivars, thereby improving the efficiency of wheat breeding programs in cultivar development especially in developing countries like Pakistan.

ARES: software to compare allelic richness between uneven samples

AbstractAllelic richness is one of the most basic measures of genetic diversity. Its calculation is, however, still problematic because estimates depend on sample size. This paper describes an r library that calculates mean allelic richness with confidence bounds for a range of sample sizes. It takes a file in genepop format as input, or alternatively a binary data matrix with columns representing different individuals and rows representing different alleles. The output is tabular as well as graphical. Unlike existing tools, ares does extrapolate beyond the sample size and provides confidence bounds for these predictions.

Revisions toPenicilliumser.Corymbifera: agents responsible for blue mould storage rot of various flower and vegetable bulbs

Fifteen strains representing each Penicillium ser. Corymbifera taxa were compared using phenotypic and chemotaxonomic characters by cluster analysis and discriminant partial least squares regression. Variability in phenotypic expression of species strains resulted in a more fragmented classification compared with secondary metabolite expression. Although the observed phenotypic expression varied for strains cultured upon the same media, it was possible to classify strains into species groupings based only upon a few distinctive phenotypic traits. Data analysis of secondary metabolite profiles generated from HPLC-diode array dectection analysis gave reliable strain classification when more than one media type was employed. Depending on the species, Czapek yeast autolysate agar typically yielded the greatest chemical diversity; however, several metabolites (terrestric acid, corymbiferone, the corymbiferan lactones, and daldinin D) were only produced when strains were grown on either yeast extract sucrose or oatmeal agar. For the classification of strains based on a binary data matrix, application of the Yule coefficient gave the best clustering. Several secondary metabolites, of importance for the classification of ser. Corymbifera strains, were identified by discriminant-partial least squares regression analysis. A diagnostic key based on phenotypic, chemotaxonomic, and pathogenic traits is provided as an aid for species identification.

Potential Heterotic Groups in Hop as Determined by AFLP Analysis

Hop (Humulus lupulus L.) is a perennial, dioecious species in which the female inflorescence (cones) are harvested and used in the beer‐brewing process to impart bittering and/or flavoring to beer. Hop breeders have typically utilized clonal selection and hybridization to develop new cultivars. The use of genetically diverse parents for the purpose of capturing heterosis in the offspring has received little attention from hop breeders. The objective of this research was to assign male (N = 80) and female (N = 26) hop genotypes into potential heterotic groups using AFLP‐generated molecular markers. The six AFLP primers used in this study amplified 550 total fragments, of which 490 (89.1%) were polymorphic. A genetic distance (GD) matrix was computed from the binary data matrix, and groupings and summary statistics were calculated from the GD matrix. Two major clusters were observed, one composed primarily of European hops, while the second group was composed primarily of European–wild American hybrids. The two major clusters were further subdivided into 13 smaller clusters (two female, nine male, two male and female) based on a qualitative analysis. These results suggest potential parental combinations for hop researchers and breeders to study heterosis in hop.

MALDI-TOF Mass Spectrometry Analysis of Cerebrospinal Fluid Tryptic Peptide Profiles to Diagnose Leptomeningeal Metastases in Patients with Breast Cancer

Leptomeningeal metastasis (LM) is a devastating complication that occurs in 5% of patients with breast cancer. Early diagnosis and initiation of treatment are essential to prevent neurological deterioration. However, early diagnosis of LM remains challenging because 25% of cerebrospinal fluid (CSF) samples produce false-negative results at first cytological examination. We developed a new, MS-based method to investigate the protein expression patterns present in the CSF from patients with breast cancer with and without LM. CSF samples from 106 patients with active breast cancer (54 with LM and 52 without LM) and 45 control subjects were digested with trypsin. The resulting peptides were measured by MALDI-TOF MS. Then, the mass spectra were analyzed and compared between patient groups using newly developed bioinformatics tools. A total of 895 possible peak positions was detected, and 164 of these peaks discriminated between the patient groups (Kruskal-Wallis, p<0.01). The discriminatory masses were clustered, and a classifier was built to distinguish patients with breast cancer with and without LM. After bootstrap validation, the classifier had a maximum accuracy of 77% with a sensitivity of 79% and a specificity of 76%. Direct MALDI-TOF analysis of tryptic digests of CSF gives reproducible peptide profiles that can assist in diagnosing LM in patients with breast cancer. The same method can be used to develop diagnostic assays for other neurological disorders.

The Correlational Agreement Coefficient CA(≤, D)—a mathematical analysis of a descriptive goodness-of-fit measure

The Correlational Agreement Coefficient, CA(≤, D), was introduced by J.F.J. van Leeuwe in 1974 within Item Tree Analysis (ITA), a data-analytic method to derive quasi orders (surmise relations) on sets of bi-valued test items. Recently, it has become of interest in connection with Knowledge Space Theory (KST). The coefficient CA(≤, D) is used as a descriptive goodness-of-fit measure to select out of competing surmise relations one with maximal CA(≤, D) value. Formal aspects like boundedness, decomposition, and the interplay between consistency of a surmise relation (with a binary data matrix) and the attainment of the maximum value of CA(≤, D) are investigated. Dependence of CA(≤, D) on trivial response patterns is quantified by a functional relationship that allows one to bunch the impact of trivial response patterns in a single “bias term”. These considerations should warn against inconsiderate use of the coefficient. Mathematical reasons for failed, however, heuristically plausible, properties are presented.

Assessment of discriminatory power of three different fingerprinting methods based on killer toxin sensitivity for the differentiation of Saccharomyces cerevisiae strains.

A panel composed of 44 taxonomically certified strains of Saccharomyces cerevisiae of different origin was used to evaluate the discriminatory power of three different fingerprinting methods based on sensitivity towards 24 killer toxins. Binary data matrix (BDM), triplet data matrix (TDM) and numerical data matrix (NDM) were used as fingerprinting methods. NDM possessed the highest discriminatory power, assessed through the Simpson's, and Hunter and Gaston's indices for the measurement of diversity. The upper limits of fingerprinting ability expressed by the three above methods have been also discussed. NDM determined a significant increase of discriminatory power than the use of BDM or TDM, in terms of an effective amplification of their fingerprinting efficacy. The NDM fingerprinting method could find application in control laboratories for the discrimination of yeast strains of industrial importance or covered by patent.

Genetic relationships of Aglaonema species and cultivars inferred from AFLP markers.

Aglaonema is an important ornamental foliage plant genus, but genetic relationships among its species and cultivars have not been reported. This study analysed genetic relatedness of 54 cultivars derived from nine species using amplified fragment length polymorphism (AFLP) markers. Initially, 48 EcoRI + 2/MseI + 3 primer set combinations were screened, from which six primer sets that showed clear scoreable and highly polymorphic fragments were selected and used for AFLP reactions. AFLP fragments were scored and entered into a binary data matrix as discrete variables. Jaccard's coefficient of similarity was calculated for all pair-wise comparisons among the 54 cultivars, and a dendrogram was constructed by the unweighted pair-group method using the arithmetic average (UPGMA). The number of AFLP fragments generated per primer set ranged from 59 to 112 with fragment sizes varying from 50 to 565 bp. A total of 449 AFLP fragments was detected, of which 314 were polymorphic (70 %). All cultivars were clearly differentiated by their AFLP fingerprints. The 54 cultivars were divided into seven clusters; cultivars within each cluster generally share similar morphological characteristics. Cluster I contains 35 cultivars, most of them are interspecific hybrids developed mainly from A. commutatum, A. crispum or A. nitidum. However, Jaccard's similarity coefficients among these hybrids are 0.84 or higher, suggesting that these popular hybrid cultivars are genetically much closer than previously thought. This genetic similarity may imply that A. nitidum and A. crispum are likely progenitors of A. commutatum. Results of this study demonstrate the efficiency and ease of using AFLP markers for investigating genetic relationships of ornamental foliage plants, a group usually propagated vegetatively. The AFLP markers developed will help future Aglaonema cultivar identification, germplasm conservation and new cultivar development.