Kemometrijska analiza udjela visokomolekularnih glutenina i struktura kruha od hrvatskih sorata pšenice

The aim of this work is to investigate functional relationships among wheat properties, high molecular mass (weight) (HMW) glutenin subunits and bread quality produced from eleven Croatian wheat cultivars by chemometric analysis. HMW glutenin subunits were fractionated by sodium dodecylsulfate polyacrylamid gel electrophoresis (SDS-PAGE) and subsequently analysed by scanning densitometry in order to quantify HMW glutenin fractions. Wheat properties are characterised by four variables: protein content, sedimentation value, wet gluten and gluten index. Bread quality is assessed by the standard measurement of loaf volume, and visual quality of bread slice is quantified by 8 parameters by the use of computer image analysis. The data matrix with 21 columns (measured variables) and 11 rows (cultivars) is analysed for determination of number of latent variables. It was found that the first two latent variables account for 92, 85 and 87 % of variance of wheat quality properties, HMW glutenin fractions, and the bread quality parameters, respectively. Classification and functional relationships are discussed from the case data (cultivars) and variable projections to the planes of the first two latent variables. Between Glu-D1y proportion and the bread quality parameters (standard parameter loaf volume and bread crumb cell area fraction determined by image analysis) the strongest positive correlations are found r = 0.651 and r = 0.885, respectively. Between Glu-B1x proportion and the bread quality parameters the strongest negative correlations are found r =-0.535 and r = –0.841, respectively. The results are discussed in view of possible development of new and improvement of existing wheat cultivars and optimisation of bread production.Svrha je rada istražiti me|usobnu ovisnost svojstava pšenice, udjela visokomolekularnih podjedinica glutenina (HMW) i kakvoće kruha proizvedenih od jedanaest hrvatskih sorata pšenice primjenom kemometrijske analize. Podjedinice HMW glutenina frakcionirane su natrijevim dodecilsulfat poliakrilamid gel-elektroforezom (SDS-PAGE), a zatim analizirane »scan« denizitrometrom radi određivanja frakcija HMW glutenina. Svojstva pšenice određena su sa četiri varijable: udjel proteina, vrijednost sedimentacije, količina vlažnog glutena i glutenski indeks. Kakvoća je kruha ocijenjena standardnim mjerenjem volumena kruha, a vizualna kvaliteta kriške kruha utvrđena je s osam parametara dobivenih računalnom analizom slike. Matrica podataka s 21 stupcem (mjerene varijable) i 11 redaka (sorte pšenice) analizirana je da bi se odredio broj latentnih varijabla. Ustanovljeno je da prve dvije latentne varijable objašnjavaju 92, 85 i 87 % varijance skupova podataka za kakvoću brašna, udjele frakcija HMW glutenina i kakvoće kruha. Projiciranjem na plohu prvih dviju latentnih varijabla razmotrena je klasifikacija i međusobna ovisnost sorata pšenice. Utvrđeno je da postoji najveća pozitivna korelacija između udjela D1y glutenina i kakvoće kruha (standardnim postupkom određivanja volumena i ukupne površine šupljikavosti kruha određene računalnom analizom slike), odgovarajuće vrijednosti su r = 0,651 i r = 0,885. Najveća negativna korelacija postignuta je između udjela Glu-B1x glutenina i kakvoće kruha, odgovarajuće su vrijednosti r = – 0,535 i r = – 0,841. Razmatrane su implikacije dobivenih rezultata za mogući daljnji razvoj i poboljšanje sorata pšenice i optimiranje procesa proizvodnje kruha

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution II: dynamics.

BackgroundTo accurately describe gene expression and computationally model animal transcriptional networks, it is essential to determine the changing locations of cells in developing embryos.ResultsUsing automated image analysis methods, we provide the first quantitative description of temporal changes in morphology and gene expression at cellular resolution in whole embryos, using the Drosophila blastoderm as a model. Analyses based on both fixed and live embryos reveal complex, previously undetected three-dimensional changes in nuclear density patterns caused by nuclear movements prior to gastrulation. Gene expression patterns move, in part, with these changes in morphology, but additional spatial shifts in expression patterns are also seen, supporting a previously proposed model of pattern dynamics based on the induction and inhibition of gene expression. We show that mutations that disrupt either the anterior/posterior (a/p) or the dorsal/ventral (d/v) transcriptional cascades alter morphology and gene expression along both the a/p and d/v axes in a way suggesting that these two patterning systems interact via both transcriptional and morphological mechanisms.ConclusionOur work establishes a new strategy for measuring temporal changes in the locations of cells and gene expression patterns that uses fixed cell material and computational modeling. It also provides a coordinate framework for the blastoderm embryo that will allow increasingly accurate spatio-temporal modeling of both the transcriptional control network and morphogenesis

Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis

Background: The distribution of the chromatin-associatedproteins plays a key role in directing nuclear function. Previously, wedeveloped an image-based method to quantify the nuclear distributions ofproteins and showed that these distributions depended on the phenotype ofhuman mammary epithelial cells. Here we describe a method that creates ahierarchical tree of the given cell phenotypes and calculates thestatistical significance between them, based on the clustering analysisof nuclear protein distributions. Results: Nuclear distributions ofnuclear mitotic apparatus protein were previously obtained fornon-neoplastic S1 and malignant T4-2 human mammary epithelial cellscultured for up to 12 days. Cell phenotype was defined as S1 or T4-2 andthe number of days in cultured. A probabilistic ensemble approach wasused to define a set of consensus clusters from the results of multipletraditional cluster analysis techniques applied to the nucleardistribution data. Cluster histograms were constructed to show how cellsin any one phenotype were distributed across the consensus clusters.Grouping various phenotypes allowed us to build phenotype trees andcalculate the statistical difference between each group. The resultsshowed that non-neoplastic S1 cells could be distinguished from malignantT4-2 cells with 94.19 percent accuracy; that proliferating S1 cells couldbe distinguished from differentiated S1 cells with 92.86 percentaccuracy; and showed no significant difference between the variousphenotypes of T4-2 cells corresponding to increasing tumor sizes.Conclusion: This work presents a cluster analysis method that canidentify significant cell phenotypes, based on the nuclear distributionof specific proteins, with high accuracy

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

BACKGROUND: To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. RESULTS: Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. CONCLUSION: The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

BACKGROUND: To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. RESULTS: Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. CONCLUSION: The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks

Chemometric Analysis of High Molecular Mass Glutenin Subunits and Image Data of Bread Crumb Structure from Croatian Wheat Cultivars

The aim of this work is to investigate functional relationships among wheat properties, high molecular mass (weight) (HMW) glutenin subunits and bread quality produced from eleven Croatian wheat cultivars by chemometric analysis. HMW glutenin subunits were fractionated by sodium dodecylsulfate polyacrylamid gel electrophoresis (SDS-PAGE) and subsequently analysed by scanning densitometry in order to quantify HMW glutenin fractions. Wheat properties are characterised by four variables: protein content, sedimentation value, wet gluten and gluten index. Bread quality is assessed by the standard measurement of loaf volume, and visual quality of bread slice is quantified by 8 parameters by the use of computer image analysis. The data matrix with 21 columns (measured variables) and 11 rows (cultivars) is analysed for determination of number of latent variables. It was found that the first two latent variables account for 92, 85 and 87 % of variance of wheat quality properties, HMW glutenin fractions, and the bread quality parameters, respectively. Classification and functional relationships are discussed from the case data (cultivars) and variable projections to the planes of the first two latent variables. Between Glu-D1y proportion and the bread quality parameters (standard parameter loaf volume and bread crumb cell area fraction determined by image analysis) the strongest positive correlations are found r = 0.651 and r = 0.885, respectively. Between Glu-B1x proportion and the bread quality parameters the strongest negative correlations are found r =-0.535 and r = –0.841, respectively. The results are discussed in view of possible development of new and improvement of existing wheat cultivars and optimisation of bread production